关键词: 鸽群优化算法, 近距空战, 机动动作决策, 无人机, 有限忍耐度策略

Abstract: Due to the rapid change of the situation during the confrontation，the autonomous maneuver decision-making for short-range Unmanned Aerial Vehicle（UAV）air combat is difficult and complex，which is a difficult point in air combat. To address this issue，a short-range UAV air combat maneuver decision-making method based on Finite Tolerance PigeonInspired Optimization（FTPIO）algorithm was proposed. Two parts were designed in the proposed method：opponent action prediction based on the maneuver library and optimization solution of maneuver control and execution time based on FTPIO algorithm. To improve the global exploration ability of the basic Pigeon-Inspired Optimization（PIO）algorithm，the finite tolerance strategy was introduced. When the pigeon individual failed to find a better solution in several iterations，its attributes would been reset to avoid falling into the local optimal trap. The optimization variables used in the proposed method were the increments of the control variables of UAV motion model，which broke the limitations of the maneuver library. Simulation and adversarial testing results with the MiniMax method，basic PIO algorithm，and Particle Swarm Optimization（PSO）algorithm show that the proposed maneuver decision-making method can effectively defeat opponents during confrontation and generate more flexible deceptive maneuver behaviors.

Key words: pigeon-inspired optimization (PIO), short-range air combat, maneuver decision-making, unmanned aerial vehicle (IAV), finite tolerance strategy