一种两步式相关极值重力匹配算法

针对相关极值重力匹配算法实时性较差且要求初始误差较小的问题,该文提出一种两步式相关极值重力匹配算法。首先使用快速均方差相关(MSD)算法进行粗匹配,然后提取合适的粗匹配结果作为刚性变换的基准,将惯性导航系统(INS)轨迹变换到实际轨迹附近,产生新的待匹配轨迹,最后在新待匹配轨迹附近进行精确搜索,寻找代价最小路径。通过仿真实验验证了两步式匹配算法效果。两步匹配结合2种方法的优势,使重力匹配法适应于INS初始误差较大的情况,提高效率和实时性,同时保持匹配结果的高精度。

A Two step Gravity Matching Algorithm Based on Correlation Extremum

Aiming at the problem that the correlation extremum gravity matching algorithm has poor real time performance and requires less initial error, a two step correlation extremum gravity matching algorithm is proposed in this paper. Firstly, the fast mean square difference (MSD) algorithm is used for rough matching, then the appropriate rough matching result is extracted as the benchmark of the rigid transformation, and the inertial navigation system (INS) trajectory is transformed to the vicinity of the actual trajectory to generate a new trajectory to be matched. Finally, a precise searching is carried out near the new trajectory to be matched to find the least cost path. The effect of the two step matching algorithm is verified through simulation experiments. Combining the advantages of the two methods, the gravity matching method can adapt to the case of the large initial error of INS, improve the efficiency and real time performance, and maintain the high accuracy of the matching results.