Sum Vector-Difference-Based Matching Area Selection Method for Underwater Gravity-Aided Navigation

For underwater gravity matching navigation, matching area selection has a significant impact on navigation accuracy. Since the changes of gravity anomaly between grids of gravity background map is different, when the underwater vehicle passes through the same matching area in different directions, the matching efficiency is also different. Therefore, for measuring the navigability of each grid point, a gravity anomaly sum vector-difference parameter is proposed. Its direction is with the largest comprehensive difference of local gravity anomaly, which can estimate the local matching direction. Its modulus value is the absolute difference of the gravity anomaly value between the central point and its local region. Compared to traditional scalar parameter, the vector parameter can obtain the matching suitability of the direction. In order to select efficient matching areas, the entropy method is applied to fuse the proposed sum vector-difference parameter with traditional gravity characteristic parameters to obtain the comprehensive characteristic parameter. Simulation results show that compared with the traditional method, the proposed method fully used the gravity information, and selected matching areas are more concentrated and continuous.