Autonomous Underwater Vehicle Search Strategy Generation Method Based on Improved GSO

Searching and positioning underwater moving target is an important basis for target tracking, recognition and judgment. This paper generates the search strategy of a single autonomous underwater vehicle (AUV) to search for the target when the general location, speed and direction range information of the target is obtained. The search strategy of AUV is divided into two phases: high-speed interception and low-speed search. Considering interception range, detection coverage target diffusion range and historical proportion of detection range, the search strategy represented by a series of features such as optimal interception speed, interception point and search point is determined by improved Glowworm swarm optimization (GSO) algorithm. Finally, the superiority of this method is demonstrated by comparing simulation with random search, geometry search and search strategies of typical GSO planning in terms of search success rate, search success time, and search distance when the search is successful.