SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Tracking variable number of targets using Sequential Monte Carlo Methods

Author(s)

William Ng	University of Cambridge
Jack Li	University of Cambridge
Simon Godsill	University of Cambridge
Jaco Vermaak	University of Cambridge

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Abstract

In this paper, we present a simulation-based method for multitarget tracking and detection using sequential Monte Carlo (SMC), or particle filtering (PF) methods. The proposed approach is applicable to nonlinear and non-Gaussian models for the target dynamics and measurement likelihood, where the environment is characterised by high clutter rate and low detection probability. The number of targets is estimated by continuously monitoring the events being represented by the regions of interest (ROIs) in the surveillance region. Subsequent to target detection, the sequential importance sampling filter is employed for recursive target state estimation, in conjunction with a 2-D data assignment method for measurement-to-target association. Computer simulations are also included to demonstrate and evaluate the performance of the proposed approach.