The Fusion Of GPS And Gyroscope Based On Kalman Filter

In order to overcome the problems that the gyroscope will produce cumulative errors during long-term operation and the magnetometer is extremely susceptible to interference from the external environment. A new method of Kalman fusion model combining gyroscope and GPS is proposed in this paper. This method uses angle information which is read by GPS as the observation value, and heading angle which is obtained through the angular velocity integral model as the prior estimation value, performing Kalman fusion between them for obtaining the posterior estimate. The experimental results show that the proposed method can dynamically adjust the heading angle calculated by the integrator so that the accuracy of the estimated heading angle is improved. The dynamic response capability of the proposed model is excellent. The MSE of the average heading angle which is obtained by reading GPS in a period of time and the heading angle which is fused with GPS and gyroscope in different time periods is 6.87.