Cooperative Area Search Algorithm for Multi-UAVs in Uncertain Battlefield Environment

Abstract

Aiming at the problem of multiple unmanned aerial vehicles (UAVs) cooperative area search in uncertain battlefield environment, a multi-UAVs cooperative area search algorithm based on co-evolutionary genetic algorithm (CEGA) is proposed. Firstly, the raster Map and extended Search Probability Map (SPM) model of the task area are constructed, the UAV state model and sensor detection model are established, and the search environment updating method based on the Bayesian criterion is presented. Then, considering the cooperative elements of multi-UAVs, the cooperative area search planning model is established, and based on the rolling optimization idea, the co-evolutionary genetic algorithm with elite retention strategy is used to optimize the solution, and the multi-UAVs cooperative search paths are generated. Through simulation experiments and comparative analysis, the effectiveness of the proposed algorithm is verified.