Robust structured total least squares algorithm for passive location

作     者：Hao Wu Shuxin Chen Yihang Zhang Hengyang Zhang Juan Ni 

作者机构：Information and Navigation College Air Force Engineering University Unit 94303 of PLA 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2015年第28卷第5期

页      面：946-953页

核心收录：

学科分类：11[军事学] 080904[工学-电磁场与微波技术] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 070105[理学-运筹学与控制论] 071101[理学-系统理论] 110503[军事学-军事通信学] 0711[理学-系统科学] 0810[工学-信息与通信工程] 1105[军事学-军队指挥学] 1104[军事学-战术学] 082601[工学-武器系统与运用工程] 081105[工学-导航、制导与控制] 0826[工学-兵器科学与技术] 081001[工学-通信与信息系统] 081101[工学-控制理论与控制工程] 081002[工学-信号与信息处理] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：supported by the National Natural Science Foundation of China(61202490) 

主　　题：passive location structured total least squares robustestimation equivalent weight function. 

摘      要：A new approach called the robust structured total least squares(RSTLS) algorithm is described for solving location inaccuracy caused by outliers in the single-observer passive location. It is built within the weighted structured total least squares(WSTLS)framework and improved based on the robust estimation ***, the improved Danish weight function is proposed according to the robust extremal function of the WSTLS, so that the new algorithm can detect outliers based on residuals and reduce the weights of outliers automatically. Finally, the inverse iteration method is discussed to deal with the RSTLS problem. Simulations show that when outliers appear, the result of the proposed algorithm is still accurate and robust, whereas that of the conventional algorithms is distorted seriously.