Resolvable Group State Estimation with Maneuver Based on Labeled RFS and Graph Theory

Weifeng Liu; Yudong Chi

doi:10.3390/s19061307

Resolvable Group State Estimation with Maneuver Based on Labeled RFS and Graph Theory

Sensors (Basel). 2019 Mar 15;19(6):1307. doi: 10.3390/s19061307.

Authors

Weifeng Liu¹, Yudong Chi²

Affiliations

¹ School of Automation, Hangzhou Dianzi University, Xiasha Higher Education Zone, Hangzhou 310018, China. dashan_liu@163.com.
² School of Automation, Hangzhou Dianzi University, Xiasha Higher Education Zone, Hangzhou 310018, China. cyd0418@163.com.

Abstract

In this paper, multiple resolvable group target tracking was considered in the frame of random finite sets. In particular, a group target model was introduced by combining graph theory with the labeled random finite sets (RFS). This accounted for dependence between group members. Simulations were presented to verify the proposed algorithm.

Keywords: GLMB; adjacency matrix; labeled random finite sets; resolvable group target tracking.