Robust Multisensor Multitarget Tracker with Application to Passive Multistatic Radar Tracking

This paper presents a novel approach to multitarget multisensor tracking, based on the combination of a probability hypothesis density (PHD) smoother and hard multisensor multiscan data association (MMDA) used in a feedback connection. The PHD smoother allows to initiate target tracks without resorting to complicated measurement-to-measurement association procedures while the feedback from the hard MMDA, besides providing track labeling, makes the PHD smoother, and hence the overall tracker, more robust to missed detections and false alarms. An application of the proposed tracker to passive multistatic radar tracking is worked out in order to demonstrate its effectiveness in critical situations where the lack of single-sensor observability prevents the use of traditional track initiation methods. As a further contribution, an extension to the multisensor case of the multicommodity approach to multiscan data association, originally presented for the single-sensor case, is provided.

[1]  Giorgio Battistelli,et al.  Multitarget tracking via joint PHD filtering and multiscan association , 2009, 2009 12th International Conference on Information Fusion.

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

[3]  Aubrey B. Poore,et al.  A Lagrangian Relaxation Algorithm for Multidimensional Assignment Problems Arising from Multitarget Tracking , 1993, SIAM J. Optim..

[4]  Giorgio Battistelli,et al.  A feedback approach to multitarget multisensor tracking with application to bearing-only tracking , 2010, 2010 13th International Conference on Information Fusion.

[5]  S. Singh,et al.  Novel data association schemes for the probability hypothesis density filter , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Aaron D. Lanterman,et al.  Techniques for birth-particle placement in the probability hypothesis density particle filter applied to passive radar , 2008 .

[7]  Giorgio Battistelli,et al.  Optimal Flow Models for Multiscan Data Association , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Christian R. Berger,et al.  Track initialization in a multistatic DAB/DVB-T network , 2008, 2008 11th International Conference on Information Fusion.

[9]  Ba-Ngu Vo,et al.  The Gaussian Mixture Probability Hypothesis Density Filter , 2006, IEEE Transactions on Signal Processing.

[10]  Y. Bar-Shalom,et al.  Track labeling and PHD filter for multitarget tracking , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[11]  Evangeline Pollard,et al.  Convoy detection processing by using the hybrid algorithm (GMCPHD/VS-IMMC-MHT) and Dynamic Bayesian Networks , 2009, 2009 12th International Conference on Information Fusion.

[12]  A. Farina,et al.  Multiscan association as a multi-commodity flow optimization problem , 2008, 2008 IEEE Radar Conference.

[13]  Narendra Karmarkar,et al.  A new polynomial-time algorithm for linear programming , 1984, STOC '84.

[14]  I. R. Goodman,et al.  Mathematics of Data Fusion , 1997 .

[15]  Aaron D. Lanterman,et al.  Multitarget tracking using multiple bistatic range measurements with probability hypothesis densities , 2004, SPIE Defense + Commercial Sensing.

[16]  Aubrey B. Poore,et al.  Multidimensional assignment formulation of data association problems arising from multitarget and multisensor tracking , 1994, Comput. Optim. Appl..

[17]  Thiagalingam Kirubarajan,et al.  Passive geolocation and tracking of an unknown number of emitters , 2005, SPIE Defense + Commercial Sensing.

[18]  M.L. Miller,et al.  Optimizing Murty's ranked assignment method , 1997, IEEE Transactions on Aerospace and Electronic Systems.

[19]  B. Vo,et al.  Data Association and Track Management for the Gaussian Mixture Probability Hypothesis Density Filter , 2009, IEEE Transactions on Aerospace and Electronic Systems.

[20]  Y. Bar-Shalom,et al.  Probability hypothesis density filter for multitarget multisensor tracking , 2005, 2005 7th International Conference on Information Fusion.

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

[22]  M.L. Miller,et al.  A comparison of two algorithms for determining ranked assignments with application to multitarget tracking and motion correspondence , 1997, IEEE Transactions on Aerospace and Electronic Systems.

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

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

[25]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[26]  A. Farina,et al.  Tracking function in bistatic and multistatic radar systems , 1986 .

[27]  R. Mahler,et al.  PHD filters of higher order in target number , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[28]  W. Koch,et al.  Multistatic target tracking for non-cooperative illumination by DAB/DVB-T , 2008, 2008 IEEE Radar Conference.

[29]  Peter Willett,et al.  The Bin-Occupancy Filter and Its Connection to the PHD Filters , 2009, IEEE Transactions on Signal Processing.

[30]  A. Doucet,et al.  Sequential Monte Carlo methods for multitarget filtering with random finite sets , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[31]  Ali Onder Bozdogan,et al.  Multistatic tracking using bistatic range - Range rate measurements , 2009, 2009 12th International Conference on Information Fusion.

[32]  Aaron D. Lanterman,et al.  Probability hypothesis density-based multitarget tracking with bistatic range and Doppler observations , 2005 .

[33]  Krzysztof S. Kulpa,et al.  Two-stage tracking algorithm for passive radar , 2009, 2009 12th International Conference on Information Fusion.

[34]  Yakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .

[35]  Nikolaos K. Uzunoglu,et al.  Solving the association problem for a multistatic range-only radar target tracker , 2008, Signal Process..

[36]  Y. Bar-Shalom,et al.  A generalized S-D assignment algorithm for multisensor-multitarget state estimation , 1997, IEEE Transactions on Aerospace and Electronic Systems.