WorldWideScience

Sample records for filter fitted tracks

  1. Kalman Filter Track Fits and Track Breakpoint Analysis

    CERN Document Server

    Astier, Pierre; Cousins, R D; Letessier-Selvon, A A; Popov, B A; Vinogradova, T G; Astier, Pierre; Cardini, Alessandro; Cousins, Robert D.; Letessier-Selvon, Antoine; Popov, Boris A.; Vinogradova, Tatiana

    2000-01-01

    We give an overview of track fitting using the Kalman filter method in the NOMAD detector at CERN, and emphasize how the wealth of by-product information can be used to analyze track breakpoints (discontinuities in track parameters caused by scattering, decay, etc.). After reviewing how this information has been previously exploited by others, we describe extensions which add power to breakpoint detection and characterization. We show how complete fits to the entire track, with breakpoint parameters added, can be easily obtained from the information from unbroken fits. Tests inspired by the Fisher F-test can then be used to judge breakpoints. Signed quantities (such as change in momentum at the breakpoint) can supplement unsigned quantities such as the various chisquares. We illustrate the method with electrons from real data, and with Monte Carlo simulations of pion decays.

  2. Parallel Kalman filter track fit based on vector classes

    Energy Technology Data Exchange (ETDEWEB)

    Kisel, Ivan [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH (Germany); Kretz, Matthias [Kirchhoff-Institut fuer Physik, Ruprecht-Karls Universitaet, Heidelberg (Germany); Kulakov, Igor [Goethe-Universitaet, Frankfurt am Main (Germany); National Taras Shevchenko University, Kyiv (Ukraine)

    2010-07-01

    Modern high energy physics experiments have to process terabytes of input data produced in particle collisions. The core of the data reconstruction in high energy physics is the Kalman filter. Therefore, developing the fast Kalman filter algorithm, which uses maximum available power of modern processors, is important, in particular for initial selection of events interesting for the new physics. One of processors features, which can speed up the algorithm, is a SIMD instruction set, which allows to pack several data items in one register and operate on all of them in one go, thus achieving more operations per clock cycle. Therefore a flexible and useful interface, which uses the SIMD instruction set on different CPU and GPU processors architectures, has been realized as a vector classes library. The Kalman filter based track fitting algorithm has been implemented with use of the vector classes. Fitting quality tests show good results with the residuals equal to 49 {mu}m and 44 {mu}m for x and y track parameters and relative momentum resolution of 0.7%. The fitting time of 0.053 {mu}s per track has been achieved on Intel Xeon X5550 with 8 cores at 2.6 GHz by using in addition Intel Threading Building Blocks.

  3. Simultaneous pattern recognition and track fitting by the Kalman filtering method

    International Nuclear Information System (INIS)

    Billoir, P.

    1990-01-01

    A progressive pattern recognition algorithm based on the Kalman filtering method has been tested. The algorithm starts from a small track segment or from a fitted track of a neighbouring detector, then extends the candidate tracks by adding measured points one by one. The fitted parameters and weight matrix of the candidate track are updated when adding a point, and give an increasing precision on prediction of the next point. Thus, pattern recognition and track fitting can be accomplished simultaneously. The method has been implemented and tested for track reconstruction for the vertex detector of the ZEUS experiment at DESY. Detailed procedures of the method and its performance are presented. Its flexibility is described as well. (orig.)

  4. Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

    Directory of Open Access Journals (Sweden)

    Yun Wang

    2016-01-01

    Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

  5. Treatment of non-Gaussian tails of multiple Coulomb scattering in track fitting with a Gaussian-sum filter

    International Nuclear Information System (INIS)

    Strandlie, A.; Wroldsen, J.

    2006-01-01

    If any of the probability densities involved in track fitting deviate from the Gaussian assumption, it is plausible that a non-linear estimator which better takes the actual shape of the distribution into account can do better. One such non-linear estimator is the Gaussian-sum filter, which is adequate if the distributions under consideration can be approximated by Gaussian mixtures. The main purpose of this paper is to present a Gaussian-sum filter for track fitting, based on a two-component approximation of the distribution of angular deflections due to multiple scattering. In a simulation study within a linear track model the Gaussian-sum filter is shown to be a competitive alternative to the Kalman filter. Scenarios at various momenta and with various maximum number of components in the Gaussian-sum filter are considered. Particularly at low momenta the Gaussian-sum filter yields a better estimate of the uncertainties than the Kalman filter, and it is also slightly more precise than the latter

  6. LHCb: Alignment of the LHCb Detector with Kalman Filter Fitted Tracks

    CERN Multimedia

    Amoraal, J; Hulsbergen, W; Needham, M; Nicolas, L; Pozzi, S; Raven, G; Vecchi, S

    2009-01-01

    We report on an implementation of a global chisquare algorithm for the simultaneous alignment of all tracking systems in the LHCb detector. Our algorithm uses hit residuals from the standard LHCb track fit which is based on a Kalman filter. The algorithm is implemented in the LHCb reconstruction framework and exploits the fact that all sensitive detector elements have the same geometry interface. A vertex constraint is implemented by fitting tracks to a common point and propagating the change in track parameters to the hit residuals. To remove unconstrained or poorly constrained degrees of freedom (so-called weak modes) the average movements of (subsets of) alignable detector elements can be fixed with Lagrange constraints. Alternatively, weak modes can be removed with a cutoff in the eigenvalue spectrum of the second derivative of the chisquare. As for all LHCb reconstruction and analysis software the configuration of the algorithm is done in python and gives detailed control over the selection of alignable ...

  7. Robust track fitting in the Belle II inner tracking detector

    International Nuclear Information System (INIS)

    Nadler, Moritz; Frühwirth, Rudolf

    2012-01-01

    Track fitting in the new inner tracker of the Belle II experiment uses the GENFIT package. In the latter both a standard Kalman filter and a robust extension, the deterministic annealing filter (DAF), are implemented. This contribution presents the results of a simulation experiment which examines the performance of the DAF in the inner tracker, in terms of outlier detection ability and of the impact of different kinds of background on the quality of the fitted tracks.

  8. Recent advances in the GENFIT track fitting package

    Energy Technology Data Exchange (ETDEWEB)

    Bicker, Karl A. [CERN, Geneva (Switzerland); Hoeppner, Christian; Ketzer, Bernhard; Neubert, Sebastian; Paul, Stephan; Rauch, Johannes [Technische Universitaet Muenchen, Munich (Germany)

    2012-07-01

    The GENFIT software package provides a framework for track fitting. Due to the modular and generic structure, it is usable with arbitrary detector and field geometries. GENFIT is used in several collaborations (e.g. Belle II, COMPASS, FOPI, PANDA). GENFIT provides hit classes for common detector types and their information is used by GENFIT in their native coordinate system. Hits are collected in tracks, as are track representations. The track representation handles the extrapolation of the track through matter and fields. Multiple track representations can be fitted simultaneously. GENFIT has recently been equipped with several new features. Besides adding Smoothing, the standard Kalman fit algorithm has been extended by a Deterministic Annealing Filter (DAF), which can tag noise hits. An interface to the RAVE vertexing package has equipped GENFIT with the capability for vertex reconstruction and fitting. Results from simulation and real data are presented.

  9. A Novel Generic Framework for Track Fitting in Complex Detector Systems

    OpenAIRE

    Höppner, C.; Neubert, S.; Ketzer, B.; Paul, S.

    2009-01-01

    This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices th...

  10. Exploration and extension of an improved Riemann track fitting algorithm

    Science.gov (United States)

    Strandlie, A.; Frühwirth, R.

    2017-09-01

    Recently, a new Riemann track fit which operates on translated and scaled measurements has been proposed. This study shows that the new Riemann fit is virtually as precise as popular approaches such as the Kalman filter or an iterative non-linear track fitting procedure, and significantly more precise than other, non-iterative circular track fitting approaches over a large range of measurement uncertainties. The fit is then extended in two directions: first, the measurements are allowed to lie on plane sensors of arbitrary orientation; second, the full error propagation from the measurements to the estimated circle parameters is computed. The covariance matrix of the estimated track parameters can therefore be computed without recourse to asymptotic properties, and is consequently valid for any number of observation. It does, however, assume normally distributed measurement errors. The calculations are validated on a simulated track sample and show excellent agreement with the theoretical expectations.

  11. Mathematical framework for fast and rigorous track fit for the ZEUS detector

    Energy Technology Data Exchange (ETDEWEB)

    Spiridonov, Alexander

    2008-12-15

    In this note we present a mathematical framework for a rigorous approach to a common track fit for trackers located in the inner region of the ZEUS detector. The approach makes use of the Kalman filter and offers a rigorous treatment of magnetic field inhomogeneity, multiple scattering and energy loss. We describe mathematical details of the implementation of the Kalman filter technique with a reduced amount of computations for a cylindrical drift chamber, barrel and forward silicon strip detectors and a forward straw drift chamber. Options with homogeneous and inhomogeneous field are discussed. The fitting of tracks in one ZEUS event takes about of 20ms on standard PC. (orig.)

  12. Kalman Filter Tracking on Parallel Architectures

    International Nuclear Information System (INIS)

    Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

    2016-01-01

    Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. In order to achieve the theoretical performance gains of these processors, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High-Luminosity Large Hadron Collider (HL-LHC), for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques such as Cellular Automata or Hough Transforms. The most common track finding techniques in use today, however, are those based on a Kalman filter approach. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust, and are in use today at the LHC. Given the utility of the Kalman filter in track finding, we have begun to port these algorithms to parallel architectures, namely Intel Xeon and Xeon Phi. We report here on our progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a simplified experimental environment

  13. A novel generic framework for track fitting in complex detector systems

    International Nuclear Information System (INIS)

    Hoeppner, C.; Neubert, S.; Ketzer, B.; Paul, S.

    2010-01-01

    This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices through the experiment are also implemented as interchangeable modules. Different track parameterizations and extrapolation routines can be used simultaneously for fitting of the same physical track. Representations of detector hits are the third modular ingredient to the framework. The hit dimensionality and orientation of planar tracking detectors are not restricted. Tracking information from detectors which do not measure the passage of particles in a fixed physical detector plane, e.g. drift chambers or TPCs, is used without any simplification. The concept is implemented in a light-weight C++ library called GENFIT, which is available as free software.

  14. A novel generic framework for track fitting in complex detector systems

    Energy Technology Data Exchange (ETDEWEB)

    Hoeppner, C., E-mail: christian.hoeppner@cern.c [Technische Universitaet Muenchen, Physik Department, 85748 Garching (Germany); Neubert, S.; Ketzer, B.; Paul, S. [Technische Universitaet Muenchen, Physik Department, 85748 Garching (Germany)

    2010-08-21

    This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices through the experiment are also implemented as interchangeable modules. Different track parameterizations and extrapolation routines can be used simultaneously for fitting of the same physical track. Representations of detector hits are the third modular ingredient to the framework. The hit dimensionality and orientation of planar tracking detectors are not restricted. Tracking information from detectors which do not measure the passage of particles in a fixed physical detector plane, e.g. drift chambers or TPCs, is used without any simplification. The concept is implemented in a light-weight C++ library called GENFIT, which is available as free software.

  15. Tracking speckle displacement by double Kalman filtering

    Institute of Scientific and Technical Information of China (English)

    Donghui Li; Li Guo

    2006-01-01

    @@ A tracking technique using two sequentially-connected Kalman filter for tracking laser speckle displacement is presented. One Kalman filter tracks temporal speckle displacement, while another Kalman filter tracks spatial speckle displacement. The temporal Kalman filter provides a prior for the spatial Kalman filter, and the spatial Kalman filter provides measurements for the temporal Kalman filter. The contribution of a prior to estimations of the spatial Kalman filter is analyzed. An optical analysis system was set up to verify the double-Kalman-filter tracker's ability of tracking laser speckle's constant displacement.

  16. Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

    International Nuclear Information System (INIS)

    Zu-Tao, Zhang; Jia-Shu, Zhang

    2010-01-01

    The unscented Kalman filter is a developed well-known method for nonlinear motion estimation and tracking. However, the standard unscented Kalman filter has the inherent drawbacks, such as numerical instability and much more time spent on calculation in practical applications. In this paper, we present a novel sampling strong tracking nonlinear unscented Kalman filter, aiming to overcome the difficulty in nonlinear eye tracking. In the above proposed filter, the simplified unscented transform sampling strategy with n + 2 sigma points leads to the computational efficiency, and suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking. Compared with the related unscented Kalman filter for eye tracking, the proposed filter has potential advantages in robustness, convergence speed, and tracking accuracy. The final experimental results show the validity of our method for eye tracking under realistic conditions. (classical areas of phenomenology)

  17. GENFIT - a generic track-fitting toolkit

    Energy Technology Data Exchange (ETDEWEB)

    Rauch, Johannes [Technische Universitaet Muenchen (Germany); Schlueter, Tobias [Ludwig-Maximilians-Universitaet Muenchen (Germany)

    2014-07-01

    GENFIT is an experiment-independent track-fitting toolkit, which combines fitting algorithms, track representations, and measurement geometries into a modular framework. We report on a significantly improved version of GENFIT, based on experience gained in the Belle II, PANDA, and FOPI experiments. Improvements concern the implementation of additional track-fitting algorithms, enhanced implementations of Kalman fitters, enhanced visualization capabilities, and additional implementations of measurement types suited for various kinds of tracking detectors. The data model has been revised, allowing for efficient track merging, smoothing, residual calculation and alignment.

  18. Particle filtering for passive fathometer tracking.

    Science.gov (United States)

    Michalopoulou, Zoi-Heleni; Yardim, Caglar; Gerstoft, Peter

    2012-01-01

    Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model particle filter with an uncertain number of reflectors. Results are compared to a classical particle filter where the number of reflectors is considered to be known. Reflector tracking is demonstrated for both conventional and adaptive processing applied to the drifting array data from the Boundary 2003 experiment. The layering information is successfully tracked by the multiple model particle filter even for noisy fathometer outputs. © 2012 Acoustical Society of America.

  19. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

    Science.gov (United States)

    Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; Masciovecchio, Mario; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

    2017-08-01

    For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

  20. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

    Directory of Open Access Journals (Sweden)

    Cerati Giuseppe

    2017-01-01

    Full Text Available For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU, ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC, for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

  1. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

    Energy Technology Data Exchange (ETDEWEB)

    Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U.; Riley, Daniel [Cornell U., LNS; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

    2017-01-01

    For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

  2. A novel strong tracking finite-difference extended Kalman filter for nonlinear eye tracking

    Institute of Scientific and Technical Information of China (English)

    ZHANG ZuTao; ZHANG JiaShu

    2009-01-01

    Non-Intrusive methods for eye tracking are Important for many applications of vision-based human computer interaction. However, due to the high nonlinearity of eye motion, how to ensure the robust-ness of external interference and accuracy of eye tracking poses the primary obstacle to the integration of eye movements into today's interfaces. In this paper, we present a strong tracking finite-difference extended Kalman filter algorithm, aiming to overcome the difficulty In modeling nonlinear eye tracking. In filtering calculation, strong tracking factor is introduced to modify a priori covariance matrix and im-prove the accuracy of the filter. The filter uses finite-difference method to calculate partial derivatives of nonlinear functions for eye tracking. The latest experimental results show the validity of our method for eye tracking under realistic conditions.

  3. 3D head pose estimation and tracking using particle filtering and ICP algorithm

    KAUST Repository

    Ben Ghorbel, Mahdi; Baklouti, Malek; Couvet, Serge

    2010-01-01

    This paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.

  4. Particle Filter Tracking without Dynamics

    Directory of Open Access Journals (Sweden)

    Jaime Ortegon-Aguilar

    2007-01-01

    Full Text Available People tracking is an interesting topic in computer vision. It has applications in industrial areas such as surveillance or human-machine interaction. Particle Filters is a common algorithm for people tracking; challenging situations occur when the target's motion is poorly modelled or with unexpected motions. In this paper, an alternative to address people tracking is presented. The proposed algorithm is based in particle filters, but instead of using a dynamical model, it uses background subtraction to predict future locations of particles. The algorithm is able to track people in omnidirectional sequences with a low frame rate (one or two frames per second. Our approach can tackle unexpected discontinuities and changes in the direction of the motion. The main goal of the paper is to track people from laboratories, but it has applications in surveillance, mainly in controlled environments.

  5. Bayesian target tracking based on particle filter

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

  6. Passive target tracking using marginalized particle filter

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A marginalized particle filtering(MPF)approach is proposed for target tracking under the background of passive measurement.Essentially,the MPF is a combination of particle filtering technique and Kalman filter.By making full use of marginalization,the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter,and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter.Simulation studies are performed on an illustrative example,and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation.Real data test results also validate the effectiveness of the presented method.

  7. Traditional Tracking with Kalman Filter on Parallel Architectures

    Science.gov (United States)

    Cerati, Giuseppe; Elmer, Peter; Lantz, Steven; MacNeill, Ian; McDermott, Kevin; Riley, Dan; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

    2015-05-01

    Power density constraints are limiting the performance improvements of modern CPUs. To address this, we have seen the introduction of lower-power, multi-core processors, but the future will be even more exciting. In order to stay within the power density limits but still obtain Moore's Law performance/price gains, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Example technologies today include Intel's Xeon Phi and GPGPUs. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High Luminosity LHC, for example, this will be by far the dominant problem. The most common track finding techniques in use today are however those based on the Kalman Filter. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. We report the results of our investigations into the potential and limitations of these algorithms on the new parallel hardware.

  8. Kalman filters for real-time magnetic island phase tracking

    International Nuclear Information System (INIS)

    Borgers, D.P.; Lauret, M.; Baar, M.R. de

    2013-01-01

    Highlights: • We propose two Kalman filters for tracking of NTMs on ASDEX Upgrade. • The Kalman filters can track NTMs in a much larger frequency range than PLLs. • The filters are tested on synthetic and experimental data from TEXTOR and TCV. • We conclude that the unscented Kalman filter can be useful for NTM control. -- Abstract: For control of neoclassical tearing modes (NTMs) and the resulting rotating magnetic islands in tokamak plasmas, the frequency and phase of the magnetic islands need to be accurately tracked in real-time. In previous experiments on TEXTOR, this was achieved using a phase-locked loop (PLL). For ASDEX Upgrade however, the desired frequency range in which the islands are to be tracked (100 Hz–10 kHz) is much larger than is possible with a PLL. In this contribution, an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are proposed for real-time frequency, phase and amplitude tracking of sinusoidal signals, based on noisy measurements. Compared to PLLs, the EKF and UKF are able to track sinusoidal signals in a much larger frequency range. The filters are applied on synthetic data and on experimental data from the TEXTOR and TCV tokamaks, from which we conclude that the UKF can be useful for real-time control of magnetic islands on ASDEX Upgrade

  9. Kalman filters for real-time magnetic island phase tracking

    Energy Technology Data Exchange (ETDEWEB)

    Borgers, D.P. [Hybrid and Networked Systems, Department of Mechanical Engineering – Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Lauret, M., E-mail: M.Lauret@tue.nl [FOM Institute DIFFER – Dutch Institute for Fundamental Energy Research, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, Nieuwegein (Netherlands); Control Systems Technology, Department of Mechanical Engineering – Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Baar, M.R. de [FOM Institute DIFFER – Dutch Institute for Fundamental Energy Research, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, Nieuwegein (Netherlands); Control Systems Technology, Department of Mechanical Engineering – Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

    2013-11-15

    Highlights: • We propose two Kalman filters for tracking of NTMs on ASDEX Upgrade. • The Kalman filters can track NTMs in a much larger frequency range than PLLs. • The filters are tested on synthetic and experimental data from TEXTOR and TCV. • We conclude that the unscented Kalman filter can be useful for NTM control. -- Abstract: For control of neoclassical tearing modes (NTMs) and the resulting rotating magnetic islands in tokamak plasmas, the frequency and phase of the magnetic islands need to be accurately tracked in real-time. In previous experiments on TEXTOR, this was achieved using a phase-locked loop (PLL). For ASDEX Upgrade however, the desired frequency range in which the islands are to be tracked (100 Hz–10 kHz) is much larger than is possible with a PLL. In this contribution, an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are proposed for real-time frequency, phase and amplitude tracking of sinusoidal signals, based on noisy measurements. Compared to PLLs, the EKF and UKF are able to track sinusoidal signals in a much larger frequency range. The filters are applied on synthetic data and on experimental data from the TEXTOR and TCV tokamaks, from which we conclude that the UKF can be useful for real-time control of magnetic islands on ASDEX Upgrade.

  10. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U., Phys. Dept.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U., Phys. Dept.; Riley, Daniel [Cornell U., Phys. Dept.; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U., Phys. Dept.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

    2017-11-16

    Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Examples include the Intel Xeon Phi, GPGPUs, and similar technologies. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.

  11. A new three-dimensional track fit with multiple scattering

    International Nuclear Information System (INIS)

    Berger, Niklaus; Kozlinskiy, Alexandr; Kiehn, Moritz; Schöning, André

    2017-01-01

    Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

  12. A new three-dimensional track fit with multiple scattering

    Energy Technology Data Exchange (ETDEWEB)

    Berger, Niklaus; Kozlinskiy, Alexandr [Physikalisches Institut, Heidelberg University, Heidelberg (Germany); Institut für Kernphysik and PRISMA cluster of excellence, Mainz University, Mainz (Germany); Kiehn, Moritz; Schöning, André [Physikalisches Institut, Heidelberg University, Heidelberg (Germany)

    2017-02-01

    Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

  13. Correlation Filter Learning Toward Peak Strength for Visual Tracking.

    Science.gov (United States)

    Sui, Yao; Wang, Guanghui; Zhang, Li

    2018-04-01

    This paper presents a novel visual tracking approach to correlation filter learning toward peak strength of correlation response. Previous methods leverage all features of the target and the immediate background to learn a correlation filter. Some features, however, may be distractive to tracking, like those from occlusion and local deformation, resulting in unstable tracking performance. This paper aims at solving this issue and proposes a novel algorithm to learn the correlation filter. The proposed approach, by imposing an elastic net constraint on the filter, can adaptively eliminate those distractive features in the correlation filtering. A new peak strength metric is proposed to measure the discriminative capability of the learned correlation filter. It is demonstrated that the proposed approach effectively strengthens the peak of the correlation response, leading to more discriminative performance than previous methods. Extensive experiments on a challenging visual tracking benchmark demonstrate that the proposed tracker outperforms most state-of-the-art methods.

  14. Random set particle filter for bearings-only multitarget tracking

    Science.gov (United States)

    Vihola, Matti

    2005-05-01

    The random set approach to multitarget tracking is a theoretically sound framework that covers joint estimation of the number of targets and the state of the targets. This paper describes a particle filter implementation of the random set multitarget filter. The contribution of this paper to the random set tracking framework is the formulation of a measurement model where each sensor report is assumed to contain at most one measurement. The implemented filter was tested in synthetic bearings-only tracking scenarios containing up to two targets in the presence of false alarms and missed measurements. The estimated target state consisted of 2D position and velocity components. The filter was capable to track the targets fairly well despite of the missing measurements and the relatively high false alarm rates. In addition, the filter showed robustness against wrong parameter values of false alarm rates. The results that were obtained during the limited tests of the filter show that the random set framework has potential for challenging tracking situations. On the other hand, the computational burden of the described implementation is quite high and increases approximately linearly with respect to the expected number of targets.

  15. Multisensor Distributed Track Fusion AlgorithmBased on Strong Tracking Filter and Feedback Integration1)

    Institute of Scientific and Technical Information of China (English)

    YANGGuo-Sheng; WENCheng-Lin; TANMin

    2004-01-01

    A new multisensor distributed track fusion algorithm is put forward based on combiningthe feedback integration with the strong tracking Kalman filter. Firstly, an effective tracking gateis constructed by taking the intersection of the tracking gates formed before and after feedback.Secondly, on the basis of the constructed effective tracking gate, probabilistic data association andstrong tracking Kalman filter are combined to form the new multisensor distributed track fusionalgorithm. At last, simulation is performed on the original algorithm and the algorithm presented.

  16. Visual object tracking by correlation filters and online learning

    Science.gov (United States)

    Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

    2018-06-01

    Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

  17. Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

    Directory of Open Access Journals (Sweden)

    M. Sanjeev Arulampalam

    2004-11-01

    Full Text Available We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs. Three different (PFs are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS framework. The proposed filters are (i multiple model PF (MMPF, (ii auxiliary MMPF (AUX-MMPF, and (iii jump Markov system PF (JMS-PF. The performance of these filters is compared with that of standard interacting multiple model (IMM-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i single-sensor case, (ii multisensor case, and (iii tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.

  18. The FitTrack Index as fitness indicator: A pilot study | van Rensburg ...

    African Journals Online (AJOL)

    Conclusions: These results suggest that the web-based FitTrack Index may be considered an appropriate tool to evaluate exercise capacity and cardiovascular fitness in healthy individuals following an aerobic training programme. Keywords: Aerobic fitness, Exercise ability, Recreational fitness, Cardiovascular fitness, ...

  19. Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning

    Institute of Scientific and Technical Information of China (English)

    XIAO Kun; FANG Shao-ji; PANG Yong-jie

    2007-01-01

    To improve underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.

  20. Robotic fish tracking method based on suboptimal interval Kalman filter

    Science.gov (United States)

    Tong, Xiaohong; Tang, Chao

    2017-11-01

    Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

  1. Learning based particle filtering object tracking for visible-light systems.

    Science.gov (United States)

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  2. Nonlinear Principal Component Analysis Using Strong Tracking Filter

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The paper analyzes the problem of blind source separation (BSS) based on the nonlinear principal component analysis (NPCA) criterion. An adaptive strong tracking filter (STF) based algorithm was developed, which is immune to system model mismatches. Simulations demonstrate that the algorithm converges quickly and has satisfactory steady-state accuracy. The Kalman filtering algorithm and the recursive leastsquares type algorithm are shown to be special cases of the STF algorithm. Since the forgetting factor is adaptively updated by adjustment of the Kalman gain, the STF scheme provides more powerful tracking capability than the Kalman filtering algorithm and recursive least-squares algorithm.

  3. Tracking of multiple objects with time-adjustable composite correlation filters

    Science.gov (United States)

    Ruchay, Alexey; Kober, Vitaly; Chernoskulov, Ilya

    2017-09-01

    An algorithm for tracking of multiple objects in video based on time-adjustable adaptive composite correlation filtering is proposed. For each frame a bank of composite correlation filters are designed in such a manner to provide invariance to pose, occlusion, clutter, and illumination changes. The filters are synthesized with the help of an iterative algorithm, which optimizes the discrimination capability for each object. The filters are adapted to the objects changes online using information from the current and past scene frames. Results obtained with the proposed algorithm using real-life scenes are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing.

  4. Further studies on the filtration of liquids using Kapton nuclear track micro filters

    International Nuclear Information System (INIS)

    Guo, S.L.; Ganz, M.; Fuest, M.; Vater, P.; Brandt, R.

    1990-01-01

    The flow rate of some liquids (water, heptane, toluene, xylene, dodecane) through Kapton nuclear track filters has been measured. The results can be interpreted with a modified Poiseuille formula. The influence of the viscosity of the liquids on their throughput through Kapton nuclear track filters has been determined. The purification of liquids with Kapton filters has been investigated. It is possible to measure the density of solid particles in deionized water by using Kapton filters. Consequently, nuclear track filters can remove solid particles from high-purity liquids. The soaking effect of some common liquid chemicals on Kapton filters has also been studied, no such soaking could be observed in most of the cases. Finally, these Kapton nuclear track filters are compared with a filter device from Hamamatsu (Japan). (orig.) [de

  5. Track filter on the basis of a cellular automation

    International Nuclear Information System (INIS)

    Glazov, A.A.; Kisel', I.V.; Konotopskaya, E.V.; Ososkov, G.A.

    1991-01-01

    The filtering method for tracks in discrete detectors based on the cellular automation is described. Results of the application of this method to experimental data (the spectrometer ARES) are quite successful: threefold reduction of input information with data grouping according to their belonging to separate tracks. They lift up percentage of useful events, which simplifies and accelerates considerably their next recognition. The described cellular automation for track filtering can be successfully applied in parallel computers and also in on-line mode if hardware implementation is used. 21 refs.; 11 figs

  6. PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

    Directory of Open Access Journals (Sweden)

    Wei Leong Khong

    2014-02-01

    Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

  7. Adaptive filtering for hidden node detection and tracking in networks.

    Science.gov (United States)

    Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L

    2017-07-01

    The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.

  8. Nonlinear Vibration Signal Tracking of Large Offshore Bridge Stayed Cable Based on Particle Filter

    Directory of Open Access Journals (Sweden)

    Ye Qingwei

    2015-12-01

    Full Text Available The stayed cables are key stress components of large offshore bridge. The fault detection of stayed cable is very important for safe of large offshore bridge. A particle filter model and algorithm of nonlinear vibration signal are used in this paper. Firstly, the particle filter model of stayed cable of large offshore bridge is created. Nonlinear dynamic model of the stayed-cable and beam coupling system is dispersed in temporal dimension by using the finite difference method. The discrete nonlinear vibration equations of any cable element are worked out. Secondly, a state equation of particle filter is fitted by least square algorithm from the discrete nonlinear vibration equations. So the particle filter algorithm can use the accurate state equations. Finally, the particle filter algorithm is used to filter the vibration signal of bridge stayed cable. According to the particle filter, the de-noised vibration signal can be tracked and be predicted for a short time accurately. Many experiments are done at some actual bridges. The simulation experiments and the actual experiments on the bridge stayed cables are all indicating that the particle filter algorithm in this paper has good performance and works stably.

  9. Track reconstruction for the Mu3e experiment based on a novel Multiple Scattering fit

    Directory of Open Access Journals (Sweden)

    Kozlinskiy Alexandr

    2017-01-01

    Full Text Available The Mu3e experiment is designed to search for the lepton flavor violating decay μ+ → e+e+e−. The aim of the experiment is to reach a branching ratio sensitivity of 10−16. In a first phase the experiment will be performed at an existing beam line at the Paul-Scherrer Institute (Switzerland providing 108 muons per second, which will allow to reach a sensitivity of 2 · 10−15. The muons with a momentum of about 28 MeV/c are stopped and decay at rest on a target. The decay products (positrons and electrons with energies below 53MeV are measured by a tracking detector consisting of two double layers of 50 μm thin silicon pixel sensors. The high granularity of the pixel detector with a pixel size of 80 μm × 80 μm allows for a precise track reconstruction in the high multiplicity environment of the Mu3e experiment, reaching 100 tracks per reconstruction frame of 50 ns in the final phase of the experiment. To deal with such high rates and combinatorics, the Mu3e track reconstruction uses a novel fit algorithm that in the simplest case takes into account only the multiple scattering, which allows for a fast online tracking on a GPU based filter farm. An implementation of the 3-dimensional multiple scattering fit based on hit triplets is described. The extension of the fit that takes into account energy losses and pixel size is used for offline track reconstruction. The algorithm and performance of the offline track reconstruction based on a full Geant4 simulation of the Mu3e detector are presented.

  10. Track finding and fitting in the H1 Forward Track Detector

    International Nuclear Information System (INIS)

    Burke, S.; Henderson, R.C.W.; Maxfield, S.J.; Patel, G.D.; Morris, J.V.; Sankey, D.P.C.; Skillicorn, I.O.

    1995-07-01

    The tracking environment in the H1 Forward Tracker Detector, where the hit multiplicity from proton fragments is high, is parituclarly hostile. The techniques and software which have been developed for pattern recognition and Kalman fitting of charged particle tracks in this region are described in detail. (orig.)

  11. Modified Extended Kalman Filtering for Tracking with Insufficient and Intermittent Observations

    Directory of Open Access Journals (Sweden)

    Pengpeng Chen

    2015-01-01

    Full Text Available This paper is concerned with the Kalman filtering problem for tracking a single target on the fixed-topology wireless sensor networks (WSNs. Both the insufficient anchor coverage and the packet dropouts have been taken into consideration in the filter design. The resulting tracking system is modeled as a multichannel nonlinear system with multiplicative noise. Noting that the channels may be correlated with each other, we use a general matrix to express the multiplicative noise. Then, a modified extended Kalman filtering algorithm is presented based on the obtained model to achieve high tracking accuracy. In particular, we evaluate the effect of various parameters on the tracking performance through simulation studies.

  12. Some Aspects on Filter Design for Target Tracking

    Directory of Open Access Journals (Sweden)

    Bertil Ekstrand

    2012-01-01

    Full Text Available Tracking filter design is discussed. It is argued that the basis of the present stochastic paradigm is questionable. White process noise is not adequate as a model for target manoeuvring, stochastic least-square optimality is not relevant or required in practice, the fact that requirements are necessary for design is ignored, and root mean square (RMS errors are insufficient as performance measure. It is argued that there is no process noise and that the covariance of the assumed process noise contains the design parameters. Focus is on the basic tracking filter, the Kalman filter, which is convenient for clarity and simplicity, but the arguments and conclusions are relevant in general. For design the possibility of an observer transfer function approach is pointed out. The issues can also be considered as a consequence of the fact that there is a difference between estimation and design. The - filter is used for illustration.

  13. On tempo tracking: Tempogram representation and Kalman filtering

    NARCIS (Netherlands)

    Cemgil, A.T.; Kappen, H.J.; Desain, P.W.M.; Honing, H.J.

    2001-01-01

    We formulate tempo tracking in a Bayesian framework where a tempo tracker is modeled as a stochastic dynamical system. The tempo is modeled as a hidden state variable of the system and is estimated by a Kalman filter. The Kalman filter operates on a Tempogram, a wavelet-like multiscale expansion of

  14. Multi-parameter studies of environmental aerosols with cascade track filters

    International Nuclear Information System (INIS)

    Ensinger, W.; Guo, S.-L.; Vater, P.; Brandt, R.

    2005-01-01

    Aerosols in the air in a factory processing nuclear reactor fuel material were collected by using cascade Kapton track filters with outer pore sizes of 12.8, 4.0 and 1.0μm consecutively and a conventional filter of glass fiber being behind to collect all aerosol particles left-over. The volume of air passed through the filters was measured by a flow meter. The weight of aerosol particles on each filter was obtained by the weight difference of the filter before and after collection of aerosol particles. α-activity on each filter was measured with a methane gas flow proportional counter. The sizes and elemental compositions of aerosol particles on the filters were analyzed by using a scanning electron microscope and an electron microprobe. Special attention was given to uranium aerosol particles. The median sizes of uranium aerosol particles were obtained being 1.97, 1.33 and 0.72μm on the first, second and third filter, respectively. The median size of all the uranium aerosol particles on the three track filters was 1.25μm

  15. Maximum Correntropy Criterion Kalman Filter for α-Jerk Tracking Model with Non-Gaussian Noise

    Directory of Open Access Journals (Sweden)

    Bowen Hou

    2017-11-01

    Full Text Available As one of the most critical issues for target track, α -jerk model is an effective maneuver target track model. Non-Gaussian noises always exist in the track process, which usually lead to inconsistency and divergence of the track filter. A novel Kalman filter is derived and applied on α -jerk tracking model to handle non-Gaussian noise. The weighted least square solution is presented and the standard Kalman filter is deduced firstly. A novel Kalman filter with the weighted least square based on the maximum correntropy criterion is deduced. The robustness of the maximum correntropy criterion is also analyzed with the influence function and compared with the Huber-based filter, and, moreover, the kernel size of Gaussian kernel plays an important role in the filter algorithm. A new adaptive kernel method is proposed in this paper to adjust the parameter in real time. Finally, simulation results indicate the validity and the efficiency of the proposed filter. The comparison study shows that the proposed filter can significantly reduce the noise influence for α -jerk model.

  16. Ballistic target tracking algorithm based on improved particle filtering

    Science.gov (United States)

    Ning, Xiao-lei; Chen, Zhan-qi; Li, Xiao-yang

    2015-10-01

    Tracking ballistic re-entry target is a typical nonlinear filtering problem. In order to track the ballistic re-entry target in the nonlinear and non-Gaussian complex environment, a novel chaos map particle filter (CMPF) is used to estimate the target state. CMPF has better performance in application to estimate the state and parameter of nonlinear and non-Gassuian system. The Monte Carlo simulation results show that, this method can effectively solve particle degeneracy and particle impoverishment problem by improving the efficiency of particle sampling to obtain the better particles to part in estimation. Meanwhile CMPF can improve the state estimation precision and convergence velocity compared with EKF, UKF and the ordinary particle filter.

  17. Joint Conditional Random Field Filter for Multi-Object Tracking

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2011-03-01

    Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

  18. UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data

    Directory of Open Access Journals (Sweden)

    Karen Uribe-Murcia

    2018-01-01

    Full Text Available In smart cities, vehicles tracking is organized to increase safety by localizing cars using the Global Positioning System (GPS. The GPS-based system provides accurate tracking but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response (UFIR filter, which meets these needs as being more robust than the Kalman filter (KF. The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs with time-stamped data discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. Applications are given for measurement data, which are cooperatively transferred from a vehicle to a central station through several nodes with k-step-lags. Better tracking performance of the UFIR filter is shown experimentally.

  19. Optimum track fitting in the presence of multiple scattering

    International Nuclear Information System (INIS)

    Lutz, G.

    1987-06-01

    A method for track fitting is proposed which attempts to be as close as possible to the real track along the full path length. This is done by the introduction of scattering planes in which the particle is allowed to change its direction. A fit over the full track length includes the probability of direction change by scattering. Using matrix notation a fairly simple formalism for error estimation has been developed. Results of this method are compared to those of more widely used procedures for 'typical' examples of High Energy Spectrometers. (orig.)

  20. A comparative study of track reconstruction methods in the context of CMS physics

    International Nuclear Information System (INIS)

    Winkler, M.

    2002-05-01

    This thesis deals mainly with the problem of reconstructing the tracks of charged particles from the measurements recorded by the CMS Tracker, in particular with track fitting. The task of the track fit is to use the available information (the subsets of hits belonging to the track of a particle found by a track finder) in a statistically optimal way for the estimation of the track parameters and the associated errors. Due to the high track multiplicity at LHC and the large background of noise hits, combinatorial methods such as the Kalman filter may have problems in the association of hits to tracks, and their results will be biased in the case of wrong hits assigned to a track. Recently developped non-linear, adaptive methods such as the deterministic annealing filter and the multi track filter try to solve the assignment problem during the track fit, by determining an assignment probability of a hit to a track. The methods are studied in the CMS Tracker using various event topologies. (author)

  1. Using Gaussian Process Annealing Particle Filter for 3D Human Tracking

    Directory of Open Access Journals (Sweden)

    Michael Rudzsky

    2008-01-01

    Full Text Available We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian process annealing particle filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker's stability and robustness. Comparing with a regular annealed particle filter-based tracker, we show that our algorithm can track better for low frame rate videos. We also show that our algorithm is capable of recovering after a temporal target loss.

  2. Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

    Directory of Open Access Journals (Sweden)

    Jing Liu

    2012-01-01

    Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

  3. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

    Science.gov (United States)

    Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

    2017-03-03

    We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  4. Estimation of three-dimensional radar tracking using modified extended kalman filter

    Science.gov (United States)

    Aditya, Prima; Apriliani, Erna; Khusnul Arif, Didik; Baihaqi, Komar

    2018-03-01

    Kalman filter is an estimation method by combining data and mathematical models then developed be extended Kalman filter to handle nonlinear systems. Three-dimensional radar tracking is one of example of nonlinear system. In this paper developed a modification method of extended Kalman filter from the direct decline of the three-dimensional radar tracking case. The development of this filter algorithm can solve the three-dimensional radar measurements in the case proposed in this case the target measured by radar with distance r, azimuth angle θ, and the elevation angle ϕ. Artificial covariance and mean adjusted directly on the three-dimensional radar system. Simulations result show that the proposed formulation is effective in the calculation of nonlinear measurement compared with extended Kalman filter with the value error at 0.77% until 1.15%.

  5. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

    Directory of Open Access Journals (Sweden)

    Anthony Hoak

    2017-03-01

    Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  6. Dual linear structured support vector machine tracking method via scale correlation filter

    Science.gov (United States)

    Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

    2018-01-01

    Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

  7. Electron microscope studies on nuclear track filters

    International Nuclear Information System (INIS)

    Roell, I.; Siegmon, W.

    1982-01-01

    Nuclear track filters became more and more important in various fields of application. The filtration process can be described by a set of suitable parameters. For some applications it may be necessary to know the structure of the surface and the pores themselves. In most cases the etching process yields surfaces and pore geometries that are quite different from ideal planes and cylinders. In the presented work the production of different filter types will be described. The resulting surfaces and pore structures have been investigated by means of a scanning electron microscope. (author)

  8. A low-complexity interacting multiple model filter for maneuvering target tracking

    KAUST Repository

    Khalid, Syed Safwan; Abrar, Shafayat

    2017-01-01

    In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

  9. A low-complexity interacting multiple model filter for maneuvering target tracking

    KAUST Repository

    Khalid, Syed Safwan

    2017-01-22

    In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

  10. INFLUENCE OF STOCHASTIC NOISE STATISTICS ON KALMAN FILTER PERFORMANCE BASED ON VIDEO TARGET TRACKING

    Institute of Scientific and Technical Information of China (English)

    Chen Ken; Napolitano; Zhang Yun; Li Dong

    2010-01-01

    The system stochastic noises involved in Kalman filtering are preconditioned on being ideally white and Gaussian distributed. In this research,efforts are exerted on exploring the influence of the noise statistics on Kalman filtering from the perspective of video target tracking quality. The correlation of tracking precision to both the process and measurement noise covariance is investigated; the signal-to-noise power density ratio is defined; the contribution of predicted states and measured outputs to Kalman filter behavior is discussed; the tracking precision relative sensitivity is derived and applied in this study case. The findings are expected to pave the way for future study on how the actual noise statistics deviating from the assumed ones impacts on the Kalman filter optimality and degradation in the application of video tracking.

  11. An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.

    Science.gov (United States)

    Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

    2017-11-18

    Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio

  12. Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

    Science.gov (United States)

    Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

    2017-11-01

    Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

  13. Fish tracking by combining motion based segmentation and particle filtering

    Science.gov (United States)

    Bichot, E.; Mascarilla, L.; Courtellemont, P.

    2006-01-01

    In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

  14. Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

    Science.gov (United States)

    Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

    2017-11-01

    The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

  15. Interacting Multiple Model (IMM Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

    Directory of Open Access Journals (Sweden)

    Hua Liu

    2017-06-01

    Full Text Available For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF. The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF, the interacting multiple model cubature Kalman filter (IMMCKF and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF.

  16. Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

    Science.gov (United States)

    Liu, Hua; Wu, Wen

    2017-06-13

    For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

  17. An Improved Strong Tracking Cubature Kalman Filter for GPS/INS Integrated Navigation Systems.

    Science.gov (United States)

    Feng, Kaiqiang; Li, Jie; Zhang, Xi; Zhang, Xiaoming; Shen, Chong; Cao, Huiliang; Yang, Yanyu; Liu, Jun

    2018-06-12

    The cubature Kalman filter (CKF) is widely used in the application of GPS/INS integrated navigation systems. However, its performance may decline in accuracy and even diverge in the presence of process uncertainties. To solve the problem, a new algorithm named improved strong tracking seventh-degree spherical simplex-radial cubature Kalman filter (IST-7thSSRCKF) is proposed in this paper. In the proposed algorithm, the effect of process uncertainty is mitigated by using the improved strong tracking Kalman filter technique, in which the hypothesis testing method is adopted to identify the process uncertainty and the prior state estimate covariance in the CKF is further modified online according to the change in vehicle dynamics. In addition, a new seventh-degree spherical simplex-radial rule is employed to further improve the estimation accuracy of the strong tracking cubature Kalman filter. In this way, the proposed comprehensive algorithm integrates the advantage of 7thSSRCKF’s high accuracy and strong tracking filter’s strong robustness against process uncertainties. The GPS/INS integrated navigation problem with significant dynamic model errors is utilized to validate the performance of proposed IST-7thSSRCKF. Results demonstrate that the improved strong tracking cubature Kalman filter can achieve higher accuracy than the existing CKF and ST-CKF, and is more robust for the GPS/INS integrated navigation system.

  18. Disclosure and Fit Capability of the Filtering Facepiece Respirator.

    Science.gov (United States)

    Lofgren, Don J

    2018-05-01

    The filtering facepiece air-purifying respirator is annually purchased in the tens of millions and widely used for worker protection from harmful airborne particulates. The workplace consumers of this safety product, i.e., employers, workers, and safety and health professionals, have assurances of its effectiveness through the respirator certification and disclosure requirements of the National Institute for Occupational Safety and Health. However, the certification of a critical performance requirement has been missing for the approved filtering facepiece respirator since 1995: fit capability. Without this certification, consumers continue to be at risk of purchasing a respirator model that may fit a small percentage of the intended users. This commentary updates and expands an earlier one by this author, addresses the consequences of poorly fitting certified models on the market and lack of disclosure, and calls for further action by National Institute for Occupational Safety and Health to meet the needs and expectations of the consumer.

  19. A hand tracking algorithm with particle filter and improved GVF snake model

    Science.gov (United States)

    Sun, Yi-qi; Wu, Ai-guo; Dong, Na; Shao, Yi-zhe

    2017-07-01

    To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion.

