Multiple target tracking with Gaussian mixture PHD filter using passive acoustic Doppler-only measurements

In this paper, we present the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple ground targets using a passive acoustic-sensor network. For this purpose, an experimental setup consisting of a network of microphones and a loudspeaker was prepared. Non-cooperative transmissions from a loudspeaker (i.e. illuminator of opportunity) are exploited by non-directional separately located microphones (i.e. Doppler measuring sensors). Experimental proof-of-concept study results show that it is possible to track multiple ground targets using only Doppler shift measurements in a passive multi-static scenario.

[1]  Walter R. Fried Principles and Performance Analysis of Doppler Navigation Systems , 1957, IRE Transactions on Aeronautical and Navigational Electronics.

[2]  Jin Jiang,et al.  Time-frequency feature representation using energy concentration: An overview of recent advances , 2009, Digit. Signal Process..

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

[4]  LJubisa Stankovic,et al.  An algorithm for the Wigner distribution based instantaneous frequency estimation in a high noise environment , 2004, Signal Process..

[5]  Sumeetpal S. Singh,et al.  Sequential monte carlo implementation of the phd filter for multi-target tracking , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[6]  Hongbo Sun,et al.  Passive radar using Global System for Mobile communication signal: theory, implementation and measurements , 2005 .

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

[8]  Ba-Ngu Vo,et al.  Improved SMC implementation of the PHD filter , 2010, 2010 13th International Conference on Information Fusion.

[9]  Fredrik Gustafsson,et al.  Ground multiple target tracking with a network of acoustic sensor arrays using PHD and CPHD filters , 2011, 14th International Conference on Information Fusion.

[10]  H. Griffiths,et al.  Passive coherent location radar systems. Part 1: performance prediction , 2005 .

[11]  Adrian N. Bishop,et al.  Remarks on the Cramer-Rao inequality for Doppler-based target parameter estimation , 2010, 2010 Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[12]  Jeremie Houssineau,et al.  Passive multi target tracking with GM-PHD filter , 2010, 2010 13th International Conference on Information Fusion.

[13]  Ba-Ngu Vo,et al.  Analytic Implementations of the Cardinalized Probability Hypothesis Density Filter , 2007, IEEE Transactions on Signal Processing.

[14]  Ba-Ngu Vo,et al.  GM-PHD filter multitarget tracking in sonar images , 2006, SPIE Defense + Commercial Sensing.

[15]  Daniel E. Clark,et al.  Convergence results for the particle PHD filter , 2006, IEEE Transactions on Signal Processing.

[16]  Fredrik Gustafsson,et al.  Gaussian mixture PHD filter for multi-target tracking using passive Doppler-only measurements , 2012 .

[17]  Anthony J. Weiss,et al.  Localization of Narrowband Radio Emitters Based on Doppler Frequency Shifts , 2008, IEEE Transactions on Signal Processing.

[18]  Ronald Mahler The multisensor PHD filter: II. Erroneous solution via Poisson magic , 2009, Defense + Commercial Sensing.

[19]  L.R. Malling Radio Doppler Effect for Aircraft Speed Measurements , 1947, Proceedings of the IRE.

[20]  Peter Willett,et al.  GMTI Tracking via the Gaussian Mixture Cardinalized Probability Hypothesis Density Filter , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[21]  Sheldon N. Salinger,et al.  Application of Recursive Estimation and Kalman Filtering to Doppler Tracking , 1970, IEEE Transactions on Aerospace and Electronic Systems.

[22]  Thiagalingam Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation , 2001 .

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

[24]  Martina Daun,et al.  Tracking in multistatic passive radar systems using DAB/DVB-T illumination , 2012, Signal Process..

[25]  Brian D. O. Anderson,et al.  Analysis of target velocity and position estimation via doppler-shift measurements , 2011, 2011 Australian Control Conference.

[26]  P. Wei,et al.  Observability and Performance Analysis of Bi/Multi-Static Doppler-Only Radar , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[27]  D. Torney,et al.  Localization and Observability of Aircraft via Doppler Shifts , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[28]  Ronald P. S. Mahler The multisensor PHD filter: I. General solution via multitarget calculus , 2009, Defense + Commercial Sensing.

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

[30]  Hui Guo,et al.  Passive bistatic WiMAX radar for marine surveillance , 2010, 2010 IEEE Radar Conference.

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