An optimization self-calibration method of rotational inertial navigation system based on genetic algorithm

Navigation error of rotational inertial navigation system still diverges because of IMU errors. An improved self-calibration method is proposed to solve this problem. Least squares is utilized in identification of the error parameters with taking velocity errors as observations. The Genetic Algorithm(GA) is utilized to optimize the rotation angles, covariance matrix of the least squares is taken as fitness function of the GA. Simulation results show that compared to traditional method, the proposed method can improve the position accuracy significantly.