Random set particle filter for bearings-only multitarget tracking

Matti Vihola

doi:10.1117/12.602682

25 May 2005 Random set particle filter for bearings-only multitarget tracking

Matti Vihola

Proceedings Volume 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV; (2005) https://doi.org/10.1117/12.602682
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

The random set approach to multitarget tracking is a theoretically sound framework that covers joint estimation of the number of targets and the state of the targets. This paper describes a particle filter implementation of the random set multitarget filter. The contribution of this paper to the random set tracking framework is the formulation of a measurement model where each sensor report is assumed to contain at most one measurement. The implemented filter was tested in synthetic bearings-only tracking scenarios containing up to two targets in the presence of false alarms and missed measurements. The estimated target state consisted of 2D position and velocity components. The filter was capable to track the targets fairly well despite of the missing measurements and the relatively high false alarm rates. In addition, the filter showed robustness against wrong parameter values of false alarm rates. The results that were obtained during the limited tests of the filter show that the random set framework has potential for challenging tracking situations. On the other hand, the computational burden of the described implementation is quite high and increases approximately linearly with respect to the expected number of targets.

Citation Download Citation

Matti Vihola "Random set particle filter for bearings-only multitarget tracking", Proc. SPIE 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV, (25 May 2005); https://doi.org/10.1117/12.602682

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