{"title":"Missile Interception Guidance With Parameter Uncertainties Using Desensitized Extended Kalman Filter","authors":"Jingsong Yang, Wei Hu, Tianhao Liu, Lingguo Cui, Jia Liang","doi":"10.1109/ICSAI57119.2022.10005408","DOIUrl":null,"url":null,"abstract":"The missile interception problem is considered in this article. As in practical applications, the real states are not available due to the existence of measurement noises and model parameter uncertainties, desensitized extended Kalman filter (DEKF) is applied to generate reliable state estimations. Compared to standard extend Kalman filter (EKF), this approach calculates state estimations by optimizing a cost function with one additional term, which reflects the state estimate error sensitivities. Such a design makes the filter less sensitive to model parameter uncertainties and can be considered as a generalization of the standard EKF. Simulation studies are conducted to evaluate the performance of DEKF when applying to integrated missile-target interception model.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI57119.2022.10005408","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
The missile interception problem is considered in this article. As in practical applications, the real states are not available due to the existence of measurement noises and model parameter uncertainties, desensitized extended Kalman filter (DEKF) is applied to generate reliable state estimations. Compared to standard extend Kalman filter (EKF), this approach calculates state estimations by optimizing a cost function with one additional term, which reflects the state estimate error sensitivities. Such a design makes the filter less sensitive to model parameter uncertainties and can be considered as a generalization of the standard EKF. Simulation studies are conducted to evaluate the performance of DEKF when applying to integrated missile-target interception model.