  20. Event-triggered Kalman-consensus filter for two-target tracking sensor networks.

    Science.gov (United States)

    Su, Housheng; Li, Zhenghao; Ye, Yanyan

    2017-11-01

    This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event-triggered protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Application of Evolution Strategies to the Design of Tracking Filters with a Large Number of Specifications

    Directory of Open Access Journals (Sweden)

    Jesús García Herrero

    2003-07-01

    Full Text Available This paper describes the application of evolution strategies to the design of interacting multiple model (IMM tracking filters in order to fulfill a large table of performance specifications. These specifications define the desired filter performance in a thorough set of selected test scenarios, for different figures of merit and input conditions, imposing hundreds of performance goals. The design problem is stated as a numeric search in the filter parameters space to attain all specifications or at least minimize, in a compromise, the excess over some specifications as much as possible, applying global optimization techniques coming from evolutionary computation field. Besides, a new methodology is proposed to integrate specifications in a fitness function able to effectively guide the search to suitable solutions. The method has been applied to the design of an IMM tracker for a real-world civil air traffic control application: the accomplishment of specifications defined for the future European ARTAS system.

  2. Particle filters for object tracking: enhanced algorithm and efficient implementations

    International Nuclear Information System (INIS)

    Abd El-Halym, H.A.

    2010-01-01

    Object tracking and recognition is a hot research topic. In spite of the extensive research efforts expended, the development of a robust and efficient object tracking algorithm remains unsolved due to the inherent difficulty of the tracking problem. Particle filters (PFs) were recently introduced as a powerful, post-Kalman filter, estimation tool that provides a general framework for estimation of nonlinear/ non-Gaussian dynamic systems. Particle filters were advanced for building robust object trackers capable of operation under severe conditions (small image size, noisy background, occlusions, fast object maneuvers ..etc.). The heavy computational load of the particle filter remains a major obstacle towards its wide use.In this thesis, an Excitation Particle Filter (EPF) is introduced for object tracking. A new likelihood model is proposed. It depends on multiple functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modified the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. This modification is based on re-exciting the particles if their weights fall below a memorized weight value. The proposed enhanced PF is implemented in software and evaluated. Its results are compared with a single likelihood function PF tracker, Particle Swarm Optimization (PSO) tracker, a correlation tracker, as well as, an edge tracker. The experimental results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness, and occlusion compared with other methods Efficient novel hardware architectures of the Sample Important Re sample Filter (SIRF) and the EPF are implemented. Three novel hardware architectures of the SIRF for object tracking are introduced. The first architecture is a two-step sequential PF machine, where particle generation, weight calculation and normalization are carried out in parallel during the first step followed by a sequential re

  3. Modified unscented Kalman filter using modified filter gain and variance scale factor for highly maneuvering target tracking

    Institute of Scientific and Technical Information of China (English)

    Changyun Liu; Penglang Shui; Gang Wei; Song Li

    2014-01-01

    To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneu-vers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is pre-sented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter (UKF) via predicted variance Pk|k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneu-vering target compared with the standard UKF.

  4. Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

    Directory of Open Access Journals (Sweden)

    Hamza Benzerrouk

    2018-03-01

    Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

  5. Calorie counting and fitness tracking technology: Associations with eating disorder symptomatology.

    Science.gov (United States)

    Simpson, Courtney C; Mazzeo, Suzanne E

    2017-08-01

    The use of online calorie tracking applications and activity monitors is increasing exponentially. Anecdotal reports document the potential for these trackers to trigger, maintain, or exacerbate eating disorder symptomatology. Yet, research has not examined the relation between use of these devices and eating disorder-related attitudes and behaviors. This study explored associations between the use of calorie counting and fitness tracking devices and eating disorder symptomatology. Participants (N=493) were college students who reported their use of tracking technology and completed measures of eating disorder symptomatology. Individuals who reported using calorie trackers manifested higher levels of eating concern and dietary restraint, controlling for BMI. Additionally, fitness tracking was uniquely associated with ED symptomatology after adjusting for gender and bingeing and purging behavior within the past month. Findings highlight associations between use of calorie and fitness trackers and eating disorder symptomatology. Although preliminary, overall results suggest that for some individuals, these devices might do more harm than good. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Signal Tracking Beyond the Time Resolution of an Atomic Sensor by Kalman Filtering

    Science.gov (United States)

    Jiménez-Martínez, Ricardo; Kołodyński, Jan; Troullinou, Charikleia; Lucivero, Vito Giovanni; Kong, Jia; Mitchell, Morgan W.

    2018-01-01

    We study causal waveform estimation (tracking) of time-varying signals in a paradigmatic atomic sensor, an alkali vapor monitored by Faraday rotation probing. We use Kalman filtering, which optimally tracks known linear Gaussian stochastic processes, to estimate stochastic input signals that we generate by optical pumping. Comparing the known input to the estimates, we confirm the accuracy of the atomic statistical model and the reliability of the Kalman filter, allowing recovery of waveform details far briefer than the sensor's intrinsic time resolution. With proper filter choice, we obtain similar benefits when tracking partially known and non-Gaussian signal processes, as are found in most practical sensing applications. The method evades the trade-off between sensitivity and time resolution in coherent sensing.

  7. A Method of Time-Varying Rayleigh Channel Tracking in MIMO Radio System

    Institute of Scientific and Technical Information of China (English)

    GONG Yan-fei; HE Zi-shu; HAN Chun-lin

    2005-01-01

    A method of MIMO channel tracking based on Kalman filter and MMSE-DFE is proposed. The Kalman filter tracks the time-varying channel by using the MMSE-DFE decision and the MMSE-DFE conducts the next decision by using the channel estimates produced by the Kalman filter. Polynomial fitting is used to bridge the gap between the channel estimates produced by the Kalman filter and those needed for the DFE decision. Computer simulation demonstrates that this method can track the MIMO time-varying channel effectively.

  8. A-Track: Detecting Moving Objects in FITS images

    Science.gov (United States)

    Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

    2017-04-01

    A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

  9. SURFACE FITTING FILTERING OF LIDAR POINT CLOUD WITH WAVEFORM INFORMATION

    Directory of Open Access Journals (Sweden)

    S. Xing

    2017-09-01

    Full Text Available Full-waveform LiDAR is an active technology of photogrammetry and remote sensing. It provides more detailed information about objects along the path of a laser pulse than discrete-return topographic LiDAR. The point cloud and waveform information with high quality can be obtained by waveform decomposition, which could make contributions to accurate filtering. The surface fitting filtering method with waveform information is proposed to present such advantage. Firstly, discrete point cloud and waveform parameters are resolved by global convergent Levenberg Marquardt decomposition. Secondly, the ground seed points are selected, of which the abnormal ones are detected by waveform parameters and robust estimation. Thirdly, the terrain surface is fitted and the height difference threshold is determined in consideration of window size and mean square error. Finally, the points are classified gradually with the rising of window size. The filtering process is finished until window size is larger than threshold. The waveform data in urban, farmland and mountain areas from “WATER (Watershed Allied Telemetry Experimental Research” are selected for experiments. Results prove that compared with traditional method, the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.

  10. CATS: a cellular automaton for tracking in silicon for the HERA-B vertex detector

    International Nuclear Information System (INIS)

    Abt, I.; Emeliyanov, D.; Kisel, I.; Masciocchi, S.

    2002-01-01

    The new track reconstruction program CATS developed for the Vertex Detector System of the HERA-B experiment at DESY is presented. It employs a cellular automaton for track searching and the Kalman filter for track fitting. This results in a very fast algorithm that combines highly efficient track recognition with accurate and reliable track parameter estimation. To reduce the computational cost of the fit an optimized numerical implementation of the Kalman filter is used. Alternative approaches to the track reconstruction in the VDS are also discussed. Since 1999, after extensive tests on simulated data, CATS has been employed to reconstruct experimental data collected in HERA-B. Results regarding tracking performance, the accuracy of track parameter estimates and CPU time consumption are presented

  11. Hierarchical Threshold Adaptive for Point Cloud Filter Algorithm of Moving Surface Fitting

    Directory of Open Access Journals (Sweden)

    ZHU Xiaoxiao

    2018-02-01

    Full Text Available In order to improve the accuracy,efficiency and adaptability of point cloud filtering algorithm,a hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting was proposed.Firstly,the noisy points are removed by using a statistic histogram method.Secondly,the grid index is established by grid segmentation,and the surface equation is set up through the lowest point among the neighborhood grids.The real height and fit are calculated.The difference between the elevation and the threshold can be determined.Finally,in order to improve the filtering accuracy,hierarchical filtering is used to change the grid size and automatically set the neighborhood size and threshold until the filtering result reaches the accuracy requirement.The test data provided by the International Photogrammetry and Remote Sensing Society (ISPRS is used to verify the algorithm.The first and second error and the total error are 7.33%,10.64% and 6.34% respectively.The algorithm is compared with the eight classical filtering algorithms published by ISPRS.The experiment results show that the method has well-adapted and it has high accurate filtering result.

  12. Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

    Directory of Open Access Journals (Sweden)

    Mónica A Silva

    Full Text Available Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km was nearly half that of LS estimates (11.6 ± 8.4 km. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

  13. GM-PHD Filter Combined with Track-Estimate Association and Numerical Interpolation

    Directory of Open Access Journals (Sweden)

    Jinguang Chen

    2015-01-01

    Full Text Available For the standard Gaussian mixture probability hypothesis density (GM-PHD filter, the number of targets can be overestimated if the clutter rate is too high or underestimated if the detection rate is too low. These problems seriously affect the accuracy of multitarget tracking for the number and the value of measurements and clutters cannot be distinguished and recognized. Therefore, we proposed an improved GM-PHD filter to tackle these problems. Firstly, a track-estimate association was implemented in the filtering process to detect and remove false-alarm targets. Secondly, a numerical interpolation technique was used to compensate the missing targets caused by low detection rate. At the end of this paper, simulation results were presented to demonstrate the proposed GM-PHD algorithm is more effective in estimating the number and state of targets than the previous ones.

  14. Joint polarization tracking and channel equalization based on radius-directed linear Kalman filter

    Science.gov (United States)

    Zhang, Qun; Yang, Yanfu; Zhong, Kangping; Liu, Jie; Wu, Xiong; Yao, Yong

    2018-01-01

    We propose a joint polarization tracking and channel equalization scheme based on radius-directed linear Kalman filter (RD-LKF) by introducing the butterfly finite-impulse-response (FIR) filter in our previously proposed RD-LKF method. Along with the fast polarization tracking, it can also simultaneously compensate the inter-symbol interference (ISI) effects including residual chromatic dispersion and polarization mode dispersion. Compared with the conventional radius-directed equalizer (RDE) algorithm, it is demonstrated experimentally that three times faster convergence speed, one order of magnitude better tracking capability, and better BER performance is obtained in polarization division multiplexing 16 quadrature amplitude modulation system. Besides, the influences of the algorithm parameters on the convergence and the tracking performance are investigated by numerical simulation.

  15. Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation : Robustness and Accuracy Assessment

    NARCIS (Netherlands)

    Bourque, Alexandra E; Bedwani, Stéphane; Carrier, Jean-François; Ménard, Cynthia; Borman, Pim; Bos, Clemens; Raaymakers, Bas W; Mickevicius, Nikolai; Paulson, Eric; Tijssen, Rob H N

    PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments. METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized

  16. The research of radar target tracking observed information linear filter method

    Science.gov (United States)

    Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

    2018-05-01

    Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

  17. Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

    Institute of Scientific and Technical Information of China (English)

    LI Shuo; TAO Ran

    2006-01-01

    We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

  18. Kalman Filter Based Tracking in an Video Surveillance System

    Directory of Open Access Journals (Sweden)

    SULIMAN, C.

    2010-05-01

    Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

  19. Chaotic secure communication based on strong tracking filtering

    International Nuclear Information System (INIS)

    Li Xiongjie; Xu Zhengguo; Zhou Donghua

    2008-01-01

    A scheme for implementing secure communication based on chaotic maps and strong tracking filter (STF) is presented, and a modified STF algorithm with message estimation is developed for the special requirement of chaotic secure communication. At the emitter, the message symbol is modulated by chaotic mapping and is output through a nonlinear function. At the receiver, the driving signal is received and the message symbol is recovered dynamically by the STF with estimation of message symbol. Simulation results of Holmes map demonstrate that when message symbols are binary codes, STF can effectively recover the codes of the message from the noisy chaotic signals. Compared with the extended Kalman filter (EKF), STF has a lower bit error rate

  20. Context-Aware Correlation Filter Tracking

    KAUST Repository

    Mueller, Matthias; Smith, Neil; Ghanem, Bernard

    2017-01-01

    Correlation filter (CF) based trackers have recently gained a lot of popularity due to their impressive performance on benchmark datasets, while maintaining high frame rates. A significant amount of recent research focuses on the incorporation of stronger features for a richer representation of the tracking target. However, this only helps to discriminate the target from background within a small neighborhood. In this paper, we present a framework that allows the explicit incorporation of global context within CF trackers. We reformulate the original optimization problem and provide a closed form solution for single and multi-dimensional features in the primal and dual domain. Extensive experiments demonstrate that this framework significantly improves the performance of many CF trackers with only a modest impact on frame rate.

  1. Context-Aware Correlation Filter Tracking

    KAUST Repository

    Mueller, Matthias

    2017-11-09

    Correlation filter (CF) based trackers have recently gained a lot of popularity due to their impressive performance on benchmark datasets, while maintaining high frame rates. A significant amount of recent research focuses on the incorporation of stronger features for a richer representation of the tracking target. However, this only helps to discriminate the target from background within a small neighborhood. In this paper, we present a framework that allows the explicit incorporation of global context within CF trackers. We reformulate the original optimization problem and provide a closed form solution for single and multi-dimensional features in the primal and dual domain. Extensive experiments demonstrate that this framework significantly improves the performance of many CF trackers with only a modest impact on frame rate.

  2. An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

    Science.gov (United States)

    Raihan A. V, Dilshad; Chakravorty, Suman

    2018-03-01

    Optimal and consistent estimation of the state of space objects is pivotal to surveillance and tracking applications. However, probabilistic estimation of space objects is made difficult by the non-Gaussianity and nonlinearity associated with orbital mechanics. In this paper, we present an unscented Kalman-particle hybrid filtering framework for recursive Bayesian estimation of space objects. The hybrid filtering scheme is designed to provide accurate and consistent estimates when measurements are sparse without incurring a large computational cost. It employs an unscented Kalman filter (UKF) for estimation when measurements are available. When the target is outside the field of view (FOV) of the sensor, it updates the state probability density function (PDF) via a sequential Monte Carlo method. The hybrid filter addresses the problem of particle depletion through a suitably designed filter transition scheme. To assess the performance of the hybrid filtering approach, we consider two test cases of space objects that are assumed to undergo full three dimensional orbital motion under the effects of J 2 and atmospheric drag perturbations. It is demonstrated that the hybrid filters can furnish fast, accurate and consistent estimates outperforming standard UKF and particle filter (PF) implementations.

  3. Preparation of Track Etch Membrane Filters Using Polystyrene Film

    International Nuclear Information System (INIS)

    Kaewsaenee, Jerawut; Ratanatongchai, Wichian; Supaphol, Pitt; Visal-athaphand, Pinpan

    2007-08-01

    Full text: Polystyrene nuclear track etch membrane filters was prepared by exposed 13 .m thin film polystyrene with fission fragment. Nuclear latent track was enlarged to through hole on the film by etching with 80 o C 40% H 2 SO 4 with K 2 Cr 2 O 7 solution for 6-10 hour. The hole size was depend on concentration of etching solution and etching time with 1.3-3.4 .m hole diameter. The flow rate test of water was 0.79-1.56 mm cm-2 min-1 at 109.8-113.7 kPa pressure

  4. Track fitting in the opal vertex detector with stereo wires

    Energy Technology Data Exchange (ETDEWEB)

    Shally, R; Hemingway, R J; McPherson, A C

    1987-10-01

    The geometry of the vertex chamber for the OPAL detector at LEP is reviewed and expressions for the coordinates of the hits are given in terms of the measured drift distance and z-coordinate. The tracks are fitted by a procedure based on the Lagrange multipliers method. The increase in the accuracy of the fit due to the use of the stereo wires is discussed.

  5. Track fitting in the opal vertex detector with stereo wires

    International Nuclear Information System (INIS)

    Shally, R.; Hemingway, R.J.; McPherson, A.C.

    1987-01-01

    The geometry of the vertex chamber for the OPAL detector at LEP is reviewed and expressions for the coordinates of the hits are given in terms of the measured drift distance and z-coordinate. The tracks are fitted by a procedure based on the Lagrange multipliers method. The increase in the accuracy of the fit due to the use of the stereo wires is discussed. (orig.)

  6. Kalman filter tracking on parallel architectures

    Science.gov (United States)

    Cerati, G.; Elmer, P.; Krutelyov, S.; Lantz, S.; Lefebvre, M.; McDermott, K.; Riley, D.; Tadel, M.; Wittich, P.; Wurthwein, F.; Yagil, A.

    2017-10-01

    We report on the progress of our studies towards a Kalman filter track reconstruction algorithm with optimal performance on manycore architectures. The combinatorial structure of these algorithms is not immediately compatible with an efficient SIMD (or SIMT) implementation; the challenge for us is to recast the existing software so it can readily generate hundreds of shared-memory threads that exploit the underlying instruction set of modern processors. We show how the data and associated tasks can be organized in a way that is conducive to both multithreading and vectorization. We demonstrate very good performance on Intel Xeon and Xeon Phi architectures, as well as promising first results on Nvidia GPUs.

  7. Frequency tracking and variable bandwidth for line noise filtering without a reference.

    Science.gov (United States)

    Kelly, John W; Collinger, Jennifer L; Degenhart, Alan D; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

    2011-01-01

    This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.

  8. Adaptive projective filters

    International Nuclear Information System (INIS)

    Dikusar, N.D.

    1993-01-01

    The new approach to solving of the finding problem is proposed. The method is based on Discrete Projective Transformations (DPT), the List Square Fitting (LSF) and uses the information feedback in tracing for linear or quadratic track segments (TS). The fast and stable with respect to measurement errors and background points recurrent algorithm is suggested. The algorithm realizes the family of digital adaptive projective filters (APF) with known nonlinear weight functions-projective invariants. APF can be used in adequate control systems for collection, processing and compression of data, including tracking problems for the wide class of detectors. 10 refs.; 9 figs

  9. Gaussian mixture probability hypothesis density filter for multipath multitarget tracking in over-the-horizon radar

    Science.gov (United States)

    Qin, Yong; Ma, Hong; Chen, Jinfeng; Cheng, Li

    2015-12-01

    Conventional multitarget tracking systems presume that each target can produce at most one measurement per scan. Due to the multiple ionospheric propagation paths in over-the-horizon radar (OTHR), this assumption is not valid. To solve this problem, this paper proposes a novel tracking algorithm based on the theory of finite set statistics (FISST) called the multipath probability hypothesis density (MP-PHD) filter in cluttered environments. First, the FISST is used to derive the update equation, and then Gaussian mixture (GM) is introduced to derive the closed-form solution of the MP-PHD filter. Moreover, the extended Kalman filter (EKF) is presented to deal with the nonlinear problem of the measurement model in OTHR. Eventually, the simulation results are provided to demonstrate the effectiveness of the proposed filter.

  10. Review of track-fitting methods in counter experiments

    International Nuclear Information System (INIS)

    Regler, M.; Eichinger, H.

    1981-01-01

    We review track-fitting methods recently used in high-energy physics experiments. Assuming that the problem of pattern recognition, i.e. of grouping the often ambiguous coordinate information (as frequently measured by wire chambers) together to form track candidates, has already been solved, we try to point out the way to obtain the ultimate geometrical resolution with the smallest and fastest possible program; owing to the wide variety of detectors and experimental set-ups, no universal method has been found. Some applications will serve as examples, and based on the experience gained we will try to indicate when and under which conditions a known algorithm could be used, and this might even help in designing future experiments. (orig.)

  11. Interface of the general fitting tool GENFIT2 in PandaRoot

    Science.gov (United States)

    Prencipe, Elisabetta; Spataro, Stefano; Stockmanns, Tobias; PANDA Collaboration

    2017-10-01

    \\bar{{{P}}}ANDA is a planned experiment at FAIR (Darmstadt) with a cooled antiproton beam in a range [1.5; 15] GeV/c, allowing a wide physics program in nuclear and particle physics. It is the only experiment worldwide, which combines a solenoid field (B=2T) and a dipole field (B=2Tm) in a spectrometer with a fixed target topology, in that energy regime. The tracking system of \\bar{{{P}}}ANDA involves the presence of a high performance silicon vertex detector, a GEM detector, a straw-tubes central tracker, a forward tracking system, and a luminosity monitor. The offline tracking algorithm is developed within the PandaRoot framework, which is a part of the FairRoot project. The tool here presented is based on algorithms containing the Kalman Filter equations and a deterministic annealing filter. This general fitting tool (GENFIT2) offers to users also a Runge-Kutta track representation, and interfaces with Millepede II (useful for alignment) and RAVE (vertex finder). It is independent on the detector geometry and the magnetic field map, and written in C++ object-oriented modular code. Several fitting algorithms are available with GENFIT2, with user-adjustable parameters; therefore the tool is of friendly usage. A check on the fit convergence is done by GENFIT2 as well. The Kalman-Filter-based algorithms have a wide range of applications; among those in particle physics they can perform extrapolations of track parameters and covariance matrices. The adoptions of the PandaRoot framework to connect to Genfit2 are described, and the impact of GENFIT2 on the physics simulations of \\bar{{{P}}}ANDA are shown: significant improvement is reported for those channels where a good low momentum tracking is required (pT < 400 MeV/c).

  12. Track reconstruction in CMS high luminosity environment

    CERN Document Server

    AUTHOR|(CDS)2067159

    2016-01-01

    The CMS tracker is the largest silicon detector ever built, covering 200 square meters and providing an average of 14 high-precision measurements per track. Tracking is essential for the reconstruction of objects like jets, muons, electrons and tau leptons starting from the raw data from the silicon pixel and strip detectors. Track reconstruction is widely used also at trigger level as it improves objects tagging and resolution.The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compat...

  13. Track reconstruction in CMS high luminosity environment

    CERN Document Server

    Goetzmann, Christophe

    2014-01-01

    The CMS tracker is the largest silicon detector ever built, covering 200 square meters and providing an average of 14 high-precision measurements per track. Tracking is essential for the reconstruction of objects like jets, muons, electrons and tau leptons starting from the raw data from the silicon pixel and strip detectors. Track reconstruction is widely used also at trigger level as it improves objects tagging and resolution.The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compat...

  14. A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers

    Science.gov (United States)

    Liu, Zhuowei; Chen, Shuxin; Wu, Hao; He, Renke; Hao, Lin

    2018-01-01

    In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student’s t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student’s t distribution as well as approximates the multi-target intensity as a mixture of Student’s t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student’s t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student’s t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers. PMID:29617348

  15. Track fitting and resolution with digital detectors

    International Nuclear Information System (INIS)

    Duerdoth, I.

    1982-01-01

    The analysis of data from detectors which give digitised measurements, such as MWPCs, is considered. These measurements are necessarily correlated and it is shown that the uncertainty in the combination of N measurements may fall faster than the canonical 1/√N. A new method of track fitting is described which exploits the digital aspects and which takes the correlations into account. It divides the parameter space into cells and the centroid of a cell is taken as the best estimate. The method is shown to have some advantages over the standard least-squares analysis. If the least-squares method is used for digital detectors the goodness-of-fit may not be a reliable estimate of the accuracy. The cell method is particularly suitable for implementation on microcomputers which lack floating point and divide facilities. (orig.)

  16. Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor.

    Science.gov (United States)

    Wu, Hao; Chen, Shuxin; Yang, Binfeng; Chen, Kun

    2016-05-09

    The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers' misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors.

  17. Detecting Power Voltage Dips using Tracking Filters - A Comparison against Kalman

    Directory of Open Access Journals (Sweden)

    STANCIU, I.-R.

    2012-11-01

    Full Text Available Due of its significant economical impact, Power-Quality (PQ analysis is an important domain today. Severe voltage distortions affect the consumers and disturb their activity. They may be caused by short circuits (in this case the voltage drops significantly or by varying loads (with a smaller drop. These two types are the PQ currently issues. Monitoring these phenomena (called dips or sags require powerful techniques. Digital Signal Processing (DSP algorithms are currently employed to fulfill this task. Discrete Wavelet Transforms, (and variants, Kalman filters, and S-Transform are currently proposed by researchers to detect voltage dips. This paper introduces and examines a new tool to detect voltage dips: the so-called tracking filters. Discovered and tested during the cold war, they can estimate a parameter of interest one-step-ahead based on the previously observed values. Two filters are implemented. Their performance is assessed by comparison against the Kalman filter?s results.

  18. An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

    Science.gov (United States)

    Li, Jian; Wei, Xinguo; Zhang, Guangjun

    2017-08-21

    Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

  19. Evaluation of an image-based tracking workflow with Kalman filtering for automatic image plane alignment in interventional MRI.

    Science.gov (United States)

    Neumann, M; Cuvillon, L; Breton, E; de Matheli, M

    2013-01-01

    Recently, a workflow for magnetic resonance (MR) image plane alignment based on tracking in real-time MR images was introduced. The workflow is based on a tracking device composed of 2 resonant micro-coils and a passive marker, and allows for tracking of the passive marker in clinical real-time images and automatic (re-)initialization using the microcoils. As the Kalman filter has proven its benefit as an estimator and predictor, it is well suited for use in tracking applications. In this paper, a Kalman filter is integrated in the previously developed workflow in order to predict position and orientation of the tracking device. Measurement noise covariances of the Kalman filter are dynamically changed in order to take into account that, according to the image plane orientation, only a subset of the 3D pose components is available. The improved tracking performance of the Kalman extended workflow could be quantified in simulation results. Also, a first experiment in the MRI scanner was performed but without quantitative results yet.

  20. Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

    Science.gov (United States)

    Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

    2014-11-11

    The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

  1. Target Response Adaptation for Correlation Filter Tracking

    KAUST Repository

    Bibi, Adel Aamer

    2016-09-16

    Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %-13.5% in precision and 3.2 %-13% in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). © Springer International Publishing AG 2016.

  2. Particle Filtering Applied to Musical Tempo Tracking

    Directory of Open Access Journals (Sweden)

    Macleod Malcolm D

    2004-01-01

    Full Text Available This paper explores the use of particle filters for beat tracking in musical audio examples. The aim is to estimate the time-varying tempo process and to find the time locations of beats, as defined by human perception. Two alternative algorithms are presented, one which performs Rao-Blackwellisation to produce an almost deterministic formulation while the second is a formulation which models tempo as a Brownian motion process. The algorithms have been tested on a large and varied database of examples and results are comparable with the current state of the art. The deterministic algorithm gives the better performance of the two algorithms.

  3. A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter

    Directory of Open Access Journals (Sweden)

    Bizhong Xia

    2015-11-01

    Full Text Available The estimation of state of charge (SOC is a crucial evaluation index in a battery management system (BMS. The value of SOC indicates the remaining capacity of a battery, which provides a good guarantee of safety and reliability of battery operation. It is difficult to get an accurate value of the SOC, being one of the inner states. In this paper, a strong tracking cubature Kalman filter (STCKF based on the cubature Kalman filter is presented to perform accurate and reliable SOC estimation. The STCKF algorithm can adjust gain matrix online by introducing fading factor to the state estimation covariance matrix. The typical second-order resistor-capacitor model is used as the battery’s equivalent circuit model to dynamically simulate characteristics of the battery. The exponential-function fitting method accomplishes the task of relevant parameters identification. Then, the developed STCKF algorithm has been introduced in detail and verified under different operation current profiles such as Dynamic Stress Test (DST and New European Driving Cycle (NEDC. Making a comparison with extended Kalman filter (EKF and CKF algorithm, the experimental results show the merits of the STCKF algorithm in SOC estimation accuracy and robustness.

  4. Adaptive Kalman Filter Applied to Vision Based Head Gesture Tracking for Playing Video Games

    Directory of Open Access Journals (Sweden)

    Mohammadreza Asghari Oskoei

    2017-11-01

    Full Text Available This paper proposes an adaptive Kalman filter (AKF to improve the performance of a vision-based human machine interface (HMI applied to a video game. The HMI identifies head gestures and decodes them into corresponding commands. Face detection and feature tracking algorithms are used to detect optical flow produced by head gestures. Such approaches often fail due to changes in head posture, occlusion and varying illumination. The adaptive Kalman filter is applied to estimate motion information and reduce the effect of missing frames in a real-time application. Failure in head gesture tracking eventually leads to malfunctioning game control, reducing the scores achieved, so the performance of the proposed vision-based HMI is examined using a game scoring mechanism. The experimental results show that the proposed interface has a good response time, and the adaptive Kalman filter improves the game scores by ten percent.

  5. Ultrasound effects on the electrolytically controlled etching of nuclear track filters (NTFs)

    International Nuclear Information System (INIS)

    Chakarvarti, S.K.; Mahna, S.K.; Sud, L.V.; Singh, P.

    1990-01-01

    The mechanical stirring of the etchant creates tremendous changes in the etching properties of SSNTDs. Ultrasound stirring also produces a number of effects in liquids by giving a rapid movement to etchant. Cavitation is the most probable phenomenon caused by ultrasound and responsible for most of the effects observed in chemical reactions. Microbubbles are created in liquid medium and explosion of these microbubbles is responsible for momentarily rise in temperature. The possible effects of ultrasound on etching of particle tracks in plastic track detectors as nuclear track filters has been studied. The ultrasound effects on V t and V b have been studied in this work. (author). 5 re fs

  6. Online track and vertex reconstruction on GPUs for the Mu3e experiment

    Energy Technology Data Exchange (ETDEWEB)

    Bruch, Dorothea vom [Institut fuer Kernphysik, Johannes Gutenberg-Universitaet Mainz (Germany); Collaboration: Mu3e-Collaboration

    2016-07-01

    The Mu3e experiment searches for the lepton flavour violating decay μ → eee, aiming at a branching ratio sensitivity better than 10{sup -16}.To reach this sensitivity, muon rates above 10{sup 9} μ/s are required. A high precision silicon tracking detector combined with excellent timing resolution from scintillating fibers and tiles will measure the momenta, vertices and timing of the decay products of muons stopped in the target to suppress background. The trigger-less readout system will deliver about 100 GB/s of zero-suppressed data. A network of optical links and switching FPGAs sends the complete detector data for a time slice to one node of the filter farm. An FPGA inside the filter farm PC transfers the event data to the GPU via PCIe direct memory access. The GPU finds and fits tracks using a 3D tracking algorithm for multiple scattering dominated resolution. In a second step, a three track vertex fit is performed, allowing for a reduction of the output data rate to below 100 MB/s by removing combinatorial background. The talk discusses the data flow from the FPGA to the GPU as well as the implementation and performance of the track and vertex fits on the GPU.

  7. Guitarist Fingertip Tracking by Integrating a Bayesian Classifier into Particle Filters

    Directory of Open Access Journals (Sweden)

    Chutisant Kerdvibulvech

    2008-01-01

    Full Text Available We propose a vision-based method for tracking guitar fingerings made by guitar players. We present it as a new framework for tracking colored finger markers by integrating a Bayesian classifier into particle filters. This adds the useful abilities of automatic track initialization and recovery from tracking failures in a dynamic background. Furthermore, by using the online adaptation of color probabilities, this method is able to cope with illumination changes. Augmented Reality Tag (ARTag is then utilized to calculate the projection matrix as an online process which allows the guitar to be moved while being played. Representative experimental results are also included. The method presented can be used to develop the application of human-computer interaction (HCI to guitar playing by recognizing the chord being played by a guitarist in virtual spaces. The aforementioned application would assist guitar learners by allowing them to automatically identify if they are using the correct chords required by the musical piece.

  8. Procedure manual for the estimation of average indoor radon-daughter concentrations using the filtered alpha-track method

    International Nuclear Information System (INIS)

    George, J.L.

    1988-04-01

    One of the measurement needs of US Department of Energy (DOE) remedial action programs is the estimation of the annual-average indoor radon-daughter concentration (RDC) in structures. The filtered alpha-track method, using a 1-year exposure period, can be used to accomplish RDC estimations for the DOE remedial action programs. This manual describes the procedure used to obtain filtered alpha-track measurements to derive average RDC estimates from the measurrements. Appropriate quality-assurance and quality-control programs are also presented. The ''prompt'' alpha-track method of exposing monitors for 2 to 6 months during specific periods of the year is also briefly discussed in this manual. However, the prompt alpha-track method has been validated only for use in the Mesa County, Colorado, area. 3 refs., 3 figs

  9. Impact of Physician Education and a Dedicated Inferior Vena Cava Filter Tracking System on Inferior Vena Cava Filter Use and Retrieval Rates Across a Large US Health Care Region.

    Science.gov (United States)

    Wang, Stephen L; Cha, Hsien-Hwa A; Lin, James R; Francis, Bolanos; Elizabeth, Wakley; Martin, Porras; Rajan, Sudhir

    2016-05-01

    To evaluate the effects of physician familiarity with current evidence and guidelines on inferior vena cava (IVC) filter use and the availability of IVC filter tracking infrastructure on retrieval rates. Fourteen continuing medical education-approved in-hospital grand rounds covering evidence-based review of the literature on IVC filter efficacy, patient-centered outcomes, guidelines for IVC filter indications, and complications were performed across a large United States (US) health care region serving more than 3.5 million members. A computer-based IVC filter tracking system was deployed simultaneously. IVC filter use, rates of attempted retrieval, and fulfillment of guidelines for IVC filter indications were retrospectively evaluated at each facility for 12 months before intervention (n = 427) and for 12 months after intervention (n = 347). After education, IVC filter use decreased 18.7%, with a member enrollment-adjusted decrease of 22.2%, despite an increasing IVC filter use trend for 4 years. Reduction in IVC filter use at each facility strongly correlated with physician attendance at grand rounds (r = -0.69; P = .007). Rates of attempted retrieval increased from 38.9% to 54.0% (P = .0006), with similar rates of successful retrieval (82.3% before education and 85.8% after education on first attempt). Improvement in IVC filter retrieval attempts correlated with physician attendance at grand rounds (r = 0.51; P = .051). IVC filter dwell times at first retrieval attempt were similar (10.2 wk before and 10.8 wk after). Physician education dramatically reduced IVC filter use across a large US health care region, and represents a learning opportunity for physicians who request and place them. Education and a novel tracking system improved rates of retrieval for IVC filter devices. Copyright © 2016 SIR. Published by Elsevier Inc. All rights reserved.

  10. Arbitrary-step randomly delayed robust filter with application to boost phase tracking

    Science.gov (United States)

    Qin, Wutao; Wang, Xiaogang; Bai, Yuliang; Cui, Naigang

    2018-04-01

    The conventional filters such as extended Kalman filter, unscented Kalman filter and cubature Kalman filter assume that the measurement is available in real-time and the measurement noise is Gaussian white noise. But in practice, both two assumptions are invalid. To solve this problem, a novel algorithm is proposed by taking the following four steps. At first, the measurement model is modified by the Bernoulli random variables to describe the random delay. Then, the expression of predicted measurement and covariance are reformulated, which could get rid of the restriction that the maximum number of delay must be one or two and the assumption that probabilities of Bernoulli random variables taking the value one are equal. Next, the arbitrary-step randomly delayed high-degree cubature Kalman filter is derived based on the 5th-degree spherical-radial rule and the reformulated expressions. Finally, the arbitrary-step randomly delayed high-degree cubature Kalman filter is modified to the arbitrary-step randomly delayed high-degree cubature Huber-based filter based on the Huber technique, which is essentially an M-estimator. Therefore, the proposed filter is not only robust to the randomly delayed measurements, but robust to the glint noise. The application to the boost phase tracking example demonstrate the superiority of the proposed algorithms.

  11. Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

    Energy Technology Data Exchange (ETDEWEB)

    Moore, Douglas, E-mail: douglas.moore@utsouthwestern.edu; Sawant, Amit [Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Ruan, Dan [Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

    2016-01-15

    Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al

  12. Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

    International Nuclear Information System (INIS)

    Moore, Douglas; Sawant, Amit; Ruan, Dan

    2016-01-01

    Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al

  13. Track and vertex reconstruction on GPUs for the Mu3e experiment

    Energy Technology Data Exchange (ETDEWEB)

    Bruch, Dorothea vom; Kozlinskiy, Alexandr [Physikalisches Institut, Universitaet Heidelberg (Germany); Berger, Niklaus [Institut fuer Kernphysik, Universitaet Mainz (Germany); Collaboration: Mu3e-Collaboration

    2015-07-01

    The Mu3e experiment searches for the lepton flavour violating decay μ → eee, aiming at a branching ratio sensitivity better than 10{sup -16}. To reach this sensitivity, muon rates above 10{sup 9} μ/s are required. A high precision silicon pixel tracking detector combined with excellent timing resolution from scintillating fibers and tiles will measure the momenta, vertices and timing of the decay products of muons stopped in the target to suppress background. The trigger-less readout system will deliver about 100 GB/s of zero-suppressed data. A network of optical links and switching FPGAs sends the complete detector data for a time slice to one node of the filter farm. An FPGA inside the filter farm PC transfers the event data to the GPU via PCIe direct memory access. The GPU finds and fits tracks using a 3D tracking algorithm for multiple scattering dominated resolution. In a second step, a three track vertex fit is performed, allowing for a reduction of the output data rate to below 100 MB/s by removing combinatorial background. The talk discusses the implementation of the fits on the GPU, which processes 10{sup 10} combinations of hits from three layers per second.

  14. Tracking of BMI, fatness and cardiorespiratory fitness from adolescence to middle adulthood: the Zagreb Growth and Development Longitudinal Study.

    Science.gov (United States)

    Sorić, Maroje; Jembrek Gostović, Mirjana; Gostović, Mladen; Hočevar, Marija; Mišigoj-Duraković, Marjeta

    2014-01-01

    Effective intervention strategies aiming to improve cardiorespiratory fitness and to decrease body fatness are needed. However, long-term stability of these traits is not well understood. To assess long-term tracking of cardiorespiratory fitness and body fatness from late adolescence to middle adulthood. The sample consisted of 50 participants (31 boys) from the Zagreb Growth and Development Longitudinal Study who were followed up in adulthood (median age = 43). Fatness was evaluated through BMI and skin-folds, while cardiorespiratory fitness was assessed using a cardiopulmonary exercise test. Inter-age partial correlation coefficients were calculated to evaluate tracking. Body mass index and skin-folds showed moderate tracking from age 15 years to middle adulthood (partial r = 0.55, p < 0.001 and partial r = 0.52, p < 0.001, respectively), while tracking of subcutaneous fat distribution was somewhat lower (partial r = 0.38, p < 0.01). At the same time, the observed tracking of peak oxygen uptake was low-to-moderate (partial r = 0.30, p = 0.03), while ventilatory aerobic and anaerobic thresholds did not show significant tracking. The results of this study indicate that preventive efforts aiming to increase cardiorespiratory fitness should include all adolescents, irrespective of their cardiorespiratory fitness status. Conversely, strategies aiming at obesity prevention should focus on high-risk groups of adolescents.

  15. Realization of nuclear track filters and their applications to the study of environmental aerosol samples

    International Nuclear Information System (INIS)

    Guo Shilun

    1993-01-01

    Detailed study of the behaviours of radon decay products requires the knowledge of environmental aerosols. A combination of devices and instruments have been tested to be superior in study of aerosol characteristics. Nuclear track filters and cascade track filter impactor are basic devices, which bring the functions of α -spectrometer, scanning electron microscope and electron microprobe into full play. This paper describes how to use these devices and instruments to collect aerosols, to determine aerosol radioactivity, size distribution and elemental compositions and to determine the concentration of aerosols in air as a function of aerosol sizes, which are important parameters in dominating the interactions between aerosol and radon decay products. (author). 15 refs, 7 figs

  16. Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

    Science.gov (United States)

    Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

    2018-01-01

    Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

  17. Performance Analysis and Design Strategy for a Second-Order, Fixed-Gain, Position-Velocity-Measured (α-β-η-θ Tracking Filter

    Directory of Open Access Journals (Sweden)

    Kenshi Saho

    2017-07-01

    Full Text Available We present a strategy for designing an α - β - η - θ filter, a fixed-gain moving-object tracking filter using position and velocity measurements. First, performance indices and stability conditions for the filter are analytically derived. Then, an optimal gain design strategy using these results is proposed and its relationship to the position-velocity-measured (PVM Kalman filter is shown. Numerical analyses demonstrate the effectiveness of the proposed strategy, as well as a performance improvement over the traditional position-only-measured α - β filter. Moreover, we apply an α - β - η - θ filter designed using this strategy to ultra-wideband Doppler radar tracking in numerical simulations. We verify that the proposed strategy can easily design the gains for an α - β - η - θ filter based on the performance of the ultra-wideband Doppler radar and a rough approximation of the target’s acceleration. Moreover, its effectiveness in predicting the steady state performance in designing the position-velocity-measured Kalman filter is also demonstrated.

  18. Users' intention to continue using social fitness-tracking apps: expectation confirmation theory and social comparison theory perspective.

    Science.gov (United States)

    Li, Jia; Liu, Xuan; Ma, Ling; Zhang, Weiqiang

    2018-03-05

    The key step in changing health behavior is understanding why users continue to use fitness apps. Therefore, we intend to investigate the users' intention to continue using social fitness-tracking apps. We identify two major forces driving continuous behavior. Expectation confirmation is the internal driving force and social comparison is the external driving force. A survey was conducted to test this proposed research model. We obtained 211 valid questionnaires. Our results indicate that activity amount ranking (p fitness-tracking apps. In addition, the impact of activity amount ranking and activity frequency ranking on continuous intention is moderated by expectation confirmation. Meanwhile, as the upward comparison tendency increases, the positive effect of confirmation on continuous intention decreases (p Social rank expectation and confirmation are the primary driving forces of continuous intention in individuals using fitness-tracking apps. Social rank is a meaningful and straightforward measurement individuals can use to evaluate their activity performance. An upward comparison tendency weakens the effect of confirmation on continuous intention.

  19. Implementation and Performance of FPGA based track fitting for the Atlas Fast TracKer

    CERN Document Server

    Zou, Rui; The ATLAS collaboration

    2018-01-01

    The Fast TracKer (FTK) within the ATLAS trigger system provides global track reconstruction for all events passing the ATLAS Level 1 trigger by dividing the detector into parallel processing pipelines that implement pattern matching in custom integrated circuits and data routing, reduction, and parameter extraction in FPGAs. In this presentation we will describe the implementation of a critical component of the system which does partial track fitting using a method based on a principal component analysis at a rate of greater than 1 fit per 10 ps, system-wide, to reduce the output of the pattern matching. Firmware design, timing performance and preliminary results will be discussed.

  20. CMS reconstruction improvements for the tracking in large pileup events

    CERN Document Server

    Rovere, M

    2015-01-01

    The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compatible with the increasing instantaneous luminosity of LHC, resulting in a large number of primary vertices and tracks per bunch crossing.The major upgrade put in place during the present LHC Long Shutdown will allow the tracking code to comply with the conditions expected during RunII and the much larger pileup. In particular, new algorithms that are intrinsically more robust in high occupancy conditions were developed, iteration...

  1. Track reconstruction algorithms for the CBM experiment at FAIR

    International Nuclear Information System (INIS)

    Lebedev, Andrey; Hoehne, Claudia; Kisel, Ivan; Ososkov, Gennady

    2010-01-01

    The Compressed Baryonic Matter (CBM) experiment at the future FAIR accelerator complex at Darmstadt is being designed for a comprehensive measurement of hadron and lepton production in heavy-ion collisions from 8-45 AGeV beam energy, producing events with large track multiplicity and high hit density. The setup consists of several detectors including as tracking detectors the silicon tracking system (STS), the muon detector (MUCH) or alternatively a set of Transition Radiation Detectors (TRD). In this contribution, the status of the track reconstruction software including track finding, fitting and propagation is presented for the MUCH and TRD detectors. The track propagation algorithm takes into account an inhomogeneous magnetic field and includes accurate calculation of multiple scattering and energy losses in the detector material. Track parameters and covariance matrices are estimated using the Kalman filter method and a Kalman filter modification by assigning weights to hits and using simulated annealing. Three different track finder algorithms based on track following have been developed which either allow for track branches, just select nearest hits or use the mentioned weighting method. The track reconstruction efficiency for central Au+Au collisions at 25 AGeV beam energy using events from the UrQMD model is at the level of 93-95% for both detectors.

  2. Particle Filter with Integrated Voice Activity Detection for Acoustic Source Tracking

    Directory of Open Access Journals (Sweden)

    Anders M. Johansson

    2007-01-01

    Full Text Available In noisy and reverberant environments, the problem of acoustic source localisation and tracking (ASLT using an array of microphones presents a number of challenging difficulties. One of the main issues when considering real-world situations involving human speakers is the temporally discontinuous nature of speech signals: the presence of silence gaps in the speech can easily misguide the tracking algorithm, even in practical environments with low to moderate noise and reverberation levels. A natural extension of currently available sound source tracking algorithms is the integration of a voice activity detection (VAD scheme. We describe a new ASLT algorithm based on a particle filtering (PF approach, where VAD measurements are fused within the statistical framework of the PF implementation. Tracking accuracy results for the proposed method is presented on the basis of synthetic audio samples generated with the image method, whereas performance results obtained with a real-time implementation of the algorithm, and using real audio data recorded in a reverberant room, are published elsewhere. Compared to a previously proposed PF algorithm, the experimental results demonstrate the improved robustness of the method described in this work when tracking sources emitting real-world speech signals, which typically involve significant silence gaps between utterances.

  3. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

    2016-01-01

    , an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  4. Model-based extended quaternion Kalman filter to inertial orientation tracking of arbitrary kinematic chains.

