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