{"title":"Hybrid derivative-free EKF for USBL/INS tightly-coupled integration in AUV","authors":"Y. Geng, J. Sousa","doi":"10.1109/AIS.2010.5547035","DOIUrl":null,"url":null,"abstract":"This paper presents a novel hybrid derivative-free extended Kalman filter, which takes advantage of both the linear time propagation of the Kalman filter and nonlinear measurement propagation of the derivative-free extended Kalman filter. The proposed filter is very suitable for the tightly coupled integration navigation system which consists of USBL or GPS with INS. The computation burden is reduced sharply compare to nonlinear estimation method such as the unscented Kalman filter (UKF). Simulations are conducted to illustrate the effectiveness of the proposed Kalman filter. The performance of the novel filter is as good as that of the UKF in integration navigation.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"41 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"自主智能系统(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/AIS.2010.5547035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper presents a novel hybrid derivative-free extended Kalman filter, which takes advantage of both the linear time propagation of the Kalman filter and nonlinear measurement propagation of the derivative-free extended Kalman filter. The proposed filter is very suitable for the tightly coupled integration navigation system which consists of USBL or GPS with INS. The computation burden is reduced sharply compare to nonlinear estimation method such as the unscented Kalman filter (UKF). Simulations are conducted to illustrate the effectiveness of the proposed Kalman filter. The performance of the novel filter is as good as that of the UKF in integration navigation.