Sensor Bias Estimation Based on Ridge Least Trimmed Squares

被引：8

作者：

Tian, Wei ^{[1
]}

Huang, Gaoming ^{[1
]}

Peng, Huafu ^{[1
]}

Wang, Xuebao ^{[1
]}

Lin, Xiaohong ^{[1
]}

机构：

[1] Naval Univ Engn, Coll Elect Engn, Wuhan 430033, Peoples R China

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2020年 / 56卷 / 02期

基金：

中国博士后科学基金;

关键词：

Estimation; Target tracking; Heuristic algorithms; Mathematical model; Azimuth; Indexes; Distributed databases; Multisensor multitarget tracking; sensor bias estimation; data association; misassociation; least trimmed squares (LTS); ill-conditioning; ridge regression (RR); ridge least trimmed squares (RLTS); MAXIMUM-LIKELIHOOD REGISTRATION; TO-TRACK ASSOCIATION; ALGORITHM; FUSION;

D O I：

10.1109/TAES.2019.2929973

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

A robust sensor bias estimation approach, named as the ridge least trimmed squares (RLTS), is proposed. Combing the advantages of ridge regression and least trimmed squares, RLTS can solve the sensor bias estimation problem with the presence of misassociations and ill-conditioning. Simulation results verify the effectiveness of the proposed approach.

引用

页码：1645 / 1651

页数：7

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