    Science.gov (United States)

    Szczęsna, Agnieszka; Pruszowski, Przemysław

    2016-01-01

    Inertial orientation tracking is still an area of active research, especially in the context of out-door, real-time, human motion capture. Existing systems either propose loosely coupled tracking approaches where each segment is considered independently, taking the resulting drawbacks into account, or tightly coupled solutions that are limited to a fixed chain with few segments. Such solutions have no flexibility to change the skeleton structure, are dedicated to a specific set of joints, and have high computational complexity. This paper describes the proposal of a new model-based extended quaternion Kalman filter that allows for estimation of orientation based on outputs from the inertial measurements unit sensors. The filter considers interdependencies resulting from the construction of the kinematic chain so that the orientation estimation is more accurate. The proposed solution is a universal filter that does not predetermine the degree of freedom at the connections between segments of the model. To validation the motion of 3-segments single link pendulum captured by optical motion capture system is used. The next step in the research will be to use this method for inertial motion capture with a human skeleton model.

  5. A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

    International Nuclear Information System (INIS)

    Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth

    2015-01-01

    In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. (author)

  6. Tracking performance of unbalanced QPSK demodulators. I - Biphase Costas loop with passive arm filters

    Science.gov (United States)

    Simon, M. K.; Alem, W. K.

    1978-01-01

    Unbalanced quadriphase-shift-keying (QPSK) is an attractive means for transmitting two digital data streams which in general have different average powers, data rates, and data formats. Previous analyses of the tracking performance of Costas loop demodulators of unbalanced QPSK have accounted only for the filtering effect produced by the loop's two arm filters on the equivalent additive noise perturbing the loop. When the bandwidth of these filters is selected on the basis of the order of the data rate, as is typical of optimum Costas loop design, the filtering degradations of the data modulations themselves and the cross-modulation noise produced by their multiplication in the loop often cannot be neglected. The purpose of this paper is to incorporate these additional filtering effects into the analysis. Many of the results obtained herein are in the form of closed-form expressions which can easily be evaluated numerically for design and performance prediction purposes.

  7. Customization of the GENFIT2 Fitting Package in P̅ANDA

    Directory of Open Access Journals (Sweden)

    Prencipe Elisabetta

    2016-01-01

    Full Text Available The availability of a cooled antiproton beam in the energy range from 2.0 to 5.5 GeV will allow the P̅ANDA experiment, planned for operation in FAIR (Darmstadt, Germany, to perform a wide nuclear and particle physics program. P̅ANDA is the only experiment worldwide in that energy regime that combines a solenoidal magnetic field (B = 2 T and a dipole field (maximum bending power equal to 2 Tm in a fixed-target experiment. The offline tracking algorithm is developed within the PandaRoot framework, which is part of the FairRoot project. Here the GENFIT2 package is presented. The tool contains an implementation of the Kalman filter and the deterministic annealing filter for charged particle track reconstruction, together with a Runge-Kutta track representation. It also interfaces with Millipede II and RAVE, for alignment and vertex reconstruction, respectively. The performance of this track-fitting package for the P̅ANDA experiment is shown for the first time, within the PandaRoot framework. For those channels where a good low momentum tracking is required, i.e. pT <350 MeV/c, an improvement by a factor of about two is shown.

  8. Kalman filter based data fusion for neutral axis tracking in wind turbine towers

    DEFF Research Database (Denmark)

    Soman, Rohan; Malinowski, Pawel; Ostachowicz, Wieslaw

    2015-01-01

    downtime, hence increasing the availability of the system. The present work is based on the use of neutral axis (NA) for SHM of the structure. The NA is tracked by data fusion of measured yaw angle and strain through the use of Extended Kalman Filter (EKF). The EKF allows accurate tracking even...... in the NA position may be used for detecting and locating the damage. The wind turbine tower has been modelled with FE software ABAQUS and validated on data from load measurements carried out on the 34m high tower of the Nordtank, NTK 500/41 wind turbine....

  9. Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar

    Directory of Open Access Journals (Sweden)

    Fei Cai

    2014-01-01

    Full Text Available A particle filter based track-before-detect (PF-TBD algorithm is proposed for the monopulse high pulse repetition frequency (PRF pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied.

  10. Tracking single dynamic MEG dipole sources using the projected Extended Kalman Filter.

    Science.gov (United States)

    Yao, Yuchen; Swindlehurst, A Lee

    2011-01-01

    This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

  11. Improved Particle Filter for Passive Target Tracking%改进粒子滤波在被动目标跟踪中的应用

    Institute of Scientific and Technical Information of China (English)

    邓小龙; 谢剑英; 杨煜普

    2005-01-01

    As a new method for dealing with any nonlinear or non-Gaussian distributions, based on the Monte Carlo methods and Bayesian filtering, particle filters (PF) are favored by researchers and widely applied in many fields. Based on particle filtering, an improved extended Kalman filter (EKF) proposal distribution is presented. Evaluation of the weights is simplified and other improved techniques including the residual resampling step and Markov Chain Monte Carlo method are introduced for target tracking. Performances of the EKF, basic PF and the improved PF are compared in target tracking examples. The simulation results confirm that the improved particle filter outperforms the others.

  12. Strong Tracking Filter for Nonlinear Systems with Randomly Delayed Measurements and Correlated Noises

    Directory of Open Access Journals (Sweden)

    Hongtao Yang

    2018-01-01

    Full Text Available This paper proposes a novel strong tracking filter (STF, which is suitable for dealing with the filtering problem of nonlinear systems when the following cases occur: that is, the constructed model does not match the actual system, the measurements have the one-step random delay, and the process and measurement noises are correlated at the same epoch. Firstly, a framework of decoupling filter (DF based on equivalent model transformation is derived. Further, according to the framework of DF, a new extended Kalman filtering (EKF algorithm via using first-order linearization approximation is developed. Secondly, the computational process of the suboptimal fading factor is derived on the basis of the extended orthogonality principle (EOP. Thirdly, the ultimate form of the proposed STF is obtained by introducing the suboptimal fading factor into the above EKF algorithm. The proposed STF can automatically tune the suboptimal fading factor on the basis of the residuals between available and predicted measurements and further the gain matrices of the proposed STF tune online to improve the filtering performance. Finally, the effectiveness of the proposed STF has been proved through numerical simulation experiments.

  13. Robust and Adaptive Block Tracking Method Based on Particle Filter

    Directory of Open Access Journals (Sweden)

    Bin Sun

    2015-10-01

    Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

  14. An efficient central DOA tracking algorithm for multiple incoherently distributed sources

    Science.gov (United States)

    Hassen, Sonia Ben; Samet, Abdelaziz

    2015-12-01

    In this paper, we develop a new tracking method for the direction of arrival (DOA) parameters assuming multiple incoherently distributed (ID) sources. The new approach is based on a simple covariance fitting optimization technique exploiting the central and noncentral moments of the source angular power densities to estimate the central DOAs. The current estimates are treated as measurements provided to the Kalman filter that model the dynamic property of directional changes for the moving sources. Then, the covariance-fitting-based algorithm and the Kalman filtering theory are combined to formulate an adaptive tracking algorithm. Our algorithm is compared to the fast approximated power iteration-total least square-estimation of signal parameters via rotational invariance technique (FAPI-TLS-ESPRIT) algorithm using the TLS-ESPRIT method and the subspace updating via FAPI-algorithm. It will be shown that the proposed algorithm offers an excellent DOA tracking performance and outperforms the FAPI-TLS-ESPRIT method especially at low signal-to-noise ratio (SNR) values. Moreover, the performances of the two methods increase as the SNR values increase. This increase is more prominent with the FAPI-TLS-ESPRIT method. However, their performances degrade when the number of sources increases. It will be also proved that our method depends on the form of the angular distribution function when tracking the central DOAs. Finally, it will be shown that the more the sources are spaced, the more the proposed method can exactly track the DOAs.

  15. Calculation of track and vertex errors for detector design studies

    International Nuclear Information System (INIS)

    Harr, R.

    1995-01-01

    The Kalman Filter technique has come into wide use for charged track reconstruction in high-energy physics experiments. It is also well suited for detector design studies, allowing for the efficient estimation of optimal track covariance matrices without the need of a hit level Monte Carlo simulation. Although much has been published about the Kalman filter equations, there is a lack of previous literature explaining how to implement the equations. In this paper, the operators necessary to implement the Kalman filter equations for two common detector configurations are worked out: a central detector in a uniform solenoidal magnetic field, and a fixed-target detector with no magnetic field in the region of the interactions. With the track covariance matrices in hand, vertex and invariant mass errors are readily calculable. These quantities are particularly interesting for evaluating experiments designed to study weakly decaying particles which give rise to displaced vertices. The optimal vertex errors are obtained via a constrained vertex fit. Solutions are presented to the constrained vertex problem with and without kinematic constraints. Invariant mass errors are obtained via propagation of errors; the use of vertex constrained track parameters is discussed. Many of the derivations are new or previously unpublished

  16. Energy awareness for supercapacitors using Kalman filter state-of-charge tracking

    Science.gov (United States)

    Nadeau, Andrew; Hassanalieragh, Moeen; Sharma, Gaurav; Soyata, Tolga

    2015-11-01

    Among energy buffering alternatives, supercapacitors can provide unmatched efficiency and durability. Additionally, the direct relation between a supercapacitor's terminal voltage and stored energy can improve energy awareness. However, a simple capacitive approximation cannot adequately represent the stored energy in a supercapacitor. It is shown that the three branch equivalent circuit model provides more accurate energy awareness. This equivalent circuit uses three capacitances and associated resistances to represent the supercapacitor's internal SOC (state-of-charge). However, the SOC cannot be determined from one observation of the terminal voltage, and must be tracked over time using inexact measurements. We present: 1) a Kalman filtering solution for tracking the SOC; 2) an on-line system identification procedure to efficiently estimate the equivalent circuit's parameters; and 3) experimental validation of both parameter estimation and SOC tracking for 5 F, 10 F, 50 F, and 350 F supercapacitors. Validation is done within the operating range of a solar powered application and the associated power variability due to energy harvesting. The proposed techniques are benchmarked against the simple capacitive model and prior parameter estimation techniques, and provide a 67% reduction in root-mean-square error for predicting usable buffered energy.

  17. Radar tracking with an interacting multiple model and probabilistic data association filter for civil aviation applications.

    Science.gov (United States)

    Jan, Shau-Shiun; Kao, Yu-Chun

    2013-05-17

    The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC) system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM) system that is enabled by global positioning system (GPS) technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF), is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF), is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods.

  18. Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications

    Directory of Open Access Journals (Sweden)

    Shau-Shiun Jan

    2013-05-01

    Full Text Available The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM system that is enabled by global positioning system (GPS technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF, is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF, is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods.

  19. LHCb Kalman Filter cross architecture studies

    Science.gov (United States)

    Hugo, Daniel; Pérez, Cámpora

    2017-10-01

    The 2020 upgrade of the LHCb detector will vastly increase the rate of collisions the Online system needs to process in software, in order to filter events in real time. 30 million collisions per second will pass through a selection chain, where each step is executed conditional to its prior acceptance. The Kalman Filter is a fit applied to all reconstructed tracks which, due to its time characteristics and early execution in the selection chain, consumes 40% of the whole reconstruction time in the current trigger software. This makes the Kalman Filter a time-critical component as the LHCb trigger evolves into a full software trigger in the Upgrade. I present a new Kalman Filter algorithm for LHCb that can efficiently make use of any kind of SIMD processor, and its design is explained in depth. Performance benchmarks are compared between a variety of hardware architectures, including x86_64 and Power8, and the Intel Xeon Phi accelerator, and the suitability of said architectures to efficiently perform the LHCb Reconstruction process is determined.

  20. Performance enhancement for a GPS vector-tracking loop utilizing an adaptive iterated extended Kalman filter.

    Science.gov (United States)

    Chen, Xiyuan; Wang, Xiying; Xu, Yuan

    2014-12-09

    This paper deals with the problem of state estimation for the vector-tracking loop of a software-defined Global Positioning System (GPS) receiver. For a nonlinear system that has the model error and white Gaussian noise, a noise statistics estimator is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) named adaptive iterated Kalman filter (AIEKF) is proposed. A vector-tracking GPS receiver utilizing AIEKF is implemented to evaluate the performance of the proposed method. Through road tests, it is shown that the proposed method has an obvious accuracy advantage over the IEKF and Adaptive Extended Kalman filter (AEKF) in position determination. The results show that the proposed method is effective to reduce the root-mean-square error (RMSE) of position (including longitude, latitude and altitude). Comparing with EKF, the position RMSE values of AIEKF are reduced by about 45.1%, 40.9% and 54.6% in the east, north and up directions, respectively. Comparing with IEKF, the position RMSE values of AIEKF are reduced by about 25.7%, 19.3% and 35.7% in the east, north and up directions, respectively. Compared with AEKF, the position RMSE values of AIEKF are reduced by about 21.6%, 15.5% and 30.7% in the east, north and up directions, respectively.

  1. Sky-Hook Control and Kalman Filtering in Nonlinear Model of Tracked Vehicle Suspension System

    Directory of Open Access Journals (Sweden)

    Jurkiewicz Andrzej

    2017-09-01

    Full Text Available The essence of the undertaken topic is application of the continuous sky-hook control strategy and the Extended Kalman Filter as the state observer in the 2S1 tracked vehicle suspension system. The half-car model of this suspension system consists of seven logarithmic spiral springs and two magnetorheological dampers which has been described by the Bingham model. The applied continuous sky-hook control strategy considers nonlinear stiffness characteristic of the logarithmic spiral springs. The control is determined on estimates generated by the Extended Kalman Filter. Improve of ride comfort is verified by comparing simulation results, under the same driving conditions, of controlled and passive vehicle suspension systems.

  2. Common barrel and forward CA tracking algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Mykhailo, Pugach [Goethe-Universitaet, Frankfurt (Germany); Frankfurt Institute for Advanced Studies, Frankfurt (Germany); KINR, Kyiv (Ukraine); Gorbunov, Sergey; Kisel, Ivan [Goethe-Universitaet, Frankfurt (Germany); Frankfurt Institute for Advanced Studies, Frankfurt (Germany); Collaboration: PANDA-Collaboration

    2016-07-01

    There are complex detector setups which consist of barrel (cylindrical) and forward parts, and such systems require a special approach in the registered charged particles track finding procedure. Currently the tracking procedure might be performed in both parts of such detector independently from each other, but the final goal on this direction is a creation of a combined tracking, which will work in both parts of the detector simultaneously. The basic algorithm is based on Kalman Filter (KF) and Cellular Automata (CA). And the tracking procedure in such a complex system is rather extraordinary as far as it requires 2 different models to describe the state vector of segments of the reconstructed track in the mathematical apparatus of the KF-algorithm. To overcome this specifics a mathematical apparatus of transition matrices must be developed and implemented, so that one can transfer from one track model to another. Afterwards the work of the CA is performed, which reduces to segments sorting, their union into track-candidates and selection of the best candidates by the chi-square criteria after fitting of the track-candidate by the KF. In this report the algorithm, status and perspectives of such combined tracking are described.

  3. Tracking Architecture Based on Dual-Filter with State Feedback and Its Application in Ultra-Tight GPS/INS Integration.

    Science.gov (United States)

    Zhang, Xi; Miao, Lingjuan; Shao, Haijun

    2016-05-02

    If a Kalman Filter (KF) is applied to Global Positioning System (GPS) baseband signal preprocessing, the estimates of signal phase and frequency can have low variance, even in highly dynamic situations. This paper presents a novel preprocessing scheme based on a dual-filter structure. Compared with the traditional model utilizing a single KF, this structure avoids carrier tracking being subjected to code tracking errors. Meanwhile, as the loop filters are completely removed, state feedback values are adopted to generate local carrier and code. Although local carrier frequency has a wide fluctuation, the accuracy of Doppler shift estimation is improved. In the ultra-tight GPS/Inertial Navigation System (INS) integration, the carrier frequency derived from the external navigation information is not viewed as the local carrier frequency directly. That facilitates retaining the design principle of state feedback. However, under harsh conditions, the GPS outputs may still bear large errors which can destroy the estimation of INS errors. Thus, an innovative integrated navigation filter is constructed by modeling the non-negligible errors in the estimated Doppler shifts, to ensure INS is properly calibrated. Finally, field test and semi-physical simulation based on telemetered missile trajectory validate the effectiveness of methods proposed in this paper.

  4. Leader-Follower Tracking System for Agricultural Vehicles: Fusion of Laser and Odometry Positioning Using Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Zhang Lin Huan

    2015-03-01

    Full Text Available The aim of this research was to develop a safe human-driven and autonomous leader-follower tracking system for an autonomous tractor. To enable the tracking system, a laser range finder (LRF-based landmark detection system was designed to observe the relative position between a leader and a follower used in agricultural operations. The virtual follower-based formation-tracking algorithm was developed to minimize tracking errors and ensure safety. An extended Kalman filter (EKF was implemented for fusing LRF and odometry position to ensure stability of tracking in noisy farmland conditions. Simulations were conducted for tracking the leader in small and large sinusoidal curved paths. Simulated results verified high accuracy of formation tracking, stable velocity, and regulated steering angle of the follower. The tracking method confirmed the follower could follow the leader with a required formation safely and steadily in noisy conditions. The EKF helped to improve observation accuracy, velocity, and steering angle stability of the follower. As a result of the improved accuracy of observation and motion action, the tracking performance for lateral, longitudinal, and heading were also improved after the EKF was implemented in the tracking system.

  5. Kalman滤波在井下人员跟踪定位中的应用%Application of Kalman filter in underground personnel tracking and positioning

    Institute of Scientific and Technical Information of China (English)

    罗宇锋; 刘勇; 李芳

    2013-01-01

    In view of problem that RSSI location algorithm does not have continuity in positioning process,the paper proposed an underground personnel positioning method with continuity based on Kalman filter.The method adopts Kalman filter to filter processing position coordinates of underground personnel estimated by RSSI location algorithm,and established a Kalman filter model on the basis of this coordinate in order to real-timely track underground personnel.The experimental results show that the positioning method based on Kalman filter has accurate tracking effect,and can improve real-time performance and tracking accuracy of underground personnel tracking and positioning system.%针对基于RSSI定位算法在定位过程中不具备连续性问题,提出了一种基于Kalman滤波的连续性并下人员定位方法.采用Kalman滤波对基于RSSI定位算法估算出的井下人员位置坐标进行滤波处理,在此坐标的基础上,建立Kalman滤波模型,利用Kalman滤波实现对井下人员的实时跟踪.实验结果表明,基于Kalman滤波的定位方法对井下人员的跟踪效果较好,提高了系统的实时性和跟踪精度.

  6. People detection and tracking using RGB-D cameras for mobile robots

    Directory of Open Access Journals (Sweden)

    Hengli Liu

    2016-09-01

    Full Text Available People detection and tracking is an essential capability for mobile robots in order to achieve natural human–robot interaction. In this article, a human detection and tracking system is designed and validated for mobile robots using color data with depth information RGB-depth (RGB-D cameras. The whole framework is composed of human detection, tracking and re-identification. Firstly, ground points and ceiling planes are removed to reduce computation effort. A prior-knowledge guided random sample consensus fitting algorithm is used to detect the ground plane and ceiling points. All left points are projected onto the ground plane and subclusters are segmented for candidate detection. Meanshift clustering with an Epanechnikov kernel is conducted to partition different points into subclusters. We propose the new idea of spatial region of interest plan view maps which are employed to identify human candidates from point cloud subclusters. Here, a depth-weighted histogram is extracted online to feature a human candidate. Then, a particle filter algorithm is adopted to track the human’s motion. The integration of the depth-weighted histogram and particle filter provides a precise tool to track the motion of human objects. Finally, data association is set up to re-identify humans who are tracked. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.

  7. Tracking of physical activity, fitness, body composition and diet from adolescence to young adulthood: The Young Hearts Project, Northern Ireland

    Directory of Open Access Journals (Sweden)

    Savage J Maurice

    2004-10-01

    Full Text Available Abstract Background The assumption that lifestyles formed early in life track into adulthood has been used to justify the targeting of health promotion programmes towards children and adolescents. The aim of the current study was to use data from the Northern Ireland Young Hearts Project to ascertain the extent of tracking, between adolescence and young adulthood, of physical activity, aerobic fitness, selected anthropometric variables, and diet. Methods Males (n 245 and females (n 231 were assessed at age 15 y, and again in young adulthood [mean (SD age 22 (1.6 y]. At both timepoints, height, weight and skinfold thicknesses were measured, and physical activity and diet were assessed by questionnaire and diet history method respectively. At 15y, fitness was assessed using the 20 metre shuttle run, while at young adulthood, the PWC170 cycle ergometer test was used. For each measurement made at 15y, subjects were ranked into 'low' (L1; lowest 25%, 'medium' (M1; middle 50% or 'high' (H1; highest 25% categories. At young adulthood, similar categories (L2, M2, H2 were created. The extent of tracking of each variable over time was calculated using 3 × 3 matrices constructed using these two sets of categories, and summarised using kappa (κ statistics. Results Tracking of diet and fitness was poor (κ ≤ 0.20 in both sexes, indicating substantial drift of subjects between the low, medium and high categories over time. The tracking of physical activity in males was fair (κ 0.202, but was poor in females (κ 0.021. In contrast, anthropometric variables such as weight, body mass index and sum of skinfolds tracked more strongly in females (κ 0.540, κ 0.307, κ 0.357 respectively than in males (κ 0.337, κ 0.199, κ 0.216 respectively. Conclusions The poor tracking of fitness and diet in both sexes, and physical activity in females, suggests that these aspects of adolescent lifestyle are unlikely to be predictive of behaviours in young adulthood. In

  8. Physics-based coastal current tomographic tracking using a Kalman filter.

    Science.gov (United States)

    Wang, Tongchen; Zhang, Ying; Yang, T C; Chen, Huifang; Xu, Wen

    2018-05-01

    Ocean acoustic tomography can be used based on measurements of two-way travel-time differences between the nodes deployed on the perimeter of the surveying area to invert/map the ocean current inside the area. Data at different times can be related using a Kalman filter, and given an ocean circulation model, one can in principle now cast and even forecast current distribution given an initial distribution and/or the travel-time difference data on the boundary. However, an ocean circulation model requires many inputs (many of them often not available) and is unpractical for estimation of the current field. A simplified form of the discretized Navier-Stokes equation is used to show that the future velocity state is just a weighted spatial average of the current state. These weights could be obtained from an ocean circulation model, but here in a data driven approach, auto-regressive methods are used to obtain the time and space dependent weights from the data. It is shown, based on simulated data, that the current field tracked using a Kalman filter (with an arbitrary initial condition) is more accurate than that estimated by the standard methods where data at different times are treated independently. Real data are also examined.

  9. Development of an optimal automatic control law and filter algorithm for steep glideslope capture and glideslope tracking

    Science.gov (United States)

    Halyo, N.

    1976-01-01

    A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.

  10. Determination of boron in aqueous solutions by solid state nuclear track detectors technique, using a filtered neutron beam

    International Nuclear Information System (INIS)

    Moraes, M.A.P.V. de; Pugliesi, R.; Khouri, M.T.F.C.

    1985-11-01

    The solid state nuclear track detectors technique has been used for determination of boron in aqueous solutions, using a filtered neutron beam. The particles tracks from the 10 B(n,α)Li 7 reaction were registered in the CR-39 film, chemically etched in a (30%) KOH solution 70 0 C during 90 minutes. The obtained results showed the usefulness of this technique for boron determination in the ppm range. The inferior detectable limit was 9 ppm. The combined track registration efficiency factor K has been evaluated in the solutions, for the CR-39 detector and its values is K= (4,60 - + 0,06). 10 -4 cm. (Author) [pt

  11. Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

    Science.gov (United States)

    Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

    2015-01-01

    The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

  12. Assessment of the pseudo-tracking approach for the calculation of material acceleration and pressure fields from time-resolved PIV: part II. Spatio-temporal filtering

    Science.gov (United States)

    van Gent, P. L.; Schrijer, F. F. J.; van Oudheusden, B. W.

    2018-04-01

    The present study characterises the spatio-temporal filtering associated with pseudo-tracking. A combined theoretical and numerical assessment is performed that uses the relatively simple flow case of a two-dimensional Taylor vortex as analytical test case. An additional experimental assessment considers the more complex flow of a low-speed axisymmetric base flow, for which time-resolved tomographic PIV measurements and microphone measurements were obtained. The results of these assessments show how filtering along Lagrangian tracks leads to amplitude modulation of flow structures. A cut-off track length and spatial resolution are specified to support future applications of the pseudo-tracking approach. The experimental results show a fair agreement between PIV and microphone pressure data in terms of fluctuation levels and pressure frequency spectra. The coherence and correlation between microphone and PIV pressure measurements were found to be substantial and almost independent of the track length, indicating that the low-frequency behaviour of the flow could be reproduced regardless of the track length. It is suggested that a spectral analysis can be used inform the selection of a suitable track length and to estimate the local error margin of reconstructed pressure values.

  13. Human tracking in thermal images using adaptive particle filters with online random forest learning

    Science.gov (United States)

    Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

    2013-11-01

    This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

  14. Parameter estimation of a three-axis spacecraft simulator using recursive least-squares approach with tracking differentiator and Extended Kalman Filter

    Science.gov (United States)

    Xu, Zheyao; Qi, Naiming; Chen, Yukun

    2015-12-01

    Spacecraft simulators are widely used to study the dynamics, guidance, navigation, and control of a spacecraft on the ground. A spacecraft simulator can have three rotational degrees of freedom by using a spherical air-bearing to simulate a frictionless and micro-gravity space environment. The moment of inertia and center of mass are essential for control system design of ground-based three-axis spacecraft simulators. Unfortunately, they cannot be known precisely. This paper presents two approaches, i.e. a recursive least-squares (RLS) approach with tracking differentiator (TD) and Extended Kalman Filter (EKF) method, to estimate inertia parameters. The tracking differentiator (TD) filter the noise coupled with the measured signals and generate derivate of the measured signals. Combination of two TD filters in series obtains the angular accelerations that are required in RLS (TD-TD-RLS). Another method that does not need to estimate the angular accelerations is using the integrated form of dynamics equation. An extended TD (ETD) filter which can also generate the integration of the function of signals is presented for RLS (denoted as ETD-RLS). States and inertia parameters are estimated simultaneously using EKF. The observability is analyzed. All proposed methods are illustrated by simulations and experiments.

  15. The FitTrack Index as fitness indicator

    African Journals Online (AJOL)

    Dina Christina Janse van Rensburg

    d Institute for Sports Research, Faculty of Humanities, University of Pretoria, South Africa e Institute for Food ... The American College of Sports Medicine's guidelines for health/fitness .... It is important to stress that the focus of this study was not.

  16. A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer.

    Science.gov (United States)

    Ligorio, Gabriele; Sabatini, Angelo M

    2015-08-01

    Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in this study. A significant accuracy improvement was achieved over state-of-the-art approaches, due to a filter design that better matched the basic optimality assumptions of Kalman filtering. Human motion tracking is the main application field of the proposed method. Accurately discriminating the two components present in the triaxial accelerometer signal is well suited for studying both the rotational and the linear body kinematics.

  17. Estimation of error components in a multi-error linear regression model, with an application to track fitting

    International Nuclear Information System (INIS)

    Fruehwirth, R.

    1993-01-01

    We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)

  18. Application and Optimization of Kalman Filter for Baseband Signal Processing of GPS Receivers

    Directory of Open Access Journals (Sweden)

    He Yanpin

    2016-01-01

    Full Text Available High sensitivity tracking in GPS receiver is required in many weak signal circumstances. The key of improving sensitivity is the optimization of the loop filter in tracking. As Kalman filter is the most optimized linear filter, it is used in many engineering fields. This article introduced the application of Kalman filter as the loop filter of the carrier tracking loop in GPS receiver, to improve tracking sensitivity. The traditional loop filter is replaced. Simulation results show that the new structure improves the tracking sensitivity by 6dB and can make the tracking loop more robust when the navigation signal is languishing. The optimization of theKalman filter is also analysed, which further improves the sensitivity by 4dB.

  19. Box-particle probability hypothesis density filtering

    OpenAIRE

    Schikora, M.; Gning, A.; Mihaylova, L.; Cremers, D.; Koch, W.

    2014-01-01

    This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic, and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small number of box-p...

  20. Target Response Adaptation for Correlation Filter Tracking

    KAUST Repository

    Bibi, Adel Aamer; Mueller, Matthias; Ghanem, Bernard

    2016-01-01

    Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations

  1. Thermal Tracking of Sports Players

    Directory of Open Access Journals (Sweden)

    Rikke Gade

    2014-07-01

    Full Text Available We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

  2. Thermal tracking of sports players.

    Science.gov (United States)

    Gade, Rikke; Moeslund, Thomas B

    2014-07-29

    We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

  3. Bottom loaded filter for radioactive liquid

    International Nuclear Information System (INIS)

    Wendland, W.G.

    1980-01-01

    A specification is given for a bottom loaded filter assembly for filtering radioactive liquids through a replaceable cartridge filter, which includes a lead-filled jacket enveloping a housing having a chamber therein for the filter cartridge. A track arrangement carries a hatch for sealing the chamber. A spacer plug supports the cartridge within guide means associated with the inlet conduit in the chamber. The plug and cartridge drop out of the chamber when the hatch is unbolted and moved laterally of the chamber along the track. During cartridge replacement a new plug and cartridge are supported in the guide means by a spacer bar inserted across the track means under the chamber. The hatch is then slid under the chamber and bolted to a flange on the housing, engaging an O-ring to seal the chamber. (author)

  4. Unscented Kalman filtering for articulated human tracking

    DEFF Research Database (Denmark)

    Boesen Lindbo Larsen, Anders; Hauberg, Søren; Pedersen, Kim Steenstrup

    2011-01-01

    We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal. While current state...... with superior results. Tracking quality is measured by comparing with ground truth data from a marker-based motion capture system....

  5. An adaptive unscented Kalman filter-based adaptive tracking control for wheeled mobile robots with control constrains in the presence of wheel slipping

    Directory of Open Access Journals (Sweden)

    Mingyue Cui

    2016-09-01

    Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.

  6. Text-mining as a methodology to assess eating disorder-relevant factors: Comparing mentions of fitness tracking technology across online communities.

    Science.gov (United States)

    McCaig, Duncan; Bhatia, Sudeep; Elliott, Mark T; Walasek, Lukasz; Meyer, Caroline

    2018-05-07

    Text-mining offers a technique to identify and extract information from a large corpus of textual data. As an example, this study presents the application of text-mining to assess and compare interest in fitness tracking technology across eating disorder and health-related online communities. A list of fitness tracking technology terms was developed, and communities (i.e., 'subreddits') on a large online discussion platform (Reddit) were compared regarding the frequency with which these terms occurred. The corpus used in this study comprised all comments posted between May 2015 and January 2018 (inclusive) on six subreddits-three eating disorder-related, and three relating to either fitness, weight-management, or nutrition. All comments relating to the same 'thread' (i.e., conversation) were concatenated, and formed the cases used in this study (N = 377,276). Within the eating disorder-related subreddits, the findings indicated that a 'pro-eating disorder' subreddit, which is less recovery focused than the other eating disorder subreddits, had the highest frequency of fitness tracker terms. Across all subreddits, the weight-management subreddit had the highest frequency of the fitness tracker terms' occurrence, and MyFitnessPal was the most frequently mentioned fitness tracker. The technique exemplified here can potentially be used to assess group differences to identify at-risk populations, generate and explore clinically relevant research questions in populations who are difficult to recruit, and scope an area for which there is little extant literature. The technique also facilitates methodological triangulation of research findings obtained through more 'traditional' techniques, such as surveys or interviews. © 2018 Wiley Periodicals, Inc.

  7. Real Time 3D Facial Movement Tracking Using a Monocular Camera

    Directory of Open Access Journals (Sweden)

    Yanchao Dong

    2016-07-01

    Full Text Available The paper proposes a robust framework for 3D facial movement tracking in real time using a monocular camera. It is designed to estimate the 3D face pose and local facial animation such as eyelid movement and mouth movement. The framework firstly utilizes the Discriminative Shape Regression method to locate the facial feature points on the 2D image and fuses the 2D data with a 3D face model using Extended Kalman Filter to yield 3D facial movement information. An alternating optimizing strategy is adopted to fit to different persons automatically. Experiments show that the proposed framework could track the 3D facial movement across various poses and illumination conditions. Given the real face scale the framework could track the eyelid with an error of 1 mm and mouth with an error of 2 mm. The tracking result is reliable for expression analysis or mental state inference.

  8. A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

    Directory of Open Access Journals (Sweden)

    Hongxiao Yu

    2015-05-01

    Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

  9. Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

    Directory of Open Access Journals (Sweden)

    Yazhe Tang

    2015-01-01

    Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

  10. A New Filtering Algorithm Utilizing Radial Velocity Measurement

    Institute of Scientific and Technical Information of China (English)

    LIU Yan-feng; DU Zi-cheng; PAN Quan

    2005-01-01

    Pulse Doppler radar measurements consist of range, azimuth, elevation and radial velocity. Most of the radar tracking algorithms in engineering only utilize position measurement. The extended Kalman filter with radial velocity measureneut is presented, then a new filtering algorithm utilizing radial velocity measurement is proposed to improve tracking results and the theoretical analysis is also given. Simulation results of the new algorithm, converted measurement Kalman filter, extended Kalman filter are compared. The effectiveness of the new algorithm is verified by simulation results.

  11. Strategy for fitting source strength and reconstruction procedure in radioactive particle tracking

    International Nuclear Information System (INIS)

    Mosorov, Volodymyr

    2015-01-01

    The Radioactive Particle Tracking (RPT) technique is widely applied to study the dynamic properties of flows inside a reactor. Usually, a single radioactive particle that is neutrally buoyant with respect to the phase is used as a tracker. The particle moves inside a 3D volume of interest, and its positions are determined by an array of scintillation detectors, which count the incoming photons. The particle position coordinates are calculated by using a reconstruction procedure that solves a minimization problem between the measured counts and calibration data. Although previous studies have described the influence of specified factors on the RPT resolution and sensitivities, the question of how to choose an appropriate source strength and reconstruction procedure for the given RPT setup remains an unsolved problem. This work describes and applies the original strategy for fitting both the source strength and the sampling time interval to a specified RPT setup to guarantee a required accuracy of measurements. Additionally, the measurement accuracy of an RPT setup can be significantly increased by changing the reconstruction procedure. The results of the simulations, based on the Monte Carlo approach, have demonstrated that the proposed strategy allows for the successful implementation of the As Low As Reasonably Achievable (ALARA) principle when designing the RPT setup. The limitations and drawbacks of the proposed procedure are also presented. - Highlights: • We develop an original strategy for fitting source strength and measurement time interval in radioactive particle tracking (RPT) technique. • The proposed strategy allows successfully to implement the ALAPA (As Low As Reasonably Achievable) principle in designing of a RPT setup. • Measurement accuracy of a RPT setup can be significantly increased by improvement of the reconstruction procedure. • The algorithm can be applied to monitor the motion of the radioactive tracer in a reactor

  12. Extended Kalman Filtering to estimate temperature and irradiation for maximum power point tracking of a photovoltaic module

    International Nuclear Information System (INIS)

    Docimo, D.J.; Ghanaatpishe, M.; Mamun, A.

    2017-01-01

    This paper develops an algorithm for estimating photovoltaic (PV) module temperature and effective irradiation level. The power output of a PV system depends directly on both of these states. Estimating the temperature and irradiation allows for improved state-based control methods while eliminating the need of additional sensors. Thermal models and irradiation estimators have been developed in the literature, but none incorporate feedback for estimation. This paper outlines an Extended Kalman Filter for temperature and irradiation estimation. These estimates are, in turn, used within a novel state-based controller that tracks the maximum power point of the PV system. Simulation results indicate this state-based controller provides up to an 8.5% increase in energy produced per day as compared to an impedance matching controller. A sensitivity analysis is provided to examine the impact state estimate errors have on the ability to find the optimal operating point of the PV system. - Highlights: • Developed a temperature and irradiation estimator for photovoltaic systems. • Designed an Extended Kalman Filter to handle model and measurement uncertainty. • Developed a state-based controller for maximum power point tracking (MPPT). • Validated combined estimator/controller algorithm for different weather conditions. • Algorithm increases energy captured up to 8.5% over traditional MPPT algorithms.

  13. Perspectives on Nonlinear Filtering

    KAUST Repository

    Law, Kody

    2015-01-01

    The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

  14. Perspectives on Nonlinear Filtering

    KAUST Repository

    Law, Kody

    2015-01-07

    The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

  15. Bottom loaded filter for radioactive liquids

    International Nuclear Information System (INIS)

    Wendland, W.G.

    1980-01-01

    A bottom loaded filter assembly for filtering radioactive liquids through a replaceable cartridge filter is disclosed. The filter assembly includes a lead-filled jacket enveloping a housing having a chamber therein for the filter cartridge. A track arrangement carries a hatch for sealing the chamber. A spacer plug supports the cartridge within guide means associated with the inlet conduit in the chamber. The plug and cartridge drop out of the chamber when the hatch is unbolted and move laterally of the chamber. During cartridge replacement, a new plug and cartridge are supported in the guide means by a spacer bar inserted across the track means under the chamber. The hatch is then slid under the chamber and bolted to the vessel, engaging an o-ring to seal the chamber

  16. Application of Knowledge-Based Techniques to Tracking Function

    National Research Council Canada - National Science Library

    Farina, A

    2006-01-01

    ...: historical survey of stochastic filtering theory; overview of tracking systems with some details on mono-sensor and multi-sensor tracking, evolution of filtering logics, evolution of correlation logics, and presentation of recent findings on non...

  17. Robust Visual Tracking Using the Bidirectional Scale Estimation

    Directory of Open Access Journals (Sweden)

    An Zhiyong

    2017-01-01

    Full Text Available Object tracking with robust scale estimation is a challenging task in computer vision. This paper presents a novel tracking algorithm that learns the translation and scale filters with a complementary scheme. The translation filter is constructed using the ridge regression and multidimensional features. A robust scale filter is constructed by the bidirectional scale estimation, including the forward scale and backward scale. Firstly, we learn the scale filter using the forward tracking information. Then the forward scale and backward scale can be estimated using the respective scale filter. Secondly, a conservative strategy is adopted to compromise the forward and backward scales. Finally, the scale filter is updated based on the final scale estimation. It is effective to update scale filter since the stable scale estimation can improve the performance of scale filter. To reveal the effectiveness of our tracker, experiments are performed on 32 sequences with significant scale variation and on the benchmark dataset with 50 challenging videos. Our results show that the proposed tracker outperforms several state-of-the-art trackers in terms of robustness and accuracy.

  18. Automated cloud tracking system for the Akatsuki Venus Climate Orbiter data

    Science.gov (United States)

    Ogohara, Kazunori; Kouyama, Toru; Yamamoto, Hiroki; Sato, Naoki; Takagi, Masahiro; Imamura, Takeshi

    2012-02-01

    Japanese Venus Climate Orbiter, Akatsuki, is cruising to approach to Venus again although its first Venus orbital insertion (VOI) has been failed. At present, we focus on the next opportunity of VOI and the following scientific observations.We have constructed an automated cloud tracking system for processing data obtained by Akatsuki in the present study. In this system, correction of the pointing of the satellite is essentially important for improving accuracy of the cloud motion vectors derived using the cloud tracking. Attitude errors of the satellite are reduced by fitting an ellipse to limb of an imaged Venus disk. Next, longitude-latitude distributions of brightness (cloud patterns) are calculated to make it easy to derive the cloud motion vectors. The grid points are distributed at regular intervals in the longitude-latitude coordinate. After applying the solar zenith correction and a highpass filter to the derived longitude-latitude distributions of brightness, the cloud features are tracked using pairs of images. As a result, we obtain cloud motion vectors on longitude-latitude grid points equally spaced. These entire processes are pipelined and automated, and are applied to all data obtained by combinations of cameras and filters onboard Akatsuki. It is shown by several tests that the cloud motion vectors are determined with a sufficient accuracy. We expect that longitude-latitude data sets created by the automated cloud tracking system will contribute to the Venus meteorology.

  19. Automatic detection, tracking and sensor integration

    Science.gov (United States)

    Trunk, G. V.

    1988-06-01

    This report surveys the state of the art of automatic detection, tracking, and sensor integration. In the area of detection, various noncoherent integrators such as the moving window integrator, feedback integrator, two-pole filter, binary integrator, and batch processor are discussed. Next, the three techniques for controlling false alarms, adapting thresholds, nonparametric detectors, and clutter maps are presented. In the area of tracking, a general outline is given of a track-while-scan system, and then a discussion is presented of the file system, contact-entry logic, coordinate systems, tracking filters, maneuver-following logic, tracking initiating, track-drop logic, and correlation procedures. Finally, in the area of multisensor integration the problems of colocated-radar integration, multisite-radar integration, radar-IFF integration, and radar-DF bearing strobe integration are treated.

  20. Digital Inequalities in the Use of Self-Tracking Diet and Fitness Apps: Interview Study on the Influence of Social, Economic, and Cultural Factors.

    Science.gov (United States)

    Régnier, Faustine; Chauvel, Louis

    2018-04-20

    Digital devices are driving economic and social transformations, but assessing the uses, perceptions, and impact of these new technologies on diet and physical activity remains a major societal challenge. We aimed to determine under which social, economic, and cultural conditions individuals in France were more likely to be actively invested in the use of self-tracking diet and fitness apps for better health behaviors. Existing users of 3 diet and fitness self-tracking apps (Weight Watchers, MyFitnessPal, and sport apps) were recruited from 3 regions of France. We interviewed 79 individuals (Weight Watchers, n=37; MyFitnessPal, n=20; sport apps, n=22). In-depth semistructured interviews were conducted with each participant, using open-ended questions about their use of diet and fitness apps. A triangulation of methods (content, textual, and quantitative analyses) was performed. We found 3 clusters of interviewees who differed by social background and curative goal linked to use under constraint versus preventive goal linked to chosen use, and intensity of their self-quantification efforts and participation in social networks. Interviewees used the apps for a diversity of uses, including measurement, tracking, quantification, and participation in digital communities. A digital divide was highlighted, comprising a major social gap. Social conditions for appropriation of self-tracking devices included sociodemographic factors, life course stages, and cross-cutting factors of heterogeneity. Individuals from affluent or intermediate social milieus were most likely to use the apps and to participate in the associated online social networks. These interviewees also demonstrated a preventive approach to a healthy lifestyle. Individuals from lower milieus were more reluctant to use digital devices relating to diet and physical activity or to participate in self-quantification. The results of the study have major implications for public health: the digital self

  1. Digital Inequalities in the Use of Self-Tracking Diet and Fitness Apps: Interview Study on the Influence of Social, Economic, and Cultural Factors

    Science.gov (United States)

    Chauvel, Louis

    2018-01-01

    Background Digital devices are driving economic and social transformations, but assessing the uses, perceptions, and impact of these new technologies on diet and physical activity remains a major societal challenge. Objective We aimed to determine under which social, economic, and cultural conditions individuals in France were more likely to be actively invested in the use of self-tracking diet and fitness apps for better health behaviors. Methods Existing users of 3 diet and fitness self-tracking apps (Weight Watchers, MyFitnessPal, and sport apps) were recruited from 3 regions of France. We interviewed 79 individuals (Weight Watchers, n=37; MyFitnessPal, n=20; sport apps, n=22). In-depth semistructured interviews were conducted with each participant, using open-ended questions about their use of diet and fitness apps. A triangulation of methods (content, textual, and quantitative analyses) was performed. Results We found 3 clusters of interviewees who differed by social background and curative goal linked to use under constraint versus preventive goal linked to chosen use, and intensity of their self-quantification efforts and participation in social networks. Interviewees used the apps for a diversity of uses, including measurement, tracking, quantification, and participation in digital communities. A digital divide was highlighted, comprising a major social gap. Social conditions for appropriation of self-tracking devices included sociodemographic factors, life course stages, and cross-cutting factors of heterogeneity. Conclusions Individuals from affluent or intermediate social milieus were most likely to use the apps and to participate in the associated online social networks. These interviewees also demonstrated a preventive approach to a healthy lifestyle. Individuals from lower milieus were more reluctant to use digital devices relating to diet and physical activity or to participate in self-quantification. The results of the study have major implications

  2. FITNESS TRAINING AS PREPARATION FOR BICYCLE TRACKING TOURS

    Directory of Open Access Journals (Sweden)

    Dragan Martinović

    2007-05-01

    Full Text Available Track, tracking“(English – a trail, to follow a trail. Tracking means hiking on marked tracks, roads and mountain paths, with the aim of being physically active surrounded by fresh air, natural beauties and cultural/historical monuments. Physical preparation (fi tness training is a very specifi c and complex process that has an active positive infl uence on the maintenance of health, on forming of good bodily posture, as well as on growth and development of physical and psycho-social values of an individual.

  3. Box-particle intensity filter

    OpenAIRE

    Schikora, Marek; Gning, Amadou; Mihaylova, Lyudmila; Cremers, Daniel; Koch, Wofgang; Streit, Roy

    2012-01-01

    This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables thi...

