Doppler-bearing passive tracking using Gaussian mixture probability hypothesis density filter

Passive tracking is a popular research topic in data fusion domain because of its good hidden nature. But the traditional bearings-only tracking (BOT) is limited by its poor observability. This paper introduces Doppler frequency measurement to passive tracking and the corresponding filtering formulation is proposed. Moreover, we present a solution to multi-target tracking based on the Gaussian mixture probability hypothesis density (GM-PHD) filter jointly using the frequency and bearing measurements. The application of the discussed approach in simulation proves its effectiveness and practicability.

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

[2]  Thia Kirubarajan,et al.  Track Quality Based Multitarget Tracking Approach for Global Nearest-Neighbor Association , 2012, IEEE Transactions on Aerospace and Electronic Systems.

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

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

[5]  Chee-Yee Chong,et al.  Evaluating a multiple-hypothesis multitarget tracking algorithm , 1994 .

[6]  Y. Bar-Shalom,et al.  The probabilistic data association filter , 2009, IEEE Control Systems.

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

[8]  K. Gong,et al.  Fundamental properties and performance of conventional bearings-only target motion analysis , 1984 .

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

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

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

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

[13]  K. C. Ho,et al.  An asymptotically unbiased estimator for bearings-only and Doppler-bearing target motion analysis , 2006, IEEE Transactions on Signal Processing.

[14]  Keinosuke Fukunaga,et al.  An Optimal Global Nearest Neighbor Metric , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  R. Streit,et al.  A linear least squares algorithm for bearings-only target motion analysis , 1999, 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403).

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

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

[18]  V. Aidala,et al.  Utilization of modified polar coordinates for bearings-only tracking , 1983 .

[19]  K. C. Ho,et al.  Geometric-Polar Tracking From Bearings-Only and Doppler-Bearing Measurements , 2008, IEEE Transactions on Signal Processing.

[20]  Ba Tuong Vo,et al.  Square root Gaussian mixture PHD filter for multi-target bearings only tracking , 2011, 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[21]  Y. Bar-Shalom,et al.  Tracking in a cluttered environment with probabilistic data association , 1975, Autom..

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

[23]  S.S. Blackman,et al.  Multiple hypothesis tracking for multiple target tracking , 2004, IEEE Aerospace and Electronic Systems Magazine.

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

[25]  Michael Beard,et al.  Performance of PHD and CPHD filtering versus JIPDA for bearings-only multi-target tracking , 2012, 2012 15th International Conference on Information Fusion.