This paper considers multitarget tracking under out-of-sequence measurements (OOSMs), i.e. when the measurements processed by the tracker might be out of order. In order to fully exploit information provided by the sensor, OOSMs should be re-utilized rather than being simply discarded so as to improve tracking performance. To this end, this paper proposes a message passing (MP) multitarget tracking algorithm under OOSMs, where MP is adopted to perform efficient association between target and (in-sequence and out-of-sequence) measurements. Simulation experiments show that, compared to simply discarding OOSMs, the accuracy in terms of target number and state estimates can be greatly enhanced by incorporating OOSMs, thus demonstrating the effectiveness of the proposed approach.

Message passing multitarget tracking with out-of-sequence measurements / Jingling Li, Giorgio Battistelli, Luigi Chisci, Ping Wei, Lin Gao. - ELETTRONICO. - (2022), pp. 0-0. (Intervento presentato al convegno 25th International Conference on Information Fusion, FUSION 2022 tenutosi a Linkoping, Sweden nel 2022) [10.23919/FUSION49751.2022.9841339].

Message passing multitarget tracking with out-of-sequence measurements

Giorgio Battistelli;Luigi Chisci;Lin Gao
2022

Abstract

This paper considers multitarget tracking under out-of-sequence measurements (OOSMs), i.e. when the measurements processed by the tracker might be out of order. In order to fully exploit information provided by the sensor, OOSMs should be re-utilized rather than being simply discarded so as to improve tracking performance. To this end, this paper proposes a message passing (MP) multitarget tracking algorithm under OOSMs, where MP is adopted to perform efficient association between target and (in-sequence and out-of-sequence) measurements. Simulation experiments show that, compared to simply discarding OOSMs, the accuracy in terms of target number and state estimates can be greatly enhanced by incorporating OOSMs, thus demonstrating the effectiveness of the proposed approach.
2022
Proc. 25th International Conference on Information Fusion, FUSION 2022
25th International Conference on Information Fusion, FUSION 2022
Linkoping, Sweden
2022
Goal 9: Industry, Innovation, and Infrastructure
Jingling Li, Giorgio Battistelli, Luigi Chisci, Ping Wei, Lin Gao
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1326872
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