Multi-Scan Generalized Labeled Multi-Bernoulli Filter
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© 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.
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Vo, Ba-Ngu; Vo, Ba Tuong; Phung, D. (2014)An analytic solution to the multi-target Bayes recursion known as the δ-Generalized Labeled Multi-Bernoulli ( δ-GLMB) filter has been recently proposed by Vo and Vo in [“Labeled Random Finite Sets and Multi-Object Conjugate ...
Jones, B.; Vo, Ba Tuong; Vo, Ba-Ngu (2016)Space-object tracking systems require robust and accurate methods of multi-target state estimation and prediction. This paper presents the application of labeled multi-Bernoulli filters for space-object tracking, and ...
Papi, Francesco; Kim, Du Yong (2015)In this paper we present a general solution for multi-target tracking with superpositional measurements. Measurements that are functions of the sum of the contributions of the targets present in the surveillance area are ...