{"title":"基于泊松-伯努利混合滤波的多传感器联合搜索与跟踪控制","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":"{\"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}","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}
Multi-Sensor Control for Jointly Searching and Tracking Multi-Target Using the Poisson Multi-Bernoulli Mixture Filter
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.