{"title":"Multi-Sensor Control for Jointly Searching and Tracking Multi-Target Using the Poisson Multi-Bernoulli Mixture Filter","authors":"Ke Chen, Lei Chai, Wei Yi","doi":"10.1109/ICCAIS56082.2022.9990345","DOIUrl":null,"url":null,"abstract":"In this paper, a multi-sensor control method with limited sensor field-of-view (FoV) based on Poisson multi-Bernoulli mixture (PMBM) filter is proposed, which provides a solution to the multi-target joint search and tracking problem. First, we propose a robust fusion method for multi-sensor PMBM posterior densities with limited sensor FoV based on the generalized covariance intersection (GCI) fusion criterion. Then, a cost function is constructed for multi-sensor control based on the fused density, which takes into account both discovered and undiscovered targets. The optimal multi-sensor control scheme is obtained by minimizing the cost function. The effectiveness of the proposed control method is demonstrated through a multi-target joint search and tracking simulation with unknown and time-varying number of targets and limited FoVs of sensors.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAIS56082.2022.9990345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a multi-sensor control method with limited sensor field-of-view (FoV) based on Poisson multi-Bernoulli mixture (PMBM) filter is proposed, which provides a solution to the multi-target joint search and tracking problem. First, we propose a robust fusion method for multi-sensor PMBM posterior densities with limited sensor FoV based on the generalized covariance intersection (GCI) fusion criterion. Then, a cost function is constructed for multi-sensor control based on the fused density, which takes into account both discovered and undiscovered targets. The optimal multi-sensor control scheme is obtained by minimizing the cost function. The effectiveness of the proposed control method is demonstrated through a multi-target joint search and tracking simulation with unknown and time-varying number of targets and limited FoVs of sensors.