Performance analysis of device-level SINS/ACFSS deeply integrated navigation method

摘要

The strap-down inertial navigation system(SINS) is a widely used navigation system. The combination of SINS and the celestial navigation system(CNS) is one of the popular measures to constitute the integrated navigation system. A star sensor(SS) is used as a precise attitude determination device in CNS. To solve the problem that the star image obtained by SS under dynamic conditions is motion-blurred, the attitude-correlated frames (ACF) is presented and the star sensor which works based on ACF approach is named ACFSS. Depending on the ACF approach, a novel device-level SINS/ACFSS deeply integrated navigation method is proposed in this paper. Feedback to the ACF process from the error of the gyro is one of the typical characters of the SINS/CNS deeply integrated navigation method. Herein, simulation results have verified its validity and efficiency in improving the accuracy of gyro and it can be proved that this method is feasible in theory.