Research on the algorithm of gravity aided Inertial Navigation based on CKF
Hao Xiong, Xingshu Wang, Jing Zhu, Dongkai Dai · 2014
Using the information of gravity filed for aided inertial navigation can ensure the system's passive resistance and anti-jamming, and has become the hot topic of integrated navigation field. In this paper, we establish state-space model derived from the error equation of Inertial Navigation System (INS), and set the difference between indicated gravity anomaly and measured gravity anomaly which contains the information of position error as the measurement. After that, Cubature Kalman Filter (CKF) is introduced for estimation of navigation error online, which avoids the linearization of measurement. At last, the simulation system is realized based on the DNSC08 gravity model to inspect and verify the algorithm. The simulation results show that, the algorithm based on CKF for gravity aided navigation can strength the system's performance effectively.