A Robust Solution of Integrated SITAN with TERCOM Algorithm: Weight-Reducing Iteration Technique for Underwater Vehicles' Gravity-Aided Inertial Navigation System

Abstract

The robustness of the Sandia Inertial Terrain-Aided Navigation (SITAN) algorithm has a pivotal influence on underwater vehicles' Gravity-Aided Inertial Navigation Systems (GAINS). An abrupt glitch of the accuracy of the GAINS will evolve into a disaster when vehicles pass through areas of smooth gravity. In order to resolve vulnerability issues of initial error and linearization error, we propose the Correlation SITAN algorithm with Weight-Reducing Iteration Technique (CSITAN + WRIT), in which the correlation process equals Terrain Contour Matching (TERCOM). The CSITAN algorithm is a Multipoint-based Extended Kalman Filtering (MEKF) method, which can work in real time. First, we need to derive the state equation and observation equation of the Multipoint-based SITAN algorithm based on the principle of the traditional SITAN algorithm. Then the accuracy of the state prediction can be improved, and the linearization error can be reduced by the correlation method based on TERCOM. Finally, the WRIT is utilized to reduce the possible influence of gross errors existing in the results of the MEKF and to extract a value with higher precision. The experimental results show that CSITAN + WRIT can achieve better accuracy and higher success rate of matching and can improve the possibilities of the occurrence of large matching errors than traditional SITAN methods in areas with smooth gravity. Copyright © 2017 Institute of Navigation