A Generalized Labeled Multi-Bernoulli Filter for Correlated Multitarget Systems

The labeled random finite set (LRFS) theory of B.-T. Vo and B.-N. Vo is the first systematic, theoretically rigorous formulation of true multitarget tracking, and is the basis for the generalized labeled multi-Bernoulli (GLMB) filter (the first implementable and provably Bayes-optimal multitarget tracking algorithm). Several of the author's earlier papers investigated Bayes filters that propagate the correlations between two unlabeled evolving multitarget systems-but with limited success. In this paper we provide a theoretically rigorous and much more general approach, by devising a GLMB filter that propagates the correlations between two evolving labeled multitarget systems.