{"title":"一种实用的多传感器数据融合跟踪算法","authors":"Yaping Dai, Jie Chen, K. Hirasawa, Youhua Wu","doi":"10.1109/SICE.2000.889688","DOIUrl":null,"url":null,"abstract":"This paper describes an algorithm for fusion of tracks created by radar and IR sensor with different dimensional measurement data. It is assumed these sensors are asynchronous and the measurement data are transmitted to a central station at different rates. By means of the technique of time matching two asynchronous data are fused and then the filter is updated according to the fused information. The rotation Kalman filter algorithm to data fusion is discussed. This approach can effectively solve the problem of nonlinear measurement and reduce the load of calculation.","PeriodicalId":254956,"journal":{"name":"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A practical tracking algorithm of multisensor data fusion\",\"authors\":\"Yaping Dai, Jie Chen, K. Hirasawa, Youhua Wu\",\"doi\":\"10.1109/SICE.2000.889688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an algorithm for fusion of tracks created by radar and IR sensor with different dimensional measurement data. It is assumed these sensors are asynchronous and the measurement data are transmitted to a central station at different rates. By means of the technique of time matching two asynchronous data are fused and then the filter is updated according to the fused information. The rotation Kalman filter algorithm to data fusion is discussed. This approach can effectively solve the problem of nonlinear measurement and reduce the load of calculation.\",\"PeriodicalId\":254956,\"journal\":{\"name\":\"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SICE.2000.889688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICE.2000.889688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A practical tracking algorithm of multisensor data fusion
This paper describes an algorithm for fusion of tracks created by radar and IR sensor with different dimensional measurement data. It is assumed these sensors are asynchronous and the measurement data are transmitted to a central station at different rates. By means of the technique of time matching two asynchronous data are fused and then the filter is updated according to the fused information. The rotation Kalman filter algorithm to data fusion is discussed. This approach can effectively solve the problem of nonlinear measurement and reduce the load of calculation.
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