  4. Enhanced online convolutional neural networks for object tracking

    Science.gov (United States)

    Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

    2018-04-01

    In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

  5. Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design

    Science.gov (United States)

    Lin, Yi-Chun

    2017-01-01

    A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was “Moving head up-and-down”, “Talking” or “Bending over” in bivariate and PCA RFTPs were 13.3–61.9% and 22.9–52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit

  6. Fusing inertial sensor data in an extended Kalman filter for 3D camera tracking.

    Science.gov (United States)

    Erdem, Arif Tanju; Ercan, Ali Özer

    2015-02-01

    In a setup where camera measurements are used to estimate 3D egomotion in an extended Kalman filter (EKF) framework, it is well-known that inertial sensors (i.e., accelerometers and gyroscopes) are especially useful when the camera undergoes fast motion. Inertial sensor data can be fused at the EKF with the camera measurements in either the correction stage (as measurement inputs) or the prediction stage (as control inputs). In general, only one type of inertial sensor is employed in the EKF in the literature, or when both are employed they are both fused in the same stage. In this paper, we provide an extensive performance comparison of every possible combination of fusing accelerometer and gyroscope data as control or measurement inputs using the same data set collected at different motion speeds. In particular, we compare the performances of different approaches based on 3D pose errors, in addition to camera reprojection errors commonly found in the literature, which provides further insight into the strengths and weaknesses of different approaches. We show using both simulated and real data that it is always better to fuse both sensors in the measurement stage and that in particular, accelerometer helps more with the 3D position tracking accuracy, whereas gyroscope helps more with the 3D orientation tracking accuracy. We also propose a simulated data generation method, which is beneficial for the design and validation of tracking algorithms involving both camera and inertial measurement unit measurements in general.

  7. Thermal Tracking of Sports Players

    DEFF Research Database (Denmark)

    Gade, Rikke; Moeslund, Thomas B.

    2014-01-01

    We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline...

  8. Scheme of adaptive polarization filtering based on Kalman model

    Institute of Scientific and Technical Information of China (English)

    Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

    2006-01-01

    A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

  9. Fast Filter Central Drift Chamber Program. MAC Note 404

    International Nuclear Information System (INIS)

    Ford, W.T.

    1979-01-01

    A fast filter of the central detector tracking program was developed and tested. The search for tracks is conducted as in the full linking program - from the outermost layer hit to the next layer in. Any hit is accepted within a road centered which is large enough to allow for stero displacement and any curvature. With the fast filter, this is continued to the innermost layer, with five or more hits accepted as a track

  10. Pose Tracking Algorithm of an Endoscopic Surgery Robot Wrist

    International Nuclear Information System (INIS)

    Wang, L; Yin, H L; Meng, Q

    2006-01-01

    In recent two decades, more and more research on the endoscopic surgery has been carried out [2]. Most of the work focuses on the development of the robot in the field of robotics and the navigation of the surgery tools based on computer graphics. But the tracking and locating of the EndoWrist is also a very important aspect. This paper deals with the the tracking algorithm of the EndoWrist's pose (position and orientation). The linear tracking of the position is handled by the Kalman Filter. The quaternion-based nonlinear orientation tracking is implemented with the Extended Kalman Filter. The most innovative point of this paper is the parameterization of the motion model of the Extended Kalman Filter

  11. Kalman Filter Predictor and Initialization Algorithm for PRI Tracking

    National Research Council Canada - National Science Library

    Hock, Melinda

    1998-01-01

    .... The algorithm uses a Kalman filter for prediction combined with a preprocessing routine to determine the period of the stagger sequence and to construct an uncorrupted data set for Kalman filter initialization...

  12. Pose Tracking Algorithm of an Endoscopic Surgery Robot Wrist

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L [Chinese-German Institute of Automatic Control Engineering, Tongji University (China); Yin, H L [Chinese-German Institute of Automatic Control Engineering, Tongji University (China); Meng, Q [Shanghai University of Electric Power (China)

    2006-10-15

    In recent two decades, more and more research on the endoscopic surgery has been carried out [2]. Most of the work focuses on the development of the robot in the field of robotics and the navigation of the surgery tools based on computer graphics. But the tracking and locating of the EndoWrist is also a very important aspect. This paper deals with the the tracking algorithm of the EndoWrist's pose (position and orientation). The linear tracking of the position is handled by the Kalman Filter. The quaternion-based nonlinear orientation tracking is implemented with the Extended Kalman Filter. The most innovative point of this paper is the parameterization of the motion model of the Extended Kalman Filter.

  13. PolarTrack: Optical Outside-In Device Tracking that Exploits Display Polarization

    DEFF Research Database (Denmark)

    Rädle, Roman; Jetter, Hans-Christian; Fischer, Jonathan

    2018-01-01

    PolarTrack is a novel camera-based approach to detecting and tracking mobile devices inside the capture volume. In PolarTrack, a polarization filter continuously rotates in front of an off-the-shelf color camera, which causes the displays of observed devices to periodically blink in the camera feed....... The periodic blinking results from the physical characteristics of current displays, which shine polarized light either through an LC overlay to produce images or through a polarizer to reduce light reflections on OLED displays. PolarTrack runs a simple detection algorithm on the camera feed to segment...... displays and track their locations and orientations, which makes PolarTrack particularly suitable as a tracking system for cross-device interaction with mobile devices. Our evaluation of PolarTrack's tracking quality and comparison with state-of-the-art camera-based multi-device tracking showed a better...

  14. Manifold Regularized Correlation Object Tracking.

    Science.gov (United States)

    Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

    2018-05-01

    In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

  15. Multi-template Scale-Adaptive Kernelized Correlation Filters

    KAUST Repository

    Bibi, Adel Aamer

    2015-12-07

    This paper identifies the major drawbacks of a very computationally efficient and state-of-the-art-tracker known as the Kernelized Correlation Filter (KCF) tracker. These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear combination of taps from the previous frame). In our approach, we update the scale of the tracker by maximizing over the posterior distribution of a grid of scales. As for the filter update, we prove and show that it is possible to use all previous training examples to update the filter taps very efficiently using fixed-point optimization. We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015.

  16. Multi-template Scale-Adaptive Kernelized Correlation Filters

    KAUST Repository

    Bibi, Adel Aamer; Ghanem, Bernard

    2015-01-01

    This paper identifies the major drawbacks of a very computationally efficient and state-of-the-art-tracker known as the Kernelized Correlation Filter (KCF) tracker. These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear combination of taps from the previous frame). In our approach, we update the scale of the tracker by maximizing over the posterior distribution of a grid of scales. As for the filter update, we prove and show that it is possible to use all previous training examples to update the filter taps very efficiently using fixed-point optimization. We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015.

  17. RSSI based indoor tracking in sensor networks using Kalman filters

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Skjøth, Flemming; Munksgaard, Lene

    2010-01-01

    We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio...

  18. Track reconstruction at the ILC: the ILD tracking software

    International Nuclear Information System (INIS)

    Gaede, Frank; Aplin, Steven; Rosemann, Christoph; Voutsinas, Georgios; Glattauer, Robin

    2014-01-01

    One of the key requirements for Higgs physics at the International Linear Collider ILC is excellent track reconstruction with very good momentum and impact parameter resolution. ILD is one of the two detector concepts at the ILC. Its central tracking system comprises of an outer Si-tracker, a highly granular TPC, an intermediate silicon tracker and a pixel vertex detector, and it is complemented by silicon tracking disks in the forward direction. Large hit densities from beam induced coherent electron-positron pairs at the ILC pose an additional challenge to the pattern recognition algorithms. We present the recently developed new ILD tracking software, the pattern recognition algorithms that are using clustering techniques, Cellular Automatons and Kalman filter based track extrapolation. The performance of the ILD tracking system is evaluated using a detailed simulation including dead material, gaps and imperfections.

  19. Mixed labelling in multitarget particle filtering

    NARCIS (Netherlands)

    Boers, Y.; Sviestins, Egils; Driessen, Hans

    2010-01-01

    The so-called mixed labelling problem inherent to a joint state multitarget particle filter implementation is treated. The mixed labelling problem would be prohibitive for track extraction from a joint state multitarget particle filter. It is shown, using the theory of Markov chains, that the mixed

  20. Application Mail Tracking Using RSA Algorithm As Security Data and HOT-Fit a Model for Evaluation System

    Science.gov (United States)

    Permadi, Ginanjar Setyo; Adi, Kusworo; Gernowo, Rahmad

    2018-02-01

    RSA algorithm give security in the process of the sending of messages or data by using 2 key, namely private key and public key .In this research to ensure and assess directly systems are made have meet goals or desire using a comprehensive evaluation methods HOT-Fit system .The purpose of this research is to build a information system sending mail by applying methods of security RSA algorithm and to evaluate in uses the method HOT-Fit to produce a system corresponding in the faculty physics. Security RSA algorithm located at the difficulty of factoring number of large coiled factors prima, the results of the prime factors has to be done to obtain private key. HOT-Fit has three aspects assessment, in the aspect of technology judging from the system status, the quality of system and quality of service. In the aspect of human judging from the use of systems and satisfaction users while in the aspect of organization judging from the structure and environment. The results of give a tracking system sending message based on the evaluation acquired.

  1. Application Mail Tracking Using RSA Algorithm As Security Data and HOT-Fit a Model for Evaluation System

    Directory of Open Access Journals (Sweden)

    Setyo Permadi Ginanjar

    2018-01-01

    Full Text Available RSA algorithm give security in the process of the sending of messages or data by using 2 key, namely private key and public key .In this research to ensure and assess directly systems are made have meet goals or desire using a comprehensive evaluation methods HOT-Fit system .The purpose of this research is to build a information system sending mail by applying methods of security RSA algorithm and to evaluate in uses the method HOT-Fit to produce a system corresponding in the faculty physics. Security RSA algorithm located at the difficulty of factoring number of large coiled factors prima, the results of the prime factors has to be done to obtain private key. HOT-Fit has three aspects assessment, in the aspect of technology judging from the system status, the quality of system and quality of service. In the aspect of human judging from the use of systems and satisfaction users while in the aspect of organization judging from the structure and environment. The results of give a tracking system sending message based on the evaluation acquired.

  2. Occlusion Handling in Videos Object Tracking: A Survey

    International Nuclear Information System (INIS)

    Lee, B Y; Liew, L H; Cheah, W S; Wang, Y C

    2014-01-01

    Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

  3. Occlusion Handling in Videos Object Tracking: A Survey

    Science.gov (United States)

    Lee, B. Y.; Liew, L. H.; Cheah, W. S.; Wang, Y. C.

    2014-02-01

    Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

  4. Track filtering by robust neural network

    International Nuclear Information System (INIS)

    Baginyan, S.A.; Kisel', I.V.; Konotopskaya, E.V.; Ososkov, G.A.

    1993-01-01

    In the present paper we study the following problems of track information extraction by the artificial neural network (ANN) rotor model: providing initial ANN configuration by an algorithm general enough to be applicable for any discrete detector in- or out of a magnetic field; robustness to heavy contaminated raw data (up to 100% signal-to-noise ratio); stability to the growing event multiplicity. These problems were carried out by corresponding innovations of our model, namely: by a special one-dimensional histogramming, by multiplying weights by a specially designed robust multiplier, and by replacing the simulated annealing schedule by ANN dynamics with an optimally fixed temperature. Our approach is valid for both circular and straight (non-magnetic) tracks and tested on 2D simulated data contaminated by 100% noise points distributed uniformly. To be closer to some reality in our simulation, we keep parameters of the cylindrical spectrometer ARES. 12 refs.; 9 figs

  5. An FPGA based track finder for the L1 trigger of the CMS experiment at the High Luminosity LHC

    CERN Document Server

    Tomalin, Ian; Ball, Fionn Amhairghen; Balzer, Matthias Norbert; Boudoul, Gaelle; Brooke, James John; Caselle, Michele; Calligaris, Luigi; Cieri, Davide; Clement, Emyr John; Dutta, Suchandra; Hall, Geoffrey; Harder, Kristian; Hobson, Peter; Iles, Gregory Michiel; James, Thomas Owen; Manolopoulos, Konstantinos; Matsushita, Takashi; Morton, Alexander; Newbold, David; Paramesvaran, Sudarshan; Pesaresi, Mark Franco; Pozzobon, Nicola; Reid, Ivan; Rose, A. W; Sander, Oliver; Shepherd-Themistocleous, Claire; Shtipliyski, Antoni; Schuh, Thomas; Skinnari, Louise; Summers, Sioni Paris; Tapper, Alexander; Thea, Alessandro; Uchida, Kirika; Vichoudis, Paschalis; Viret, Sebastien; Weber, M; Aggleton, Robin Cameron

    2017-12-14

    A new tracking detector is under development for use by the CMS experiment at the High-Luminosity LHC (HL-LHC). A crucial requirement of this upgrade is to provide the ability to reconstruct all charged particle tracks with transverse momentum above 2-3 GeV within 4$\\mu$s so they can be used in the Level-1 trigger decision. A concept for an FPGA-based track finder using a fully time-multiplexed architecture is presented, where track candidates are reconstructed using a projective binning algorithm based on the Hough Transform, followed by a combinatorial Kalman Filter. A hardware demonstrator using MP7 processing boards has been assembled to prove the entire system functionality, from the output of the tracker readout boards to the reconstruction of tracks with fitted helix parameters. It successfully operates on one eighth of the tracker solid angle acceptance at a time, processing events taken at 40 MHz, each with up to 200 superimposed proton-proton interactions, whilst satisfying the latency requirement. ...

  6. Adaptive Colour Feature Identification in Image for Object Tracking

    Directory of Open Access Journals (Sweden)

    Feng Su

    2012-01-01

    Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

  7. Target Centroid Position Estimation of Phase-Path Volume Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Fengjun Hu

    2016-01-01

    Full Text Available For the problem of easily losing track target when obstacles appear in intelligent robot target tracking, this paper proposes a target tracking algorithm integrating reduced dimension optimal Kalman filtering algorithm based on phase-path volume integral with Camshift algorithm. After analyzing the defects of Camshift algorithm, compare the performance with the SIFT algorithm and Mean Shift algorithm, and Kalman filtering algorithm is used for fusion optimization aiming at the defects. Then aiming at the increasing amount of calculation in integrated algorithm, reduce dimension with the phase-path volume integral instead of the Gaussian integral in Kalman algorithm and reduce the number of sampling points in the filtering process without influencing the operational precision of the original algorithm. Finally set the target centroid position from the Camshift algorithm iteration as the observation value of the improved Kalman filtering algorithm to fix predictive value; thus to make optimal estimation of target centroid position and keep the target tracking so that the robot can understand the environmental scene and react in time correctly according to the changes. The experiments show that the improved algorithm proposed in this paper shows good performance in target tracking with obstructions and reduces the computational complexity of the algorithm through the dimension reduction.

  8. Track Reconstruction in the ATLAS Experiment The Deterministic Annealing Filter

    CERN Document Server

    Fleischmann, S

    2006-01-01

    The reconstruction of the trajectories of charged particles is essential for experiments at the LHC. The experiments contain precise tracking systems structured in layers around the collision point which measure the positions where particle trajectories intersect those layers. The physics analysis on the other hand mainly needs the momentum and direction of the particle at the estimated creation or reaction point. It is therefore needed to determine these parameters from the initial measurements. At the LHC one has to deal with high backgrounds while even small deficits or artifacts can reduce the signal or may produce additional background after event selection. The track reconstruction does not only contain the estimation of the track parameters, but also a pattern recognition deciding which measurements belong to a track and how many particle tracks can be found. Track reconstruction at the ATLAS experiment suffers from the high event rate at the LHC resulting in a high occupancy of the tracking devices. A...

  9. H(infinity)/H(2)/Kalman filtering of linear dynamical systems via variational techniques with applications to target tracking

    Science.gov (United States)

    Rawicz, Paul Lawrence

    In this thesis, the similarities between the structure of the H infinity, H2, and Kalman filters are examined. The filters used in this examination have been derived through duality to the full information controller. In addition, a direct variation of parameters derivation of the Hinfinity filter is presented for both continuous and discrete time (staler case). Direct and controller dual derivations using differential games exist in the literature and also employ variational techniques. Using a variational, rather than a differential games, viewpoint has resulted in a simple relationship between the Riccati equations that arise from the derivation and the results of the Bounded Real Lemma. This same relation has previously been found in the literature and used to relate the Riccati inequality for linear systems to the Hamilton Jacobi inequality for nonlinear systems when implementing the Hinfinity controller. The Hinfinity, H2, and Kalman filters are applied to the two-state target tracking problem. In continuous time, closed form analytic expressions for the trackers and their performance are determined. To evaluate the trackers using a neutral, realistic, criterion, the probability of target escape is developed. That is, the probability that the target position error will be such that the target is outside the radar beam width resulting in a loss of measurement. In discrete time, a numerical example, using the probability of target escape, is presented to illustrate the differences in tracker performance.

  10. COMPARATIVE EVALUATION OF FILTERS USED IN TRACKING AIR TARGETS

    Directory of Open Access Journals (Sweden)

    Y. I. Strekalovskaya

    2015-01-01

    Full Text Available Using an imitation model for a flow of heterogeneous air targets the comparative assessment of the αβ, αβγ and the Kalman filters efficiency is evaluated. In the case of slightly maneuvering target the difference in filters’ efficiency is statistically insignificant; in the case of sharp maneuvering the Kalman filter is significantly more precise.

  11. Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

    Science.gov (United States)

    Alam, Mohammad S.; Bhuiyan, Sharif M. A.

    2014-01-01

    In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

  12. Developmental pathways of fitness, and not baseline, predict fitness status at the end of childhood

    OpenAIRE

    Rodrigues, Luis Paulo; Stodden, David F.; Lopes, Vítor P.

    2013-01-01

    It is generally described that children fitness levels increase along childhood. Complementary to this idea is the notion that the tracking of children’s fitness is good to moderate during this developmental time, and that baseline (initial values) of fitness are determinant on fitness development. The importance of developmental pathways has been recently reinforced by a theoretical argument that predicts that healthy lifestyle trajectories will evolve through either a positive or n...

  13. Computer Vision Tracking Using Particle Filters for 3D Position Estimation

    Science.gov (United States)

    2014-03-27

    List of Acronyms Acronym Definition AFIT Air Force Institute of Technology ASIR Auxiliary Sampling Importance Re-sampling BPF Bootstrap Particle Filter...Auxiliary Sampling Importance Re-sampling ( ASIR ) filter, and Regularized Particle Filter (RPF), also seek to eliminate weight collapse through a variety

  14. The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

    Science.gov (United States)

    Farrell, Steven; Anderson, Dustin; Calafiura, Paolo; Cerati, Giuseppe; Gray, Lindsey; Kowalkowski, Jim; Mudigonda, Mayur; Prabhat; Spentzouris, Panagiotis; Spiropoulou, Maria; Tsaris, Aristeidis; Vlimant, Jean-Roch; Zheng, Stephan

    2017-08-01

    Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data.

  15. The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

    Directory of Open Access Journals (Sweden)

    Farrell Steven

    2017-01-01

    Full Text Available Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM and convolutional neural networks to find and fit tracks in toy detector data.

  16. Kalman Filtering with Real-Time Applications

    CERN Document Server

    Chui, Charles K

    2009-01-01

    Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering.

  17. Hydrodynamics of microbial filter feeding

    DEFF Research Database (Denmark)

    Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia

    2017-01-01

    Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate......-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude......; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet...

  18. Event-triggered cooperative target tracking in wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Lu Kelin

    2016-10-01

    Full Text Available Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measurements. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership measurements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.

  19. Effect of cross-correlation on track-to-track fusion

    Science.gov (United States)

    Saha, Rajat K.

    1994-07-01

    Since the advent of target tracking systems employing a diverse mixture of sensors, there has been increasing recognition by air defense system planners and other military system analysts of the need to integrate these tracks so that a clear air picture can be obtained in a command center. A popular methodology to achieve this goal is to perform track-to-track fusion, which performs track-to-track association as well as kinematic state vector fusion. This paper seeks to answer analytically the extent of improvement achievable by means of kinetic state vector fusion when the tracks are obtained from dissimilar sensors (e.g., Radar/ESM/IRST/IFF). It is well known that evaluation of the performance of state vector fusion algorithms at steady state must take into account the effects of cross-correlation between eligible tracks introduced by the input noise which, unfortunately, is often neglected because of added computational complexity. In this paper, an expression for the steady-state cross-covariance matrix for a 2D state vector track-to-track fusion is obtained. This matrix is shown to be a function of the parameters of the Kalman filters associated with the candidate tracks being fused. Conditions for positive definiteness of the cross-covariance matrix have been derived and the effect of positive definiteness on performance of track-to-track fusion is also discussed.

  20. Kalman filter based data fusion for neutral axis tracking in wind turbine towers

    Science.gov (United States)

    Soman, Rohan; Malinowski, Pawel; Ostachowicz, Wieslaw; Paulsen, Uwe S.

    2015-03-01

    Wind energy is seen as one of the most promising solutions to man's ever increasing demands of a clean source of energy. In particular to reduce the cost of energy (COE) generated, there are efforts to increase the life-time of the wind turbines, to reduce maintenance costs and to ensure high availability. Maintenance costs may be lowered and the high availability and low repair costs ensured through the use of condition monitoring (CM) and structural health monitoring (SHM). SHM allows early detection of damage and allows maintenance planning. Furthermore, it can allow us to avoid unnecessary downtime, hence increasing the availability of the system. The present work is based on the use of neutral axis (NA) for SHM of the structure. The NA is tracked by data fusion of measured yaw angle and strain through the use of Extended Kalman Filter (EKF). The EKF allows accurate tracking even in the presence of changing ambient conditions. NA is defined as the line or plane in the section of the beam which does not experience any tensile or compressive forces when loaded. The NA is the property of the cross section of the tower and is independent of the applied loads and ambient conditions. Any change in the NA position may be used for detecting and locating the damage. The wind turbine tower has been modelled with FE software ABAQUS and validated on data from load measurements carried out on the 34m high tower of the Nordtank, NTK 500/41 wind turbine.

  1. Linear Regression Based Real-Time Filtering

    Directory of Open Access Journals (Sweden)

    Misel Batmend

    2013-01-01

    Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.

  2. Development of etched nuclear tracks

    International Nuclear Information System (INIS)

    Somogyi, G.

    1980-01-01

    The theoretical description of the evolution of etched tracks in solid state nuclear track detectors is considered for different initial conditions, for the cases of constant and varying track etch rates, isotropic and anisotropic bulk etching as well as for thick and thin detectors. It is summarized how one can calculate the main parameters of etch-pit geometry, the track length, the axes of a surface track opening, track profile and track contour. The application of the theory of etch-track evolution is demonstrated with selected practical problems. Attention is paid to certain questions related to the determination of unknown track parameters and calculation of surface track sizes. Finally, the theory is extended to the description of the perforation and etch-hole evolution process in thin detectors, which is of particular interest for track radiography and nuclear filter production. (orig.)

  3. Development of etched nuclear tracks

    International Nuclear Information System (INIS)

    Somogyi, G.

    1979-01-01

    The theoretical description of the evolution of etched tracks in solid state nuclear track detectors is considered for different initial conditions, for the cases of constant and varying track etch rates, isotopic and unisotropic bulk etching as well as for thick and thin detectors. It is summarized how the main parameters of etch-pit geometry, the track length, the axes of a surface track opening, the track profile and the track contour can be calculated. The application of the theory of etch-track evolution is demonstrated with selected practical problems. Attention is paid to certain questions related to the determination of unknown track parameters and calculation of surface track sizes. Finally, the theory is extended to the description of the perforation and etch-hole evolution process in thin detectors, which is of particular interest for track radiography and nuclear filter production. (author)

  4. Particle tracking from image sequences of complex plasma crystals

    International Nuclear Information System (INIS)

    Hadziavdic, Vedad; Melandsoe, Frank; Hanssen, Alfred

    2006-01-01

    In order to gather information about the physics of the complex plasma crystals from the experimental data, particles have to be tracked through a sequence of images. An application of the Kalman filter for that purpose is presented, using a one-dimensional approximation of the particle dynamics as a model for the filter. It is shown that Kalman filter is capable of tracking dust particles even with high levels of measurement noise. An inherent part of the Kalman filter, the innovation process, can be used to estimate values of the physical system parameters from the experimental data. The method is shown to be able to estimate the characteristic oscillation frequency from noisy data

  5. Primer uticaja filtriranja slike u sistemima za praćenje ciljeva primenom termovizije / An example of image filtering in target tracking systems with thermal imagery

    Directory of Open Access Journals (Sweden)

    Zvonko M. Radosavljević

    2003-07-01

    Full Text Available U radu je dat primer primene jedne vrste niskofrekventnog filtriranja sa usrednjavanjem, koje se primenjuje u sistemima za detekciju i praćenje ciljeva u vazdušnom prostoru primenom termovizije. Date su dve metode filtriranja slike. Prva metoda koristi niskofrekventno konvoluciono filtriranje a druga usrednjavajući filtar na osnovu srednje vrednosti nivoa sivog. Ovi filtri su primenjeni u sistemima za praćenje uz pomoć infracrvenih senzora. Određivanje nivoa praga filtriranja vrši se uz pomoć statističkih osobina slike. Veoma važan korak u procesu praćenja je određivanje prozora praćenja, koji maze biti, po dimenzijama, fiksan ili adaptibilan. Pogrešna procena o postojanju cilja u prozoru može se doneti u slučaju prisustva šuma pozadine, predpojačavača, detektora, itd. Filtriranje je neophodan korak u ovim sistemima, kao značajan činilac U povećanju brzine i tačnosti praćenja. / A case of image filtering in air target detecting and tracking systems is described in this paper. Two image filtering methods are given. The first method is performed using a low pass convolving filter and the second one uses the mean value of gray level filter. The main goal of the cited filtering is implementation in IR (infra red systems. Some statistical features of the images were used for selecting the threshold level. The next step in the algorithm is the determination of a 'tracking window' that can be fixed or adaptive in size. A false estimation of a target existing in the window may be influenced by the background noise, low noise amplifier detector, etc.

  6. Integrated tracking, classification, and sensor management theory and applications

    CERN Document Server

    Krishnamurthy, Vikram; Vo, Ba-Ngu

    2012-01-01

    A unique guide to the state of the art of tracking, classification, and sensor management. This book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking approaches, target classification procedures, and large scale sensor management problem-solving techniques.

  7. The singular value filter: a general filter design strategy for PCA-based signal separation in medical ultrasound imaging.

    Science.gov (United States)

    Mauldin, F William; Lin, Dan; Hossack, John A

    2011-11-01

    A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, which we refer to as the blind source separation (BSS) method, as well as a simple frequency-based finite impulse response (FIR) filter used as a baseline for comparison. The performance of each filter was quantified in simulated lesion images as well as experimental cardiac ultrasound data. SVF was demonstrated in both simulation and experimental results, over a wide range of imaging conditions, to outperform the BSS and FIR filtering methods in terms of contrast-to-noise ratio (CNR) and motion tracking performance. In experimental mouse heart data, SVF provided excellent artifact suppression with an average CNR improvement of 1.8 dB with over 40% reduction in displacement tracking error. It was further demonstrated from simulation and experimental results that SVF provided superior clutter rejection, as reflected in larger CNR values, when filtering was achieved using complex pulse-echo received data and non-binary filter coefficients.

  8. A game theory approach to target tracking in sensor networks.

    Science.gov (United States)

    Gu, Dongbing

    2011-02-01

    In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.

  9. Filtered-X Affine Projection Algorithms for Active Noise Control Using Volterra Filters

    Directory of Open Access Journals (Sweden)

    Sicuranza Giovanni L

    2004-01-01

    Full Text Available We consider the use of adaptive Volterra filters, implemented in the form of multichannel filter banks, as nonlinear active noise controllers. In particular, we discuss the derivation of filtered-X affine projection algorithms for homogeneous quadratic filters. According to the multichannel approach, it is then easy to pass from these algorithms to those of a generic Volterra filter. It is shown in the paper that the AP technique offers better convergence and tracking capabilities than the classical LMS and NLMS algorithms usually applied in nonlinear active noise controllers, with a limited complexity increase. This paper extends in two ways the content of a previous contribution published in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03, Grado, Italy, June 2003. First of all, a general adaptation algorithm valid for any order of affine projections is presented. Secondly, a more complete set of experiments is reported. In particular, the effects of using multichannel filter banks with a reduced number of channels are investigated and relevant results are shown.

  10. Personal Dosemeter of Thermal Neutron Using A Cr-39 Detector with Filter Natural LiF

    International Nuclear Information System (INIS)

    Sofyan, Hasnel; Thamrin, M.Thoyib

    1996-01-01

    The research of personal dosemeter for thermal neutron using Cr-39 detector with different thicknesses of natural LiF filter was carried out. The irradiation of Cr-39 detector with neutron source from reactor research TRIGA mark II of Rikkyo University Tokyo, Japan. Nuclear track was counted by automatic method with ASPECT ver.4.22 Series A4T124 software and manual method for correction. The result of research, the maximum of nuclear tracks was obtained at 8 mm of LiF filter was 10 mm with 11,630x10E-5 track/neutron for air radiation. And on phantom radiation, the thickness of filter was 10 mm with 11,630x10E-5 track/neutron. Its values were 3.6 and 7.5 bigger than the response of Cr-39 non filter in air and on phantom radiation, respectively

  11. Kalman Filter Based Data Fusion for Bi-Axial Neutral Axis Tracking in Wind Turbine Towers

    DEFF Research Database (Denmark)

    Soman, Rohan; Malinowski, Pawel; Schmidt Paulsen, Uwe

    2015-01-01

    demonstrates a methodology for the selection of threshold for damage detection based on qualitative data acquired from several damage scenarios of a 10 MW wind turbine. The damage indicator is the change of neutral axis (NA) which is tracked using Kalman Filter (KF). Based on the level of damage to be detected...... in the structure is reflected by a change in this feature. If this change is above a threshold the structure is said to be damaged. In most applications the determination of this threshold is based on engineering judgment and the previous experience of the operator. These practices are highly subjective...... and the probability of occurrence of false positive and false negative detections, a threshold value is selected. This threshold is then applied to strain data from the Nordtank NTK500/41 wind turbine for validation....

  12. A comparison of wearable fitness devices.

    Science.gov (United States)

    Kaewkannate, Kanitthika; Kim, Soochan

    2016-05-24

    Wearable trackers can help motivate you during workouts and provide information about your daily routine or fitness in combination with your smartphone without requiring potentially disruptive manual calculations or records. This paper summarizes and compares wearable fitness devices, also called "fitness trackers" or "activity trackers." These devices are becoming increasingly popular in personal healthcare, motivating people to exercise more throughout the day without the need for lifestyle changes. The various choices in the market for wearable devices are also increasing, with customers searching for products that best suit their personal needs. Further, using a wearable device or fitness tracker can help people reach a fitness goal or finish line. Generally, companies display advertising for these kinds of products and depict them as beneficial, user friendly, and accurate. However, there are no objective research results to prove the veracity of their words. This research features subjective and objective experimental results, which reveal that some devices perform better than others. The four most popular wristband style wearable devices currently on the market (Withings Pulse, Misfit Shine, Jawbone Up24, and Fitbit Flex) are selected and compared. The accuracy of fitness tracking is one of the key components for fitness tracking, and some devices perform better than others. This research shows subjective and objective experimental results that are used to compare the accuracy of four wearable devices in conjunction with user friendliness and satisfaction of 7 real users. In addition, this research matches the opinions between reviewers on an Internet site and those of subjects when using the device. Withings Pulse is the most friendly and satisfactory from the users' viewpoint. It is the most accurate and repeatable for step and distance tracking, which is the most important measurement of fitness tracking, followed by Fitbit Flex, Jawbone Up24, and Misfit

  13. A comparison of wearable fitness devices

    Directory of Open Access Journals (Sweden)

    Kanitthika Kaewkannate

    2016-05-01

    Full Text Available Abstract Background Wearable trackers can help motivate you during workouts and provide information about your daily routine or fitness in combination with your smartphone without requiring potentially disruptive manual calculations or records. This paper summarizes and compares wearable fitness devices, also called “fitness trackers” or “activity trackers.” These devices are becoming increasingly popular in personal healthcare, motivating people to exercise more throughout the day without the need for lifestyle changes. The various choices in the market for wearable devices are also increasing, with customers searching for products that best suit their personal needs. Further, using a wearable device or fitness tracker can help people reach a fitness goal or finish line. Generally, companies display advertising for these kinds of products and depict them as beneficial, user friendly, and accurate. However, there are no objective research results to prove the veracity of their words. This research features subjective and objective experimental results, which reveal that some devices perform better than others. Methods The four most popular wristband style wearable devices currently on the market (Withings Pulse, Misfit Shine, Jawbone Up24, and Fitbit Flex are selected and compared. The accuracy of fitness tracking is one of the key components for fitness tracking, and some devices perform better than others. This research shows subjective and objective experimental results that are used to compare the accuracy of four wearable devices in conjunction with user friendliness and satisfaction of 7 real users. In addition, this research matches the opinions between reviewers on an Internet site and those of subjects when using the device. Results Withings Pulse is the most friendly and satisfactory from the users’ viewpoint. It is the most accurate and repeatable for step and distance tracking, which is the most important measurement of

  14. Kaon Filtering For CLAS Data

    International Nuclear Information System (INIS)

    McNabb, J.

    2001-01-01

    The analysis of data from CLAS is a multi-step process. After the detectors for a given running period have been calibrated, the data is processed in the so called pass-1 cooking. During the pass-1 cooking each event is reconstructed by the program a1c which finds particle tracks and computes momenta from the raw data. The results are then passed on to several data monitoring and filtering utilities. In CLAS software, a filter is a parameterless function which returns an integer indicating whether an event should be kept by that filter or not. There is a main filter program called g1-filter which controls several specific filters and outputs several files, one for each filter. These files may then be analyzed separately, allowing individuals interested in one reaction channel to work from smaller files than using the whole data set would require. There are several constraints on what the filter functions should do. Obviously, the filtered files should be as small as possible, however the filter should also not reject any events that might be used in the later analysis for which the filter was intended

  15. Where does fitness fit in theories of perception?

    Science.gov (United States)

    Anderson, Barton L

    2015-12-01

    Interface theory asserts that neither our perceptual experience of the world nor the scientific constructs used to describe the world are veridical. The primary argument used to uphold this claim is that (1) evolution is driven by a process of natural selection that favors fitness over veridicality, and (2) payoffs do not vary monotonically with truth. I argue that both the arguments used to bolster this claim and the conclusions derived from it are flawed. Interface theory assumes that perception evolved to directly track fitness but fails to consider the role of adaptation on ontogenetic time scales. I argue that the ubiquity of nonmonotonic payoff functions requires that (1) perception tracks "truth" for species that adapt on ontogenetic time scales and (2) that perception should be distinct from utility. These conditions are required to pursue an adaptive strategy to mitigate homeostatic imbalances. I also discuss issues with the interface metaphor, the particular formulation of veridicality that is considered, and the relationship of interface theory to the history of ideas on these topics.

  16. Kalman filtering with real-time applications

    CERN Document Server

    Chui, Charles K

    2017-01-01

    This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help de...

  17. A fit method for the determination of inherent filtration with diagnostic x-ray units

    International Nuclear Information System (INIS)

    Meghzifene, K; Nowotny, R; Aiginger, H

    2006-01-01

    A method for the determination of total inherent filtration for clinical x-ray units using attenuation curves was devised. A model for the calculation of x-ray spectra is used to calculate kerma values which are then adjusted to the experimental data in minimizing the sum of the squared relative differences in kerma using a modified simplex fit process. The model considers tube voltage, voltage ripple, anode angle and additional filters. Fit parameters are the thickness of an additional inherent Al filter and a general normalization factor. Nineteen sets of measurements including attenuation data for three tube voltages and five Al-filter settings each were obtained. Relative differences of experimental and calculated kerma using the data for the additional filter thickness are within a range of -7.6% to 6.4%. Quality curves, i.e. the relationship of additional filtration to HVL, are often used to determine filtration but the results show that standard quality curves do not reflect the variety of conditions encountered in practice. To relate the thickness of the additional filter to the condition of the anode surface, the data fits were also made using tungsten as the filter material. These fits gave an identical fit quality compared to aluminium with a tungsten filter thickness of 2.12-8.21 μm which is within the range of the additional absorbing layers determined for rough anodes

  18. Making tracks

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1986-10-15

    In many modern tracking chambers, the sense wires, rather than being lined up uniformly, are grouped into clusters to facilitate the pattern recognition process. However, with higher energy machines providing collisions richer in secondary particles, event reconstruction becomes more complicated. A Caltech / Illinois / SLAC / Washington group developed an ingenious track finding and fitting approach for the Mark III detector used at the SPEAR electron-positron ring at SLAC (Stanford). This capitalizes on the detector's triggering, which uses programmable logic circuits operating in parallel, each 'knowing' the cell patterns for all tracks passing through a specific portion of the tracker (drift chamber)

  19. Robust visual tracking via multi-task sparse learning

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

    2012-01-01

    In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates

  20. Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

    Science.gov (United States)

    Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

    2016-01-01

    Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

  1. Stabilization diagrams using operational modal analysis and sliding filters

    DEFF Research Database (Denmark)

    Olsen, Peter; Juul, Martin Ørum Ørhem; Tarpø, Marius Glindtvad

    2017-01-01

    This paper presents a filtering technique for doing effective operational modal analysis. The result of the filtering method is construction of stabilization diagram that clearly separates physical poles from spurious noise poles needed for unbiased fitting. A band pass filter is moved slowly over...

  2. Tracking magma volume recovery at okmok volcano using GPS and an unscented kalman filter

    Science.gov (United States)

    Fournier, T.; Freymueller, Jeffrey T.; Cervelli, Peter

    2009-01-01

    Changes beneath a volcano can be observed through position changes in a GPS network, but distinguishing the source of site motion is not always straightforward. The records of continuous GPS sites provide a favorable data set for tracking magma migration. Dense campaign observations usually provide a better spatial picture of the overall deformation field, at the expense of an episodic temporal record. Combining these observations provides the best of both worlds. A Kalman filter provides a means for integrating discrete and continuous measurements and for interpreting subtle signals. The unscented Kalman filter (UKF) is a nonlinear method for time-dependent observations. We demonstrate the application of this technique to deformation data by applying it to GPS data collected at Okmok volcano. Seven years of GPS observations at Okmok are analyzed using a Mogi source model and the UKF. The deformation source at Okmok is relatively stable at 2.5 km depth below sea level, located beneath the center of the caldera, which means the surface deformation is caused by changes in the strength of the source. During the 7 years of GPS observations more than 0.5 m of uplift has occurred, a majority of that during the time period January 2003 to July 2004. The total volume recovery at Okmok since the last eruption in 1997 is ??60-80%. The UKF allows us to solve simultaneously for the time-dependence of the source strength and for the location without a priori information about the source. ?? 2009 by the American Geophysical Union.

  3. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    Science.gov (United States)

    Ma, Jian; Lu, Chen; Liu, Hongmei

    2015-01-01

    The aircraft environmental control system (ECS) is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF) and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF) and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger.

  4. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    Directory of Open Access Journals (Sweden)

    Jian Ma

    Full Text Available The aircraft environmental control system (ECS is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger.

  5. Optimal Control Strategy for Marine Ssp Podded Propulsion Motor Based on Strong Tracking-Epf

    Directory of Open Access Journals (Sweden)

    Yao Wenlong

    2015-09-01

    Full Text Available Aiming at the non-linearity of state equation and observation equation of SSP (Siemen Schottel Propulsor propulsion motor, an improved particle filter algorithm based on strong tracking extent Kalman filter (ST-EKF was presented, and it was imported into the marine SSP propulsion motor control system. The strong tracking filter was used to update particles in the new algorithm and produce importance densities. As a result, the problems of particle degeneracy and sample impoverishment were ameliorated, the propulsion motor states and the rotor resistance were estimated simultaneously using strong track filter (STF, and the tracking ability of marine SSP propulsion motor control system was improved. Simulation result shown that the improved EPF algorithm was not only improving the prediction accuracy of the motor states and the rotor resistance, but also it can satisfy the requirement of navigation in harbor. It had the better accuracy than EPF algorithm.

  6. A Signal Decomposition Method for Ultrasonic Guided Wave Generated from Debonding Combining Smoothed Pseudo Wigner-Ville Distribution and Vold–Kalman Filter Order Tracking

    Directory of Open Access Journals (Sweden)

    Junhua Wu

    2017-01-01

    Full Text Available Carbon fibre composites have a promising application future of the vehicle, due to its excellent physical properties. Debonding is a major defect of the material. Analyses of wave packets are critical for identification of the defect on ultrasonic nondestructive evaluation and testing. In order to isolate different components of ultrasonic guided waves (GWs, a signal decomposition algorithm combining Smoothed Pseudo Wigner-Ville distribution and Vold–Kalman filter order tracking is presented. In the algorithm, the time-frequency distribution of GW is first obtained by using Smoothed Pseudo Wigner-Ville distribution. The frequencies of different modes are computed based on summation of the time-frequency coefficients in the frequency direction. On the basis of these frequencies, isolation of different modes is done by Vold–Kalman filter order tracking. The results of the simulation signal and the experimental signal reveal that the presented algorithm succeeds in decomposing the multicomponent signal into monocomponents. Even though components overlap in corresponding Fourier spectrum, they can be isolated by using the presented algorithm. So the frequency resolution of the presented method is promising. Based on this, we can do research about defect identification, calculation of the defect size, and locating the position of the defect.

  7. Mobile Tracking Systems Using Meter Class Reflective Telescopes

    Science.gov (United States)

    Sturzenbecher, K.; Ehrhorn, B.

    This paper is a discussion on the use of large reflective telescopes on mobile tracking systems with modern instrument control systems. Large optics can be defined as reflective telescopes with an aperture of at least 20 inches in diameter. New carbon composite construction techniques allow for larger, stronger, and lighter telescopes ranging from 240 pounds for a 20 inch, to 800 pounds for a 32 inch, making them ideal for mobile tracking systems. These telescopes have better light gathering capability and produce larger images with greater detail at a longer range than conventional refractive lenses. In a mobile configuration these systems provide the ability to move the observation platform to the optimal location anywhere in the world. Mounting and systems integration - We will discuss how large telescopes can be physically fit to the mobile tracking system and the integration with the tracking systems' digital control system. We will highlight the remote control capabilities. We will discuss special calibration techniques available in a modern instrument control system such as star calibration, calibration of sensors. Tracking Performance - We will discuss the impact of using large telescopes on the performance of the mobile tracking system. We will highlight the capabilities for auto-tracking and sidereal rate tracking in a mobile mount. Large optics performance - We will discuss the advantages of two-mirror Ritchey-Chrétien reflective optics which offer in-focus imaging across the spectrum, from visible to Long Wave Infrared. These zero expansion optics won't lose figure or focus during temperature changes. And the carbon composite telescope tube is thermally inert. The primary mirror is a modern lightweight "dish" mirror for low thermal mass and is center supported/self balancing. Applications - We will discuss Visible - IR Imaging requirements, Optical Rangefinders, and capabilities for special filters to increase resolution in difficult conditions such as

  8. High resolution vertical profiles of wind, temperature and humidity obtained by computer processing and digital filtering of radiosonde and radar tracking data from the ITCZ experiment of 1977

    Science.gov (United States)

    Danielson, E. F.; Hipskind, R. S.; Gaines, S. E.

    1980-01-01

    Results are presented from computer processing and digital filtering of radiosonde and radar tracking data obtained during the ITCZ experiment when coordinated measurements were taken daily over a 16 day period across the Panama Canal Zone. The temperature relative humidity and wind velocity profiles are discussed.

  9. Fitness function and nonunique solutions in x-ray reflectivity curve fitting: crosserror between surface roughness and mass density

    International Nuclear Information System (INIS)

    Tiilikainen, J; Bosund, V; Mattila, M; Hakkarainen, T; Sormunen, J; Lipsanen, H

    2007-01-01

    Nonunique solutions of the x-ray reflectivity (XRR) curve fitting problem were studied by modelling layer structures with neural networks and designing a fitness function to handle the nonidealities of measurements. Modelled atomic-layer-deposited aluminium oxide film structures were used in the simulations to calculate XRR curves based on Parratt's formalism. This approach reduced the dimensionality of the parameter space and allowed the use of fitness landscapes in the study of nonunique solutions. Fitness landscapes, where the height in a map represents the fitness value as a function of the process parameters, revealed tracks where the local fitness optima lie. The tracks were projected on the physical parameter space thus allowing the construction of the crosserror equation between weakly determined parameters, i.e. between the mass density and the surface roughness of a layer. The equation gives the minimum error for the other parameters which is a consequence of the nonuniqueness of the solution if noise is present. Furthermore, the existence of a possible unique solution in a certain parameter range was found to be dependent on the layer thickness and the signal-to-noise ratio

  10. Updating the OMERACT filter

    DEFF Research Database (Denmark)

    Kirwan, John R; Boers, Maarten; Hewlett, Sarah

    2014-01-01

    OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Filter provides guidelines for the development and validation of outcome measures for use in clinical research. The "Truth" section of the OMERACT Filter presupposes an explicit framework for identifying the relevant core outcomes...... for defining core areas of measurement ("Filter 2.0 Core Areas of Measurement") was presented at OMERACT 11 to explore areas of consensus and to consider whether already endorsed core outcome sets fit into this newly proposed framework. METHODS: Discussion groups critically reviewed the extent to which case......, presentation, and clarity of the framework were questioned. The discussion groups and subsequent feedback highlighted 20 such issues. CONCLUSION: These issues will require resolution to reach consensus on accepting the proposed Filter 2.0 framework of Core Areas as the basis for the selection of Core Outcome...

  11. Learning Rotation for Kernel Correlation Filter

    KAUST Repository

    Hamdi, Abdullah

    2017-08-11

    Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks. However it suffers from problems that affect its performance like occlusion, rotation and scale change. This paper tries to tackle the problem of rotation by reformulating the optimization problem for learning the correlation filter. This modification (RKCF) includes learning rotation filter that utilizes circulant structure of HOG feature to guesstimate rotation from one frame to another and enhance the detection of KCF. Hence it gains boost in overall accuracy in many of OBT50 detest videos with minimal additional computation.

