基于双变异遗传算法的无人机对海侦察航路规划

Path Planning of Unmanned Aerial Vehicle’s Sea Reconnaissance Based on Double Variation Genetic Algorithm

针对目前关于无人机(UAV)对海侦察航路规划问题研究较少的现状,文中以UAV侦察美国"小鹰"号航母编队为例,将UAV对海侦察航路规划问题按照侦察方式,分为临空侦察和非临空侦察航路规划问题。对于临空侦察问题,提出一种改进的双变异遗传算法(DVGA)对最优路径进行求解;将非临空侦察问题转化为不具体旅行商和位置替换旅行商问题,设计了三点连线夹角法和位置替换法对问题进行处理,并结合DVGA对最优路径进行求解;最后,通过仿真实验证明了DVGA的高效性,并且得到了UAV在不同侦察条件下对"小鹰"号航母编队的最优侦察路径。

In view of current situation that there is less research on the path planning of unmanned aerial vehicle’s(UAV’s) sea reconnaissance,UAV reconnaissance of "Kitty Hawk" aircraft carrier formation is taken as an example,which divides path planning of UAV into overhead reconnaissance and non-overhead reconnaissance path planning according to the UAV’s reconnaissance mode. For the overhead reconnaissance problem,an improved double variation genetic algorithm(DVGA) is proposed to solve optimal path. The non-overhead reconnaissance problem is transformed into unspecific traveling salesman problem and substitutive traveling salesman problem. The three-point connection angle method and the location replacement method are designed to deal with the problems,and DVGA is used to solve optimal path. Finally,simulation results show that DVGA is efficient,and optimal reconnaissance paths of UAV to "Kitty Hawk"aircraft carrier formation is obtained under different reconnaissance conditions.