Particle Filters for Tracking an

This paper addresses the application of sequential importance sampling (SIS) schemes to tracking DOAs of an unknown number of sources, using a passive array of sensors. This proposed technique has signi cant advantages in this application, including the ability to detect a changing number of signals at arbitrary times throughout the observation period, and that the requirement for quasi-stationarity over a limited interval may be relaxed. We propose the use of a reversible jump MCMC [1] step to enhance the statistical diversity of the particles. This step also enables us to introduce two novel moves which signi cantly enhance the performance of the algorithm when the DOA tracks cross. The superior performance of the method is demonstrated by examples of application of the particle lter to sequential tracking of the DOAs of an unknown and non-stationary number of sources, and to a scenario where the targets cross. Our results are compared to the PASTd method [2]. *Permission to publish abstract separately is granted. J. Reilly, corresponding author: ph: 905 525 9140 x22895, fax: 905 521 2922, email: [email protected]