  12. An efficient incremental learning mechanism for tracking concept drift in spam filtering.

    Directory of Open Access Journals (Sweden)

    Jyh-Jian Sheu

    Full Text Available This research manages in-depth analysis on the knowledge about spams and expects to propose an efficient spam filtering method with the ability of adapting to the dynamic environment. We focus on the analysis of email's header and apply decision tree data mining technique to look for the association rules about spams. Then, we propose an efficient systematic filtering method based on these association rules. Our systematic method has the following major advantages: (1 Checking only the header sections of emails, which is different from those spam filtering methods at present that have to analyze fully the email's content. Meanwhile, the email filtering accuracy is expected to be enhanced. (2 Regarding the solution to the problem of concept drift, we propose a window-based technique to estimate for the condition of concept drift for each unknown email, which will help our filtering method in recognizing the occurrence of spam. (3 We propose an incremental learning mechanism for our filtering method to strengthen the ability of adapting to the dynamic environment.

  13. Elastic tracking versus neural network tracking for very high multiplicity problems

    International Nuclear Information System (INIS)

    Harlander, M.; Gyulassy, M.

    1991-04-01

    A new Elastic Tracking (ET) algorithm is proposed for finding tracks in very high multiplicity and noisy environments. It is based on a dynamical reinterpretation and generalization of the Radon transform and is related to elastic net algorithms for geometrical optimization. ET performs an adaptive nonlinear fit to noisy data with a variable number of tracks. Its numerics is more efficient than that of the traditional Radon or Hough transform method because it avoids binning of phase space and the costly search for valid minima. Spurious local minima are avoided in ET by introducing a time-dependent effective potential. The method is shown to be very robust to noise and measurement error and extends tracking capabilities to much higher track densities than possible via local road finding or even the novel Denby-Peterson neural network tracking algorithms. 12 refs., 2 figs

  14. Finding the Right Fit: Understanding Health Tracking in Workplace Wellness Programs

    DEFF Research Database (Denmark)

    Chung, Chia-Fang; Jensen, Nanna Gorm; Shklovski, Irina

    2017-01-01

    Workplace health and wellness programs are increasingly integrating personal health tracking technologies, such as Fitbit and Apple Watch. Many question whether these technologies truly support employees in their pursuit of better wellness levels, raising objections about workplace surveillance...... and further blurring of boundaries between work and personal life. We conducted a study to understand how tracking tools are adopted in wellness programs and employees' opinions about these programs. We find that employees are generally positive about incentivized health tracking in the workplace, as it helps...... raise awareness of activity levels. However, there is a gap between the intentions of the programs and individual experiences and health goals. This sometimes results in confusion and creates barriers to participation. Even if this gap can be addressed, health tracking in the workplace...

  15. Online multi-modal robust non-negative dictionary learning for visual tracking.

    Science.gov (United States)

    Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

    2015-01-01

    Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

  16. Robust visual tracking via structured multi-task sparse learning

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

    2012-01-01

    In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary

  17. An inventory of the South African fitness industry

    African Journals Online (AJOL)

    Among many of the key players within the South African fitness industry, there ..... Tennis courts. Indoor track .... to track the influence of this initiative on the growth of the industry, both in ... members have NQF-aligned qualifications in their field.

  18. Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter.

    Science.gov (United States)

    Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

    2017-01-17

    The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor's stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

  19. Method of mounting filter elements and mounting therefor

    International Nuclear Information System (INIS)

    Karelin, J.; Neumann, G.M.

    1981-01-01

    A process for the insertion and exchange of the filter elements for suspended matter is performed from the clean-air-side. During the insertion of a filter element, a plastic tube (Which encircles the circumference of the filter element and which exceeds in its length the layer thickness of the filter element several times) is tightly connected in its middle section with the side walls, which side walls form a border around the filter element; and then the open end of the plastic tube, which faces the frame, is connected by way of a tight fit with a ring, which is actually known and which surrounds the orifice of the frame into which the filter element is inserted. The filter element is connected with the frame by means of tightening devices, and the outer free end of the tube is turned inside out and around the filter element for the purpose of unhindered air passage through the filter layer, that during the exchange of the contaminated filter element, the outer open end of the tube is heat sealed. The filter element is disconnected and removed from the frame by flipping down of the tightening devices, and the tube is heat sealed in the section between the filter element and the frame, and, that during the insertion of a new filter element, a new tube is attached by way of tight fitting to the ring of the frame , which tube is at its middle section tightly connected with the filter element, and which tube is attached to the ring of the frame in an actually known by overlapping of the heat-sealed tube rest. The tube rest is pulled onto the new tube and pulled off the ring, and the filter element is tightly connected with the frame by means of the tightening devices

  20. High-bandwidth and flexible tracking control for precision motion with application to a piezo nanopositioner.

    Science.gov (United States)

    Feng, Zhao; Ling, Jie; Ming, Min; Xiao, Xiao-Hui

    2017-08-01

    For precision motion, high-bandwidth and flexible tracking are the two important issues for significant performance improvement. Iterative learning control (ILC) is an effective feedforward control method only for systems that operate strictly repetitively. Although projection ILC can track varying references, the performance is still limited by the fixed-bandwidth Q-filter, especially for triangular waves tracking commonly used in a piezo nanopositioner. In this paper, a wavelet transform-based linear time-varying (LTV) Q-filter design for projection ILC is proposed to compensate high-frequency errors and improve the ability to tracking varying references simultaneously. The LVT Q-filter is designed based on the modulus maximum of wavelet detail coefficients calculated by wavelet transform to determine the high-frequency locations of each iteration with the advantages of avoiding cross-terms and segmenting manually. The proposed approach was verified on a piezo nanopositioner. Experimental results indicate that the proposed approach can locate the high-frequency regions accurately and achieve the best performance under varying references compared with traditional frequency-domain and projection ILC with a fixed-bandwidth Q-filter, which validates that through implementing the LTV filter on projection ILC, high-bandwidth and flexible tracking can be achieved simultaneously by the proposed approach.

  1. Multi-filter spectrophotometry of quasar environments

    Science.gov (United States)

    Craven, Sally E.; Hickson, Paul; Yee, Howard K. C.

    1993-01-01

    A many-filter photometric technique for determining redshifts and morphological types, by fitting spectral templates to spectral energy distributions, has good potential for application in surveys. Despite success in studies performed on simulated data, the results have not been fully reliable when applied to real, low signal-to-noise data. We are investigating techniques to improve the fitting process.

  2. Nanoscale measurements of proton tracks using fluorescent nuclear track detectors

    Energy Technology Data Exchange (ETDEWEB)

    Sawakuchi, Gabriel O., E-mail: gsawakuchi@mdanderson.org; Sahoo, Narayan [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and Graduate School of Biomedical Sciences, The University of Texas, Houston, Texas 77030 (United States); Ferreira, Felisberto A. [Department of Nuclear Physics, University of Sao Paulo, SP 05508-090 (Brazil); McFadden, Conor H. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Hallacy, Timothy M. [Biophysics Program, Harvard University, Cambridge, Massachusetts 02138 (United States); Granville, Dal A. [Department of Medical Physics, The Ottawa Hospital Cancer Centre, Ottawa, Ontario K1H 8L6 (Canada); Akselrod, Mark S. [Crystal Growth Division, Landauer, Inc., Stillwater, Oklahoma 74074 (United States)

    2016-05-15

    Purpose: The authors describe a method in which fluorescence nuclear track detectors (FNTDs), novel track detectors with nanoscale spatial resolution, are used to determine the linear energy transfer (LET) of individual proton tracks from proton therapy beams by allowing visualization and 3D reconstruction of such tracks. Methods: FNTDs were exposed to proton therapy beams with nominal energies ranging from 100 to 250 MeV. Proton track images were then recorded by confocal microscopy of the FNTDs. Proton tracks in the FNTD images were fit by using a Gaussian function to extract fluorescence amplitudes. Histograms of fluorescence amplitudes were then compared with LET spectra. Results: The authors successfully used FNTDs to register individual proton tracks from high-energy proton therapy beams, allowing reconstruction of 3D images of proton tracks along with delta rays. The track amplitudes from FNTDs could be used to parameterize LET spectra, allowing the LET of individual proton tracks from therapeutic proton beams to be determined. Conclusions: FNTDs can be used to directly visualize proton tracks and their delta rays at the nanoscale level. Because the track intensities in the FNTDs correlate with LET, they could be used further to measure LET of individual proton tracks. This method may be useful for measuring nanoscale radiation quantities and for measuring the LET of individual proton tracks in radiation biology experiments.

  3. An Adaptive Filter for the Removal of Drifting Sinusoidal Noise Without a Reference.

    Science.gov (United States)

    Kelly, John W; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

    2016-01-01

    This paper presents a method for filtering sinusoidal noise with a variable bandwidth filter that is capable of tracking a sinusoid's drifting frequency. The method, which is based on the adaptive noise canceling (ANC) technique, will be referred to here as the adaptive sinusoid canceler (ASC). The ASC eliminates sinusoidal contamination by tracking its frequency and achieving a narrower bandwidth than typical notch filters. The detected frequency is used to digitally generate an internal reference instead of relying on an external one as ANC filters typically do. The filter's bandwidth adjusts to achieve faster and more accurate convergence. In this paper, the focus of the discussion and the data is physiological signals, specifically electrocorticographic (ECoG) neural data contaminated with power line noise, but the presented technique could be applicable to other recordings as well. On simulated data, the ASC was able to reliably track the noise's frequency, properly adjust its bandwidth, and outperform comparative methods including standard notch filters and an adaptive line enhancer. These results were reinforced by visual results obtained from real ECoG data. The ASC showed that it could be an effective method for increasing signal to noise ratio in the presence of drifting sinusoidal noise, which is of significant interest for biomedical applications.

  4. Etched track radiometers in radon measurements: a review

    CERN Document Server

    Nikolaev, V A

    1999-01-01

    Passive radon radiometers, based on alpha particle etched track detectors, are very attractive for the assessment of radon exposure. The present review considers various devices used for measurement of the volume activity of radon isotopes and their daughters and determination of equilibrium coefficients. Such devices can be classified into 8 groups: (i) open or 'bare' detectors, (ii) open chambers, (iii) sup 2 sup 2 sup 2 Rn chambers with an inlet filter, (iv) advanced sup 2 sup 2 sup 2 Rn radiometers, (v) multipurpose radiometers, (vi) radiometers based on a combination of etched track detectors and an electrostatic field, (vii) radiometers based on etched track detectors and activated charcoal and (viii) devices for the measurement of radon isotopes and/or radon daughters by means of track parameter measurements. Some of them such as the open detector and the chamber with an inlet filter have a variety of modifications and are applied widely both in geophysical research and radon dosimetric surveys. At the...

  5. Evidence for and implications of self-background of radon dosimeters with glass-fiber filters

    International Nuclear Information System (INIS)

    Put, L.W.; Lembrechts, J.; Graaf, E.R. van der; Stoop, P.

    2000-01-01

    The first national radon survey in the Netherlands was conducted in 1984 with passive radon dosimeters that contain glass-fiber diffusion filters. During the last few years, measurements of outdoor-radon concentrations and information in the literature suggested that these dosimeters may give falsely elevated readings. A systematic contribution would be present due to alpha particles from natural radionuclides in the glass-fiber filter producing tracks on the track-etch foil. In the framework of the quality assurance of their laboratories, the origin of this offset was systematically assessed by means of measurements of alpha and gamma radiation from the glass-fiber filters and by intercomparisons between different types of detectors at low radon concentrations. It was found that alpha particles from the decay of 214 Po in the glass-fiber filter are the main cause of the extra tracks (only 12% originates from decay of 212 Po), leading, for this type of filter, to an offset in concentration of approximately 8 Bq m -3 . The implications of this offset are discussed

  6. Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

    International Nuclear Information System (INIS)

    Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

    2009-01-01

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

  7. Tracking Subpixel Targets with Critically Sampled Optical Sensors

    Science.gov (United States)

    2012-09-01

    LEFT BLANK xii LIST OF ACRONYMS AND ABBREVIATIONS PSF point spread function SNR signal-to-noise ratio SLAM simultaneous localization and tracking EO... LIDAR light detection and ranging FOV field of view RMS root mean squared PF particle filter TBD track before detect MCMC monte carlo markov chain

  8. Pedestrian Tracking Based on Camshift with Kalman Prediction for Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Lie Guo

    2016-06-01

    Full Text Available Pedestrian detection and tracking is the key to autonomous vehicle navigation systems avoiding potentially dangerous situations. Firstly, the probability distribution of colour information is established after a pedestrian is located in an image. Then the detected results are utilized to initialize a Kalman filter to predict the possible position of the pedestrian centroid in the future frame. A Camshift tracking algorithm is used to track the pedestrian in the specific search window of the next frame based on the prediction results. The actual position of the pedestrian centroid is output from the Camshift tracking algorithm to update the gain and error covariance matrix of the Kalman filter. Experimental results in real traffic situations show the proposed pedestrian tracking algorithm can achieve good performance even when they are partly occluded in inconsistent illumination circumstances.

  9. Open-loop position tracking control of a piezoceramic flexible beam using a dynamic hysteresis compensator

    International Nuclear Information System (INIS)

    Nguyen, Phuong-Bac; Choi, Seung-Bok

    2010-01-01

    This paper proposes a novel hysteresis compensator to enhance control accuracy in open-loop position tracking control of a piezoceramic flexible beam. The proposed hysteresis compensator consists of two components: a rate-independent hysteresis compensator and a nonlinear filter. The compensator is formulated based on the inverse Preisach model, while the weight coefficients of the filter are identified adaptively using a recursive least square (RLS) algorithm. In this work, two dynamic hysteresis compensators (or rate-independent hysteresis compensators) are developed by adopting two different nonlinear filters: Volterra and bilinear filters. In order to demonstrate the improved control accuracy of the proposed dynamic compensators, a flexible beam associated with the piezoceramic actuator is modeled using the finite element method (FEM) and Euler–Bernoulli beam theory. The beam model is then integrated with the proposed hysteresis model to achieve accurate position tracking control at the tip of the beam. An experimental investigation on the tip position tracking control is undertaken by realizing three different hysteresis compensators: a rate-independent hysteresis compensator, a rate-dependent hysteresis compensator with a Volterra nonlinear filter and a rate-independent hysteresis compensator with a bilinear nonlinear filter. It is shown that the proposed dynamic hysteresis compensators can provide much better tracking control accuracy than conventional rate-independent hysteresis compensators

  10. Research on the filtering algorithm in speed and position detection of maglev trains.

    Science.gov (United States)

    Dai, Chunhui; Long, Zhiqiang; Xie, Yunde; Xue, Song

    2011-01-01

    This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS) train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train's structure, the permanent magnet electrodynamic suspension (EDS) train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD) and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

  11. Kalman Filter Application to Symmetrical Fault Detection during Power Swing

    DEFF Research Database (Denmark)

    Khodaparast, Jalal; Silva, Filipe Miguel Faria da; Khederzadeh, M.

    2016-01-01

    capability of Kalman Filter. The proposed index is calculated by assessing the difference between predicted and actual samples of impedance. The predicted impedance samples are obtained using Kalman filter and Taylor expansion, which is used in this paper to track the phasor precisely. Second order of Taylor...... expansion is used to decrease corrugation effect of impedance estimation and increase the reliability of proposed method. The instantaneous estimation and prediction capability of Kalman filter are two reasons for proposing utilizing Kalman filter....

  12. Track Detection in Railway Sidings Based on MEMS Gyroscope Sensors

    Science.gov (United States)

    Broquetas, Antoni; Comerón, Adolf; Gelonch, Antoni; Fuertes, Josep M.; Castro, J. Antonio; Felip, Damià; López, Miguel A.; Pulido, José A.

    2012-01-01

    The paper presents a two-step technique for real-time track detection in single-track railway sidings using low-cost MEMS gyroscopes. The objective is to reliably know the path the train has taken in a switch, diverted or main road, immediately after the train head leaves the switch. The signal delivered by the gyroscope is first processed by an adaptive low-pass filter that rejects noise and converts the temporal turn rate data in degree/second units into spatial turn rate data in degree/meter. The conversion is based on the travelled distance taken from odometer data. The filter is implemented to achieve a speed-dependent cut-off frequency to maximize the signal-to-noise ratio. Although direct comparison of the filtered turn rate signal with a predetermined threshold is possible, the paper shows that better detection performance can be achieved by processing the turn rate signal with a filter matched to the rail switch curvature parameters. Implementation aspects of the track detector have been optimized for real-time operation. The detector has been tested with both simulated data and real data acquired in railway campaigns. PMID:23443376

  13. Real time eye tracking using Kalman extended spatio-temporal context learning

    Science.gov (United States)

    Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

    2017-06-01

    Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

  14. The ATLAS Fast Tracker Processing Units - track finding and fitting

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00384270; The ATLAS collaboration; Alison, John; Ancu, Lucian Stefan; Andreani, Alessandro; Annovi, Alberto; Beccherle, Roberto; Beretta, Matteo; Biesuz, Nicolo Vladi; Bogdan, Mircea Arghir; Bryant, Patrick; Calabro, Domenico; Citraro, Saverio; Crescioli, Francesco; Dell'Orso, Mauro; Donati, Simone; Gentsos, Christos; Giannetti, Paola; Gkaitatzis, Stamatios; Gramling, Johanna; Greco, Virginia; Horyn, Lesya Anna; Iovene, Alessandro; Kalaitzidis, Panagiotis; Kim, Young-Kee; Kimura, Naoki; Kordas, Kostantinos; Kubota, Takashi; Lanza, Agostino; Liberali, Valentino; Luciano, Pierluigi; Magnin, Betty; Sakellariou, Andreas; Sampsonidis, Dimitrios; Saxon, James; Shojaii, Seyed Ruhollah; Sotiropoulou, Calliope Louisa; Stabile, Alberto; Swiatlowski, Maximilian; Volpi, Guido; Zou, Rui; Shochet, Mel

    2016-01-01

    The Fast Tracker is a hardware upgrade to the ATLAS trigger and data-acquisition system, with the goal of providing global track reconstruction by the start of the High Level Trigger starts. The Fast Tracker can process incoming data from the whole inner detector at full first level trigger rate, up to 100 kHz, using custom electronic boards. At the core of the system is a Processing Unit installed in a VMEbus crate, formed by two sets of boards: the Associative Memory Board and a powerful rear transition module called the Auxiliary card, while the second set is the Second Stage board. The associative memories perform the pattern matching looking for correlations within the incoming data, compatible with track candidates at coarse resolution. The pattern matching task is performed using custom application specific integrated circuits, called associative memory chips. The auxiliary card prepares the input and reject bad track candidates obtained from from the Associative Memory Board using the full precision a...

  15. Box-Particle Cardinality Balanced Multi-Target Multi-Bernoulli Filter

    OpenAIRE

    L. Song; X. Zhao

    2014-01-01

    As a generalized particle filtering, the box-particle filter (Box-PF) has a potential to process the measurements affected by bounded error of unknown distributions and biases. Inspired by the Box-PF, a novel implementation for multi-target tracking, called box-particle cardinality balanced multi-target multi-Bernoulli (Box-CBMeMBer) filter is presented in this paper. More important, to eliminate the negative effect of clutters in the estimation of the numbers of targets, an improved generali...

  16. The stochastic filtering problem: a brief historical account

    OpenAIRE

    Crisan, Dan

    2014-01-01

    Onwards from the mid-twentieth century, the stochastic filtering problem has caught the attention of thousands of mathematicians, engineers, statisticians, and computer scientists. Its applications span the whole spectrum of human endeavour, including satellite tracking, credit risk estimation, human genome analysis, and speech recognition. Stochastic filtering has engendered a surprising number of mathematical techniques for its treatment and has played an important role in...

  17. Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

    Directory of Open Access Journals (Sweden)

    Seongwan Kim

    2017-01-01

    Full Text Available The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor, usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

  18. Drift chamber tracking with neural networks

    International Nuclear Information System (INIS)

    Lindsey, C.S.; Denby, B.; Haggerty, H.

    1992-10-01

    We discuss drift chamber tracking with a commercial log VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed

  19. Tracking of ball and players in beach volleyball videos.

    Directory of Open Access Journals (Sweden)

    Gabriel Gomez

    Full Text Available This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points.

  20. Tracking of Ball and Players in Beach Volleyball Videos

    Science.gov (United States)

    Gomez, Gabriel; Herrera López, Patricia; Link, Daniel; Eskofier, Bjoern

    2014-01-01

    This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points. PMID:25426936

  1. Research on the Filtering Algorithm in Speed and Position Detection of Maglev Trains

    Directory of Open Access Journals (Sweden)

    Chunhui Dai

    2011-07-01

    Full Text Available This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train’s structure, the permanent magnet electrodynamic suspension (EDS train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

  2. A fast ellipse extended target PHD filter using box-particle implementation

    Science.gov (United States)

    Zhang, Yongquan; Ji, Hongbing; Hu, Qi

    2018-01-01

    This paper presents a box-particle implementation of the ellipse extended target probability hypothesis density (ET-PHD) filter, called the ellipse extended target box particle PHD (EET-BP-PHD) filter, where the extended targets are described as a Poisson model developed by Gilholm et al. and the term "box" is here equivalent to the term "interval" used in interval analysis. The proposed EET-BP-PHD filter is capable of dynamically tracking multiple ellipse extended targets and estimating the target states and the number of targets, in the presence of clutter measurements, false alarms and missed detections. To derive the PHD recursion of the EET-BP-PHD filter, a suitable measurement likelihood is defined for a given partitioning cell, and the main implementation steps are presented along with the necessary box approximations and manipulations. The limitations and capabilities of the proposed EET-BP-PHD filter are illustrated by simulation examples. The simulation results show that a box-particle implementation of the ET-PHD filter can avoid the high number of particles and reduce computational burden, compared to a particle implementation of that for extended target tracking.

  3. Hydrodynamics of microbial filter feeding.

    Science.gov (United States)

    Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia; Walther, Jens H; Kiørboe, Thomas; Andersen, Anders

    2017-08-29

    Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate amounts of water. Also, the trade-off in the filter spacing remains unexplored, despite its simple formulation: A filter too coarse will allow suitably sized prey to pass unintercepted, whereas a filter too fine will cause strong flow resistance. We quantify the feeding flow of the filter-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), something notoriously difficult to visualize but sporadically observed in the related choanocytes (sponges). A CFD model with a flagellar vane correctly predicts the filtration rate of D. grandis , and using a simple model we can account for the filtration rates of other microbial filter feeders. We finally predict how optimum filter mesh size increases with cell size in microbial filter feeders, a prediction that accords very well with observations. We expect our results to be of significance for small-scale biophysics and trait-based ecological modeling.

  4. A Synthetic Algorithm for Tracking a Moving Object in a Multiple-Dynamic Obstacles Environment Based on Kinematically Planar Redundant Manipulators

    Directory of Open Access Journals (Sweden)

    Hongzhe Jin

    2017-01-01

    Full Text Available This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.

  5. Multi-agent target tracking using particle filters enhanced with context data

    CSIR Research Space (South Africa)

    Claessens, R

    2015-05-01

    Full Text Available The proposed framework for Multi-Agent Target Tracking supports i) tracking of objects and ii) search and rescue based on the fusion of very heterogeneous data. The system is based on a novel approach to fusing sensory observations, intelligence...

  6. High Pass Filtering of Satellite Altimeter Data,

    Science.gov (United States)

    1982-10-01

    bathymetry [7] and filtered data tracks (N = 3, X = 200 km) near the Clipperton Fracture Zone just East of the Christmas Island Ridge. Along the multiple...We also notice a negative signature associated with the Clipperton Fracture Zone and extending over all the tracks. It may indicate a trough covered...in Mid-Pacific Seamount Province..Mid-Iat tic and near the Western Clipperton Fracture Zone respectively. These charts arc to he overlaid by Figures

  7. Fitness Tracker for Weight Lifting Style Workouts

    Energy Technology Data Exchange (ETDEWEB)

    Wihl, B. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-02-01

    This document proposes an early, high level design for a fitness tracking system which can automatically log weight lifting style workouts. The system will provide an easy to use interface both physically through the use of several wireless wristband style motion trackers worn on the limbs, and graphically through a smartphone application. Exercise classification will be accomplished by calibration of the user’s specific motions. The system will accurately track a user’s workout, miscounting no more than one repetition in every 20, have sufficient battery life to last several hours, work with existing smartphones and have a cost similar to those of current fitness tracking devices. This document presents the mission background, current state-of-theart, stakeholders and their expectations, the proposed system’s context and concepts, implementation concepts, system requirements, first sublevel function decomposition, possible risks for the system, and a reflection on the design process.

  8. On the use of particle filters for electromagnetic tracking in high dose rate brachytherapy

    Science.gov (United States)

    Götz, Th I.; Lahmer, G.; Brandt, T.; Kallis, K.; Strnad, V.; Bert, Ch; Hensel, B.; Tomé, A. M.; Lang, E. W.

    2017-10-01

    Modern radiotherapy of female breast cancers often employs high dose rate brachytherapy, where a radioactive source is moved inside catheters, implanted in the female breast, according to a prescribed treatment plan. Source localization relative to the patient’s anatomy is determined with solenoid sensors whose spatial positions are measured with an electromagnetic tracking system. Precise sensor dwell position determination is of utmost importance to assure irradiation of the cancerous tissue according to the treatment plan. We present a hybrid data analysis system which combines multi-dimensional scaling with particle filters to precisely determine sensor dwell positions in the catheters during subsequent radiation treatment sessions. Both techniques are complemented with empirical mode decomposition for the removal of superimposed breathing artifacts. We show that the hybrid model robustly and reliably determines the spatial positions of all catheters used during the treatment and precisely determines any deviations of actual sensor dwell positions from the treatment plan. The hybrid system only relies on sensor positions measured with an EMT system and relates them to the spatial positions of the implanted catheters as initially determined with a computed x-ray tomography.

  9. Autonomous underwater vehicle motion tracking using a Kalman filter for sensor fusion

    CSIR Research Space (South Africa)

    Holtzhausen, S

    2008-11-01

    Full Text Available it will be shown how a Kalman Filter is used to estimate the position of an autonomous vehicle in a three dimensional space. The Kalman filter is used to estimate movement and position using measurements from multiple sensors...

  10. Stack filter classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory

    2009-01-01

    Just as linear models generalize the sample mean and weighted average, weighted order statistic models generalize the sample median and weighted median. This analogy can be continued informally to generalized additive modeels in the case of the mean, and Stack Filters in the case of the median. Both of these model classes have been extensively studied for signal and image processing but it is surprising to find that for pattern classification, their treatment has been significantly one sided. Generalized additive models are now a major tool in pattern classification and many different learning algorithms have been developed to fit model parameters to finite data. However Stack Filters remain largely confined to signal and image processing and learning algorithms for classification are yet to be seen. This paper is a step towards Stack Filter Classifiers and it shows that the approach is interesting from both a theoretical and a practical perspective.

  11. NONLINEAR ESTIMATION METHODS FOR AUTONOMOUS TRACKED VEHICLE WITH SLIP

    Institute of Scientific and Technical Information of China (English)

    ZHOU Bo; HAN Jianda

    2007-01-01

    In order to achieve precise, robust autonomous guidance and control of a tracked vehicle, a kinematic model with longitudinal and lateral slip is established. Four different nonlinear filters are used to estimate both state vector and time-varying parameter vector of the created model jointly. The first filter is the well-known extended Kalman filter. The second filter is an unscented version of the Kalman filter. The third one is a particle filter using the unscented Kalman filter to generate the importance proposal distribution. The last one is a novel and guaranteed filter that uses a linear set-membership estimator and can give an ellipsoid set in which the true state lies. The four different approaches have different complexities, behavior and advantages that are surveyed and compared.

  12. Rank Detector Preprocessor for Glint Reduction in a Tracking Radar

    CSIR Research Space (South Africa)

    Guest, IW

    1993-04-01

    Full Text Available A rank detector is used to defect instantaneous received power fades in tracking radar. On detection of a fade, censorship of the angular position measurement is implemented in a Kalman tracking filter. It is shown that this technique can typically...

  13. Tracking shocked dust: State estimation for a complex plasma during a shock wave

    International Nuclear Information System (INIS)

    Oxtoby, Neil P.; Ralph, Jason F.; Durniak, Celine; Samsonov, Dmitry

    2012-01-01

    We consider a two-dimensional complex (dusty) plasma crystal excited by an electrostatically-induced shock wave. Dust particle kinematics in such a system are usually determined using particle tracking velocimetry. In this work we present a particle tracking algorithm which determines the dust particle kinematics with significantly higher accuracy than particle tracking velocimetry. The algorithm uses multiple extended Kalman filters to estimate the particle states and an interacting multiple model to assign probabilities to the different filters. This enables the determination of relevant physical properties of the dust, such as kinetic energy and kinetic temperature, with high precision. We use a Hugoniot shock-jump relation to calculate a pressure-volume diagram from the shocked dust kinematics. Calculation of the full pressure-volume diagram was possible with our tracking algorithm, but not with particle tracking velocimetry.

  14. Extracting Rail Track Geometry from Static Terrestrial Laser Scans for Monitoring Purposes

    Directory of Open Access Journals (Sweden)

    A. Soni

    2014-06-01

    Full Text Available This paper presents the capabilities of detecting relevant geometry of railway track for monitoring purposes from static terrestrial laser scanning (TLS systems at platform level. The quality of the scans from a phased based scanner (Scanner A and a hybrid timeof- flight scanner (Scanner B are compared by fitting different sections of the track profile to its matching standardised rail model. The various sections of track investigated are able to fit to the model with an RMS of less than 3 mm. Both scanners show that once obvious noise and artefacts have been removed from the data, the most confident fit of the point cloud to the model is the section closest to the scanner position. The results of the fit highlight the potential to use this method as a bespoke track monitoring tool during major redevelopment projects where traditional methods, such as robotic total stations, results in missed information, for example due to passing trains or knocked prisms and must account for offset target locations to compute track parameters.

  15. Frequency-scanning interferometry using a time-varying Kalman filter for dynamic tracking measurements.

    Science.gov (United States)

    Jia, Xingyu; Liu, Zhigang; Tao, Long; Deng, Zhongwen

    2017-10-16

    Frequency scanning interferometry (FSI) with a single external cavity diode laser (ECDL) and time-invariant Kalman filtering is an effective technique for measuring the distance of a dynamic target. However, due to the hysteresis of the piezoelectric ceramic transducer (PZT) actuator in the ECDL, the optical frequency sweeps of the ECDL exhibit different behaviors, depending on whether the frequency is increasing or decreasing. Consequently, the model parameters of Kalman filter appear time varying in each iteration, which produces state estimation errors with time-invariant filtering. To address this, in this paper, a time-varying Kalman filter is proposed to model the instantaneous movement of a target relative to the different optical frequency tuning durations of the ECDL. The combination of the FSI method with the time-varying Kalman filter was theoretically analyzed, and the simulation and experimental results show the proposed method greatly improves the performance of dynamic FSI measurements.

  16. Proposed FPGA based tracking for a Level-1 track trigger at CMS for the HL-LHC

    CERN Document Server

    Pozzobon, Nicola

    2014-01-01

    The High Luminosity LHC (HL-LHC) is expected to deliver a luminosity in excess of $5\\times10^{34}$ cm$^{-2}$/s. The high event rate places stringent requirements on the trigger system. A key component of the CMS upgrade for the HL-LHC is a track trigger system which will identify tracks with transverse momenta above 2 GeV already at the first-level trigger within 5 $\\mu$s. This presentation will discuss a proposed track finding and fitting based on the tracklet based approach implemented on FPGAs. Tracklets are formed from pairs of hits in nearby layers in the detector and used in a road search. Summary Fast pattern recognition in Silicon trackers for triggering has often made use of Associative Memories for the pattern recognition step. We propose an alternative approach to solving the pattern recognition and track fitting problem for the upgraded CMS tracker for the HL-LHC operation. We make use of the trigger primitives,stubs, from the tracker. The stubs are formed from pairs of hits in sensors separated r...

  17. Sparse adaptive filters for echo cancellation

    CERN Document Server

    Paleologu, Constantin

    2011-01-01

    Adaptive filters with a large number of coefficients are usually involved in both network and acoustic echo cancellation. Consequently, it is important to improve the convergence rate and tracking of the conventional algorithms used for these applications. This can be achieved by exploiting the sparseness character of the echo paths. Identification of sparse impulse responses was addressed mainly in the last decade with the development of the so-called ``proportionate''-type algorithms. The goal of this book is to present the most important sparse adaptive filters developed for echo cancellati

  18. Structural functional associations of the orbit in thyroid eye disease: Kalman filters to track extraocular rectal muscles

    Science.gov (United States)

    Chaganti, Shikha; Nelson, Katrina; Mundy, Kevin; Luo, Yifu; Harrigan, Robert L.; Damon, Steve; Fabbri, Daniel; Mawn, Louise; Landman, Bennett

    2016-03-01

    Pathologies of the optic nerve and orbit impact millions of Americans and quantitative assessment of the orbital structures on 3-D imaging would provide objective markers to enhance diagnostic accuracy, improve timely intervention, and eventually preserve visual function. Recent studies have shown that the multi-atlas methodology is suitable for identifying orbital structures, but challenges arise in the identification of the individual extraocular rectus muscles that control eye movement. This is increasingly problematic in diseased eyes, where these muscles often appear to fuse at the back of the orbit (at the resolution of clinical computed tomography imaging) due to inflammation or crowding. We propose the use of Kalman filters to track the muscles in three-dimensions to refine multi-atlas segmentation and resolve ambiguity due to imaging resolution, noise, and artifacts. The purpose of our study is to investigate a method of automatically generating orbital metrics from CT imaging and demonstrate the utility of the approach by correlating structural metrics of the eye orbit with clinical data and visual function measures in subjects with thyroid eye disease. The pilot study demonstrates that automatically calculated orbital metrics are strongly correlated with several clinical characteristics. Moreover, it is shown that the superior, inferior, medial and lateral rectus muscles obtained using Kalman filters are each correlated with different categories of functional deficit. These findings serve as foundation for further investigation in the use of CT imaging in the study, analysis and diagnosis of ocular diseases, specifically thyroid eye disease.

  19. Graph-based geometric-iconic guide-wire tracking.

    Science.gov (United States)

    Honnorat, Nicolas; Vaillant, Régis; Paragios, Nikos

    2011-01-01

    In this paper we introduce a novel hybrid graph-based approach for Guide-wire tracking. The image support is captured by steerable filters and improved through tensor voting. Then, a graphical model is considered that represents guide-wire extraction/tracking through a B-spline control-point model. Points with strong geometric interest (landmarks) are automatically determined and anchored to such a representation. Tracking is then performed through discrete MRFs that optimize the spatio-temporal positions of the control points while establishing landmark temporal correspondences. Promising results demonstrate the potentials of our method.

  20. Proposed hardware architectures of particle filter for object tracking

    Science.gov (United States)

    Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED

    2012-12-01

    In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.

  1. Convolutional Neural Network for Track Seed Filtering at the CMS HLT

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Collider will constantly bring nominal luminosity increase, with the ultimate goal of reaching a peak luminosity of $5 · 10^{34} cm^{−2} s^{−1}$ for ATLAS and CMS experiments planned for the High Luminosity LHC (HL-LHC) upgrade. This rise in luminosity will directly result in an increased number of simultaneous proton collisions (pileup), up to 200, that will pose new challenges for the CMS detector and, specifically, for track reconstruction in the Silicon Pixel Tracker. One of the first steps of the track finding workflow is the creation of track seeds, i.e. compatible pairs of hits from different detector layers, that are subsequently fed to to higher level pattern recognition steps. However the set of compatible hit pairs is highly affected by combinatorial background resulting in the next steps of the tracking algorithm to process a significant fraction of fake doublets. A possible way of reducing this effect is taking into account the shape of the hit pixel cluster to check the compatibility bet...

  2. KALMAN FILTER BASED FEATURE ANALYSIS FOR TRACKING PEOPLE FROM AIRBORNE IMAGES

    Directory of Open Access Journals (Sweden)

    B. Sirmacek

    2012-09-01

    Full Text Available Recently, analysis of man events in real-time using computer vision techniques became a very important research field. Especially, understanding motion of people can be helpful to prevent unpleasant conditions. Understanding behavioral dynamics of people can also help to estimate future states of underground passages, shopping center like public entrances, or streets. In order to bring an automated solution to this problem, we propose a novel approach using airborne image sequences. Although airborne image resolutions are not enough to see each person in detail, we can still notice a change of color components in the place where a person exists. Therefore, we propose a color feature detection based probabilistic framework in order to detect people automatically. Extracted local features behave as observations of the probability density function (pdf of the people locations to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf. First, we use estimated pdf to detect boundaries of dense crowds. After that, using background information of dense crowds and previously extracted local features, we detect other people in non-crowd regions automatically for each image in the sequence. We benefit from Kalman filtering to track motion of detected people. To test our algorithm, we use a stadium entrance image data set taken from airborne camera system. Our experimental results indicate possible usage of the algorithm in real-life man events. We believe that the proposed approach can also provide crucial information to police departments and crisis management teams to achieve more detailed observations of people in large open area events to prevent possible accidents or unpleasant conditions.

  3. Development and validation of a Kalman filter-based model for vehicle slip angle estimation

    Science.gov (United States)

    Gadola, M.; Chindamo, D.; Romano, M.; Padula, F.

    2014-01-01

    It is well known that vehicle slip angle is one of the most difficult parameters to measure on a vehicle during testing or racing activities. Moreover, the appropriate sensor is very expensive and it is often difficult to fit to a car, especially on race cars. We propose here a strategy to eliminate the need for this sensor by using a mathematical tool which gives a good estimation of the vehicle slip angle. A single-track car model, coupled with an extended Kalman filter, was used in order to achieve the result. Moreover, a tuning procedure is proposed that takes into consideration both nonlinear and saturation characteristics typical of vehicle lateral dynamics. The effectiveness of the proposed algorithm has been proven by both simulation results and real-world data.

  4. Multiradar tracking for theater missile defense

    Science.gov (United States)

    Sviestins, Egils

    1995-09-01

    A prototype system for tracking tactical ballistic missiles using multiple radars has been developed. The tracking is based on measurement level fusion (`true' multi-radar) tracking. Strobes from passive sensors can also be used. We describe various features of the system with some emphasis on the filtering technique. This is based on the Interacting Multiple Model framework where the states are Free Flight, Drag, Boost, and Auxiliary. Measurement error modeling includes the signal to noise ratio dependence; outliers and miscorrelations are handled in the same way. The launch point is calculated within one minute from the detection of the missile. The impact point, and its uncertainty region, is calculated continually by extrapolating the track state vector using the equations of planetary motion.

  5. Hotels Make Room for Fitness.

    Science.gov (United States)

    Koszuta, Laurie Einstein

    1986-01-01

    Hotels, in hopes of gaining a competitive edge, are offering workout rooms, exercise equipment, fitness trails, and jogging tracks, but no standards have been set for safety of the facilities or staff preparedness in exercise screening, equipment use, injury prevention, or first aid. (MT)

  6. Electron Energy Resolution of the ATLAS TILECAL Modules with Fit Filter Method (July 2002 test beam)

    CERN Document Server

    Kulchitskii, Yu A; Vinogradov, V B

    2006-01-01

    The constructed ATLAS detector at the LHC will have the great physics discovery potential, in particular in the detection of a heavy Higgs boson. Calorimeters will play a crucial role in it. It is necessary to have confidence that the calorimeters will perform as expected. With the aim of understanding of performance of the ATLAS Tile hadronic calorimeter to electrons 12\\% of modules have been exposed in electron beams with various energies by three possible ways: cell-scan at $\\theta =20^o$ at the centers of the front face cells, $\\eta$-scan and tilerow scan at $\\theta = 90^o$ for the module side cells. We have extracted the electron energy resolutions of the $EBM-$ (ANL-44), $EBM+$ (IFA-42) and $BM$ (JINR-55) Modules of the ATLAS Tile Calorimeter at energies E = 10, 20, 50, 100 and 180 GeV and $\\theta = 20^o$ and $90^o $ and $\\eta$ scan from the July 2002 testbeam run data using the fit filter method of the PMT signal reconstruction. We have determined the statistical and constant terms for the electron ene...

  7. Contrast effects of a gadolinium filter

    International Nuclear Information System (INIS)

    Burgess, A.E.

    1981-01-01

    Several authors have suggested using heavy metal filters with K edges in the diagnostic energy range to reduce the width of the x-ray spectrum and hence reduce patient radiation exposure. This spectral narrowing also increases subject contrast and permits an increase in tube potential. Results of contrast measurements are presented for a 250 mu gadolinium filter. It was found that aluminum filter contrast could be matched by using 8 to 10 kVp higher potential with the gadolinium filter. Similar results were found for calcium tungstate and rare-earth screens. Measurements were also done to determine skin exposure and mAs ratios for both constant contrast and constant kVp technique conversion methods. A simple theory with one adjustable parameter gives a reasonable fit to the experimental results

  8. Characterization of aerosols containing fissionable elements using solid-state track recorders

    International Nuclear Information System (INIS)

    Roberts, J.H.; Kafalenos, V.P.; Yule, T.J.

    1976-01-01

    An aerosol of U 3 O 3 highly enriched in 235 U was generated with a nebulizer from a suspension of U 3 O 8 powder in distilled water. The aerosol was collected on a membrane filter. Polycarbonate plastic, placed in good contact with the filter, was used to record fission tracks when the package was exposed to known fluences of slow neutrons. Fission-track stars associated with individual particles of U 3 O 8 were observed in the plastic. The fission-track distributions were converted to a particle size distribution for the aerosol. For a log normal distribution the geometric mean and standard deviation can be determined with better than 5% accuracy. This method can be applied to plutonium and other transuranic aerosols. (orig.) [de

  9. TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers.

    Science.gov (United States)

    Matysik, Artur; Kraut, Rachel S

    2014-05-01

    Single molecule tracking (SMT) analysis of fluorescently tagged lipid and protein probes is an attractive alternative to ensemble averaged methods such as fluorescence correlation spectroscopy (FCS) or fluorescence recovery after photobleaching (FRAP) for measuring diffusion in artificial and plasma membranes. The meaningful estimation of diffusion coefficients and their errors is however not straightforward, and is heavily dependent on sample type, acquisition method, and equipment used. Many approaches require advanced computing and programming skills for their implementation. Here we present TrackArt software, an accessible graphic interface for simulation and complex analysis of multiple particle paths. Imported trajectories can be filtered to eliminate spurious or corrupted tracks, and are then analyzed using several previously described methodologies, to yield single or multiple diffusion coefficients, their population fractions, and estimated errors. We use TrackArt to analyze the single-molecule diffusion behavior of a sphingolipid analog SM-Atto647N, in mica supported DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) bilayers. Fitting with a two-component diffusion model confirms the existence of two separate populations of diffusing particles in these bilayers on mica. As a demonstration of the TrackArt workflow, we characterize and discuss the effective activation energies required to increase the diffusion rates of these populations, obtained from Arrhenius plots of temperature-dependent diffusion. Finally, TrackArt provides a simulation module, allowing the user to generate models with multiple particle trajectories, diffusing with different characteristics. Maps of domains, acting as impermeable or permeable obstacles for particles diffusing with given rate constants and diffusion coefficients, can be simulated or imported from an image. Importantly, this allows one to use simulated data with a known diffusion behavior as a comparison for results

  10. Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach

    Science.gov (United States)

    Miran, Sina; Akram, Sahar; Sheikhattar, Alireza; Simon, Jonathan Z.; Zhang, Tao; Babadi, Behtash

    2018-01-01

    Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach). To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1) Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2) Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3) Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our proposed

  11. Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach

    Directory of Open Access Journals (Sweden)

    Sina Miran

    2018-05-01

    Full Text Available Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG and electroencephalography (EEG. To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach or vice versa (the encoding approach. To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1 Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2 Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3 Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our

  12. Method for Multiple Targets Tracking in Cognitive Radar Based on Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Yang Jun

    2016-02-01

    Full Text Available A multiple targets cognitive radar tracking method based on Compressed Sensing (CS is proposed. In this method, the theory of CS is introduced to the case of cognitive radar tracking process in multiple targets scenario. The echo signal is sparsely expressed. The designs of sparse matrix and measurement matrix are accomplished by expressing the echo signal sparsely, and subsequently, the restruction of measurement signal under the down-sampling condition is realized. On the receiving end, after considering that the problems that traditional particle filter suffers from degeneracy, and require a large number of particles, the particle swarm optimization particle filter is used to track the targets. On the transmitting end, the Posterior Cramér-Rao Bounds (PCRB of the tracking accuracy is deduced, and the radar waveform parameters are further cognitively designed using PCRB. Simulation results show that the proposed method can not only reduce the data quantity, but also provide a better tracking performance compared with traditional method.

  13. Real-Time Order Tracking of Gear Mesh Vibration in High Speed Planetary Gearboxes

    Directory of Open Access Journals (Sweden)

    Plöger Daniel Fritz

    2018-01-01

    Full Text Available Possible approaches to real-time order tracking are discussed. Two methods for real-time order tracking are developed and validated experimentally for the entire audible spectrum. An adaptive heterodyne filter bank is compared to a direct integral transform. The performance of both methods is adequate for usage in an active vibration control (AVC algorithm. Vold-Kalman filters are not suitable for AVC. The vibration data of three different planetary gearboxes is analyzed using order tracking. While some of the existing research could be reproduced, the data contradicts statements made by several authors. Lastly, the architecture of a novel AVC algorithm is sketched out.

