A co-occurrence matrix-based matching area selection algorithm for underwater gravity-aided inertial navigation

The matching area selection algorithm is one of the key technologies for underwater gravity-aided inertial navigation system, which directly affects the positioning accuracy and matching rate of underwater navigation. The traditional matching area selection algorithms usually use the statistical characteristic parameters of gravity field. However, the traditional algorithms are difficult to reflect the spatial relation characteristic of gravity field, which always miss some latent matching areas with obvious change of gravity field. In order to solve this problem, the matching area selection algorithm based on co-occurrence matrix is proposed. The proposed algorithm establishes gravity anomaly co-occurrence matrix and extracts spatial relation characteristic parameters to reflect the gravity field. The comprehensive spatial characteristic parameter is built by entropy and is used to select the matching area by maximization of inter-class variance. The experimental results show that the proposed algorithm can select more effective matching areas than the traditional algorithms.