Xia Keqiang, Xing Meng, Fu Na, Wei Jun, Liang Jixin, Yang Yongan, Li Ganhua
{"title":"An Improved Global State Fusion Filter for Track Estimation","authors":"Xia Keqiang, Xing Meng, Fu Na, Wei Jun, Liang Jixin, Yang Yongan, Li Ganhua","doi":"10.1109/IMCEC51613.2021.9482389","DOIUrl":null,"url":null,"abstract":"According to the characteristics of target motion and composite guidance, this paper establishes the state motion equation, designs the global state feedback model based on Kalman filter method and proposes an improved track fusion estimation method of the moving target on the sea by introducing the scalar weighting optimal state fusion. The method avoids the matrix inverse operation, so it significantly reduces the computational amount and effectively improves the timeliness in multi-mode composite guidance engineering. Simulation results of active and passive radar composite guidance show that this method can effectively reduce the computation amount and meet the time limitation requirement of composite guidance under conditions of ensuring the precision of track estimation.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"136 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCEC51613.2021.9482389","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
According to the characteristics of target motion and composite guidance, this paper establishes the state motion equation, designs the global state feedback model based on Kalman filter method and proposes an improved track fusion estimation method of the moving target on the sea by introducing the scalar weighting optimal state fusion. The method avoids the matrix inverse operation, so it significantly reduces the computational amount and effectively improves the timeliness in multi-mode composite guidance engineering. Simulation results of active and passive radar composite guidance show that this method can effectively reduce the computation amount and meet the time limitation requirement of composite guidance under conditions of ensuring the precision of track estimation.