Improved ICCP algorithm and its application in gravity matching aided inertial navigation system

Considering two disadvantages in traditional gravity matching aided inertial navigation system, low matching accuracy and error accumulation, we propose an improved gravity matching algorithm and aided method for inertial navigation system. Instead of using the sequence sampling, the single point sampling is applied to improve the structure of proposed algorithm, enhancing the matching speed and efficiency. In the aided navigation system method, we use combination of Sage-Husa adaptive filter and strong-tracked Kalman filter to make further optimal estimation of the matching trajectory. Simulation results show the effectiveness of the real-time ICCP algorithm and the combined filter algorithm. Comparing to the traditional methods, proposed method provides higher matching and navigation accuracy.