低空突防航迹规划是实现有人机和无人机(unmanned aerial vehicle,UAV)编队协同作战的关键技术,针对目前智能算法在求解低空突防航迹规划问题中存在的不足,充分发挥人脑这个超级智能系统来引导飞行航迹求解过程,将基于角度量编码的小生境伪并行自适应遗传算法(niche adaptive pseudo parallel genetic algorithm,NAPPGA)和人有限干预情况下的智能决策结合起来,提出UAV低空突防航迹规划技术。通过大量仿真计算,结果表明,应用该技术预规划和重规划的三维航迹能够有效实现威胁回避、地形回避和地形跟随,满足UAV低空突防要求,具有一定的实用性。
The flight path planning for unmanned aerial vehicle (UAV) low-altitude penetration is a key technology for achieving manned and unmanned aerial vehicles cooperative combat. The technique of human in- tervention flight path planning for UAV low-altitude penetration against several limitations of the existing intelligent algorithms is proposed. It makes full use of the human brain to guide the solution procedures of the flight path planning, combining the niche adaptive pseudo parallel genetic algorithm (NAPPGA) based on angle codes and the intelligent decision with human intervention. A lot of simulation studies show that the solving off-line and on-line three-dimensional flight paths by this technique can meet the requirements for UAV low-altitude penetration to realize efficient implementation of threat avoidance, terrain avoidance and terrain following. This method has a certain practicality.