Application of Magnetic Filter Technology in Improving the Precision of a Micro Attitude Reference System

Abstract

A micro attitude reference system is vulnerable to overload interference. To solve this problem, a type of Kalman filter was designed on the basis of a geomagnetic technique. Allan variance analysis was used to improve the Sage–Husa adaptive filter algorithm. Attitude error and gyro drifts were used as state variables for adaptive filtering updates, and a three-component magnetic vector was used for adaptive filtering measurement updates. Experimental results show that the pitch accuracy of the attitude reference system with magnetic filter technology working in 2 g vibrations improves by 4.7 times, the roll accuracy improves by 1.5 times, and the heading accuracy improves by 5.4 times. The proposed method can effectively reduce overload interference and ensure angular accuracy.