Moving Vehicle Attitude Tracking Algorithm Based on MEMS Inertial Navigation System

Aiming at the dynamic attitude tracking system of vehicle motion, the vehicle attitude measurement and calculation are performed using a combination of three-axis accelerometer and three-axis gyroscope. Proposed a quaternion Extended Kalman Filter (EKF) algorithm for dynamic attitude tracking system. Through the Euler angle and quaternion transformation method, the attitude quaternion of the gyroscope is used as the state quantity of the EKF algorithm. The attitude quaternion calculated by the accelerometer is used as the observation quantity. And corrected by adaptive measurement noise covariance matrix. Established Kalman equation to obtain a high-precision attitude quaternion to solve the attitude angle. The experimental results show that the algorithm effectively solves the shortcomings of low accuracy and large error of MEMS sensors, and improves the accuracy of vehicle attitude tracking system.