基于改进遗传算法的飞行航迹规划

Flight Path Planning Based on Improved Genetic Algorithm

航迹规划技术是有效提高飞行器突防概率的关键技术之一,能在大范围的真实环境中规划出满足各种约束的较优航迹,因此对所采用的算法有比较高的要求。基于此,首先研究了航迹包含的角度、高度、航迹段长度及飞行器的最大航程等约束条件;其次对航迹编码方式进行了改进,采用数组混合编码方式;并对遗传算法的交叉概率和变异概率的计算、交叉算子和变异算子进行了改进,并应用该算法在求解航迹规划问题上进行了应用仿真研究。对应用不同的航迹编码方式所得结果进行了对比分析。仿真计算表明,该算法能够规划出一条满足要求的航迹,避免了分层规划的复杂性,提高了算法的工程实用性。

Path planning, which was one of the key technologies increasing the survival probability of the military aircraft, could get an optimal path in large-scale real environment. So it was important to choose a suitable algorithm. In recent years, genetic algorithm （GA） had been successfully applied to path planning problems for umnanned aerial vehicle （UAV） systems, including single-vehicle system and multi-vehicle systems. This paper designed a new encoding method by using array-encoding, and improved the mutation operator with combination of reconstruction operator and disturbance operator. And it developed adaptive genetic algorithm for optimal path planning, which determined the optimal path between the nodes with respect to a set of cost factors and constraints. By the example simulation, it gets reasonable result which indicated that the new algorithm could satisfy the compute efficiency and the precision of solution. It was easier to realize and improved its practicability.