Research On Application Of Multi-UAV Cooperative Area Search For Uncertain Targets

The application of multiple unmanned aerial vehicles(multi-UAV)cooperative target search is one of the hot topics in the field of UAV swarm intelligence research.With the widespread application of UAVs in the future battlefield,especially the reconnaissance and detection missions in the combat environment,the research work of multi-UAV collaborative target search application is of great significance.This paper focuses on the application of multi-UAV cooperative area search for uncertain targets.Through the establishment of objective and environmental mathematical model,the flight path planning algorithm is designed to improve the efficiency of multi-UAV cooperative area search for uncertain targets.The main research contents of this paper are as follows:(1)Through researching and analysing the flight dynamic performance and flight environment of UAV,a rasterized search environment model,a three-directional flight model that satisfies the UAV’s turning constraints,a predictive flight model that can avoid obstacle areas,and a target probability model that updated based on the Bayesian criterion are established.(2)Based on the prominent corner points position of the grid obstacle area in the flight environment,a divide-and-conquer and deterministic path optimization algorithm is proposed to plan a optimal flight path for the UAV.(3)For the coverage search mission,by analyzing the relationship between the UAV’s detection radius and the minimum turning radius,a corresponding turning flight model is established.According to the different search area boundaries,the method of judging the starting and ending positions of search turning flight is designed.In order to satisfy the search tasks under different conditions,a variety of coverage flight strategies are proposed.(4)Aiming at the uncertain search environment,the environment uncertainty information map and the target existence probability map are established to guide the UAV to search the area with higher target existence probability.In order to improve the mulit-UAV collaborative search efficiency,an immune genetic algorithm is proposed to determine the search flight path of UAVs.The effectiveness of the proposed algorithm is verified by comparing simulation experiments with multiple algorithms.(5)For the mobile target search task,based on the digital pheromone method,the attraction and repulsion pheromone map of the search environment is constructed to guide the UAV to detect the unsearched area.The time threshold mechanism is used to set a time switch for updating the environmental certainty information map and the digital pheromone map,so as to improve the return visit rate of the UAV.Based on the pigeon inspired optimization algorithm,an improved pigeon algorithm is proposed to determine the search flight trajectory of UAVs.The feasibility of the algorithm is verified by simulation experiments.