Multi-Scan Generalized Labeled Multi-Bernoulli Filter

Abstract

© 2018 ISIF This paper extends the generalized labeled multi-Bernoulli (GLMB) tracking filter to a batch multi-target tracker. In a labeled random finite set formulation, a multi-target tracking filter propagates the labeled multi-target filtering density while a batch multi-target tracker propagates the labeled multi-target posterior density. The GLMB filter is an analytic solution to the labeled multi-target filtering recursion. In this work, we show that the GLMB filter can be extended to an analytic multi-object posterior recursion.