Topology optimisation method for MACL formation based on acoustic measurement network

Abstract

The topology of formation is an important factor that directly affects the performance of multiple autonomous underwater vehicle (AUV) cooperative localisation (MACL). This study presents a new optimisation design method, and the main contributions are as follows: (i) the evaluation function of the observable performance is constructed based on Cramér-Rao lower bound and Fisher information matrix considering the factors such as the situation of multiple leaders and multiple followers (MLs-MFs) and the correlation between acoustic ranging error and distance. (ii) In view of the uncertainty of the location information, the Monte Carlo method was applied to complete the reconstruction of the evaluation function and the formation configuration in the possible distribution region is optimised. (iii) A step recursive strategy based on annealing idea is proposed to solve the constraint equation for ML-MF system. The simulation results show that the MACL system composed of three leaders (3Ls) and one follower or 3Ls and three followers can complete the optimal formation configuration under position certainty or uncertainty. In addition, the proposed recursive strategy makes the iterative result no longer dependent on the selection of initial position, and the iterative process is no longer interfered by the local optimal solution.