自主式微航姿系统信息融合方法比较

Comparison of Information Fusion Methods of AHRS

自主式微航姿系统是利用微惯性传感器设计的载体姿态测量系统,信息融合算法是自主式微航姿系统的重要组成部分,对于系统测量精度有重要影响。根据实际工程应用,对当前主流的航姿系统信息融合算法,包括直接卡尔曼滤波法、间接卡尔曼滤波法和互补滤波器法,进行了总结分析和算法设计,并且应用所设计的微航姿系统进行半物理仿真实验,对3种算法的精度、计算量和实时性进行比较。实验结果表明:和KF算法相比,互补滤波器算法简单、运算量小,实时性更好,适用于单片机的AHRS硬件平台。对不同算法优劣进行分析和总结,为工程应用中AHRS算法选择提供选择依据。

The autonomous micro attitude heading reference system(AHRS)is a vehicle attitude measurement system,which is designed by using micro inertial sensors.Information fusion algorithm is an important part of AHRS,and has important influence on the measurement accuracy of the system.Based on the practical applications,current mainstream AHRS information fusion methods,including direct Kalman filtering,indirect Kalman filtering,and complementary filter,are summarized and the algorithms are designed.Moreover,the semi-physical simulation experiment is carried out with the designed AHRS system,and the accuracy,and analyzed computation and real time of three kinds of algorithms are compared.The experimental resutls show that,compared with KF algorithm,the complementary filter algorithm is simple,less computation,and better real time,which is suitable for AHRS hardware platform of single chip microcomputer.The advantages and disadvantages of the three algorithms are analyzed and summarized.This paper provides a reference for the design of AHRS algorithm and system engineering.