{"title":"GPS navigation processing using the IMM-based EKF","authors":"Dah-Jing Jwo, Chien-Hao Tseng","doi":"10.1109/ICSENST.2008.4757174","DOIUrl":null,"url":null,"abstract":"This paper presents an interacting multiple model (IMM)-based extended Kalman filter (EKF) approach for the Global Positioning System (GPS) navigation processing. The well-known extended Kalman filter has been widely applied to the GPS navigation processing. The ldquosoft-switchingrdquo IMM estimator obtains its estimate as a weighted sum of the individual estimates from a number of parallel filters matched to different motion modes of the platform. The IMM estimators can substantially improve navigation accuracy during vehicle maneuvering (such as circular motion and acceleration) as well as during constant velocity straight-line motion over the conventional EKF. Simulation results show that the IMM-based EKF outperforms the single model EKF in navigation estimation accuracy.","PeriodicalId":6299,"journal":{"name":"2008 3rd International Conference on Sensing Technology","volume":"17 1","pages":"589-594"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 3rd International Conference on Sensing Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENST.2008.4757174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper presents an interacting multiple model (IMM)-based extended Kalman filter (EKF) approach for the Global Positioning System (GPS) navigation processing. The well-known extended Kalman filter has been widely applied to the GPS navigation processing. The ldquosoft-switchingrdquo IMM estimator obtains its estimate as a weighted sum of the individual estimates from a number of parallel filters matched to different motion modes of the platform. The IMM estimators can substantially improve navigation accuracy during vehicle maneuvering (such as circular motion and acceleration) as well as during constant velocity straight-line motion over the conventional EKF. Simulation results show that the IMM-based EKF outperforms the single model EKF in navigation estimation accuracy.