A comparison of several different approaches for target tracking with clutter

Five different methods suitable for tracking single targets in clutter are compared: the nearest neighbor algorithm, the probabilistic multi-hypothesis tracking filter, the probabilistic data association filter, the mixture reduction algorithm, and the mean-field event-averaged maximum likelihood estimator. Across a range of clutter densities, comparison results were generated for a common, fixed set of Monte Carlo target, target measurement, and clutter measurement realizations. The relative performances, as measured by track lifetime, RMS tracking error, and computational complexity are compared.

[1]  David J. Salmond.  Mixture reduction algorithms for target tracking in clutter , 1990 .

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

[3]  Keith D. Kastella.  Maximum likelihood estimator for report-to-track association , 1993, Defense, Security, and Sensing.

[4]  R.G. Hutchins,et al.  Evaluation of a probabilistic multihypothesis tracking algorithm in cluttered environments , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[5]  D. Salmond.  Mixture reduction algorithms for target tracking , 1989 .

[6]  Roy L. Streit,et al.  Maximum likelihood method for probabilistic multihypothesis tracking , 1994, Defense, Security, and Sensing.

[7]  Peter Willett,et al.  Comparison of PMHT and S-D assignment trackers , 1999 .

[8]  Roy L. Streit,et al.  A comparison of the JPDAF and PMHT tracking algorithms , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[9]  Edward W. Kamen,et al.  SME filter approach to multiple target tracking with false and missing measurements , 1993, Defense, Security, and Sensing.

[10]  Peter Willett,et al.  Direct data fusion using the PMHT , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[11]  Peter Willett,et al.  PMHT: problems and some solutions , 2002 .

[12]  K. Kastella,et al.  Event-averaged maximum likelihood estimation and mean-field theory in multitarget tracking , 1995, IEEE Trans. Autom. Control..

[13]  Lucy Y. Pao,et al.  Multisensor multitarget mixture reduction algorithms for tracking , 1994 .

[14]  C. Jauffret,et al.  A formulation of multitarget tracking as an incomplete data problem , 1997, IEEE Transactions on Aerospace and Electronic Systems.