A novel under-water terrain-aided navigation algorithm based on particle swarm optimization
Gannan Yuan, Jialin Tan · 2009
A novel under-water terrain-aided navigation algorithm is proposed in this paper. Unlike the conventional terrain-aided navigation approaches, the particle swarm optimization (PSO) is used as the searching strategy in the proposed algorithm instead of traversal search, and the mean hausdorff distance (MHD) is used as the similarity metric for its super performance of anti-interference and fault-tolerance. Furthermore, a hybrid PSO algorithm combined with chaotic search is introduced into the application to improve the local exploitation quality. The simulation experiments based on the real electronic chart are conducted, and the experimental results indicate the algorithm's great superiority, the number of computation and positioning error are reduced greatly.