Abstract:

The target motion is described by the model of discrete state, discrete time Markov chain. According to a hospitalbility map of bathygram, the target’s probabilistic state transition matrix is figured out. On the basis of target’ location distributed information and state transition matrix, unmanned underwater vehicles continually estimate and update the the target’s present state. Additionally, by using a new partition realtime greedy algorithm, the optimal search paths could be obtained so that unmanned underwater vehicles could complete the task with high success rate and little time cost. This new searching method is proved feasibility and superiority by the results of simulation in the end, and is worthful for the cooperative tactics of multiple unmanned underwater vehicles.