  14. A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters

    Directory of Open Access Journals (Sweden)

    Danilo Pelusi

    2018-03-01

    Full Text Available The goodness of Infinite Impulse Response (IIR digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA. In this way, a Fuzzy Gravitational Search Algorithm (FGSA is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.

  15. Motivation and User Engagement in Fitness Tracking: Heuristics for Mobile Healthcare Wearables

    Directory of Open Access Journals (Sweden)

    Stavros Asimakopoulos

    2017-01-01

    Full Text Available Wearable fitness trackers have gained a new level of popularity due to their ambient data gathering and analysis. This has signalled a trend toward self-efficacy and increased motivation among users of these devices. For consumers looking to improve their health, fitness trackers offer a way to more readily gain motivation via the personal data-based insights the devices offer. However, the user experience (UX that accompanies wearables is critical to helping users interpret, understand, gain motivation and act on their data. Despite this, there is little evidence as to specific aspects of fitness tracker user engagement and long-term motivation. We report on a 4-week situated diary study and Healthcare Technology Self-efficacy (HTSE questionnaire assessment of 34 users of two popular American fitness trackers: JawBone and FitBit. The study results illustrate design implications and requirements for fitness trackers and other self-efficacy mobile healthcare applications.

  16. Low-momentum track finding in Belle II

    International Nuclear Information System (INIS)

    Lettenbichler, J; Frühwirth, R; Nadler, M; Glattauer, R

    2012-01-01

    The Silicon Vertex Detector (SVD) of the Belle II experiment is a newly developed device with four measurement layers. Track finding in the SVD will be done both in conjunction with the Central Drift Chamber and in stand-alone mode. The reconstruction of very-low-momentum tracks in stand-alone mode is a big challenge, especially in view of the low redundancy and the large expected background. We describe an approach for track finding in this domain, where a cellular automaton and a Kalman filter is combined with a Hopfield network which finds an optimal subset of non-overlapping tracks. We present results on simulated data and evaluate them in terms of efficiency and purity.

  17. ALICE HLT high speed tracking on GPU

    CERN Document Server

    Gorbunov, Sergey; Aamodt, Kenneth; Alt, Torsten; Appelshauser, Harald; Arend, Andreas; Bach, Matthias; Becker, Bruce; Bottger, Stefan; Breitner, Timo; Busching, Henner; Chattopadhyay, Sukalyan; Cleymans, Jean; Cicalo, Corrado; Das, Indranil; Djuvsland, Oystein; Engel, Heiko; Erdal, Hege Austrheim; Fearick, Roger; Haaland, Oystein Senneset; Hille, Per Thomas; Kalcher, Sebastian; Kanaki, Kalliopi; Kebschull, Udo Wolfgang; Kisel, Ivan; Kretz, Matthias; Lara, Camillo; Lindal, Sven; Lindenstruth, Volker; Masoodi, Arshad Ahmad; Ovrebekk, Gaute; Panse, Ralf; Peschek, Jorg; Ploskon, Mateusz; Pocheptsov, Timur; Ram, Dinesh; Rascanu, Theodor; Richter, Matthias; Rohrich, Dieter; Ronchetti, Federico; Skaali, Bernhard; Smorholm, Olav; Stokkevag, Camilla; Steinbeck, Timm Morten; Szostak, Artur; Thader, Jochen; Tveter, Trine; Ullaland, Kjetil; Vilakazi, Zeblon; Weis, Robert; Yin, Zhong-Bao; Zelnicek, Pierre

    2011-01-01

    The on-line event reconstruction in ALICE is performed by the High Level Trigger, which should process up to 2000 events per second in proton-proton collisions and up to 300 central events per second in heavy-ion collisions, corresponding to an inp ut data stream of 30 GB/s. In order to fulfill the time requirements, a fast on-line tracker has been developed. The algorithm combines a Cellular Automaton method being used for a fast pattern recognition and the Kalman Filter method for fitting of found trajectories and for the final track selection. The tracker was adapted to run on Graphics Processing Units (GPU) using the NVIDIA Compute Unified Device Architecture (CUDA) framework. The implementation of the algorithm had to be adjusted at many points to allow for an efficient usage of the graphics cards. In particular, achieving a good overall workload for many processor cores, efficient transfer to and from the GPU, as well as optimized utilization of the different memories the GPU offers turned out to be cri...

  18. A New Track Reconstruction Algorithm suitable for Parallel Processing based on Hit Triplets and Broken Lines

    Directory of Open Access Journals (Sweden)

    Schöning André

    2016-01-01

    Full Text Available Track reconstruction in high track multiplicity environments at current and future high rate particle physics experiments is a big challenge and very time consuming. The search for track seeds and the fitting of track candidates are usually the most time consuming steps in the track reconstruction. Here, a new and fast track reconstruction method based on hit triplets is proposed which exploits a three-dimensional fit model including multiple scattering and hit uncertainties from the very start, including the search for track seeds. The hit triplet based reconstruction method assumes a homogeneous magnetic field which allows to give an analytical solutions for the triplet fit result. This method is highly parallelizable, needs fewer operations than other standard track reconstruction methods and is therefore ideal for the implementation on parallel computing architectures. The proposed track reconstruction algorithm has been studied in the context of the Mu3e-experiment and a typical LHC experiment.

  19. A tool for filtering information in complex systems

    Science.gov (United States)

    Tumminello, M.; Aste, T.; Di Matteo, T.; Mantegna, R. N.

    2005-07-01

    We introduce a technique to filter out complex data sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation-based graphs, giving filtered graphs that preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0), triangular loops and four-element cliques are formed. The application of this filtering procedure to 100 stocks in the U.S. equity markets shows that such loops and cliques have important and significant relationships with the market structure and properties. This paper was submitted directly (Track II) to the PNAS office.Abbreviations: MST, minimum spanning tree; PMFG, Planar Maximally Filtered Graph; r-clique, clique of r elements.

  20. Evolution of the SOFIA tracking control system

    Science.gov (United States)

    Fiebig, Norbert; Jakob, Holger; Pfüller, Enrico; Röser, Hans-Peter; Wiedemann, Manuel; Wolf, Jürgen

    2014-07-01

    The airborne observatory SOFIA (Stratospheric Observatory for Infrared Astronomy) is undergoing a modernization of its tracking system. This included new, highly sensitive tracking cameras, control computers, filter wheels and other equipment, as well as a major redesign of the control software. The experiences along the migration path from an aged 19" VMbus based control system to the application of modern industrial PCs, from VxWorks real-time operating system to embedded Linux and a state of the art software architecture are presented. Further, the concept is presented to operate the new camera also as a scientific instrument, in parallel to tracking.

  1. Guidelines for the fitting of anomalous diffusion mean square displacement graphs from single particle tracking experiments.

    Directory of Open Access Journals (Sweden)

    Eldad Kepten

    Full Text Available Single particle tracking is an essential tool in the study of complex systems and biophysics and it is commonly analyzed by the time-averaged mean square displacement (MSD of the diffusive trajectories. However, past work has shown that MSDs are susceptible to significant errors and biases, preventing the comparison and assessment of experimental studies. Here, we attempt to extract practical guidelines for the estimation of anomalous time averaged MSDs through the simulation of multiple scenarios with fractional Brownian motion as a representative of a large class of fractional ergodic processes. We extract the precision and accuracy of the fitted MSD for various anomalous exponents and measurement errors with respect to measurement length and maximum time lags. Based on the calculated precision maps, we present guidelines to improve accuracy in single particle studies. Importantly, we find that in some experimental conditions, the time averaged MSD should not be used as an estimator.

  2. The DOe Silicon Track Trigger

    International Nuclear Information System (INIS)

    Steinbrueck, Georg

    2003-01-01

    We describe a trigger preprocessor to be used by the DOe experiment for selecting events with tracks from the decay of long-lived particles. This Level 2 impact parameter trigger utilizes information from the Silicon Microstrip Tracker to reconstruct tracks with improved spatial and momentum resolutions compared to those obtained by the Level 1 tracking trigger. It is constructed of VME boards with much of the logic existing in programmable processors. A common motherboard provides the I/O infrastructure and three different daughter boards perform the tasks of identifying the roads from the tracking trigger data, finding the clusters in the roads in the silicon detector, and fitting tracks to the clusters. This approach provides flexibility for the design, testing and maintenance phases of the project. The track parameters are provided to the trigger framework in 25 μs. The effective impact parameter resolution for high-momentum tracks is 35 μm, dominated by the size of the Tevatron beam

  3. Super-resolution pupil filtering for visual performance enhancement using adaptive optics

    Science.gov (United States)

    Zhao, Lina; Dai, Yun; Zhao, Junlei; Zhou, Xiaojun

    2018-05-01

    Ocular aberration correction can significantly improve visual function of the human eye. However, even under ideal aberration correction conditions, pupil diffraction restricts the resolution of retinal images. Pupil filtering is a simple super-resolution (SR) method that can overcome this diffraction barrier. In this study, a 145-element piezoelectric deformable mirror was used as a pupil phase filter because of its programmability and high fitting accuracy. Continuous phase-only filters were designed based on Zernike polynomial series and fitted through closed-loop adaptive optics. SR results were validated using double-pass point spread function images. Contrast sensitivity was further assessed to verify the SR effect on visual function. An F-test was conducted for nested models to statistically compare different CSFs. These results indicated CSFs for the proposed SR filter were significantly higher than the diffraction correction (p vision optical correction of the human eye.

  4. Low-rank sparse learning for robust visual tracking

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

    2012-01-01

    In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm

  5. Kinematic Fitting of Detached Vertices

    Energy Technology Data Exchange (ETDEWEB)

    Mattione, Paul [Rice Univ., Houston, TX (United States)

    2007-05-01

    The eg3 experiment at the Jefferson Lab CLAS detector aims to determine the existence of the $\\Xi_{5}$ pentaquarks and investigate the excited $\\Xi$ states. Specifically, the exotic $\\Xi_{5}^{--}$ pentaquark will be sought by first reconstructing the $\\Xi^{-}$ particle through its weak decays, $\\Xi^{-}\\to\\pi^{-}\\Lambda$ and $\\Lambda\\to\\pi^{-}$. A kinematic fitting routine was developed to reconstruct the detached vertices of these decays, where confidence level cuts on the fits are used to remove background events. Prior to fitting these decays, the exclusive reaction $\\gamma D\\rightarrow pp\\pi^{-}$ was studied in order to correct the track measurements and covariance matrices of the charged particles. The $\\Lambda\\rightarrow p\\pi^{-}$ and $\\Xi^{-}\\to\\pi^{-}\\Lambda$ decays were then investigated to demonstrate that the kinematic fitting routine reconstructs the decaying particles and their detached vertices correctly.

  6. PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

    Science.gov (United States)

    Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

    2015-11-06

    Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

  7. A Cubature-Principle-Assisted IMM-Adaptive UKF Algorithm for Maneuvering Target Tracking Caused by Sensor Faults

    Directory of Open Access Journals (Sweden)

    Huan Zhou

    2017-09-01

    Full Text Available Aimed at solving the problem of decreased filtering precision while maneuvering target tracking caused by non-Gaussian distribution and sensor faults, we developed an efficient interacting multiple model-unscented Kalman filter (IMM-UKF algorithm. By dividing the IMM-UKF into two links, the algorithm introduces the cubature principle to approximate the probability density of the random variable, after the interaction, by considering the external link of IMM-UKF, which constitutes the cubature-principle-assisted IMM method (CPIMM for solving the non-Gaussian problem, and leads to an adaptive matrix to balance the contribution of the state. The algorithm provides filtering solutions by considering the internal link of IMM-UKF, which is called a new adaptive UKF algorithm (NAUKF to address sensor faults. The proposed CPIMM-NAUKF is evaluated in a numerical simulation and two practical experiments including one navigation experiment and one maneuvering target tracking experiment. The simulation and experiment results show that the proposed CPIMM-NAUKF has greater filtering precision and faster convergence than the existing IMM-UKF. The proposed algorithm achieves a very good tracking performance, and will be effective and applicable in the field of maneuvering target tracking.

  8. Research on infrared small-target tracking technology under complex background

    Science.gov (United States)

    Liu, Lei; Wang, Xin; Chen, Jilu; Pan, Tao

    2012-10-01

    In this paper, some basic principles and the implementing flow charts of a series of algorithms for target tracking are described. On the foundation of above works, a moving target tracking software base on the OpenCV is developed by the software developing platform MFC. Three kinds of tracking algorithms are integrated in this software. These two tracking algorithms are Kalman Filter tracking method and Camshift tracking method. In order to explain the software clearly, the framework and the function are described in this paper. At last, the implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. This paper is very significant in the application of the infrared target tracking technology.

  9. Three-Dimensional Triplet Tracking for LHC and Future High Rate Experiments

    CERN Document Server

    Schöning, Andre

    2014-10-20

    The hit combinatorial problem is a main challenge for track reconstruction and triggering at high rate experiments. At hadron colliders the dominant fraction of hits is due to low momentum tracks for which multiple scattering (MS) effects dominate the hit resolution. MS is also the dominating source for hit confusion and track uncertainties in low energy precision experiments. In all such environments, where MS dominates, track reconstruction and fitting can be largely simplified by using three-dimensional (3D) hit-triplets as provided by pixel detectors. This simplification is possible since track uncertainties are solely determined by MS if high precision spatial information is provided. Fitting of hit-triplets is especially simple for tracking detectors in solenoidal magnetic fields. The over-constrained 3D-triplet method provides a complete set of track parameters and is robust against fake hit combinations. The triplet method is ideally suited for pixel detectors where hits can be treated as 3D-space poi...

  10. Automatically processed alpha-track radon monitor

    International Nuclear Information System (INIS)

    Langner, G.H. Jr.

    1993-01-01

    An automatically processed alpha-track radon monitor is provided which includes a housing having an aperture allowing radon entry, and a filter that excludes the entry of radon daughters into the housing. A flexible track registration material is located within the housing that records alpha-particle emissions from the decay of radon and radon daughters inside the housing. The flexible track registration material is capable of being spliced such that the registration material from a plurality of monitors can be spliced into a single strip to facilitate automatic processing of the registration material from the plurality of monitors. A process for the automatic counting of radon registered by a radon monitor is also provided

  11. High Degree Cubature Federated Filter for Multisensor Information Fusion with Correlated Noises

    Directory of Open Access Journals (Sweden)

    Lijun Wang

    2016-01-01

    Full Text Available This paper proposes an improved high degree cubature federated filter for the nonlinear fusion system with cross-correlation between process and measurement noises at the same time using the fifth-degree cubature rule and the decorrelated principle in its local filters. The master filter of the federated filter adopts the no-reset mode to fuse local estimates of local filters to generate a global estimate according to the scalar weighted rule. The air-traffic maneuvering target tracking simulations are performed between the proposed filter and the fifth-degree cubature federated filter. Simulations results demonstrate that the proposed filter not only can achieve almost the same accuracy as the fifth-degree cubature federated filter with independent white noises, but also has superior performance to the fifth-degree cubature federated filter while the noises are cross-correlated at the same time.

  12. Real-time Non-linear Target Tracking Control of Wheeled Mobile Robots

    Institute of Scientific and Technical Information of China (English)

    YU Wenyong

    2006-01-01

    A control strategy for real-time target tracking for wheeled mobile robots is presented. Using a modified Kalman filter for environment perception, a novel tracking control law derived from Lyapunov stability theory is introduced. Tuning of linear velocity and angular velocity with mechanical constraints is applied. The proposed control system can simultaneously solve the target trajectory prediction, real-time tracking, and posture regulation problems of a wheeled mobile robot. Experimental results illustrate the effectiveness of the proposed tracking control laws.

  13. Kalman filters for real-time magnetic island phase tracking

    NARCIS (Netherlands)

    Borgers, D. P.; Lauret, M.; M.R. de Baar,

    2013-01-01

    For control of neoclassical tearing modes (NTMs) and the resulting rotating magnetic islands in tokamak plasmas, the frequency and phase of the magnetic islands need to be accurately tracked in real-time. In previous experiments on TEXTOR, this was achieved using a phase-locked loop (PLL). For ASDEX

  14. Motion Tracking for Medical Imaging: A Non-Visible Structured Light Tracking Approach

    DEFF Research Database (Denmark)

    Olesen, Oline Vinter; Paulsen, Rasmus Reinhold; Højgaard, Liselotte

    2012-01-01

    We present a system for head motion tracking in 3D brain imaging. The system is based on facial surface reconstruction and tracking using a structured light (SL) scanning principle. The system is designed to fit into narrow 3D medical scanner geometries limiting the field of view. It is tested......, is that it is not necessary to place markers on the patient. This provides a simpler workflow and eliminates uncertainties related to marker attachment and stability. We show proof of concept of a marker less tracking system especially designed for clinical use with promising results....... in a clinical setting on the high resolution research tomograph (HRRT), Siemens PET scanner with a head phantom and volunteers. The SL system is compared to a commercial optical tracking system, the Polaris Vicra system, from NDI based on translatory and rotary ground truth motions of the head phantom...

  15. Online track reconstruction at hadron colliders

    International Nuclear Information System (INIS)

    Amerio, Silvia; Bettini, Marco; Nicoletto, Marino; Crescioli, Francesco; Bucciantonio, Martina; DELL'ORSO, Mauro; Piendibene, Marco; VOLPI, Guido; Annovi, Alberto; Catastini, Pierluigi; Giannetti, Paola; Lucchesi, Donatella

    2010-01-01

    Real time event reconstruction plays a fundamental role in High Energy Physics experiments. Reducing the rate of data to be saved on tape from millions to hundreds per second is critical. In order to increase the purity of the collected samples, rate reduction has to be coupled with the capability to simultaneously perform a first selection of the most interesting events. A fast and efficient online track reconstruction is important to effectively trigger on leptons and/or displaced tracks from b-quark decays. This talk will be an overview of online tracking techniques in different HEP environments: we will show how H1 experiment at HERA faced the challenges of online track reconstruction implementing pattern matching and track linking algorithms on CAMs and FPGAs in the Fast Track Processor (FTT). The pattern recognition technique is also at the basis of the Silicon Vertex Trigger (SVT) at the CDF experiment at Tevatron: coupled to a very fast fitting phase, SVT allows to trigger on displaced tracks, thus greatly increasing the efficiency for the hadronic B decay modes. A recent upgrade of the SVT track fitter, the Giga-fitter, can perform more than 1 fit/ns and further improves the CDF online trigger capabilities at high luminosity. At SLHC, where luminosities will be 2 orders of magnitude greater than Tevatron, online tracking will be much more challenging: we will describe CMS future plans for a Level-1 track trigger and the Fast Tracker (FTK) processor at the ATLAS experiment, based on the Giga-fitter architecture and designed to provide high quality tracks reconstructed over the entire detector in time for a Level-2 trigger decision.luminosity. At SLHC, where luminosities will be 2 orders of magnitude greater than Tevatron, online tracking will be much more challenging: we will describe CMS future plans for a Level-1 track trigger and the Fast Tracker (FTK) processor at the Atlas experiment, based on the Giga-fitter architecture and designed to provide high

  16. Research on Kalman-filter based multisensor data fusion

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc.Various multisensor data fusion methods have been extensively investigated by researchers,of which Klaman filtering is one of the most important.Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown.states of a dynamic system,which has found widespread application in many areas.The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods.then a new method of state fusion is proposed.Finally the simulation results demonstrate the effectiveness of the introduced method.

  17. Measuring microbial fitness in a field reciprocal transplant experiment.

    Science.gov (United States)

    Boynton, Primrose J; Stelkens, Rike; Kowallik, Vienna; Greig, Duncan

    2017-05-01

    Microbial fitness is easy to measure in the laboratory, but difficult to measure in the field. Laboratory fitness assays make use of controlled conditions and genetically modified organisms, neither of which are available in the field. Among other applications, fitness assays can help researchers detect adaptation to different habitats or locations. We designed a competitive fitness assay to detect adaptation of Saccharomyces paradoxus isolates to the habitat they were isolated from (oak or larch leaf litter). The assay accurately measures relative fitness by tracking genotype frequency changes in the field using digital droplet PCR (DDPCR). We expected locally adapted S. paradoxus strains to increase in frequency over time when growing on the leaf litter type from which they were isolated. The DDPCR assay successfully detected fitness differences among S. paradoxus strains, but did not find a tendency for strains to be adapted to the habitat they were isolated from. Instead, we found that the natural alleles of the hexose transport gene we used to distinguish S. paradoxus strains had significant effects on fitness. The origin of a strain also affected its fitness: strains isolated from oak litter were generally fitter than strains from larch litter. Our results suggest that dispersal limitation and genetic drift shape S. paradoxus populations in the forest more than local selection does, although further research is needed to confirm this. Tracking genotype frequency changes using DDPCR is a practical and accurate microbial fitness assay for natural environments. © 2016 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

  18. Impact of the genfit2 Kalman-filter-based algorithms on physics simulations performed with PandaRoot

    Energy Technology Data Exchange (ETDEWEB)

    Prencipe, Elisabetta; Ritman, James [Forschungszentrum Juelich, IKP1, Juelich (Germany); Collaboration: PANDA-Collaboration

    2016-07-01

    PANDA is a planned experiment at FAIR (Darmstadt) with a cooled antiproton beam in a range [1.5;15] GeV/c, allowing a wide physics program in nuclear and particle physics. It is the only experiment worldwide, which combines a solenoid field (B=2 T) and a dipole field (B=2 Tm) in an experiment with a fixed target topology, in that energy regime. The tracking system of PANDA involves the presence of a high performance silicon vertex detector, a GEM detector, a Straw-Tubes central tracker, a forward tracking system, and a luminosity monitor. The offline tracking algorithm is developed within the PandaRoot framework, which is a part of the FAIRRoot project. The algorithm here presented is based on a tool containing the Kalman Filter equations and a deterministic annealing filter (genfit). The Kalman-Filter-based algorithms have a wide range of applications; among those in particle physics they can perform extrapolations of track parameters and covariance matrices. The impact on physics simulations performed for the PANDA experiment is shown for the first time, with the PandaRoot framework: improvement is shown for those channels where a good low momentum tracking is required (p{sub T}<400 MeV/c), i.e. D mesons and Λ reconstruction, of about a factor 2.

  19. Automatic track counting with an optic RAM-based instrument

    International Nuclear Information System (INIS)

    Staderini, E.M.; Castellano, Alfredo

    1986-01-01

    A new image sensor, the optic RAM, is now used in a microprocessor controlled instrument to read and digitize images from CR39 solid state nuclear track detectors. The system performs image analysis, filtering, tracks counting and evaluation in a fully automatic way, not requiring an optic microscope, nor photographic or television devices. The proposed system is a very compact and low power device. (author)

  20. Regularized Adaptive Notch Filters for Acoustic Howling Suppression

    DEFF Research Database (Denmark)

    Gil-Cacho, Pepe; van Waterschoot, Toon; Moonen, Marc

    2009-01-01

    In this paper, a method for the suppression of acoustic howling is developed, based on adaptive notch filters (ANF) with regularization (RANF). The method features three RANFs working in parallel to achieve frequency tracking, howling detection and suppression. The ANF-based approach to howling...

  1. Image processing algorithm for robot tracking in reactor vessel

    International Nuclear Information System (INIS)

    Kim, Tae Won; Choi, Young Soo; Lee, Sung Uk; Jeong, Kyung Min; Kim, Nam Kyun

    2011-01-01

    In this paper, we proposed an image processing algorithm to find the position of an underwater robot in the reactor vessel. Proposed algorithm is composed of Modified SURF(Speeded Up Robust Feature) based on Mean-Shift and CAMSHIFT(Continuously Adaptive Mean Shift Algorithm) based on color tracking algorithm. Noise filtering using luminosity blend method and color clipping are preprocessed. Initial tracking area for the CAMSHIFT is determined by using modified SURF. And then extracting the contour and corner points in the area of target tracked by CAMSHIFT method. Experiments are performed at the reactor vessel mockup and verified to use in the control of robot by visual tracking

  2. Fault estimation of satellite reaction wheels using covariance based adaptive unscented Kalman filter

    Science.gov (United States)

    Rahimi, Afshin; Kumar, Krishna Dev; Alighanbari, Hekmat

    2017-05-01

    Reaction wheels, as one of the most commonly used actuators in satellite attitude control systems, are prone to malfunction which could lead to catastrophic failures. Such malfunctions can be detected and addressed in time if proper analytical redundancy algorithms such as parameter estimation and control reconfiguration are employed. Major challenges in parameter estimation include speed and accuracy of the employed algorithm. This paper presents a new approach for improving parameter estimation with adaptive unscented Kalman filter. The enhancement in tracking speed of unscented Kalman filter is achieved by systematically adapting the covariance matrix to the faulty estimates using innovation and residual sequences combined with an adaptive fault annunciation scheme. The proposed approach provides the filter with the advantage of tracking sudden changes in the system non-measurable parameters accurately. Results showed successful detection of reaction wheel malfunctions without requiring a priori knowledge about system performance in the presence of abrupt, transient, intermittent, and incipient faults. Furthermore, the proposed approach resulted in superior filter performance with less mean squared errors for residuals compared to generic and adaptive unscented Kalman filters, and thus, it can be a promising method for the development of fail-safe satellites.

  3. Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid.

    Science.gov (United States)

    Byambasuren, Bat-Erdene; Kim, Donghan; Oyun-Erdene, Mandakh; Bold, Chinguun; Yura, Jargalbaatar

    2016-02-19

    Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results.

  4. Full-field particle velocimetry with a photorefractive optical novelty filter

    International Nuclear Information System (INIS)

    Woerdemann, Mike; Holtmann, Frank; Denz, Cornelia

    2008-01-01

    We utilize the finite time constant of a photorefractive optical novelty filter microscope to access full-field velocity information of fluid flows on microscopic scales. In contrast to conventional methods such as particle image velocimetry and particle tracking velocimetry, not only image acquisition of the tracer particle field but also evaluation of tracer particle velocities is done all-optically by the novelty filter. We investigate the velocity dependent parameters of two-beam coupling based optical novelty filters and demonstrate calibration and application of a photorefractive velocimetry system. Theoretical and practical limits to the range of accessible velocities are discussed

  5. Gating Techniques for Rao-Blackwellized Monte Carlo Data Association Filter

    Directory of Open Access Journals (Sweden)

    Yazhao Wang

    2014-01-01

    Full Text Available This paper studies the Rao-Blackwellized Monte Carlo data association (RBMCDA filter for multiple target tracking. The elliptical gating strategies are redesigned and incorporated into the framework of the RBMCDA filter. The obvious benefit is the reduction of the time cost because the data association procedure can be carried out with less validated measurements. In addition, the overlapped parts of the neighboring validation regions are divided into several separated subregions according to the possible origins of the validated measurements. In these subregions, the measurement uncertainties can be taken into account more reasonably than those of the simple elliptical gate. This would help to achieve higher tracking ability of the RBMCDA algorithm by a better association prior approximation. Simulation results are provided to show the effectiveness of the proposed gating techniques.

  6. The ATLAS Track Extrapolation Package

    CERN Document Server

    Salzburger, A

    2007-01-01

    The extrapolation of track parameters and their associated covariances to destination surfaces of different types is a very frequent process in the event reconstruction of high energy physics experiments. This is amongst other reasons due to the fact that most track and vertex fitting techniques are based on the first and second momentum of the underlying probability density distribution. The correct stochastic or deterministic treatment of interactions with the traversed detector material is hereby crucial for high quality track reconstruction throughout the entire momentum range of final state particles that are produced in high energy physics collision experiments. This document presents the main concepts, the algorithms and the implementation of the newly developed, powerful ATLAS track extrapolation engine. It also emphasises on validation procedures, timing measurements and the integration into the ATLAS offline reconstruction software.

  7. Track reconstruction principle in ALICE for LHC run I and run II

    CERN Multimedia

    Maire, Antonin

    2011-01-01

    Principles of tracking for an ALICE event, showing the three successive paths allowing to build a track and refine its parameters. Numbers ranging from 1 to 10 mention the bits that are activated in case of success during the propgation of the Kalman filter at the considered stage.

  8. Reconstructing events, from electronic signals to tracks

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Reconstructing tracks in the events taken by LHC experiments is one of the most challenging and computationally expensive software tasks to be carried out in the data processing chain. A typical LHC event is composed of multiple p-p interactions, each leaving signals from many charged particles in the detector and jus building up an environment of unprecedented complexity. In the lecture I will give an overview of event reconstruction in a typical High Energy Physics experiment. After an introduction to particle tracking detectors I will discuss the concepts and techniques required to master the tracking challenge at the LHC. I will explain how track propagation in a realistic detector works, present different techniques for track fitting and track finding. At the end we will see how all of those techniques play together in the ATLAS track reconstruction application.

  9. Random Scenario Generation for a Multiple Target Tracking Environment Evaluation

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2006-01-01

    , which were normally crossing targets, was to test the efficiency of the track splitting algorithm for different situations. However this approach only gives a measure of performance for a specific, possibly unrealistic, scenario and it was felt appropriate to develop procedures that would enable a more...... general performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the track splitting algorithm using Kalman filters is used and a couple of tracking performance parameters are computed to investigate such random scenarios....

  10. Track-Etched Magnetic Micropores for Immunomagnetic Isolation of Pathogens

    Science.gov (United States)

    Muluneh, Melaku; Shang, Wu

    2014-01-01

    A microfluidic chip is developed to selectively isolate magnetically tagged cells from heterogeneous suspensions, the track-etched magnetic micropore (TEMPO) filter. The TEMPO consists of an ion track-etched polycarbonate membrane coated with soft magnetic film (Ni20Fe80). In the presence of an applied field, provided by a small external magnet, the filter becomes magnetized and strong magnetic traps are created along the edges of the micropores. In contrast to conventional microfluidics, fluid flows vertically through the porous membrane allowing large flow rates while keeping the capture rate high and the chip compact. By utilizing track-etching instead of conventional semiconductor fabrication, TEMPOs can be fabricated with microscale pores over large areas A > 1 cm2 at little cost ( 500 at a flow rate of Φ = 5 mL h−1. Furthermore, the large density of micropores (ρ = 106 cm−2) allows the TEMPO to sort E. coli from unprocessed environmental and clinical samples, as the blockage of a few pores does not significantly change the behavior of the device. PMID:24535921

  11. TREC2002 Web, Novelty and Filtering Track Experiments Using PIRCS

    National Research Council Canada - National Science Library

    Kwok, K. L; Deng, P; Dinstl, N; Chan, M

    2006-01-01

    .... The Web track has two tasks: distillation and named-page retrieval. Distillation is a new utility concept for ranking documents, and needs new design on the output document ranked list after an ad-hoc retrieval from the web (.gov) collection...

  12. Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid

    Directory of Open Access Journals (Sweden)

    Bat-erdene Byambasuren

    2016-02-01

    Full Text Available Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results.

  13. Target Tracking of a Linear Time Invariant System under Irregular Sampling

    Directory of Open Access Journals (Sweden)

    Jin Xue-Bo

    2012-11-01

    Full Text Available Due to event-triggered sampling in a system, or maybe with the aim of reducing data storage, tracking many applications will encounter irregular sampling time. By calculating the matrix exponential using an inverse Laplace transform, this paper transforms the irregular sampling tracking problem to the problem of tracking with time-varying parameters of a system. Using the common Kalman filter, the developed method is used to track a target for the simulated trajectory and video tracking. The results of simulation experiments have shown that it can obtain good estimation performance even at a very high irregular rate of measurement sampling time.

  14. A passive monitor for radon using electrochemical track etch detector

    International Nuclear Information System (INIS)

    Massera, G.E.; Hassib, G.M.; Piesch, E.

    1980-01-01

    A passive, inexpensive monitor for radon detection and dosimetry is described in detail. It consists of a Makrofoil track etch detector inside a diffusion chamber which is sealed by a fibreglass filter through which radon may diffuse while radon daughters and aerosols are retained on the surface of the filter. The α-particle tracks are revealed by etching the Makrofoil in KOH. The lower detection limit of the radon dosimeter is equivalent to a mean dose in the lung of 130 mrem. After an exposure period of 3 months, a mean radon concentration of 0.3 pCi/l can be detected. The instrument is intended for use in a study to measure the long-term radon exposure in buildings in West Germany. (UK)

  15. Low-rank Kalman filtering for efficient state estimation of subsurface advective contaminant transport models

    KAUST Repository

    El Gharamti, Mohamad

    2012-04-01

    Accurate knowledge of the movement of contaminants in porous media is essential to track their trajectory and later extract them from the aquifer. A two-dimensional flow model is implemented and then applied on a linear contaminant transport model in the same porous medium. Because of different sources of uncertainties, this coupled model might not be able to accurately track the contaminant state. Incorporating observations through the process of data assimilation can guide the model toward the true trajectory of the system. The Kalman filter (KF), or its nonlinear invariants, can be used to tackle this problem. To overcome the prohibitive computational cost of the KF, the singular evolutive Kalman filter (SEKF) and the singular fixed Kalman filter (SFKF) are used, which are variants of the KF operating with low-rank covariance matrices. Experimental results suggest that under perfect and imperfect model setups, the low-rank filters can provide estimates as accurate as the full KF but at much lower computational effort. Low-rank filters are demonstrated to significantly reduce the computational effort of the KF to almost 3%. © 2012 American Society of Civil Engineers.

  16. OpenCV and TYZX : video surveillance for tracking.

    Energy Technology Data Exchange (ETDEWEB)

    He, Jim; Spencer, Andrew; Chu, Eric

    2008-08-01

    As part of the National Security Engineering Institute (NSEI) project, several sensors were developed in conjunction with an assessment algorithm. A camera system was developed in-house to track the locations of personnel within a secure room. In addition, a commercial, off-the-shelf (COTS) tracking system developed by TYZX was examined. TYZX is a Bay Area start-up that has developed its own tracking hardware and software which we use as COTS support for robust tracking. This report discusses the pros and cons of each camera system, how they work, a proposed data fusion method, and some visual results. Distributed, embedded image processing solutions show the most promise in their ability to track multiple targets in complex environments and in real-time. Future work on the camera system may include three-dimensional volumetric tracking by using multiple simple cameras, Kalman or particle filtering, automated camera calibration and registration, and gesture or path recognition.

  17. OpenCV and TYZX : video surveillance for tracking

    International Nuclear Information System (INIS)

    He, Jim; Spencer, Andrew; Chu, Eric

    2008-01-01

    As part of the National Security Engineering Institute (NSEI) project, several sensors were developed in conjunction with an assessment algorithm. A camera system was developed in-house to track the locations of personnel within a secure room. In addition, a commercial, off-the-shelf (COTS) tracking system developed by TYZX was examined. TYZX is a Bay Area start-up that has developed its own tracking hardware and software which we use as COTS support for robust tracking. This report discusses the pros and cons of each camera system, how they work, a proposed data fusion method, and some visual results. Distributed, embedded image processing solutions show the most promise in their ability to track multiple targets in complex environments and in real-time. Future work on the camera system may include three-dimensional volumetric tracking by using multiple simple cameras, Kalman or particle filtering, automated camera calibration and registration, and gesture or path recognition

  18. Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

    Science.gov (United States)

    Simon, Dan; Simon, Donald L.

    2005-01-01

    Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

  19. Visual tracking of da Vinci instruments for laparoscopic surgery

    Science.gov (United States)

    Speidel, S.; Kuhn, E.; Bodenstedt, S.; Röhl, S.; Kenngott, H.; Müller-Stich, B.; Dillmann, R.

    2014-03-01

    Intraoperative tracking of laparoscopic instruments is a prerequisite to realize further assistance functions. Since endoscopic images are always available, this sensor input can be used to localize the instruments without special devices or robot kinematics. In this paper, we present an image-based markerless 3D tracking of different da Vinci instruments in near real-time without an explicit model. The method is based on different visual cues to segment the instrument tip, calculates a tip point and uses a multiple object particle filter for tracking. The accuracy and robustness is evaluated with in vivo data.

  20. Mobile Robot Positioning by using Low-Cost Visual Tracking System

    Directory of Open Access Journals (Sweden)

    Ruangpayoongsak Niramon

    2017-01-01

    Full Text Available This paper presents an application of visual tracking system on mobile robot positioning. The proposed method is verified on a constructed low-cost tracking system consisting of 2 DOF pan-tilt unit, web camera and distance sensor. The motion of pan-tilt joints is realized and controlled by using LQR controller running on microcontroller. Without needs of camera calibration, robot trajectory is tracked by Kalman filter integrating distance information and joint positions. The experimental results demonstrate validity of the proposed positioning technique and the obtained mobile robot trajectory is benchmarked against laser rangefinder positioning. The implemented system can successfully track a mobile robot driving at 14 cm/s.

  1. Fir Filters Compliant with the IEEE Standard for M Class PMU

    Directory of Open Access Journals (Sweden)

    Duda Krzysztof

    2016-12-01

    Full Text Available In this paper it is shown that M class PMU (Phasor Measurement Unit reference model for phasor estimation recommended by the IEEE Standard C37.118.1 with the Amendment 1 is not compliant with the Standard. The reference filter preserves only the limits for TVE (total vector error, and exceeds FE (frequency error and RFE (rate of frequency error limits. As a remedy we propose new filters for phasor estimation for M class PMU that are fully compliant with the Standard requirements. The proposed filters are designed: 1 by the window method; 2 as flat-top windows; or as 3 optimal min-max filters. The results for all Standard compliance tests are presented, confirming good performance of the proposed filters. The proposed filters are fixed at the nominal frequency, i.e. frequency tracking and adaptive filter tuning are not required, therefore they are well suited for application in lowcost popular PMUs.

  2. Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study.

    Science.gov (United States)

    Xie, Junqing; Wen, Dong; Liang, Lizhong; Jia, Yuxi; Gao, Li; Lei, Jianbo

    2018-04-12

    Wearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion. The aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities. A total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs). Wearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under

  3. δ-Generalized Labeled Multi-Bernoulli Filter Using Amplitude Information of Neighboring Cells

    Directory of Open Access Journals (Sweden)

    Chao Liu

    2018-04-01

    Full Text Available The amplitude information (AI of echoed signals plays an important role in radar target detection and tracking. A lot of research shows that the introduction of AI enables the tracking algorithm to distinguish targets from clutter better and then improves the performance of data association. The current AI-aided tracking algorithms only consider the signal amplitude in the range-azimuth cell where measurement exists. However, since radar echoes always contain backscattered signals from multiple cells, the useful information of neighboring cells would be lost if directly applying those existing methods. In order to solve this issue, a new δ-generalized labeled multi-Bernoulli (δ-GLMB filter is proposed. It exploits the AI of radar echoes from neighboring cells to construct a united amplitude likelihood ratio, and then plugs it into the update process and the measurement-track assignment cost matrix of the δ-GLMB filter. Simulation results show that the proposed approach has better performance in target’s state and number estimation than that of the δ-GLMB only using single-cell AI in low signal-to-clutter-ratio (SCR environment.

  4. Real-time tracking for virtual environments using scaat kalman filtering and unsynchronised cameras

    DEFF Research Database (Denmark)

    Rasmussen, Niels Tjørnly; Störring, Morritz; Moeslund, Thomas B.

    2006-01-01

    This paper presents a real-time outside-in camera-based tracking system for wireless 3D pose tracking of a user’s head and hand in a virtual environment. The system uses four unsynchronised cameras as sensors and passive retroreflective markers arranged in rigid bodies as targets. In order to ach...

  5. Hypersonic sliding target tracking in near space

    Directory of Open Access Journals (Sweden)

    Xiang-yu Zhang

    2015-12-01

    Full Text Available To improve the tracking accuracy of hypersonic sliding target in near space, the influence of target hypersonic movement on radar detection and tracking is analyzed, and an IMM tracking algorithm is proposed based on radial velocity compensating and cancellation processing of high dynamic biases under the earth centered earth fixed (ECEF coordinate. Based on the analysis of effect of target hypersonic movement, a measurement model is constructed to reduce the filter divergence which is caused by the model mismatch. The high dynamic biases due to the target hypersonic movement are approximately compensated through radial velocity estimation to achieve the hypersonic target tracking at low systematic biases in near space. The high dynamic biases are further eliminated by the cancellation processing of different radars, in which the track association problem can be solved when the dynamic biases are low. An IMM algorithm based on constant acceleration (CA, constant turning (CT and Singer models is used to achieve the hypersonic sliding target tracking in near space. Simulation results show that the target tracking in near space can be achieved more effectively by using the proposed algorithm.

  6. Video-based Chinese Input System via Fingertip Tracking

    Directory of Open Access Journals (Sweden)

    Chih-Chang Yu

    2012-10-01

    Full Text Available In this paper, we propose a system to detect and track fingertips online and recognize Mandarin Phonetic Symbol (MPS for user-friendly Chinese input purposes. Using fingertips and cameras to replace pens and touch panels as input devices could reduce the cost and improve the ease-of-use and comfort of computer-human interface. In the proposed framework, particle filters with enhanced appearance models are applied for robust fingertip tracking. Afterwards, MPS combination recognition is performed on the tracked fingertip trajectories using Hidden Markov Models. In the proposed system, the fingertips of the users could be robustly tracked. Also, the challenges of entering, leaving and virtual strokes caused by video-based fingertip input can be overcome. Experimental results have shown the feasibility and effectiveness of the proposed work.

  7. Use of astronomy filters in fluorescence microscopy.

    Science.gov (United States)

    Piper, Jörg

    2012-02-01

    Monochrome astronomy filters are well suited for use as excitation or suppression filters in fluorescence microscopy. Because of their particular optical design, such filters can be combined with standard halogen light sources for excitation in many fluorescent probes. In this "low energy excitation," photobleaching (fading) or other irritations of native specimens are avoided. Photomicrographs can be taken from living motile fluorescent specimens also with a flash so that fluorescence images can be created free from indistinctness caused by movement. Special filter cubes or dichroic mirrors are not needed for our method. By use of suitable astronomy filters, fluorescence microscopy can be carried out with standard laboratory microscopes equipped with condensers for bright-field (BF) and dark-field (DF) illumination in transmitted light. In BF excitation, the background brightness can be modulated in tiny steps up to dark or black. Moreover, standard industry microscopes fitted with a vertical illuminator for examinations of opaque probes in DF or BF illumination based on incident light (wafer inspections, for instance) can also be used for excitation in epi-illumination when adequate astronomy filters are inserted as excitatory and suppression filters in the illuminating and imaging light path. In all variants, transmission bands can be modulated by transmission shift.

  8. Science and technology with nuclear tracks in solids

    CERN Document Server

    Buford-Price, P

    2005-01-01

    Fission track dating has greatly expanded its usefulness to geology over the last 40 years. It is central to thermochronology—the use of shortened fission tracks to decipher the thermal history, movement, and provenance of rocks. When combined with other indicators, such as zircon color and (U–Th)/He, a range of temperatures from C to C can be studied. Combining fission track analysis with cosmogenic nuclide decay rates, one can study landscape development and denudation of passive margins. Technological applications have expanded from biological filters, radon mapping, and dosimetry to the use of ion track microtechnology in microlithography, micromachining by ion track etching, microscopic field emission tips, magnetic nanowires as magnetoresistive sensors, microfluidic devices, physiology of ion channels in single cells, and so on. In nuclear and particle physics, relatively insensitive glass detectors have been almost single-handedly responsible for our knowledge of cluster radioactivity, and plastic ...

  9. Computer-aided method for recognition of proton track in nuclear emulsion

    International Nuclear Information System (INIS)

    Ruan Jinlu; Li Hongyun; Song Jiwen; Zhang Jianfu; Chen Liang; Zhang Zhongbing; Liu Jinliang

    2014-01-01

    In order to overcome the shortcomings of the manual method for proton-recoil track recognition in nuclear emulsions, a computer-aided track recognition method was studied. In this method, image sequences captured by a microscope system were processed through image convolution with composite filters, binarization by multi thresholds, track grains clustering and redundant grains removing to recognize the track grains in the image sequences. Then the proton-recoil tracks were reconstructed from the recognized track grains through track reconstruction. The proton-recoil tracks in the nuclear emulsion irradiated by the neutron beam at energy of 14.9 MeV were recognized by the computer-aided method. The results show that proton-recoil tracks reconstructed by this method consist well with those reconstructed by the manual method. This compute-raided track recognition method lays an important technical foundation of developments of a proton-recoil track automatic recognition system and applications of nuclear emulsions in pulsed neutron spectrum measurement. (authors)

  10. Radionuclide release rate inversion of nuclear accidents in nuclear facility based on Kalman filter

    International Nuclear Information System (INIS)

    Tang Xiuhuan; Bao Lihong; Li Hua; Wan Junsheng

    2014-01-01

    The rapidly and continually back-calculating source term is important for nuclear emergency response. The Gaussian multi-puff atmospheric dispersion model was used to produce regional environment monitoring data virtually, and then a Kalman filter was designed to inverse radionuclide release rate of nuclear accidents in nuclear facility and the release rate tracking in real time was achieved. The results show that the Kalman filter combined with Gaussian multi-puff atmospheric dispersion model can successfully track the virtually stable, linear or nonlinear release rate after being iterated about 10 times. The standard error of inversion results increases with the true value. Meanwhile extended Kalman filter cannot inverse the height parameter of accident release as interceptive error is too large to converge. Kalman filter constructed from environment monitoring data and Gaussian multi-puff atmospheric dispersion model can be applied to source inversion in nuclear accident which is characterized by static height and position, short and continual release in nuclear facility. Hence it turns out to be an alternative source inversion method in nuclear emergency response. (authors)

  11. The ATLAS FTK Auxiliary Card: A Highly Functional VME Rear Transition Module for a Hardware Track Finding Processing Unit

    CERN Document Server

    Alison, John; The ATLAS collaboration; Bogdan, Mircea; Bryant, Patrick; Cheng, Yangyang; Krizka, Karol; Shochet, Mel; Tompkins, Lauren; Webster, Jordan S

    2014-01-01

    The ATLAS Fast TracKer is a hardware-based charged particle track finder for the High Level Trigger system of the ATLAS Experiment at the LHC. Using a multi-component system, it finds charged particle trajectories of 1 GeV/c and greater using data from the full ATLAS silicon tracking detectors at a rate of 100 kHz. Pattern recognition and preliminary track fitting are performed by VME Processing Units consisting of an Associative Memory Board containing custom associative memory chips for pattern recognition, and the Auxiliary Card (AUX), a powerful rear transition module which formats the data for pattern recognition and performs linearized fits on track candidates. We report on the design and testing of the AUX, which utilizes six FPGAs to process up to 32 Gbps of hit data, as well as fit the helical trajectory of one track candidate per nanosecond through a highly parallel track fitting architecture. Both the board and firmware design will be discussed, as well as the performance observed in tests at CERN ...

