Parameter estimation and tracking algorithm for resolvable group targets based on GLMB filter and RLS algorithm

Abstract

Current resolvable group targets tracking algorithms can only track a small number of group targets assuming the standard deviation vectors (SDVs) are known. Based on generalized labeled multi-Bernoulli filter, this paper first proposes a serial tracking algorithm, in order to save the computational cost of filter tracking large-batch and multi-structure group targets. Then, the least squares and the k-means algorithms are used to jointly estimate the SDVs and the group target states. The experimental simulation results verify the effectiveness of the proposed methods.