Tracking multiple targets with particle filtering using multiple receivers

Multitarget tracking (MTT) deals with the state estimation of an unknown number of moving targets. Available measurements may both arise from the targets if they are detected, and from clutter. Clutter is generally considered as a model describing false alarms. Its (spatio-temporal) statistical properties are quite different from those of the target, which makes the extraction of target tracks from clutter possible. To perform multitarget tracking the observer has at his disposal a huge amount of data, possibly collected on multiple receivers. Elementary measurements are receiver outputs, e.g., bearings, ranges, time-delays, Doppler, etc. But the main difficulty comes from the assignment of a given measurement to a target model. These assignments are generally unknown, as are the true target models. Thus, two distinct problems have to be solved jointly: the data association and the estimation. We propose here a general algorithm for multitarget tracking in the passive sonar context and take advantage of its versatility to extend it to multiple receivers.