{"title":"Self-recovering extended Kalman filter for frequency tracking","authors":"J. Pak, C. Ahn, M. Lim","doi":"10.1109/ICCAS.2015.7364945","DOIUrl":null,"url":null,"abstract":"This paper proposes a new nonlinear filtering algorithm called the self-recovering extended Kalman filter (SREKF). In the SREKF algorithm, the EKF's failure or abnormal operation is automatically diagnosed. When the failure is diagnosed, an assisting filter, a nonlinear finite impulse response (FIR) filter, is operated. Using the output of the nonlinear FIR filter, the EKF is reset and rebooted. In this way, the SREKF can self-recover from failures. The SREKF is applied to a frequency tracking problem for demonstration of its effectiveness.","PeriodicalId":6641,"journal":{"name":"2015 15th International Conference on Control, Automation and Systems (ICCAS)","volume":"166 1","pages":"389-392"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAS.2015.7364945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a new nonlinear filtering algorithm called the self-recovering extended Kalman filter (SREKF). In the SREKF algorithm, the EKF's failure or abnormal operation is automatically diagnosed. When the failure is diagnosed, an assisting filter, a nonlinear finite impulse response (FIR) filter, is operated. Using the output of the nonlinear FIR filter, the EKF is reset and rebooted. In this way, the SREKF can self-recover from failures. The SREKF is applied to a frequency tracking problem for demonstration of its effectiveness.