Resolving range ambiguity in long baseline synchronous acoustic positioning

For locating underwater targets moving in a large range, long baseline (LBL) synchronous acoustic positioning is always employed. Aiming at suppressing range ambiguity and improving performance of the LBL system, a novel range ambiguity resolution technique is proposed which is based on parameter fusion and optimization (RAR-PFO). From the perspective of parameter estimation, the basic idea was to build an optimization model with distance and direction parameters under maximum likelihood criterion. Furthermore, the nonlinear multimodal optimization problem was solved through differential evolution (DE). The constraint function limits the area where the target is located and suppresses premature convergence of DE. Performance of the proposed approach is evaluated using simulations, and compared with some widely applied methods and the Cramer-Rao bound. Simulation results demonstrated the effectiveness and robustness of the proposed method.