{"title":"Simultaneous target state and sensor bias estimation: Is more better?","authors":"M. Kowalski, P. Willett","doi":"10.1109/CAMSAP.2017.8313183","DOIUrl":null,"url":null,"abstract":"This paper provides an analysis of several scenarios of target tracking state estimation when additionally estimating the biases of the measuring sensors in the state. Line of Sight (LOS) sensors are used with noisy data and angle biases that are unknown to the estimator. The addition of new state components can potentially be a drawback to the estimator and this is addressed by comparing the accuracy of estimation with 2, 3, and 4 sensors. Of particular interest to us is whether “more” is worth it: More sensors? Is bias estimation even worth doing? The answers are a qualified “yes” and a definite “sometimes.”.","PeriodicalId":315977,"journal":{"name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMSAP.2017.8313183","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
This paper provides an analysis of several scenarios of target tracking state estimation when additionally estimating the biases of the measuring sensors in the state. Line of Sight (LOS) sensors are used with noisy data and angle biases that are unknown to the estimator. The addition of new state components can potentially be a drawback to the estimator and this is addressed by comparing the accuracy of estimation with 2, 3, and 4 sensors. Of particular interest to us is whether “more” is worth it: More sensors? Is bias estimation even worth doing? The answers are a qualified “yes” and a definite “sometimes.”.