  12. Spectral analysis and filter theory in applied geophysics

    CERN Document Server

    Buttkus, Burkhard

    2000-01-01

    This book is intended to be an introduction to the fundamentals and methods of spectral analysis and filter theory and their appli­ cations in geophysics. The principles and theoretical basis of the various methods are described, their efficiency and effectiveness eval­ uated, and instructions provided for their practical application. Be­ sides the conventional methods, newer methods arediscussed, such as the spectral analysis ofrandom processes by fitting models to the ob­ served data, maximum-entropy spectral analysis and maximum-like­ lihood spectral analysis, the Wiener and Kalman filtering methods, homomorphic deconvolution, and adaptive methods for nonstation­ ary processes. Multidimensional spectral analysis and filtering, as well as multichannel filters, are given extensive treatment. The book provides a survey of the state-of-the-art of spectral analysis and fil­ ter theory. The importance and possibilities ofspectral analysis and filter theory in geophysics for data acquisition, processing an...

  13. Recirculating electric air filter for use in confined spaces

    International Nuclear Information System (INIS)

    Bergman, W.; Biermann, A.; Kuhl, W.

    1985-01-01

    We have developed recirculating electric air filters for use in confined spaces where the existing ventilation system is not adequate for removing suspended particles. Two experimental filters were built and evaluated, both of which consisted of a cylindrical cartridge filter fitted over an air blower. In one design the cylindrical cartridge is a disposable unit with the electrodes and filter medium built as an integrated unit. The second design has a cylindrical cartridge that can be easily disassembled to allow replacement of the filter medium. Both designs were evaluated in a 354-ft 3 test cell using NaCl aerosols. The second design was installed and evaluated in a chamber where highly radioactive 238 PuO 2 powder is formed into pellets. We have derived equations that describe the theory of recirculating air filters. The predicted performance compares well with experimental measurements under controlled conditions. 2 refs., 7 figs., 1 tab. (DT)

  14. A difference tracking algorithm based on discrete sine transform

    Science.gov (United States)

    Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

    2018-04-01

    Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

  15. Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

    Science.gov (United States)

    Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

    2017-01-01

    Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

  16. The Application of Barnes Filter to Positioning the Center of Landed Tropical Cyclone in Numerical Models

    Directory of Open Access Journals (Sweden)

    Haibo Zou

    2018-01-01

    Full Text Available After a tropical cyclone (TC making landfall, the numerical model output sea level pressure (SLP presents many small-scale perturbations which significantly influence the positioning of the TC center. To fix the problem, Barnes filter with weighting parameters C=2500 and G=0.35 is used to remove these perturbations. A case study of TC Fung-Wong which landed China in 2008 shows that Barnes filter not only cleanly removes these perturbations, but also well preserves the TC signals. Meanwhile, the centers (track obtained from SLP processed with Barnes filter are much closer to the observations than that from SLP without Barnes filter. Based on the distance difference (DD between the TC center determined by SLP with/without Barnes filter and observation, statistics analysis of 12 TCs which landed China during 2005–2015 shows that in most cases (about 85% the DDs are small (between −30 km and 30 km, while in a few cases (about 15% the DDs are large (greater than 30 km even 70 km. This further verifies that the TC centers identified from SLP with Barnes filter are more accurate compared to that directly obtained from model output SLP. Moreover, the TC track identified with Barnes filter is much smoother than that without Barnes filter.

  17. RGBD Video Based Human Hand Trajectory Tracking and Gesture Recognition System

    Directory of Open Access Journals (Sweden)

    Weihua Liu

    2015-01-01

    Full Text Available The task of human hand trajectory tracking and gesture trajectory recognition based on synchronized color and depth video is considered. Toward this end, in the facet of hand tracking, a joint observation model with the hand cues of skin saliency, motion and depth is integrated into particle filter in order to move particles to local peak in the likelihood. The proposed hand tracking method, namely, salient skin, motion, and depth based particle filter (SSMD-PF, is capable of improving the tracking accuracy considerably, in the context of the signer performing the gesture toward the camera device and in front of moving, cluttered backgrounds. In the facet of gesture recognition, a shape-order context descriptor on the basis of shape context is introduced, which can describe the gesture in spatiotemporal domain. The efficient shape-order context descriptor can reveal the shape relationship and embed gesture sequence order information into descriptor. Moreover, the shape-order context leads to a robust score for gesture invariant. Our approach is complemented with experimental results on the settings of the challenging hand-signed digits datasets and American sign language dataset, which corroborate the performance of the novel techniques.

  18. Low Complexity Track Initialization from a Small Set of Non-Invertible Measurements

    Directory of Open Access Journals (Sweden)

    Wolfgang Koch

    2008-02-01

    Full Text Available Target tracking from non-invertible measurement sets, for example, incomplete spherical coordinates measured by asynchronous sensors in a sensor network, is a task of data fusion present in a lot of applications. Difficulties in tracking using extended Kalman filters lead to unstable behavior, mainly caused by poor initialization. Instead of using high complexity numerical batch-estimators, we offer an analytical approach to initialize the filter from a minimum number of observations. This directly pertains to multi-hypothesis tracking (MHT, where in the presence of clutter and/or multiple targets (i low complexity algorithms are desirable and (ii using a small set of measurements avoids the combinatorial explosion. Our approach uses no numerical optimization, simply evaluating several equations to find the state estimates. This is possible since we avoid an over-determined setup by initializing only from the minimum necessary subset of measurements. Loss in accuracy is minimized by choosing the best subset using an optimality criterion and incorporating the leftover measurements afterwards. Additionally, we provide the possibility to estimate only sub-sets of parameters, and to reliably model the resulting added uncertainties by the covariance matrix. We compare two different implementations, differing in the approximation of the posterior: linearizing the measurement equation as in the extended Kalman filter (EKF or employing the unscented transform (UT. The approach will be studied in two practical examples: 3D track initialization using bearingsonly measurements or using slant-range and azimuth only.

  19. Face Recognition and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Swapnil Vitthal Tathe

    2017-07-01

    Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

  20. The intractable cigarette 'filter problem'.

    Science.gov (United States)

    Harris, Bradford

    2011-05-01

    When lung cancer fears emerged in the 1950s, cigarette companies initiated a shift in cigarette design from unfiltered to filtered cigarettes. Both the ineffectiveness of cigarette filters and the tobacco industry's misleading marketing of the benefits of filtered cigarettes have been well documented. However, during the 1950s and 1960s, American cigarette companies spent millions of dollars to solve what the industry identified as the 'filter problem'. These extensive filter research and development efforts suggest a phase of genuine optimism among cigarette designers that cigarette filters could be engineered to mitigate the health hazards of smoking. This paper explores the early history of cigarette filter research and development in order to elucidate why and when seemingly sincere filter engineering efforts devolved into manipulations in cigarette design to sustain cigarette marketing and mitigate consumers' concerns about the health consequences of smoking. Relevant word and phrase searches were conducted in the Legacy Tobacco Documents Library online database, Google Patents, and media and medical databases including ProQuest, JSTOR, Medline and PubMed. 13 tobacco industry documents were identified that track prominent developments involved in what the industry referred to as the 'filter problem'. These reveal a period of intense focus on the 'filter problem' that persisted from the mid-1950s to the mid-1960s, featuring collaborations between cigarette producers and large American chemical and textile companies to develop effective filters. In addition, the documents reveal how cigarette filter researchers' growing scientific knowledge of smoke chemistry led to increasing recognition that filters were unlikely to offer significant health protection. One of the primary concerns of cigarette producers was to design cigarette filters that could be economically incorporated into the massive scale of cigarette production. The synthetic plastic cellulose acetate

  1. A study of CR-39 track response to charged particles from NOVA implosions

    International Nuclear Information System (INIS)

    Phillips, T.W.; Cable, M.D.; Hicks, D.G.; Li, C.K.; Petrasso, R.D.; Seguin, F.H.

    1996-01-01

    We have exposed CR-39 track recording material to a number of NOVA implosions. Radiation from the implosion passed through an array of ranging filters, which aided identification of the incident particles and their energies. The etching procedure was calibrated by including a piece of track exposed to DD protons from a small accelerator. For the same shots, we quantitatively compare the DD neutron yield with the DD proton yield determined from the track. In DT implosions, tracks produced by neutron interactions prevent observation of charged-particle tracks that are produced by the processes of knock-on, secondary or tertiary fusion

  2. Random-subset fitting of digital holograms for fast three-dimensional particle tracking [invited].

    Science.gov (United States)

    Dimiduk, Thomas G; Perry, Rebecca W; Fung, Jerome; Manoharan, Vinothan N

    2014-09-20

    Fitting scattering solutions to time series of digital holograms is a precise way to measure three-dimensional dynamics of microscale objects such as colloidal particles. However, this inverse-problem approach is computationally expensive. We show that the computational time can be reduced by an order of magnitude or more by fitting to a random subset of the pixels in a hologram. We demonstrate our algorithm on experimentally measured holograms of micrometer-scale colloidal particles, and we show that 20-fold increases in speed, relative to fitting full frames, can be attained while introducing errors in the particle positions of 10 nm or less. The method is straightforward to implement and works for any scattering model. It also enables a parallelization strategy wherein random-subset fitting is used to quickly determine initial guesses that are subsequently used to fit full frames in parallel. This approach may prove particularly useful for studying rare events, such as nucleation, that can only be captured with high frame rates over long times.

  3. Technical Note: Kinect V2 surface filtering during gantry motion for radiotherapy applications.

    Science.gov (United States)

    Nazir, Souha; Rihana, Sandy; Visvikis, Dimitris; Fayad, Hadi

    2018-04-01

    In radiotherapy, the Kinect V2 camera, has recently received a lot of attention concerning many clinical applications including patient positioning, respiratory motion tracking, and collision detection during the radiotherapy delivery phase. However, issues associated with such applications are related to some materials and surfaces reflections generating an offset in depth measurements especially during gantry motion. This phenomenon appears in particular when the collimator surface is observed by the camera; resulting in erroneous depth measurements, not only in Kinect surfaces itself, but also as a large peak when extracting a 1D respiratory signal from these data. In this paper, we proposed filtering techniques to reduce the noise effect in the Kinect-based 1D respiratory signal, using a trend removal filter, and in associated 2D surfaces, using a temporal median filter. Filtering process was validated using a phantom, in order to simulate a patient undergoing radiotherapy treatment while having the ground truth. Our results indicate a better correlation between the reference respiratory signal and its corresponding filtered signal (Correlation coefficient of 0.76) than that of the nonfiltered signal (Correlation coefficient of 0.13). Furthermore, surface filtering results show a decrease in the mean square distance error (85%) between the reference and the measured point clouds. This work shows a significant noise compensation and surface restitution after surface filtering and therefore a potential use of the Kinect V2 camera for different radiotherapy-based applications, such as respiratory tracking and collision detection. © 2018 American Association of Physicists in Medicine.

  4. Calibration of scintillation-light filters for neutron time-of-flight spectrometers at the National Ignition Facility

    Energy Technology Data Exchange (ETDEWEB)

    Sayre, D. B., E-mail: sayre4@llnl.gov; Barbosa, F.; Caggiano, J. A.; Eckart, M. J.; Grim, G. P.; Hartouni, E. P.; Hatarik, R. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); DiPuccio, V. N.; Weber, F. A. [National Security Technologies, Livermore, California 94551 (United States)

    2016-11-15

    Sixty-four neutral density filters constructed of metal plates with 88 apertures of varying diameter have been radiographed with a soft x-ray source and CCD camera at National Security Technologies, Livermore. An analysis of the radiographs fits the radial dependence of the apertures’ image intensities to sigmoid functions, which can describe the rapidly decreasing intensity towards the apertures’ edges. The fitted image intensities determine the relative attenuation value of each filter. Absolute attenuation values of several imaged filters, measured in situ during calibration experiments, normalize the relative quantities which are now used in analyses of neutron spectrometer data at the National Ignition Facility.

  5. The CLEO-III Trigger: Calorimetry and tracking

    International Nuclear Information System (INIS)

    Bergfeld, T.J.; Gollin, G.D.; Haney, M.J.

    1996-01-01

    The CLEO-III Trigger provides a trigger decision every 42ns, with a latency of approximately 2.5μs. This paper describes the pipelined signal processing and pattern recognition schemes used by the calorimeter, and the axial and stereo portions of the drift chamber, to provide the information necessary to make these decisions. Field programmable gate arrays are used extensively to provide cluster filtering and location sorting for calorimetry, and path finding for tracking. Analog processing is also employed in the calorimetry to provide additional leverage on the problem. Timing information is extracted from both calorimetry and tracking

  6. Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

    Science.gov (United States)

    Huang, Zhi; Fan, Baozheng; Song, Xiaolin

    2018-03-01

    As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

  7. A multiscale filter for noise reduction of low-dose cone beam projections.

    Science.gov (United States)

    Yao, Weiguang; Farr, Jonathan B

    2015-08-21

    The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(-x2/2σ(2)(f)) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σ(f), which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ(2)(f)) is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024   ×   768 pixels.

  8. Fast pattern recognition with the ATLAS L1 track trigger for the HL-LHC

    CERN Document Server

    Martensson, Mikael; The ATLAS collaboration

    2016-01-01

    A fast hardware based track trigger for high luminosity upgrade of the Large Hadron Collider (HL- LHC) is being developed in ATLAS. The goal is to achieve trigger levels in high pileup collisions that are similar or even better than those achieved at low pile-up running of LHC by adding tracking information to the ATLAS hardware trigger which is currently based on information from calorimeters and muon trigger chambers only. Two methods for fast pattern recognition are investigated. The first is based on matching tracker hits to pattern banks of simulated high momentum tracks which are stored in a custom made Associative Memory (AM) ASIC. The second is based on the Hough transform where detector hits are transformed into 2D Hough space with one variable related to track pt and one to track direction. Hits found by pattern recognition will be sent to a track fitting step which calculates the track parameters . The speed and precision of the track fitting depends on the quality of the hits selected by the patte...

  9. How Can I Keep Track of Physical Activity and Eating?

    Science.gov (United States)

    ... ANSWERS by heart Lifestyle + Risk Reduction Fitness + Weight Management How Can I Keep Track of Physical Activity and Healthy Eating? Food Diary — Once you’ve set your eating goals, use this sample chart to track your efforts. WEEK: ________________________ DAY: ________________________ Food or Beverage Amount Number of Calories Grams of Saturated Fat ...

  10. Track-before-detect procedures for detection of extended object

    Science.gov (United States)

    Fan, Ling; Zhang, Xiaoling; Shi, Jun

    2011-12-01

    In this article, we present a particle filter (PF)-based track-before-detect (PF TBD) procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance). Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.

  11. Centralized Cooperative Positioning and Tracking with Realistic Communications Constraints

    DEFF Research Database (Denmark)

    Mensing, Christian; Nielsen, Jimmy Jessen

    2010-01-01

    on the overall performance will be assessed. As we are considering a dynamic scenario, the cooperative positioning algorithms are based on extended Kalman filtering for position estimation and tracking. Simulation results for ultra-wideband based ranging information and WLAN based communications infrastructure...

  12. Tracking of overweight and obesity from early childhood to adolescence in a population-based cohort - the Tromsø Study, Fit Futures.

    Science.gov (United States)

    Evensen, Elin; Wilsgaard, Tom; Furberg, Anne-Sofie; Skeie, Guri

    2016-05-10

    Obesity is a serious childhood health problem today. Studies have shown that overweight and obesity tend to be stable (track) from birth, through childhood and adolescence, to adulthood. However, existing studies are heterogeneous; there is still no consensus on the strength of the association between high birth weight or high body mass index (BMI) early in life and overweight and obesity later in life, nor on the appropriate age or target group for intervention and prevention efforts. This study aimed to determine the presence and degree of tracking of overweight and obesity and development in BMI and BMI standard deviation scores (SDS) from childhood to adolescence in the Fit Futures cohort from North Norway. Using a retrospective cohort design, data on 532 adolescents from the Fit Futures cohort were supplemented with height and weight data from childhood health records, and BMI was calculated at 2-4, 5-7, and 15-17 years of age. Participants were categorized into weight classes by BMI according to the International Obesity Taskforce's age- and sex-specific cut-off values for children 2-18 years of age (thinness: adult BMI obesity: adult BMI ≥30 kg/m(2)). Non-parametric tests, Cohen's weighted Kappa statistic and logistic regression were used in the analyses. The prevalence of overweight and obesity combined, increased from 11.5 % at 2-4 years of age and 13.7 % at 5-7 years of age, to 20.1 % at 15-17 years of age. Children who were overweight/obese at 5-7 years of age had increased odds of being overweight/obese at 15-17 years of age, compared to thin/normal weight children (crude odds ratio: 11.1, 95 % confidence interval: 6.4-19.2). Six out of 10 children who were overweight/obese at 5-7 years of age were overweight/obese at 15-17 years of age. The prevalence of overweight and obesity increased with age. We found a moderate indication of tracking of overweight/obesity from childhood to adolescence. Preventive and treatment initiatives among children at

  13. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

  14. Nuclear track radiography of 'hot' aerosol particles

    CERN Document Server

    Boulyga, S F; Kievets, M K; Lomonosova, E M; Zhuk, I V; Yaroshevich, O I; Perelygin, V P; Petrova, R I; Brandt, R; Vater, P

    1999-01-01

    Nuclear track radiography was applied to identify aerosol 'hot' particles which contain elements of nuclear fuel and fallout after Chernobyl NPP accident. For the determination of the content of transuranium elements in radioactive aerosols the measurement of the alpha-activity of 'hot' particles by SSNTD was used in this work, as well as radiography of fission fragments formed as a result of the reactions (n,f) and (gamma,f) in the irradiation of aerosol filters by thermal neutrons and high energy gamma quanta. The technique allowed the sizes and alpha-activity of 'hot' particles to be determined without extracting them from the filter, as well as the determination of the uranium content and its enrichment by sup 2 sup 3 sup 5 U, sup 2 sup 3 sup 9 Pu and sup 2 sup 4 sup 1 Pu isotopes. Sensitivity of determination of alpha activity by fission method is 5x10 sup - sup 6 Bq per particle. The software for the system of image analysis was created. It ensured the identification of track clusters on an optical imag...

  15. Nuclear track radiography of 'hot' aerosol particles

    International Nuclear Information System (INIS)

    Boulyga, S.F.; Kievitskaja, A.I.; Kievets, M.K.; Lomonosova, E.M.; Zhuk, I.V.; Yaroshevich, O.I.; Perelygin, V.P.; Petrova, R.; Brandt, R.; Vater, P.

    1999-01-01

    Nuclear track radiography was applied to identify aerosol 'hot' particles which contain elements of nuclear fuel and fallout after Chernobyl NPP accident. For the determination of the content of transuranium elements in radioactive aerosols the measurement of the α-activity of 'hot' particles by SSNTD was used in this work, as well as radiography of fission fragments formed as a result of the reactions (n,f) and (γ,f) in the irradiation of aerosol filters by thermal neutrons and high energy gamma quanta. The technique allowed the sizes and alpha-activity of 'hot' particles to be determined without extracting them from the filter, as well as the determination of the uranium content and its enrichment by 235 U, 239 Pu and 241 Pu isotopes. Sensitivity of determination of alpha activity by fission method is 5x10 -6 Bq per particle. The software for the system of image analysis was created. It ensured the identification of track clusters on an optical image of the SSNTD surface obtained through a video camera and the determination of size and activity of 'hot' particles

  16. Tracking the business cycle of the Euro area: A multivariate model-based band-pass filter

    NARCIS (Netherlands)

    Azevedo, J.M.; Koopman, S.J.; Rua, A.

    2006-01-01

    This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition model. The underlying multivariate dynamic factor model relies on specific formulations for trend and cycle components and produces smooth business cycle indicators with bandpass filter properties.

  17. Sim Track User's Manual (v 1.0)

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Y.

    2010-01-27

    SimTrack is a simple c++ library designed for the numeric particle tracking in the high energy accelerators. It adopts the 4th order symplectic integrator for the optical transport in the magnetic elements. The 4-D and 6-D weak-strong beam-beam treatments are integrated in it for the beam-beam studies. SimTrack is written with c++ class and standard template library. It provides versatile functions to manage elements and lines. It supports a large range of types of elements. New type of element can be easily created in the library. SimTrack calculates Twiss, coupling and fits tunes, chromaticities and corrects closed orbits. AC dipole and AC multipole are available in this library. SimTrack allows change of element parameters during tracking.

  18. FPGA curved track fitter with very low resource usage

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Jin-Yuan; Wang, M.; Gottschalk, E.; Shi, Z.; /Fermilab

    2006-11-01

    Standard least-squares curved track fitting process is tailored for FPGA implementation. The coefficients in the fitting matrices are carefully chosen so that only shift and accumulation operations are used in the process. The divisions and full multiplications are eliminated. Comparison in an application example shows that the fitting errors of the low resource usage implementation are less than 4% bigger than the fitting errors of the exact least-squares algorithm. The implementation is suitable for low-cost, low-power applications such as high energy physics detector trigger systems.

  19. Manufacturing a low-cost ceramic water filter and filter system for the elimination of common pathogenic bacteria

    Science.gov (United States)

    Simonis, J. J.; Basson, A. K.

    Africa is one of the most water-scarce continents in the world but it is the lack of potable water which results in diarrhoea being the leading cause of death amongst children under the age of five in Africa (696 million children under 5 years old in Africa contract diarrhoea resulting in 2000 deaths per day: WHO and UNICEF, 2009). Most potable water treatment methods use bulk water treatment not suitable or available to the majority of rural poor in Sub-Saharan Africa. One simple but effective way of making sure that water is of good quality is by purifying it by means of a household ceramic water filter. The making and supply of water filters suitable for the removal of suspended solids, pathogenic bacteria and other toxins from drinking water is therefore critical. A micro-porous ceramic water filter with micron-sized pores was developed using the traditional slip casting process. This locally produced filter has the advantage of making use of less raw materials, cost, labour, energy and expertise and being more effective and efficient than other low cost produced filters. The filter is fitted with a silicone tube inserted into a collapsible bag that acts as container and protection for the filter. Enhanced flow is obtained through this filter system. The product was tested using water inoculated with high concentrations of different bacterial cultures as well as with locally polluted stream water. The filter is highly effective (log10 > 4 with 99.99% reduction efficiency) in providing protection from bacteria and suspended solids found in natural water. With correct cleaning and basic maintenance this filter technology can effectively provide drinking water to rural families affected by polluted surface water sources. This is an African solution for the more than 340 million people in Africa without access to clean drinking water (WHO and UNICEF, 2008).

  20. Carrier tracking by smoothing filter improves symbol SNR

    Science.gov (United States)

    Pomalaza-Raez, Carlos A.; Hurd, William J.

    1986-01-01

    The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (SNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

  1. GPU-accelerated 3-D model-based tracking

    International Nuclear Information System (INIS)

    Brown, J Anthony; Capson, David W

    2010-01-01

    Model-based approaches to tracking the pose of a 3-D object in video are effective but computationally demanding. While statistical estimation techniques, such as the particle filter, are often employed to minimize the search space, real-time performance remains unachievable on current generation CPUs. Recent advances in graphics processing units (GPUs) have brought massively parallel computational power to the desktop environment and powerful developer tools, such as NVIDIA Compute Unified Device Architecture (CUDA), have provided programmers with a mechanism to exploit it. NVIDIA GPUs' single-instruction multiple-thread (SIMT) programming model is well-suited to many computer vision tasks, particularly model-based tracking, which requires several hundred 3-D model poses to be dynamically configured, rendered, and evaluated against each frame in the video sequence. Using 6 degree-of-freedom (DOF) rigid hand tracking as an example application, this work harnesses consumer-grade GPUs to achieve real-time, 3-D model-based, markerless object tracking in monocular video.

  2. Robust Object Tracking Using Valid Fragments Selection.

    Science.gov (United States)

    Zheng, Jin; Li, Bo; Tian, Peng; Luo, Gang

    Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.

  3. LHCb: The LHCb tracking concept and performance

    CERN Multimedia

    Rodrigues, E

    2009-01-01

    The LHCb tracking system is designed to reconstruct charged particle trajectories in the forward spectrometer, in view of high precision studies of CP-violating phenomena and searches for rare b-hadron decays at the LHC. The system is composed of four major subdetectors and a dedicated magnet, providing an excellent momentum resolution just above 0.4%. The tracking model is based on the innovative trajectories concept introduced by the BaBar collaboration to reconstruct and fit the tracks, and has been further developed and improved. It is now able to cope with realistic geometries and misalignments in a sophisticated, robust and detector-independent way. The LHCb tracking concept including the interplay of various complementary pattern recognition algorithms and the bi-directional Kalman fitter will be described. The current performance of the tracking, based on the latest simulations, will be presented. Recent results obtained with the first LHC beam tracks from injection tests will be discussed.

  4. Three-dimensional triplet tracking for LHC and future high rate experiments

    International Nuclear Information System (INIS)

    Schöning, A

    2014-01-01

    The hit combinatorial problem is a main challenge for track reconstruction and triggering at high rate experiments. At hadron colliders the dominant fraction of hits is due to low momentum tracks for which multiple scattering (MS) effects dominate the hit resolution. MS is also the dominating source for hit confusion and track uncertainties in low energy precision experiments. In all such environments, where MS dominates, track reconstruction and fitting can be largely simplified by using three-dimensional (3D) hit-triplets as provided by pixel detectors. This simplification is possible since track uncertainties are solely determined by MS if high precision spatial information is provided. Fitting of hit-triplets is especially simple for tracking detectors in solenoidal magnetic fields. The over-constrained 3D-triplet method provides a complete set of track parameters and is robust against fake hit combinations. Full tracks can be reconstructed step-wise by connecting hit triplet combinations from different layers, thus heavily reducing the combinatorial problem and accelerating track linking. The triplet method is ideally suited for pixel detectors where hits can be treated as 3D-space points. With the advent of relatively cheap and industrially available CMOS-sensors the construction of highly granular full scale pixel tracking detectors seems to be possible also for experiments at LHC or future high energy (hadron) colliders. In this paper tracking performance studies for full-scale pixel detectors, including their optimisation for 3D-triplet tracking, are presented. The results obtained for different types of tracker geometries and different reconstruction methods are compared. The potential of reducing the number of tracking layers and - along with that - the material budget using this new tracking concept is discussed. The possibility of using 3D-triplet tracking for triggering and fast online reconstruction is highlighted

  5. Electrochemical synthesis of metallic microstructures using etched ion tracks in nuclear track filters

    International Nuclear Information System (INIS)

    Sanjeev Kumar; Shyam Kumar; Rajesh Kumar; Chakravarti, K.

    2004-01-01

    Interest in nano/microstructures results from their numerous potential applications in various areas such as materials and biomedical sciences, electronics, optics, magnetism, energy storage and electrochemistry. Materials with micro/nanoscopic dimensions not only have potential technological applications in areas such as device technology and drug delivery, but also are of fundamental interest in that the properties of a material can change in this regime of transition between the bulk and molecular scales. Electrodeposition is a versatile technique combining low processing cost with ambient conditions that can be used to prepare metallic, polymeric and semiconducting microstructures. In the present work ion track membranes of Makrofol (KG) have been used as templates for synthesis of metallic microstructures using the technique of electrodeposition. (author)

  6. Robust Individual-Cell/Object Tracking via PCANet Deep Network in Biomedicine and Computer Vision

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    2016-01-01

    Full Text Available Tracking individual-cell/object over time is important in understanding drug treatment effects on cancer cells and video surveillance. A fundamental problem of individual-cell/object tracking is to simultaneously address the cell/object appearance variations caused by intrinsic and extrinsic factors. In this paper, inspired by the architecture of deep learning, we propose a robust feature learning method for constructing discriminative appearance models without large-scale pretraining. Specifically, in the initial frames, an unsupervised method is firstly used to learn the abstract feature of a target by exploiting both classic principal component analysis (PCA algorithms with recent deep learning representation architectures. We use learned PCA eigenvectors as filters and develop a novel algorithm to represent a target by composing of a PCA-based filter bank layer, a nonlinear layer, and a patch-based pooling layer, respectively. Then, based on the feature representation, a neural network with one hidden layer is trained in a supervised mode to construct a discriminative appearance model. Finally, to alleviate the tracker drifting problem, a sample update scheme is carefully designed to keep track of the most representative and diverse samples during tracking. We test the proposed tracking method on two standard individual cell/object tracking benchmarks to show our tracker's state-of-the-art performance.

  7. A lightweight target-tracking scheme using wireless sensor network

    International Nuclear Information System (INIS)

    Kuang, Xing-hong; Shao, Hui-he; Feng, Rui

    2008-01-01

    This paper describes a lightweight target-tracking scheme using wireless sensor network, where randomly distributed sensor nodes take responsibility for tracking the moving target based on the acoustic sensing signal. At every localization interval, a backoff timer algorithm is performed to elect the leader node and determine the transmission order of the localization nodes. An adaptive active region size algorithm based on the node density is proposed to select the optimal nodes taking part in localization. An improved particle filter algorithm performed by the leader node estimates the target state based on the selected nodes' acoustic energy measurements. Some refinements such as optimal linear combination algorithm, residual resampling algorithm, Markov chain Monte Carlo method are introduced in the scheme to improve the tracking performance. Simulation results validate the efficiency of the proposed tracking scheme

  8. Position Tracking During Human Walking Using an Integrated Wearable Sensing System

    Directory of Open Access Journals (Sweden)

    Giulio Zizzo

    2017-12-01

    Full Text Available Progress has been made enabling expensive, high-end inertial measurement units (IMUs to be used as tracking sensors. However, the cost of these IMUs is prohibitive to their widespread use, and hence the potential of low-cost IMUs is investigated in this study. A wearable low-cost sensing system consisting of IMUs and ultrasound sensors was developed. Core to this system is an extended Kalman filter (EKF, which provides both zero-velocity updates (ZUPTs and Heuristic Drift Reduction (HDR. The IMU data was combined with ultrasound range measurements to improve accuracy. When a map of the environment was available, a particle filter was used to impose constraints on the possible user motions. The system was therefore composed of three subsystems: IMUs, ultrasound sensors, and a particle filter. A Vicon motion capture system was used to provide ground truth information, enabling validation of the sensing system. Using only the IMU, the system showed loop misclosure errors of 1% with a maximum error of 4–5% during walking. The addition of the ultrasound sensors resulted in a 15% reduction in the total accumulated error. Lastly, the particle filter was capable of providing noticeable corrections, which could keep the tracking error below 2% after the first few steps.

  9. A self seeded first level track trigger for ATLAS

    International Nuclear Information System (INIS)

    Schöning, A

    2012-01-01

    For the planned high luminosity upgrade of the Large Hadron Collider, aiming to increase the instantaneous luminosity to 5 × 10 34 cm −2 s −1 , the implementation of a first level track trigger has been proposed. This trigger could be installed in the year ∼ 2021 along with the complete renewal of the ATLAS inner detector. The fast readout of the hit information from the Inner Detector is considered as the main challenge of such a track trigger. Different concepts for the implementation of a first level trigger are currently studied within the ATLAS collaboration. The so called 'Self Seeded' track trigger concept exploits fast frontend filtering algorithms based on cluster size reconstruction and fast vector tracking to select hits associated to high momentum tracks. Simulation studies have been performed and results on efficiencies, purities and trigger rates are presented for different layouts.

  10. Manifold Regularized Correlation Object Tracking

    OpenAIRE

    Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

    2017-01-01

    In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped fr...

  11. Joint passive radar tracking and target classification using radar cross section

    Science.gov (United States)

    Herman, Shawn M.

    2004-01-01

    We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

  12. Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

    Directory of Open Access Journals (Sweden)

    Baofeng Wang

    Full Text Available Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

  13. Fuzzy Vector Field Orientation Feedback Control-Based Slip Compensation for Trajectory Tracking Control of a Four Track Wheel Skid-steered Mobile Robot

    Directory of Open Access Journals (Sweden)

    Xuan Vinh Ha

    2013-04-01

    Full Text Available Skid-steered mobile robots have been widely used in exploring unknown environments and in military applications. In this paper, the tuning fuzzy Vector Field Orientation (FVFO feedback control method is proposed for a four track wheel skid-steered mobile robot (4-TW SSMR using flexible fuzzy logic control (FLC. The extended Kalman filter is utilized to estimate the positions, velocities and orientation angles, which are used for feedback control signals in the FVFO method, based on the AHRS kinematic motion model and velocity constraints. In addition, in light of the wheel slip and the braking ability of the robot, we propose a new method for estimating online wheel slip parameters based on a discrete Kalman filter to compensate for the velocity constraints. As demonstrated by our experimental results, the advantages of the combination of the proposed FVFO and wheel slip estimation methods overcome the limitations of the others in the trajectory tracking control problem for a 4-TW SSMR.

  14. Unscented Kalman Filter-Trained Neural Networks for Slip Model Prediction

    Science.gov (United States)

    Li, Zhencai; Wang, Yang; Liu, Zhen

    2016-01-01

    The purpose of this work is to investigate the accurate trajectory tracking control of a wheeled mobile robot (WMR) based on the slip model prediction. Generally, a nonholonomic WMR may increase the slippage risk, when traveling on outdoor unstructured terrain (such as longitudinal and lateral slippage of wheels). In order to control a WMR stably and accurately under the effect of slippage, an unscented Kalman filter and neural networks (NNs) are applied to estimate the slip model in real time. This method exploits the model approximating capabilities of nonlinear state–space NN, and the unscented Kalman filter is used to train NN’s weights online. The slip parameters can be estimated and used to predict the time series of deviation velocity, which can be used to compensate control inputs of a WMR. The results of numerical simulation show that the desired trajectory tracking control can be performed by predicting the nonlinear slip model. PMID:27467703

  15. Tracking Mobile Robot in Indoor Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Liping Zhang

    2014-01-01

    Full Text Available This work addresses the problem of tracking mobile robots in indoor wireless sensor networks (WSNs. Our approach is based on a localization scheme with RSSI (received signal strength indication which is used widely in WSN. The developed tracking system is designed for continuous estimation of the robot’s trajectory. A WSN, which is composed of many very simple and cheap wireless sensor nodes, is deployed at a specific region of interest. The wireless sensor nodes collect RSSI information sent by mobile robots. A range-based data fusion scheme is used to estimate the robot’s trajectory. Moreover, a Kalman filter is designed to improve tracking accuracy. Experiments are provided to assess the performance of the proposed scheme.

  16. Kalman Orbit Optimized Loop Tracking

    Science.gov (United States)

    Young, Lawrence E.; Meehan, Thomas K.

    2011-01-01

    Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

  17. Resonator memories and optical novelty filters

    Science.gov (United States)

    Anderson, Dana Z.; Erle, Marie C.

    Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

  18. Monitors Track Vital Signs for Fitness and Safety

    Science.gov (United States)

    2012-01-01

    Have you ever felt nauseous reading a book in the back seat of a car? Or woken from a deep sleep feeling disoriented, unsure which way is up? Momentary mixups like these happen when the sensory systems that track the body's orientation in space become confused. (In the case of the backseat bookworm, the conflict arises when the reader s inner ear, part of the body s vestibular system, senses the car s motion while her eyes are fixed on the stationary pages of the book.) Conditions like motion sickness are common on Earth, but they also present a significant challenge to astronauts in space. Human sensory systems use the pull of gravity to help determine orientation. In the microgravity environment onboard the International Space Station, for example, the body experiences a period of confusion before it adapts to the new circumstances. (In space, even the body s proprioceptive system, which tells the brain where the arms and legs are oriented without the need for visual confirmation, goes haywire, meaning astronauts sometimes lose track of where their limbs are when they are not moving them.) This Space Adaptation Syndrome affects a majority of astronauts, even experienced ones, causing everything from mild disorientation to nausea to severe vomiting. "It can be quite debilitating," says William Toscano, a research scientist in NASA s Ames Research Center Psychophysiology Laboratory, part of the Center s Human Systems Integration Division. "When this happens, as you can imagine, work proficiency declines considerably." Since astronauts cannot afford to be distracted or incapacitated during critical missions, NASA has explored various means for preventing and countering motion sickness in space, including a range of drug treatments. Many effective motion sickness drugs, however, cause undesirable side effects, such as drowsiness. Toscano and his NASA colleague, Patricia Cowings, have developed a different approach: Utilizing biofeedback training methods, the pair can

  19. Application of velocity filtering to optical-flow passive ranging

    Science.gov (United States)

    Barniv, Yair

    1992-01-01

    The performance of the velocity filtering method as applied to optical-flow passive ranging under real-world conditions is evaluated. The theory of the 3-D Fourier transform as applied to constant-speed moving points is reviewed, and the space-domain shift-and-add algorithm is derived from the general 3-D matched filtering formulation. The constant-speed algorithm is then modified to fit the actual speed encountered in the optical flow application, and the passband of that filter is found in terms of depth (sensor/object distance) so as to cover any given range of depths. Two algorithmic solutions for the problems associated with pixel interpolation and object expansion are developed, and experimental results are presented.

  20. Track-before-detect procedures for detection of extended object

    Directory of Open Access Journals (Sweden)

    Fan Ling

    2011-01-01

    Full Text Available Abstract In this article, we present a particle filter (PF-based track-before-detect (PF TBD procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance. Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.

  1. Determination of radon and thoron permeability through some plastics by track technique

    Energy Technology Data Exchange (ETDEWEB)

    Hafez, A.-F.; Somogyi, G.

    1986-01-01

    Experiments have been performed to study the usefulness of several types of plastic foils as filter to separate radon and thoron. Time-integrated alpha-activity measurements have been carried out by using the so-called ''can-technique'' equipped with both LR-115 and CR-39 track detectors. The track density observed on the detectors, taken as a measure of radon activity concentration, has been determined as a function of the thickness of filter foils. The radon permeability and the thoron separation factors have been determined. It is shown that various plastic foils exhibit considerable differences in radon diffusion coefficient owing to their different chemical structures. Among the plastic foils investigated the polyethylene proved to have the highest gas diffusion coefficient.

  2. daptive Filter Used as a Dynamic Compensator in Automatic Gauge Control of Strip Rolling Processes

    Directory of Open Access Journals (Sweden)

    N. ROMAN

    2010-12-01

    Full Text Available The paper deals with a control structure of the strip thickness in a rolling mill of quarto type (AGC – Automatic Gauge Control. It performs two functions: the compensation of errors induced by unideal dynamics of the tracking systems lead by AGC system and the control adaptation to the change of dynamic properties of the tracking systems. The compensation of dynamical errors is achieved through inverse models of the tracking system, implemented as adaptive filters.

  3. Fitting a function to time-dependent ensemble averaged data

    DEFF Research Database (Denmark)

    Fogelmark, Karl; Lomholt, Michael A.; Irbäck, Anders

    2018-01-01

    Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion...... method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software....

  4. Real time tracking by LOPF algorithm with mixture model

    Science.gov (United States)

    Meng, Bo; Zhu, Ming; Han, Guangliang; Wu, Zhiguo

    2007-11-01

    A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

  5. Rail Track Detection and Modelling in Mobile Laser Scanner Data

    Directory of Open Access Journals (Sweden)

    S. Oude Elberink

    2013-10-01

    Full Text Available We present a method for detecting and modelling rails in mobile laser scanner data. The detection is based on the properties of the rail tracks and contact wires such as relative height, linearity and relative position with respect to other objects. Points classified as rail track are used in a 3D modelling algorithm. The modelling is done by first fitting a parametric model of a rail piece to the points along each track, and estimating the position and orientation parameters of each piece model. For each position and orientation parameter a smooth low-order Fourier curve is interpolated. Using all interpolated parameters a mesh model of the rail is reconstructed. The method is explained using two areas from a dataset acquired by a LYNX mobile mapping system in a mountainous area. Residuals between railway laser points and 3D models are in the range of 2 cm. It is concluded that a curve fitting algorithm is essential to reliably and accurately model the rail tracks by using the knowledge that railways are following a continuous and smooth path.

  6. Hardware-based tracking at trigger level for ATLAS: The Fast Tracker (FTK) Project

    CERN Document Server

    Gramling, Johanna; The ATLAS collaboration

    2015-01-01

    Physics collisions at 13 TeV are expected at the LHC with an average of 40-50 proton-proton collisions per bunch crossing. Tracking at trigger level is an essential tool to control the rate in high-pileup conditions while maintaining a good efficiency for relevant physics processes. The Fast TracKer (FTK) is an integral part of the trigger upgrade for the ATLAS detector. For every event passing the Level 1 trigger (at a maximum rate of 100 kHz) the FTK receives data from the 80 million channels of the silicon detectors, providing tracking information to the High Level Trigger in order to ensure a selection robust against pile-up. The FTK performs a hardware-based track reconstruction, using associative memory (AM) that is based on the use of a custom chip, designed to perform pattern matching at very high speed. It finds track candidates at low resolution (roads) that seed a full-resolution track fitting done by FPGAs. Narrow roads permit a fast track fitting but need many patterns stored in the AM to ensure ...

  7. Laser-based pedestrian tracking in outdoor environments by multiple mobile robots.

    Science.gov (United States)

    Ozaki, Masataka; Kakimuma, Kei; Hashimoto, Masafumi; Takahashi, Kazuhiko

    2012-10-29

    This paper presents an outdoors laser-based pedestrian tracking system using a group of mobile robots located near each other. Each robot detects pedestrians from its own laser scan image using an occupancy-grid-based method, and the robot tracks the detected pedestrians via Kalman filtering and global-nearest-neighbor (GNN)-based data association. The tracking data is broadcast to multiple robots through intercommunication and is combined using the covariance intersection (CI) method. For pedestrian tracking, each robot identifies its own posture using real-time-kinematic GPS (RTK-GPS) and laser scan matching. Using our cooperative tracking method, all the robots share the tracking data with each other; hence, individual robots can always recognize pedestrians that are invisible to any other robot. The simulation and experimental results show that cooperating tracking provides the tracking performance better than conventional individual tracking does. Our tracking system functions in a decentralized manner without any central server, and therefore, this provides a degree of scalability and robustness that cannot be achieved by conventional centralized architectures.

  8. Contrast Gain Control Model Fits Masking Data

    Science.gov (United States)

    Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

  9. Multiple hypothesis tracking for the cyber domain

    Science.gov (United States)

    Schwoegler, Stefan; Blackman, Sam; Holsopple, Jared; Hirsch, Michael J.

    2011-09-01

    This paper discusses how methods used for conventional multiple hypothesis tracking (MHT) can be extended to domain-agnostic tracking of entities from non-kinematic constraints such as those imposed by cyber attacks in a potentially dense false alarm background. MHT is widely recognized as the premier method to avoid corrupting tracks with spurious data in the kinematic domain but it has not been extensively applied to other problem domains. The traditional approach is to tightly couple track maintenance (prediction, gating, filtering, probabilistic pruning, and target confirmation) with hypothesis management (clustering, incompatibility maintenance, hypothesis formation, and Nassociation pruning). However, by separating the domain specific track maintenance portion from the domain agnostic hypothesis management piece, we can begin to apply the wealth of knowledge gained from ground and air tracking solutions to the cyber (and other) domains. These realizations led to the creation of Raytheon's Multiple Hypothesis Extensible Tracking Architecture (MHETA). In this paper, we showcase MHETA for the cyber domain, plugging in a well established method, CUBRC's INFormation Engine for Real-time Decision making, (INFERD), for the association portion of the MHT. The result is a CyberMHT. We demonstrate the power of MHETA-INFERD using simulated data. Using metrics from both the tracking and cyber domains, we show that while no tracker is perfect, by applying MHETA-INFERD, advanced nonkinematic tracks can be captured in an automated way, perform better than non-MHT approaches, and decrease analyst response time to cyber threats.

  10. An improved particle filtering algorithm for aircraft engine gas-path fault diagnosis

    Directory of Open Access Journals (Sweden)

    Qihang Wang

    2016-07-01

    Full Text Available In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.

  11. False star detection and isolation during star tracking based on improved chi-square tests.

    Science.gov (United States)

    Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Yang, Yanqiang; Su, Guohua

    2017-08-01

    The star sensor is a precise attitude measurement device for a spacecraft. Star tracking is the main and key working mode for a star sensor. However, during star tracking, false stars become an inevitable interference for star sensor applications, which may result in declined measurement accuracy. A false star detection and isolation algorithm in star tracking based on improved chi-square tests is proposed in this paper. Two estimations are established based on a Kalman filter and a priori information, respectively. The false star detection is operated through adopting the global state chi-square test in a Kalman filter. The false star isolation is achieved using a local state chi-square test. Semi-physical experiments under different trajectories with various false stars are designed for verification. Experiment results show that various false stars can be detected and isolated from navigation stars during star tracking, and the attitude measurement accuracy is hardly influenced by false stars. The proposed algorithm is proved to have an excellent performance in terms of speed, stability, and robustness.

