Recurrent EKF-Based Inertial-Aided Magnetometer Online Calibration for Complex Interference Environment

被引:0
|
作者
Wang, Jinwen [1 ]
Deng, Zhihong [2 ,3 ]
Shen, Kai [2 ,3 ]
Bo, Yuming [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China
[2] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
[3] Beijing Inst Technol, Natl Key Lab Intelligent Control & Decis Complex S, Beijing 100081, Peoples R China
关键词
Magnetometers; Soft magnetic materials; Calibration; Interference; Covariance matrices; Mathematical models; Accuracy; Complex interference environment; inertial sensor; magnetometer; online calibration; recurrent EKF (REKF); KALMAN FILTER; SENSORS;
D O I
10.1109/TIE.2024.3406881
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Magnetometer is easily disturbed via external magnetic fields in complex interference environment, which reduces attitude estimation accuracy and seriously affects navigation and positioning accuracy. In this article, we propose an inertial-aided magnetometer online calibration method based on recurrent extended Kalman filter (EKF). First, state equation is constructed in complex interference environment according to relationship between attitude change matrix calculated via gyros and magnetometers output. Then, nonlinear measurement equation is constructed according to magnetometer error calibration model. A recurrent EKF is proposed for solving inertial-aided magnetometer online calibration filtering model. The state estimation accuracy is improved via recurrent filtering measurement updating process to realize high-precision magnetometer online calibration. The simulation and experiment results show that magnetometer calibration accuracy method proposed in this article is superior to the traditional filtering method, and dead reckoning accuracy is improved by 75%.
引用
收藏
页数:11
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