Abstract

Aiming to address the problem of regional dynamic target search under weak communication conditions, this paper proposes a UUV cluster search method based on cumulative probability optimization. First, by estimating the probability distribution of the initial target location, an initial probability map is established. Then, based on the Bayesian model and Markov decision model, the target probability distribution is periodically updated, and based on the cumulative detection probability optimal principle of the UUV cluster, the UUV cluster is guided to search the region with high detection probability preferentially. Finally, we implement the simulation experiment and compare with the random search method. The results verify that the proposed method has higher search efficiency in the cases of without prior information and with prior information.

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