{"title":"多传感器系统中传感器偏差的估计","authors":"E. Dela Cruz, A. Alouani, T. R. Rice, W. Blair","doi":"10.1109/SECON.1992.202338","DOIUrl":null,"url":null,"abstract":"An adaptive Kalman-filter-based technique to estimate and remove the sensor biases in a multiradar system is presented. The measurement model is based on the Taylor series approximation of the exact model and it incorporates range bias, bearing bias, and elevation bias. The technique was implemented using target tracks. The simulation results are presented. It was found that this technique gives accurate estimates of the sensor biases when given a reasonable model of the bias dynamics.<<ETX>>","PeriodicalId":230446,"journal":{"name":"Proceedings IEEE Southeastcon '92","volume":"333 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Estimation of sensor bias in multisensor systems\",\"authors\":\"E. Dela Cruz, A. Alouani, T. R. Rice, W. Blair\",\"doi\":\"10.1109/SECON.1992.202338\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An adaptive Kalman-filter-based technique to estimate and remove the sensor biases in a multiradar system is presented. The measurement model is based on the Taylor series approximation of the exact model and it incorporates range bias, bearing bias, and elevation bias. The technique was implemented using target tracks. The simulation results are presented. It was found that this technique gives accurate estimates of the sensor biases when given a reasonable model of the bias dynamics.<<ETX>>\",\"PeriodicalId\":230446,\"journal\":{\"name\":\"Proceedings IEEE Southeastcon '92\",\"volume\":\"333 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE Southeastcon '92\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.1992.202338\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE Southeastcon '92","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.1992.202338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An adaptive Kalman-filter-based technique to estimate and remove the sensor biases in a multiradar system is presented. The measurement model is based on the Taylor series approximation of the exact model and it incorporates range bias, bearing bias, and elevation bias. The technique was implemented using target tracks. The simulation results are presented. It was found that this technique gives accurate estimates of the sensor biases when given a reasonable model of the bias dynamics.<>