传感技术学报2024，Vol.37Issue(9)：1593-1601,9.DOI:10.3969/j.issn.1004-1699.2024.09.017
基于MACF-CKF多传感器融合的姿态解算算法
Attitude Algorithm Based on MACF-CKF Multi-Sensor Fusion
摘要
Abstract
Targeting at the problem that the unit attitude solving accuracy is low for the inertial navigation measurement,an attitude calcu-lation algorithm based on the fusion of multi-sensor membership adaptive complementary filtering(MACF)and volumetric Kalman filter(CKF)is proposed.The exponential weighted moving average is used to correct the gyro noise deviation.In order to avoid the large error of pitch angle and roll angle caused by the improper distribution of the weight of gyroscope and accelerometer in the complementary filtering,the membership function of gyro deviation is constructed to judge the trust of complementary filtering to gyroscope,and the adaptive factor of complementary filtering is dynamically adjusted according to the trust,and the problem of course angle divergence is solved by CKF with magnetometer and gyroscope.Experimental results show that the proposed algorithm can achieve the attitude solution quickly and accurate-ly under both static and dynamic conditions.In the dynamic vehicle experiment,the accuracy of roll angle and pitch angle increases by 24.5%and 63.2%respectively,and the heading angle increases by 48.8%,which can guarantee the solution accuracy.关键词
惯性传感器/姿态解算/隶属度函数/互补滤波/容积卡尔曼滤波Key words
inertial sensor/attitude algorithm/membership function/complementary filtering/cubature Kalman filter分类
能源科技引用本文复制引用
乔美英,韩昊天,李宛妮,杜衡..基于MACF-CKF多传感器融合的姿态解算算法[J].传感技术学报,2024,37(9):1593-1601,9.基金项目
国家自然科学基金项目(U1404510) （U1404510）
河南省科技攻关项目(222102220076) （222102220076）
河南省自然科学基金项目(232300421152) （232300421152）
