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Sensors 2019, 19(6), 1307; https://doi.org/10.3390/s19061307

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

School of Automation, Hangzhou Dianzi University, Xiasha Higher Education Zone, Hangzhou 310018, China
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This paper is an extension version of the conference paper: Chi, Y. and Liu, W. Resolvable Group State Estimation with Maneuver Movement Based on Labeled RFS. In Proceedings of the ICCAIS 2018 Conference, Hangzhou, China, 24–27 October 2018.
Received: 9 February 2019 / Revised: 7 March 2019 / Accepted: 11 March 2019 / Published: 15 March 2019
(This article belongs to the Special Issue Multiple Object Tracking: Making Sense of the Sensors)
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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. View Full-Text
Keywords: resolvable group target tracking; labeled random finite sets; GLMB; adjacency matrix resolvable group target tracking; labeled random finite sets; GLMB; adjacency matrix
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Liu, W.; Chi, Y. Resolvable Group State Estimation with Maneuver Based on Labeled RFS and Graph Theory. Sensors 2019, 19, 1307.

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