Recursive estimate-maximize (EM) algorithms for time varying parameters with applications to multiple target tracking

We investigate the application of EM algorithm to the classical problem of multiple target tracking (MTT) for a known number of targets. Conventional algorithms, have a computational complexity that depends exponentially on the targets' number, and usually divide the problem into a localization stage and a tracking stage. The new algorithms achieve a linear dependency, and integrate those hire stages. Three major optimization criteria are proposed, using deterministic and stochastic dynamic models for the targets.