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

Abstract

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.