  12. Real-time vehicle detection and tracking in video based on faster R-CNN

    Science.gov (United States)

    Zhang, Yongjie; Wang, Jian; Yang, Xin

    2017-08-01

    Vehicle detection and tracking is a significant part in auxiliary vehicle driving system. Using the traditional detection method based on image information has encountered enormous difficulties, especially in complex background. To solve this problem, a detection method based on deep learning, Faster R-CNN, which has very high detection accuracy and flexibility, is introduced. An algorithm of target tracking with the combination of Camshift and Kalman filter is proposed for vehicle tracking. The computation time of Faster R-CNN cannot achieve realtime detection. We use multi-thread technique to detect and track vehicle by parallel computation for real-time application.

  13. A Novel Sliding Mode Control Technique for Indirect Current Controlled Active Power Filter

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2012-01-01

    Full Text Available A novel sliding mode control (SMC method for indirect current controlled three-phase parallel active power filter is presented in this paper. There are two designed closed loops in the system: one is the DC voltage controlling loop and the other is the reference current tracking loop. The first loop with a PI regulator is used to control the DC voltage approximating to the given voltage of capacitor, and the output of PI regulator through a low-pass filter is applied as the input of the power supply reference currents. The second loop implements the tracking of the reference currents using integral sliding mode controller, which can improve the harmonic treating performance. Compared with the direct current control technique, it is convenient to be implemented with digital signal processing system because of simpler system structure and better harmonic treating property. Simulation results verify that the generated reference currents have the same amplitude with the load currents, demonstrating the superior harmonic compensating effects with the proposed shunt active power filter compared with the hysteresis method.

  14. New approach of modeling charged particles track development in CR-39 detectors

    International Nuclear Information System (INIS)

    Azooz, A.A.; Hermsdorf, D.; Al-Jubbori, M.A.

    2013-01-01

    In this work, previous modeling of protons and alpha particles track length development in CR-39 solid state nuclear track detectors SSNTD is modified and further extended. The extension involved the accommodation of heavier ions into the model. These ions include deuteron, lithium, boron, carbon, nitrogen and oxygen ions. The new modeling does not contain any case sensitive free fitting parameters. Model calculation results are found to be in good agreement with both experimental data and SRIM software range energy dependence predictions. The access to a single unified and differentiable track length development equation results in the ability to obtain direct results for track etching rates. - Highlights: • New modeling of ions track length evolution measured by different authors. • Ions considered are p, d, α, Li, B, C, N, O. • Equations obtained to describe L(t) and etch rate for all ions at wide energy range. • Equations obtained do not involve any free fitting parameters. • Ions range values obtained compare well with results of SRIM software

  15. The intractable cigarette ‘filter problem’

    Science.gov (United States)

    2011-01-01

    Background When lung cancer fears emerged in the 1950s, cigarette companies initiated a shift in cigarette design from unfiltered to filtered cigarettes. Both the ineffectiveness of cigarette filters and the tobacco industry's misleading marketing of the benefits of filtered cigarettes have been well documented. However, during the 1950s and 1960s, American cigarette companies spent millions of dollars to solve what the industry identified as the ‘filter problem’. These extensive filter research and development efforts suggest a phase of genuine optimism among cigarette designers that cigarette filters could be engineered to mitigate the health hazards of smoking. Objective This paper explores the early history of cigarette filter research and development in order to elucidate why and when seemingly sincere filter engineering efforts devolved into manipulations in cigarette design to sustain cigarette marketing and mitigate consumers' concerns about the health consequences of smoking. Methods Relevant word and phrase searches were conducted in the Legacy Tobacco Documents Library online database, Google Patents, and media and medical databases including ProQuest, JSTOR, Medline and PubMed. Results 13 tobacco industry documents were identified that track prominent developments involved in what the industry referred to as the ‘filter problem’. These reveal a period of intense focus on the ‘filter problem’ that persisted from the mid-1950s to the mid-1960s, featuring collaborations between cigarette producers and large American chemical and textile companies to develop effective filters. In addition, the documents reveal how cigarette filter researchers' growing scientific knowledge of smoke chemistry led to increasing recognition that filters were unlikely to offer significant health protection. One of the primary concerns of cigarette producers was to design cigarette filters that could be economically incorporated into the massive scale of cigarette

  16. Nasal Filters For Relief From Atopic Dermatitis Caused by Inhalants

    Directory of Open Access Journals (Sweden)

    J S Pasricha

    1989-01-01

    Full Text Available Nasal filter is a simple device consisting of a net mounted in a frame made to fit inside the nostrils. These filters thus are not visible from outside. If a person uses the nasal filters the .u particulate material from the air that the person breathes gets removed and in case the person is allergic to an inhalant antigen, he stops having the allergic symptoms. We tried nasal filters on two females patients aged 32 and 7 years respectively, having topics dermatitis the age of I year, caused by an inhalant (indicated by seasonal aggravations, and spontaneous recovery during brief visits to other towns. Unrig a follow-up of 2 1/2 and 2 years respectively, both the patients experienced almost 80-90% relief from the dermatitis and required only animal treatment.

  17. Practical Gammatone-Like Filters for Auditory Processing

    Directory of Open Access Journals (Sweden)

    R. F. Lyon

    2007-12-01

    Full Text Available This paper deals with continuous-time filter transfer functions that resemble tuning curves at particular set of places on the basilar membrane of the biological cochlea and that are suitable for practical VLSI implementations. The resulting filters can be used in a filterbank architecture to realize cochlea implants or auditory processors of increased biorealism. To put the reader into context, the paper starts with a short review on the gammatone filter and then exposes two of its variants, namely, the differentiated all-pole gammatone filter (DAPGF and one-zero gammatone filter (OZGF, filter responses that provide a robust foundation for modeling cochlea transfer functions. The DAPGF and OZGF responses are attractive because they exhibit certain characteristics suitable for modeling a variety of auditory data: level-dependent gain, linear tail for frequencies well below the center frequency, asymmetry, and so forth. In addition, their form suggests their implementation by means of cascades of N identical two-pole systems which render them as excellent candidates for efficient analog or digital VLSI realizations. We provide results that shed light on their characteristics and attributes and which can also serve as “design curves” for fitting these responses to frequency-domain physiological data. The DAPGF and OZGF responses are essentially a “missing link” between physiological, electrical, and mechanical models for auditory filtering.

  18. Distributed Extended Kalman Filter for Position, Velocity, Time, Estimation in Satellite Navigation Receivers

    Directory of Open Access Journals (Sweden)

    O. Jakubov

    2013-09-01

    Full Text Available Common techniques for position-velocity-time estimation in satellite navigation, iterative least squares and the extended Kalman filter, involve matrix operations. The matrix inversion and inclusion of a matrix library pose requirements on a computational power and operating platform of the navigation processor. In this paper, we introduce a novel distributed algorithm suitable for implementation in simple parallel processing units each for a tracked satellite. Such a unit performs only scalar sum, subtraction, multiplication, and division. The algorithm can be efficiently implemented in hardware logic. Given the fast position-velocity-time estimator, frequent estimates can foster dynamic performance of a vector tracking receiver. The algorithm has been designed from a factor graph representing the extended Kalman filter by splitting vector nodes into scalar ones resulting in a cyclic graph with few iterations needed. Monte Carlo simulations have been conducted to investigate convergence and accuracy. Simulation case studies for a vector tracking architecture and experimental measurements with a real-time software receiver developed at CTU in Prague were conducted. The algorithm offers compromises in stability, accuracy, and complexity depending on the number of iterations. In scenarios with a large number of tracked satellites, it can outperform the traditional methods at low complexity.

  19. Track Finding for the Level-1 Trigger of the CMS Experiment

    CERN Document Server

    James, Thomas Owen

    2017-01-01

    A new tracking system is under development for the CMS experiment at the High Luminosity LHC (HL-LHC), located at CERN. It includes a silicon tracker that will correlate clusters in two closely spaced sensor layers, for the rejection of hits from low transverse momentum tracks. This will allow tracker data to be read out to the Level-1 trigger at 40\\,MHz. The Level-1 track-finder must be able to identify tracks with transverse momentum above 2--3\\,$\\mathrm{GeV}/c$ within latency constraints. A concept for an FPGA-based track finder using a fully time-multiplexed architecture is presented, where track candidates are identified using a Hough Transform, and then refined with a Kalman Filter. Both steps are fully implemented in FPGA firmware. A hardware system built from MP7 MicroTCA processing cards has been assembled, which demonstrates a realistic slice of the track finder in order to help gauge the performance and requirements for a final system.

  20. Generation of Long Waves using Non-Linear Digital Filters

    DEFF Research Database (Denmark)

    Høgedal, Michael; Frigaard, Peter

    1994-01-01

    transform of the 1st order surface elevation and subsequently inverse Fourier transformed. Hence, the methods are unsuitable for real-time applications, for example where white noise are filtered digitally to obtain a wave spectrum with built-in stochastic variabillity. In the present paper an approximative...... method for including the correct 2nd order bound terms in such applications is presented. The technique utilizes non-liner digital filters fitted to the appropriate transfer function is derived only for bounded 2nd order subharmonics, as they laboratory experiments generally are considered the most...

  1. Speech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering

    Directory of Open Access Journals (Sweden)

    M. Geravanchizadeh

    2014-12-01

    Full Text Available This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS leads to better performance of adaptive filter. Furthermore, convex combination of two adaptive filters improves its performance. In this paper, new convex combinational adaptive filtering methods in the framework of speech enhancement system are proposed. The proposed methods utilize the idea of normalization and fractional derivative, both in the design of different convex mixing strategies and their related component filters. To assess our proposed methods, simulation results of different LMS-based algorithms based on their convergence behavior (i.e., MSE plots and different objective and subjective criteria are compared. The objective and subjective evaluations include examining the results of SNR improvement, PESQ test, and listening tests for dual-channel speech enhancement. The powerful aspects of proposed methods are their low complexity, as expected with all LMS-based methods, along with a high convergence rate.

  2. A Real-time Face/Hand Tracking Method for Chinese Sign Language Recognition

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper introduces a new Chinese Sign Language recognition (CSLR) system and a method of real-time tracking face and hand applied in the system. In the method, an improved agent algorithm is used to extract the region of face and hand and track them. Kalman filter is introduced to forecast the position and rectangle of search, and self-adapting of target color is designed to counteract the effect of illumination.

  3. Multitarget Tracking with Spatial Nonmaximum Suppressed Sensor Selection

    Directory of Open Access Journals (Sweden)

    Liang Ma

    2015-01-01

    Full Text Available Multitarget tracking is one of the most important applications of sensor networks, yet it is an extremely challenging problem since multisensor multitarget tracking itself is nontrivial and the difficulty is further compounded by sensor management. Recently, random finite set based Bayesian framework has opened doors for multitarget tracking with sensor management, which is modelled in the framework of partially observed Markov decision process (POMDP. However, sensor management posed as a POMDP is in essence a combinatorial optimization problem which is NP-hard and computationally unacceptable. In this paper, we propose a novel sensor selection method for multitarget tracking. We first present the sequential multi-Bernoulli filter as a centralized multisensor fusion scheme for multitarget tracking. In order to perform sensor selection, we define the hypothesis information gain (HIG of a sensor to measure its information quantity when the sensor is selected alone. Then, we propose spatial nonmaximum suppression approach to select sensors with respect to their locations and HIGs. Two distinguished implementations have been provided using the greedy spatial nonmaximum suppression. Simulation results verify the effectiveness of proposed sensor selection approach for multitarget tracking.

  4. Catching the Drift : Using Feature-Free Case-Based Reasoning for Spam Filtering.

    OpenAIRE

    Delany, Sarah Jane; Bridge, Derek

    2007-01-01

    n this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam filter that uses a feature-free distance measure based on text compression. In our experiments, we compare two ways to normalise such a distance measure, finding that the one proposed in [1] performs better. We show that a policy as simple as retaining misclassified examples has a hugely beneficial effect on handling con...

  5. Are consistent equal-weight particle filters possible?

    Science.gov (United States)

    van Leeuwen, P. J.

    2017-12-01

    Particle filters are fully nonlinear data-assimilation methods that could potentially change the way we do data-assimilation in highly nonlinear high-dimensional geophysical systems. However, the standard particle filter in which the observations come in by changing the relative weights of the particles is degenerate. This means that one particle obtains weight one, and all other particles obtain a very small weight, effectively meaning that the ensemble of particles reduces to that one particle. For over 10 years now scientists have searched for solutions to this problem. One obvious solution seems to be localisation, in which each part of the state only sees a limited number of observations. However, for a realistic localisation radius based on physical arguments, the number of observations is typically too large, and the filter is still degenerate. Another route taken is trying to find proposal densities that lead to more similar particle weights. There is a simple proof, however, that shows that there is an optimum, the so-called optimal proposal density, and that optimum will lead to a degenerate filter. On the other hand, it is easy to come up with a counter example of a particle filter that is not degenerate in high-dimensional systems. Furthermore, several particle filters have been developed recently that claim to have equal or equivalent weights. In this presentation I will show how to construct a particle filter that is never degenerate in high-dimensional systems, and how that is still consistent with the proof that one cannot do better than the optimal proposal density. Furthermore, it will be shown how equal- and equivalent-weights particle filters fit within this framework. This insight will then lead to new ways to generate particle filters that are non-degenerate, opening up the field of nonlinear filtering in high-dimensional systems.

  6. SWISTRACK - AN OPEN SOURCE, SOFTWARE PACKAGE APPLICABLE TO TRACKING OF FISH LOCOMOTION AND BEHAVIOUR

    DEFF Research Database (Denmark)

    Steffensen, John Fleng

    2010-01-01

    including swimming speed, acceleration and directionality of movements as well as the examination of locomotory panems during swimming. SWiSlrdL:k, a [n: t; and downloadable software package (available from www.sourceforge.com) is widely used for tracking robots, humans and other animals. Accordingly......, Swistrack can be easily adopted for the tracking offish. Benefits associated with the free software include: • Contrast or marker based tracking enabling tracking of either the whole animal, or tagged marks placed upon the animal • The ability to track multiple tags placed upon an individual animal • Highly...... effective background subtraction algorithms and filters ensuring smooth tracking of fish • Application of tags of different colour enables the software to track multiple fish without the problem of track exchange between individuals • Low processing requirements enable tracking in real-time • Further...

  7. The relationship between physical fitness and clustered risk, and tracking of clustered risk from adolescence to young adulthood: eight years follow-up in the Danish Youth and Sport Study

    Directory of Open Access Journals (Sweden)

    Grønfeldt Vivian

    2004-03-01

    Full Text Available Abstract Introduction Cardiovascular disease (CVD is usually caused by high levels of many risk factors simultaneously over many years. Therefore, it is of great interest to study if subjects stay within rank order over time in both the biological risk factors and the behaviour that influences these risk factors. Many studies have described stability (tracking in single risk factors, especially in children where hard endpoints are lacking, but few have analysed tracking in clustered risk. Methods Two examinations were conducted 8 years apart. The first time, 133 males and 172 females were 16–19 years of age. Eight years later, 98 males and 137 females participated. They were each time ranked into quartiles by sex in four CVD risk factors all related to the metabolic syndrome. Risk factors were the ratio between total cholesterol and HDL, triglyceride, systolic BP and body fat. The upper quartile was defined as being at risk, and if a subject had two or more risk factors, he/she was defined as a case (15–20 % of the subjects. Odds ratios (OR for being a case was calculated between quartiles of fitness in both cross-sectional studies. The stability of combined risk was calculated as the OR between cases and non-cases at the first examination to be a case at the second examination. Results ORs for having two or more risk factors between quartiles of fitness were 3.1, 3.8 and 4.9 for quartiles two to four, respectively. At the second examination, OR were 0.7, 3.5 and 4.9, respectively. The probability for "a case" at the first examination to be "a case" at the second was 6.0. Conclusions The relationship between an exposure like physical fitness and CVD risk factors is much stronger when clustering of risk factors are analysed compared to the relationship to single risk factors. The stability over time in multiple risk factors analysed together is strong. This relationship should be seen in the light of moderate or weak tracking of single risk

  8. Efficient Constrained Local Model Fitting for Non-Rigid Face Alignment.

    Science.gov (United States)

    Lucey, Simon; Wang, Yang; Cox, Mark; Sridharan, Sridha; Cohn, Jeffery F

    2009-11-01

    Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The "simultaneous" algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2-3 fps). The "project-out" algorithm for fitting an AAM achieves faster than real time performance (> 200 fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the "simultaneous" AAM algorithm along with real time fitting speeds (35 fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the "exhaustive local search" (ELS) algorithm. Experiments were conducted on the CMU Multi-PIE database.

  9. Hardware-based Tracking at Trigger Level for ATLAS: The Fast TracKer (FTK) Project

    CERN Document Server

    Gramling, Johanna; The ATLAS collaboration

    2015-01-01

    Physics collisions at 13 TeV are expected at the LHC with an average of 40-50 proton-proton collisions per bunch crossing. Tracking at trigger level is an essential tool to control the rate in high-pileup conditions while maintaining a good efficiency for relevant physics processes. The Fast TracKer (FTK) is an integral part of the trigger upgrade for the ATLAS detector. For every event passing the Level 1 trigger (at a maximum rate of 100 kHz) the FTK receives data from the 80 million channels of the silicon detectors, providing tracking information to the High Level Trigger in order to ensure a selection robust against pile-up. The FTK performs a hardware- based track reconstruction, using associative memory (AM) that is based on the use of a custom chip, designed to perform pattern matching at very high speed. It finds track candidates at low resolution (roads) that seed a full-resolution track fitting done by FPGAs. Narrow roads permit a fast track fitting but need many patterns stored in the AM to ensure...

  10. Volcano monitoring using the Global Positioning System: Filtering strategies

    Science.gov (United States)

    Larson, K.M.; Cervelli, Peter; Lisowski, M.; Miklius, Asta; Segall, P.; Owen, S.

    2001-01-01

    Permanent Global Positioning System (GPS) networks are routinely used for producing improved orbits and monitoring secular tectonic deformation. For these applications, data are transferred to an analysis center each day and routinely processed in 24-hour segments. To use GPS for monitoring volcanic events, which may last only a few hours, real-time or near real-time data processing and subdaily position estimates are valuable. Strategies have been researched for obtaining station coordinates every 15 min using a Kalman filter; these strategies have been tested on data collected by a GPS network on Kilauea Volcano. Data from this network are tracked continuously, recorded every 30 s, and telemetered hourly to the Hawaiian Volcano Observatory. A white noise model is heavily impacted by data outages and poor satellite geometry, but a properly constrained random walk model fits the data well. Using a borehole tiltmeter at Kilauea's summit as ground-truth, solutions using different random walk constraints were compared. This study indicates that signals on the order of 5 mm/h are resolvable using a random walk standard deviation of 0.45 cm/???h. Values lower than this suppress small signals, and values greater than this have significantly higher noise at periods of 1-6 hours. Copyright 2001 by the American Geophysical Union.

  11. TPC track distortions III: fiat lux

    CERN Document Server

    Boyko, I; Dydak, F; Elagin, A; Gostkin, M; Guskov, A; Koreshev, V; Nefedov, Y; Nikolaev, K; Veenhof, R; Wotschack, J; Zhemchugov, A

    2005-01-01

    We present a comprehensive overview and final summary of all four types of static track distortions seen in the HARP TPC, in terms of physical origins, mathematical modelling, and correction algorithms. 'Static'™ distortions are defined as not depending on the event time within the 400 ms long accelerator spill. Calculated static distortions are compared with measurements from cosmic-muon tracks. We characterize track distortions by the r phi residuals of cluster positions with respect to the transverse projection of a helical trajectory constrained by hits in the RPC overlap regions. This method provides a fixed TPC-external reference system (by contrast to the co-moving coordinate system associated with a fit) which solely permits to identify individually, and measure quantitatively, the static TPC track distortions arising from (i) the inhomogeneity of the solenoidal magnetic field, (ii) the inhomogeneity of the electric field from the high-voltage mismatch between the inner and outer TPC field cages, (...

  12. Fast Track Finding in the ILC's Silicon Detector, SiD01

    International Nuclear Information System (INIS)

    Baker, David E.

    2007-01-01

    A fast track finder is presented which, unlike its more efficient, more computationally costly O(n3) time counterparts, tracks particles in O(n) time (for n being the number of hits). Developed as a tool for processing data from the ILC's proposed SiD detector, development of this fast track finder began with that proposed by Pablo Yepes in 1996 and adjusted to accommodate the changes in geometry of the SiD detector. First, space within the detector is voxellated, with hits assigned to voxels according to their r, φ, and η coordinates. A hit on the outermost layer is selected, and a 'sample space' is built from the hits in the selected hit's surrounding voxels. The hit in the sample space with the smallest distance to the first is then selected, and the sample space recalculated for this hit. This process continues until the list of hits becomes large enough, at which point the helical circle in the x, y plane is conformally mapped to a line in the x', y' plane, and hits are chosen from the sample spaces of the previous fit by selecting the hits which fit a line to the previously selected points with the smallest χ 2 . Track finding terminates when the innermost layer has been reached or no hit in the sample space fits those previously selected to an acceptable χ 2 . Again, a hit on the outermost layer is selected and the process repeats until no assignable hits remain. The algorithm proved to be very efficient on artificial diagnostic events, such as one hundred muons scattered at momenta of 1 GeV/c to 10 GeV/c. Unfortunately, when tracking simulated events corresponding to actual physics, the track finder's efficiency decreased drastically (mostly due to signal noise), though future data cleaning programs could noticeably increase its efficiency on these events

  13. A Global Moving Hotspot Reference Frame: How well it fits?

    Science.gov (United States)

    Doubrovine, P. V.; Steinberger, B.; Torsvik, T. H.

    2010-12-01

    Since the early 1970s, when Jason Morgan proposed that hotspot tracks record motion of lithosphere over deep-seated mantle plumes, the concept of fixed hotspots has dominated the way we think about absolute plate reconstructions. In the last decade, with compelling evidence for southward drift of the Hawaiian hotspot from paleomagnetic studies, and for the relative motion between the Pacific and Indo-Atlantic hotspots from refined plate circuit reconstructions, the perception changed and a global moving hotspot reference frame (GMHRF) was introduced, in which numerical models of mantle convection and advection of plume conduits in the mantle flow were used to estimate hotspot motion. This reference frame showed qualitatively better performance in fitting hotspot tracks globally, but the error analysis and formal estimates of the goodness of fitted rotations were lacking in this model. Here we present a new generation of the GMHRF, in which updated plate circuit reconstructions and radiometric age data from the hotspot tracks were combined with numerical models of plume motion, and uncertainties of absolute plate rotations were estimated through spherical regression analysis. The overall quality of fit was evaluated using a formal statistical test, by comparing misfits produced by the model with uncertainties assigned to the data. Alternative plate circuit models linking the Pacific plate to the plates of Indo-Atlantic hemisphere were tested and compared to the fixed hotspot models with identical error budgets. Our results show that, with an appropriate choice of the Pacific plate circuit, it is possible to reconcile relative plate motions and modeled motions of mantle plumes globally back to Late Cretaceous time (80 Ma). In contrast, all fixed hotspot models failed to produce acceptable fits for Paleogene to Late Cretaceous time (30-80 Ma), highlighting significance of relative motion between the Pacific and Indo-Atlantic hotspots during this interval. The

  14. Nonlinear Filtering with IMM Algorithm for Ultra-Tight GPS/INS Integration

    Directory of Open Access Journals (Sweden)

    Dah-Jing Jwo

    2013-05-01

    Full Text Available Abstract This paper conducts a performance evaluation for the ultra-tight integration of a Global positioning system (GPS and an inertial navigation system (INS, using nonlinear filtering approaches with an interacting multiple model (IMM algorithm. An ultra-tight GPS/INS architecture involves the integration of in-phase and quadrature components from the correlator of a GPS receiver with INS data. An unscented Kalman filter (UKF, which employs a set of sigma points by deterministic sampling, avoids the error caused by linearization as in an extended Kalman filter (EKF. Based on the filter structural adaptation for describing various dynamic behaviours, the IMM nonlinear filtering provides an alternative for designing the adaptive filter in the ultra-tight GPS/INS integration. The use of IMM enables tuning of an appropriate value for the process of noise covariance so as to maintain good estimation accuracy and tracking capability. Two examples are provided to illustrate the effectiveness of the design and demonstrate the effective improvement in navigation estimation accuracy. A performance comparison among various filtering methods for ultra-tight integration of GPS and INS is also presented. The IMM based nonlinear filtering approach demonstrates the effectiveness of the algorithm for improved positioning performance.

  15. Research on Key Technologies of Network Centric System Distributed Target Track Fusion

    Directory of Open Access Journals (Sweden)

    Yi Mao

    2017-01-01

    Full Text Available To realize common tactical picture in network-centered system, this paper proposes a layered architecture for distributed information processing and a method for distributed track fusion on the basis of analyzing the characteristics of network-centered systems. Basing on the noncorrelation of three-dimensional measurement of surveillance and reconnaissance sensors under polar coordinates, it also puts forward an algorithm for evaluating track quality (TQ using statistical decision theory. According to simulation results, the TQ value is associated with the measurement accuracy of sensors and the motion state of targets, which is well matched with the convergence process of tracking filters. Besides, the proposed algorithm has good reliability and timeliness in track quality evaluation.

  16. Scanning electron microscope investigations of nuclear pore filters in polyester foils

    International Nuclear Information System (INIS)

    Hopfe, J.

    1980-01-01

    In order to understand and characterize the action of nuclear pore filters it is necessary to know their surface, as well as their bulk, structure. In the present work, investigations of the surface structure (pore size, pore density, pore distribution) and of the pore geometry, especially in the bulk of the filters, are carried out by scanning electron microscopic (SEM) studies. The preparation technique needed is liquid-nitrogen freeze-fracturing followed by a conductive-coating step. Nuclear pore filters studied in this paper were produced by a track etching technique. Laboratory specimens were obtained by bombarding 10 μm thick polyester foils with Xe-ions and a subsequent etching with 20% NaOH. The SEM results are shown and discussed. (author)

  17. Real-Time Radar-Based Tracking and State Estimation of Multiple Non-Conformant Aircraft

    Science.gov (United States)

    Cook, Brandon; Arnett, Timothy; Macmann, Owen; Kumar, Manish

    2017-01-01

    In this study, a novel solution for automated tracking of multiple unknown aircraft is proposed. Many current methods use transponders to self-report state information and augment track identification. While conformant aircraft typically report transponder information to alert surrounding aircraft of its state, vehicles may exist in the airspace that are non-compliant and need to be accurately tracked using alternative methods. In this study, a multi-agent tracking solution is presented that solely utilizes primary surveillance radar data to estimate aircraft state information. Main research challenges include state estimation, track management, data association, and establishing persistent track validity. In an effort to realize these challenges, techniques such as Maximum a Posteriori estimation, Kalman filtering, degree of membership data association, and Nearest Neighbor Spanning Tree clustering are implemented for this application.

  18. Model Adaptation for Prognostics in a Particle Filtering Framework

    Directory of Open Access Journals (Sweden)

    Bhaskar Saha

    2011-01-01

    Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  19. Comparison of three filters in asteroid-based autonomous navigation

    International Nuclear Information System (INIS)

    Cui Wen; Zhu Kai-Jian

    2014-01-01

    At present, optical autonomous navigation has become a key technology in deep space exploration programs. Recent studies focus on the problem of orbit determination using autonomous navigation, and the choice of filter is one of the main issues. To prepare for a possible exploration mission to Mars, the primary emphasis of this paper is to evaluate the capability of three filters, the extended Kalman filter (EKF), unscented Kalman filter (UKF) and weighted least-squares (WLS) algorithm, which have different initial states during the cruise phase. One initial state is assumed to have high accuracy with the support of ground tracking when autonomous navigation is operating; for the other state, errors are set to be large without this support. In addition, the method of selecting asteroids that can be used for navigation from known lists of asteroids to form a sequence is also presented in this study. The simulation results show that WLS and UKF should be the first choice for optical autonomous navigation during the cruise phase to Mars

  20. Model Adaptation for Prognostics in a Particle Filtering Framework

    Science.gov (United States)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  1. Do Fitness Apps Need Text Reminders? An Experiment Testing Goal-Setting Text Message Reminders to Promote Self-Monitoring.

    Science.gov (United States)

    Liu, Shuang; Willoughby, Jessica F

    2018-01-01

    Fitness tracking apps have the potential to change unhealthy lifestyles, but users' lack of compliance is an issue. The current intervention examined the effectiveness of using goal-setting theory-based text message reminders to promote tracking activities on fitness apps. We conducted a 2-week experiment with pre- and post-tests with young adults (n = 50). Participants were randomly assigned to two groups-a goal-setting text message reminder group and a generic text message reminder group. Participants were asked to use a fitness tracking app to log physical activity and diet for the duration of the study. Participants who received goal-setting reminders logged significantly more physical activities than those who only received generic reminders. Further, participants who received goal-setting reminders liked the messages and showed significantly increased self-efficacy, awareness of personal goals, motivation, and intention to use the app. The study shows that incorporating goal-setting theory-based text message reminders can be useful to boost user compliance with self-monitoring fitness apps by reinforcing users' personal goals and enhancing cognitive factors associated with health behavior change.

  2. AUV-Based Plume Tracking: A Simulation Study

    Directory of Open Access Journals (Sweden)

    Awantha Jayasiri

    2016-01-01

    Full Text Available This paper presents a simulation study of an autonomous underwater vehicle (AUV navigation system operating in a GPS-denied environment. The AUV navigation method makes use of underwater transponder positioning and requires only one transponder. A multirate unscented Kalman filter is used to determine the AUV orientation and position by fusing high-rate sensor data and low-rate information. The paper also proposes a gradient-based, efficient, and adaptive novel algorithm for plume boundary tracking missions. The algorithm follows a centralized approach and it includes path optimization features based on gradient information. The proposed algorithm is implemented in simulation on the AUV-based navigation system and successful boundary tracking results are obtained.

  3. Time-based Cellular Automaton track finder for the CBM experiment

    International Nuclear Information System (INIS)

    Akishina, Valentina; Kisel, Ivan

    2015-01-01

    The future heavy-ion experiment CBM (FAIR/GSI, Darmstadt, Germany) will focus on the measurement of rare probes at interaction rates up to 10 MHz with data flow of up to 1 TB/s. The beam will provide free stream of particles without bunch structure. That requires full online event reconstruction and selection not only in space, but also in time, so- called 4D event building and selection. This is a task of the First-Level Event Selection (FLES) package. The FLES reconstruction and selection package consists of several modules: track finding, track fitting, short-lived particles finding, event building and event selection. The input data are distributed within the FLES farm in a form of so-called time-slices, in which time length is proportional to a compute power of a processing node. A time-slice is reconstructed in parallel between cores within a CPU, thus minimising communication between CPUs. After all tracks of the whole time-slice are found and fitted, they are collected into clusters of tracks originated from common primary vertices. After that short-lived particles are found and the full event building process is finished. (paper)

  4. Front-end Intelligence for triggering and local track recognition in Gas Pixel Detectors

    CERN Document Server

    Hessey, NP; The ATLAS collaboration; van der Graaf, H; Vermeulen, J; Jansweijer, P; Romaniouk, A

    2012-01-01

    The combination of gaseous detectors with pixel readout chips gives unprecedented hit resolution (improving from O(100 um) for wire chambers to 10 um), as well as high-rate capability, low radiation length and giving in addition angular information on the local track. These devices measure individually every electron liberated by the passage of a charged particle, leading to a large quantity of data to be read out. Typically an external trigger is used to start the read-out. We are investigating the addition of local intelligence to the pixel read-out chip. A first level of processing detects the passage of a particle through the gas volume, and accurately determines the time of passage. A second level measures in an approximate but fast way the tilt-angle of the track. This can be used to trigger a third stage in which all hits associated to the track are processed locally to give a least-squares-fit to the track. The chip can then send out just the fitted track parameters instead of the individual electron ...

  5. Neural network fusion capabilities for efficient implementation of tracking algorithms

    Science.gov (United States)

    Sundareshan, Malur K.; Amoozegar, Farid

    1997-03-01

    The ability to efficiently fuse information of different forms to facilitate intelligent decision making is one of the major capabilities of trained multilayer neural networks that is now being recognized. While development of innovative adaptive control algorithms for nonlinear dynamical plants that attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. We describe the capabilities and functionality of neural network algorithms for data fusion and implementation of tracking filters. To discuss details and to serve as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target- tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The innovation lies in the way the fusion of multisensor data is accomplished to facilitate improved estimation without increasing the computational complexity of the dynamical state estimator itself.

  6. Air alpha monitoring device and system for the calibration of the track detectors

    International Nuclear Information System (INIS)

    Danis, A; Oncescu, M.; Ciubotariu, M.

    2001-01-01

    The radon measurement plays a critical role: - in monitoring the human health and safety, due to radon destructive health effects. Sustained exposures of humans to high concentration of radon, in fact to high concentrations of its decay products, can produce lung cancer; - in a variety of geophysical, geochemical, hydrological and atmospheric investigations, such as exploring resources of uranium or hydrocarbons. The transport of radon within the earth, waters and atmosphere makes it a useful tracer in these purposes. in both cases, the reliable long-term measurements are required because usual short-term variations in concentration need to be averaged. These variations are caused by factors such as relative humidity, temperature, atmospheric pressure and their seasonal variations, moisture content in the air, or ventilation in the dwelling or working places. The integrating measurement methods meet these requirements. Among them, the alpha track method is one of the adequate and useful method and it is used by authors in radon measurements in dwelling and working places including mines and house cellars. The best etched track alpha detector for radon measurements proved to be the detector CR-39 due to: - its sensitivity to alpha particles emitted by radon decay products; - its stability against various environmental factors; - its high degree of optical clarity, was used in a proper device for alpha monitoring in air. Its calibration for radon measurements was performed in the proper calibration system. The general descriptions and specifications were given previously. Only some characteristics of these devices are given here. For air alpha monitoring device: i) equipped with filter, during alpha exposure, the alpha particles of radon are registered in the etched track detector mounted inside (ρ Rn - track density); ii) without filter, the alpha particles emitted by radon + its alpha decay products/their aerosols are registered in the detector (ρ tot - track

  7. FILTER-INDUCED BIAS IN Lyα EMITTER SURVEYS: A COMPARISON BETWEEN STANDARD AND TUNABLE FILTERS. GRAN TELESCOPIO CANARIAS PRELIMINARY RESULTS

    Energy Technology Data Exchange (ETDEWEB)

    De Diego, J. A.; De Leo, M. A. [Instituto de Astronomía, Universidad Nacional Autónoma de México Avenida Universidad 3000, Ciudad Universitaria, C.P. 04510, Distrito Federal (Mexico); Cepa, J.; Bongiovanni, A. [Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife (Spain); Verdugo, T. [Centro de Investigaciones de Astronomía (CIDA), Apartado Postal 264, Mérida 5101-A (Venezuela, Bolivarian Republic of); Sánchez-Portal, M. [Herschel Science Centre (HSC), European Space Agency Centre (ESAC)/INSA, Villanueva de la Cañada, Madrid (Spain); González-Serrano, J. I., E-mail: jdo@astro.unam.mx [Instituto de Física de Cantabria (CSIC-Universidad de Cantabria), E-39005 Santander (Spain)

    2013-10-01

    Lyα emitter (LAE) surveys have successfully used the excess in a narrowband filter compared to a nearby broadband image to find candidates. However, the odd spectral energy distribution (SED) of LAEs combined with the instrumental profile has important effects on the properties of the candidate samples extracted from these surveys. We investigate the effect of the bandpass width and the transmission profile of the narrowband filters used for extracting LAE candidates at redshifts z ≅ 6.5 through Monte Carlo simulations, and we present pilot observations to test the performance of tunable filters to find LAEs and other emission-line candidates. We compare the samples obtained using a narrow ideal rectangular filter, the Subaru NB921 narrowband filter, and sweeping across a wavelength range using the ultra-narrow-band tunable filters of the instrument OSIRIS, installed at the 10.4 m Gran Telescopio Canarias. We use this instrument for extracting LAE candidates from a small set of real observations. Broadband data from the Subaru, Hubble Space Telescope, and Spitzer databases were used for fitting SEDs to calculate photometric redshifts and to identify interlopers. Narrowband surveys are very efficient in finding LAEs in large sky areas, but the samples obtained are not evenly distributed in redshift along the filter bandpass, and the number of LAEs with equivalent widths <60 Å can be underestimated. These biased results do not appear in samples obtained using ultra-narrow-band tunable filters. However, the field size of tunable filters is restricted because of the variation of the effective wavelength across the image. Thus, narrowband and ultra-narrow-band surveys are complementary strategies to investigate high-redshift LAEs.

  8. FILTER-INDUCED BIAS IN Lyα EMITTER SURVEYS: A COMPARISON BETWEEN STANDARD AND TUNABLE FILTERS. GRAN TELESCOPIO CANARIAS PRELIMINARY RESULTS

    International Nuclear Information System (INIS)

    De Diego, J. A.; De Leo, M. A.; Cepa, J.; Bongiovanni, A.; Verdugo, T.; Sánchez-Portal, M.; González-Serrano, J. I.

    2013-01-01

    Lyα emitter (LAE) surveys have successfully used the excess in a narrowband filter compared to a nearby broadband image to find candidates. However, the odd spectral energy distribution (SED) of LAEs combined with the instrumental profile has important effects on the properties of the candidate samples extracted from these surveys. We investigate the effect of the bandpass width and the transmission profile of the narrowband filters used for extracting LAE candidates at redshifts z ≅ 6.5 through Monte Carlo simulations, and we present pilot observations to test the performance of tunable filters to find LAEs and other emission-line candidates. We compare the samples obtained using a narrow ideal rectangular filter, the Subaru NB921 narrowband filter, and sweeping across a wavelength range using the ultra-narrow-band tunable filters of the instrument OSIRIS, installed at the 10.4 m Gran Telescopio Canarias. We use this instrument for extracting LAE candidates from a small set of real observations. Broadband data from the Subaru, Hubble Space Telescope, and Spitzer databases were used for fitting SEDs to calculate photometric redshifts and to identify interlopers. Narrowband surveys are very efficient in finding LAEs in large sky areas, but the samples obtained are not evenly distributed in redshift along the filter bandpass, and the number of LAEs with equivalent widths <60 Å can be underestimated. These biased results do not appear in samples obtained using ultra-narrow-band tunable filters. However, the field size of tunable filters is restricted because of the variation of the effective wavelength across the image. Thus, narrowband and ultra-narrow-band surveys are complementary strategies to investigate high-redshift LAEs

  9. Comparative investigation into Viterbi based and multiple hypothesis based track stitching

    CSIR Research Space (South Africa)

    Van der Merwe, LJ

    2016-12-01

    Full Text Available . A sequential Viterbi data association algorithm is then used to solve the trellis and associate track fragments with each other. A Kalman filter is used to determine the possible associations as well as the probabilities of the associations between...

  10. Tuning of Human Modulation Filters Is Carrier-Frequency Dependent

    Science.gov (United States)

    Simpson, Andrew J. R.; Reiss, Joshua D.; McAlpine, David

    2013-01-01

    Recent studies employing speech stimuli to investigate ‘cocktail-party’ listening have focused on entrainment of cortical activity to modulations at syllabic (5 Hz) and phonemic (20 Hz) rates. The data suggest that cortical modulation filters (CMFs) are dependent on the sound-frequency channel in which modulations are conveyed, potentially underpinning a strategy for separating speech from background noise. Here, we characterize modulation filters in human listeners using a novel behavioral method. Within an ‘inverted’ adaptive forced-choice increment detection task, listening level was varied whilst contrast was held constant for ramped increments with effective modulation rates between 0.5 and 33 Hz. Our data suggest that modulation filters are tonotopically organized (i.e., vary along the primary, frequency-organized, dimension). This suggests that the human auditory system is optimized to track rapid (phonemic) modulations at high sound-frequencies and slow (prosodic/syllabic) modulations at low frequencies. PMID:24009759

  11. ATLAS Fast Tracker Status and Tracking at High luminosity LHC

    CERN Document Server

    Ilic, Nikolina; The ATLAS collaboration

    2018-01-01

    The LHC’s increase in centre of mass energy and luminosity in 2015 makes controlling trigger rates with high efficiency challenging. The ATLAS Fast TracKer (FTK) is a hardware processor built to reconstruct tracks at a rate of up to 100 kHz and provide them to the high level trigger. The FTK reconstructs tracks by matching incoming detector hits with pre-defined track patterns stored in associative memory on custom ASICs. Inner detector hits are fit to these track patterns using modern FPGAs. This talk describes the electronics system used for the FTK’s massive parallelization. The installation, commissioning and running of the system is happening in 2016, and is detailed in this talk. Tracking at High luminosity LHC is also presented.

  12. An adaptive compensation algorithm for temperature drift of micro-electro-mechanical systems gyroscopes using a strong tracking Kalman filter.

    Science.gov (United States)

    Feng, Yibo; Li, Xisheng; Zhang, Xiaojuan

    2015-05-13

    We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF), the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to -2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation.

  13. An Adaptive Compensation Algorithm for Temperature Drift of Micro-Electro-Mechanical Systems Gyroscopes Using a Strong Tracking Kalman Filter

    Directory of Open Access Journals (Sweden)

    Yibo Feng

    2015-05-01

    Full Text Available We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF, the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to −2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation.

  14. An experimental test of fitness variation across a hydrologic gradient predicts willow and poplar species distributions.

    Science.gov (United States)

    Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine

    2017-05-01

    Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values

  15. Location detection and tracking of moving targets by a 2D IR-UWB radar system.

    Science.gov (United States)

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-03-19

    In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.

  16. Robust tracking and distributed synchronization control of a multi-motor servomechanism with H-infinity performance.

    Science.gov (United States)

    Wang, Minlin; Ren, Xuemei; Chen, Qiang

    2018-01-01

    The multi-motor servomechanism (MMS) is a multi-variable, high coupling and nonlinear system, which makes the controller design challenging. In this paper, an adaptive robust H-infinity control scheme is proposed to achieve both the load tracking and multi-motor synchronization of MMS. This control scheme consists of two parts: a robust tracking controller and a distributed synchronization controller. The robust tracking controller is constructed by incorporating a neural network (NN) K-filter observer into the dynamic surface control, while the distributed synchronization controller is designed by combining the mean deviation coupling control strategy with the distributed technique. The proposed control scheme has several merits: 1) by using the mean deviation coupling synchronization control strategy, the tracking controller and the synchronization controller can be designed individually without any coupling problem; 2) the immeasurable states and unknown nonlinearities are handled by a NN K-filter observer, where the number of NN weights is largely reduced by using the minimal learning parameter technique; 3) the H-infinity performances of tracking error and synchronization error are guaranteed by introducing a robust term into the tracking controller and the synchronization controller, respectively. The stabilities of the tracking and synchronization control systems are analyzed by the Lyapunov theory. Simulation and experimental results based on a four-motor servomechanism are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  17. In Defense of Sparse Tracking: Circulant Sparse Tracker

    KAUST Repository

    Zhang, Tianzhu; Bibi, Adel Aamer; Ghanem, Bernard

    2016-01-01

    Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers have high computational cost, less than promising tracking performance, and limited feature representation. To deal with the above issues, we propose a novel circulant sparse tracker (CST), which exploits circulant target templates. Because of the circulant structure property, CST has the following advantages: (1) It can refine and reduce particles using circular shifts of target templates. (2) The optimization can be efficiently solved entirely in the Fourier domain. (3) High dimensional features can be embedded into CST to significantly improve tracking performance without sacrificing much computation time. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that CST performs better than all other sparse trackers and favorably against state-of-the-art methods.

  18. In Defense of Sparse Tracking: Circulant Sparse Tracker

    KAUST Repository

    Zhang, Tianzhu

    2016-12-13

    Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers have high computational cost, less than promising tracking performance, and limited feature representation. To deal with the above issues, we propose a novel circulant sparse tracker (CST), which exploits circulant target templates. Because of the circulant structure property, CST has the following advantages: (1) It can refine and reduce particles using circular shifts of target templates. (2) The optimization can be efficiently solved entirely in the Fourier domain. (3) High dimensional features can be embedded into CST to significantly improve tracking performance without sacrificing much computation time. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that CST performs better than all other sparse trackers and favorably against state-of-the-art methods.

  19. Track Irregularity Time Series Analysis and Trend Forecasting

    Directory of Open Access Journals (Sweden)

    Jia Chaolong

    2012-01-01

    Full Text Available The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM (1,1 is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.

  20. On the compensating filter in pulmonary hilar tomography

    International Nuclear Information System (INIS)

    Okayama, Akio; Nakanishi, Takashi; Fujikawa, Tsuyoshi

    1980-01-01

    It is difficult to make the optimal density for all area of the pulmonary hilar region on a same film in conventional tomography. But, it is possible to observe all area of the pulmonary hilar region on a same film by equalizing the uneven density of pulmonary hilar region with compensating filter. On this study, the filter which could compensated density in all shifts of Polytome U was constructed and discussed about diagnostic evaluation for those shifts. As a results, by using this filter, the density for all area of the pulmonary hilar region in all shifts of Polytome U could be compensated and grasp the mutral relation of its region. As a conclusion, using this filter is useful method to diagnose pulmonary hilar region. If it is possible to make a patient enough hold a breath, using circular shift is better than other's. If it is difficult to do so, it can not help using linear shift. In such a case, it shall be taken a tomograph in direction of linear shift fitting the object. (author)