Seabed Terrain Match Algorithm Based on Hausdorff Distance and Particle Swarm Optimization

Abstract

When most of terrain match algorithms were directly applied to seabed terrain-aided navigation system (STAN), the positioning accuracy would fall off sharply and become unstable because of the particularity of seabed terrain. Here, a new approach of seabed terrain matching algorithm was proposed. It used the mean Hausdorff distance as similarity measure for its great anti-interference performance and fault-tolerance performance. As to searching strategy, particle swarm optimization algorithm was used to achieve high searching speed. The experiments of seabed terrain match based on electronic chart confirmed the effectiveness of the proposed approach. The algorithm was robust, and reduced the calculation complexity greatly. The positioning accuracy had been increased by 20% at least.