针对运动目标的多无人机协同鸽群优化搜索方法

Aiming at the problem of multi-UAV cooperative moving target search, a cooperative search algorithm based on the improved pigeon-inspired optimization (IPIO) is designed. Firstly, based on the independence of moving targets, a target probability information graph model with normal distribution is established. In order to enhance the certainty of the presence of the targets in the environment, the information graph of search environment certainty is established. Secondly, in order to reduce the probability of repeated search and improve the efficiency of collaborative target search, the attractive and repulsive digital pheromone graphs are established to guide the UAVs to fly to the unsearched area. Based on the conventional pigeon-inspired optimization, the IPIO is designed by adding speed update and correction mechanism and elite generation mechanism. Then, combining with the existence probability information of the targets in the environment and the detection information of UAVs, the IPIO algorithm is used to determine the optimal searching flight paths for UAVs. And then, a collision avoidance strategy is designed to prevent the collision between UAVs in the searching process. Finally, the effectiveness of the present cooperative moving target search algorithm is verfied by comparative simulation experiments.