High Dynamic Vehicle Attitude Algorithm Based on Multi-sensor Inertial Navigation System

Abstract

A high dynamic attitude solution and calculation system for vehicle motion, which combines a three-axis gyroscope with a three-axis accelerometer and a speedometer for the measurement and calculation of vehicle navigation information. For the attitude algorithm in the motion state, an Extended Kalman filtering algorithm based on the quaternion is proposed. The gyroscope attitude quaternion is used as the state amount of the Extended Kalman filtering algorithm through transform methods of Euler angular and quaternion. The calculated attitude quaternion is used as observational measurement after the compensation of the accelerometer via the speedometer. The measurement of noise covariance matrix is used to correct it. The Kalman equation is established, and the attitude angle is solved by obtaining the high-precision attitude quaternion. The experimental results show that the algorithm effectively solves the disadvantages of low accuracy, high error, tendency to be easily affected by motion acceleration, and improves the accuracy of high dynamic vehicle inertial navigation system.