Yiqi Chen, P. Wei, Gaiyou Li, Lin Gao, Yuansheng Li
{"title":"样条多目标多伯努利滤波器","authors":"Yiqi Chen, P. Wei, Gaiyou Li, Lin Gao, Yuansheng Li","doi":"10.23919/FUSION45008.2020.9190412","DOIUrl":null,"url":null,"abstract":"A B-Spline implementation of the multi-target multi-Bernoulli (MeMBer) filter for nonlinear Gaussian/non-Gaussian models is proposed. Specifically, the spatial PDF (SPDF) of each Bernoulli component in the MeMBer density is represented by a B-Spline curve, which is characterized by the spline knots and control points. The spline knots and control points are then propagated via prediction and update steps of the MeMBer filter. Besides, a revised fitting algorithm is proposed so as to improve the implementation efficiency. The effectiveness of the proposed method is assessed via simulation experiments.","PeriodicalId":419881,"journal":{"name":"2020 IEEE 23rd International Conference on Information Fusion (FUSION)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Spline Multi-Target Multi-Bernoulli Filter\",\"authors\":\"Yiqi Chen, P. Wei, Gaiyou Li, Lin Gao, Yuansheng Li\",\"doi\":\"10.23919/FUSION45008.2020.9190412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A B-Spline implementation of the multi-target multi-Bernoulli (MeMBer) filter for nonlinear Gaussian/non-Gaussian models is proposed. Specifically, the spatial PDF (SPDF) of each Bernoulli component in the MeMBer density is represented by a B-Spline curve, which is characterized by the spline knots and control points. The spline knots and control points are then propagated via prediction and update steps of the MeMBer filter. Besides, a revised fitting algorithm is proposed so as to improve the implementation efficiency. The effectiveness of the proposed method is assessed via simulation experiments.\",\"PeriodicalId\":419881,\"journal\":{\"name\":\"2020 IEEE 23rd International Conference on Information Fusion (FUSION)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 23rd International Conference on Information Fusion (FUSION)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/FUSION45008.2020.9190412\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 23rd International Conference on Information Fusion (FUSION)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/FUSION45008.2020.9190412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A B-Spline implementation of the multi-target multi-Bernoulli (MeMBer) filter for nonlinear Gaussian/non-Gaussian models is proposed. Specifically, the spatial PDF (SPDF) of each Bernoulli component in the MeMBer density is represented by a B-Spline curve, which is characterized by the spline knots and control points. The spline knots and control points are then propagated via prediction and update steps of the MeMBer filter. Besides, a revised fitting algorithm is proposed so as to improve the implementation efficiency. The effectiveness of the proposed method is assessed via simulation experiments.
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