Two-Layer Particle Filter for Multiple Target Detection and Tracking

The detection and tracking of an unknown number of targets using a Bayesian hierarchical model with target labels is presented. To approximate the posterior probability density function (PDF), we develop a two-layer particle filter (PF). One deals with track initiation, and the other deals with track maintenance. In addition the parallel partition (PP) method is proposed to sample the states of the surviving targets.

[1]  J. Hammersley SIMULATION AND THE MONTE CARLO METHOD , 1982 .

[2]  William Fitzgerald,et al.  A Bayesian approach to tracking multiple targets using sensor arrays and particle filters , 2002, IEEE Trans. Signal Process..

[3]  Robin J. Evans,et al.  Integrated probabilistic data association , 1994, IEEE Trans. Autom. Control..

[4]  P. Green,et al.  Trans-dimensional Markov chain Monte Carlo , 2000 .

[5]  Henk A. P. Blom,et al.  Permutation invariance in Bayesian estimation of two targets that maneuver in and out formation flight , 2009, 2009 12th International Conference on Information Fusion.

[6]  Alfred O. Hero,et al.  An Information-Based Approach to Sensor Management in Large Dynamic Networks , 2007, Proceedings of the IEEE.

[7]  Ángel F. García-Fernández,et al.  Particle filter for extracting target label information when targets move in close proximity , 2011, 14th International Conference on Information Fusion.

[8]  Yan Lin,et al.  Particle labeling PHD filter for multi-target track-valued estimates , 2011, 14th International Conference on Information Fusion.

[9]  Chee-Yee Chong,et al.  Point process formalism for multiple target tracking , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[10]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[11]  S. Shankar Sastry,et al.  Markov Chain Monte Carlo Data Association for Multi-Target Tracking , 2009, IEEE Transactions on Automatic Control.

[12]  W. Blair,et al.  Unresolved Rayleigh target detection using monopulse measurements , 1998 .

[13]  Jianyu Yang,et al.  An efficient particle filter for multi-target tracking using an independence assumption , 2012, 2012 15th International Conference on Information Fusion.

[14]  Samuel J. Davey,et al.  A Comparison of Detection Performance for Several Track-before-Detect Algorithms , 2008, 2008 11th International Conference on Information Fusion.

[15]  Jouko Lampinen,et al.  Rao-Blackwellized particle filter for multiple target tracking , 2007, Inf. Fusion.

[16]  Donald B. Rubin,et al.  Comment : A noniterative sampling/importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest : The SIR Algorithm , 1987 .

[17]  S. Godsill,et al.  Monte Carlo filtering for multi target tracking and data association , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[18]  S. Wittevrongel,et al.  Queueing Systems , 2019, Introduction to Stochastic Processes and Simulation.

[19]  Branko Ristic,et al.  Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[20]  J. Huang,et al.  Curse of dimensionality and particle filters , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[21]  A. Hero,et al.  Multitarget tracking using the joint multitarget probability density , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[22]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[23]  M. Vihola Rao-blackwellised particle filtering in random set multitarget tracking , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[24]  Jesus Grajal,et al.  Sequential multiple target detection using particle filters , 2011, 2011 IEEE Statistical Signal Processing Workshop (SSP).

[25]  Darryl Morrell,et al.  Sequential Monte Carlo Methods for Tracking Multiple Targets With Deterministic and Stochastic Constraints , 2008, IEEE Transactions on Signal Processing.

[26]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[27]  R.P.S. Mahler,et al.  "Statistics 101" for multisensor, multitarget data fusion , 2004, IEEE Aerospace and Electronic Systems Magazine.

[28]  J. Vermaak,et al.  A unifying framework for multi-target tracking and existence , 2005, 2005 7th International Conference on Information Fusion.

[29]  S. Mori,et al.  Tracking and classifying multiple targets without a priori identification , 1986 .

[30]  Ba-Ngu Vo,et al.  Tracking an unknown time-varying number of speakers using TDOA measurements: a random finite set approach , 2006, IEEE Transactions on Signal Processing.

[31]  Alfred O. Hero,et al.  Joint Multi-Target Particle Filtering , 2008 .

[32]  Ba-Ngu Vo,et al.  On performance evaluation of multi-object filters , 2008, 2008 11th International Conference on Information Fusion.

[33]  Ba-Ngu Vo,et al.  A Consistent Metric for Performance Evaluation of Multi-Object Filters , 2008, IEEE Transactions on Signal Processing.

[34]  D. Cotter,et al.  Ultra-high-bit-rate networking: from the transcontinental backbone to the desktop , 1997, IEEE Commun. Mag..

[35]  Mark R. Morelande,et al.  A Bayesian Approach to Multiple Target Detection and Tracking , 2007, IEEE Transactions on Signal Processing.

[36]  Xiaodong Wang,et al.  Joint multiple target tracking and classification in collaborative sensor networks , 2004, ISIT.

[37]  A. Doucet,et al.  Particle filtering for partially observed Gaussian state space models , 2002 .

[38]  M. Pitt,et al.  Filtering via Simulation: Auxiliary Particle Filters , 1999 .

[39]  G. Fernández,et al.  Detection and tracking of multiple targets using wireless sensor networks - Detección y seguimiento de múltiples blancos en redes inalámbricas de sensores , 2011 .

[40]  P. Pérez,et al.  Tracking multiple objects with particle filtering , 2002 .

[41]  R. Mahler Multitarget Bayes filtering via first-order multitarget moments , 2003 .

[42]  Pramod K. Varshney,et al.  Performance Analysis of Distributed Detection in a Random Sensor Field , 2008, IEEE Transactions on Signal Processing.

[43]  D. Rubin,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[44]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .

[45]  B. Sklar,et al.  Rayleigh fading channels in mobile digital communication systems Part I: Characterization , 1997, IEEE Commun. Mag..

[46]  Christophe Andrieu,et al.  Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC , 1999, IEEE Trans. Signal Process..

[47]  P. Green Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .

[48]  Mark R. Morelande Tracking multiple targets with a sensor network , 2006, 2006 9th International Conference on Information Fusion.

[49]  Hans Driessen,et al.  Mixed Labelling in Multitarget Particle Filtering , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[50]  Ángel F. García-Fernández,et al.  Multitarget tracking using the Joint Multitrack Probability Density , 2009, 2009 12th International Conference on Information Fusion.

[51]  David Suter,et al.  Joint Detection and Estimation of Multiple Objects From Image Observations , 2010, IEEE Transactions on Signal Processing.

[52]  Volkan Cevher,et al.  General direction-of-arrival tracking with acoustic nodes , 2005, IEEE Transactions on Signal Processing.

[53]  Y. Boers,et al.  Multitarget particle filter track before detect application , 2004 .

[54]  M. Fallon,et al.  Multi Target Acoustic Source Tracking with an Unknown and Time Varying Number of Targets , 2008, 2008 Hands-Free Speech Communication and Microphone Arrays.

[55]  Yaakov Bar-Shalom,et al.  Sonar tracking of multiple targets using joint probabilistic data association , 1983 .

[56]  Ronald P. S. Mahler,et al.  Statistical Multisource-Multitarget Information Fusion , 2007 .