A novel variable structure multi-model approach based on error-ambiguity decomposition

作     者：Han SHEN-TU Yingjiao RONG Dongliang PENG Mengfan XUE Yunfei GUO Han SHEN-TU;Yingjiao RONG;Dongliang PENG;Mengfan XUE;Yunfei GUO

作者机构：Institution of Information and ControlHangzhou Dianzi UniversityHangzhou 310018China Science and Technology on Near-Surface Detection LaboratoryWuxi 214035China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2020年第33卷第6期

页      面：1731-1746页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：funded by the National Natural Science Foundation of China(Nos.61703128,61871166,61701148,61703131) the Science and Technology on Near-Surface Detection Laboratory Foundation,China(No.6142414180208) the Zhejiang Provincial Natural Science Foundation of China(No.LZ20F010002) 

主　　题：Error-ambiguity decomposi­tion Maneuvering target tracking Model sequence set adapta­tion Multi-model estimation Variable structure 

摘      要：Model Set Adaptation(MSA)plays a key role in the Variable Structure Multi-Model tracking approach(VSMM).In this paper,the Error-Ambiguity Decomposition(EAD)principle is adopted to derive the EAD-MSA criterion that is optimal in the sense of minimizing the square error between the estimate and the ***,the EAD Variable Structure first-order General Pseudo Bayesian(EAD-VSGPB1)algorithm and the EAD Variable Structure Interacting Multiple Model(EAD-VSIMM)algorithm are *** proposed algorithms are tested in two groups of maneuvering target tracking scenarios under different modes and observation error *** simulation results demonstrate the effectiveness of the EAD-VSMM approach and show that,compared to some existing multi-model algorithms,the proposed EAD-VSMM algorithms achieve more robust and accurate tracking results.