An Improved ICCP-Based Underwater Terrain Matching Algorithm for Large Initial Position Error

The matching algorithm is a key technology in underwater terrain-relative navigation (TRN). An improved iterative Closest Contour Point (ICCP) matching algorithm is proposed to address the mismatch of the sequence mapping algorithm in the event of the significant initial position error. Based on the rich topographical information provided by the multi-beam echosounder (MBES) in a short time, the conventional ICCP method of searching for target contour points based on single-point matching is improved. In order to reduce the interference of heading error, the terrain distribution feature is modeled as a two-dimensional Gaussian distribution, and a terrain feature descriptor with rotation invariance is established. The similarity between the measured local topographic map and the reference digital topographic map (DTM) is evaluated by the terrain characteristics descriptor to derive the target path. The results of simulation and field tests demonstrate that the improved method can not only realize position matching under large initial errors but also improve the matching accuracy. Furthermore, the simulation and field tests show that the improved ICCP algorithm works well in both flat and rough areas.