Optimal mobile observation platform maneuver based on warping transform of signal autocorrelation function in shallow water

The underwater mobile observation platform maneuver trajectory has an important influence on the performance of the bearings-only target motion analysis method.Aiming at this problem,an optimal mobile observation platform maneuver method based on warping transform of signal autocorrelation function in shallow water is proposed.In order to estimate the distance characteristic,this method extracts the characteristic frequencies of the modal coherence items from signal's autocorrelation function using warping transform.Then this method estimates target motion situation based on the prior information of the initial target range.Aiming at the situation that the maneuvering mode of the observation platform is uniform turning motion,this method estimates the optimal turning angular rate within the estimated range of the target motion situation using the bearing rate as the evaluation index.The numerical simulation results in Pekeris waveguide and the sea trial results show that the bearing rate is closely related to the performance of bearings-only extended Kalman filter algorithm.Moreover,this method can estimate the distance characteristic effectively using warping transform.When the observation platform maneuvers with the optimal turning angular rate obtained by using the bearing rate as the evaluation index,this method can achieve better target tracking performance.The convergence time is shorter and the target position estimation error is smaller.