A Combinational Aided Navigation Algorithm Based on Terrain Variance Entropy and ICCP

Abstract

In order to solve problems that the aided navigation system cannot work well in the flat region and Iterated Closest Contour Point(ICCP) algorithm diverges easily when the initial error of Inertial Navigation System (INS) is big, a new combinational algorithm based on terrain variance entropy and ICCP is proposed. In light of the advantages and disadvantages of two algorithms, they can complement each other. Terrain variance entropy algorithm is firstly applied to reducing the initial error of INS, then the best matching position is obtained by ICCP algorithm. The terrain entropy and the standard deviation of water depth are used as the terrain discriminant index. Simulation experiments are carried out in three different areas and result shows that the error of combinational algorithm maintains below 290m and navigation requirement of underwater vehicle can be satisfied.