Investigation on optimal path for submarine search by an unmanned underwater vehicle

Abstract

Unmanned underwater vehicle (UUV) is one of the significant equipment for underwater anti-submarine warfare. In this paper, the optimal anti-submarine search path of a UUV is investigated through maximizing the cumulative detection probability (CDP). The mathematical programming model for optimal UUV search path is established by utilizing an adaptive mutation genetic algorithm (AMGA). The enemy submarine is described as a Markovian target. The search radius and search width of the UUV are considered. In simulation analysis, an approximately logarithmic spiral path is found. Moreover, the influence of different parameters, such as detection distance, different initial distance, different detection velocity, and different escape velocity, on the CDP is revealed. The results indicate that the optimal UUV search path is effective and suggestive for anti-submarine operation.