多UCAV协同目标分配算法研究

Cooperation mission assignment algorithm for multi-UCAV

针对多无人作战飞机(unmanned combat aerial vehicle,UCAV)协同目标分配问题,提出了一种基于离散粒子群算法的多UCAV协同目标分配方法。根据多UCAV协同目标分配问题的特点,建立了粒子与实际问题间的映射,设计了新的粒子群位置和速度更新公式,并且对标准粒子群算法作了改进。充分利用粒子群优化算法的全局搜索能力,有效地解决多约束条件下多UCAV协同目标分配问题。仿真结果表明,离散粒子群算法能够稳定快速地找到较优分配方案,并且算法简单、灵活。

A discrete particle swarm optimization （DPSO） algorithm is put forward for multi-UCAV （unmanned combat aerial vehicle）cooperation mission assignment problems. In the algorithm, a new code for particles and new update strategy for the position and speed of particles are applied so as to make the DPSO algorithm more suitable for multi-UCAV cooperation mission assignment problems. Aiming at the shortcoming of prematurity and poorness resulted from pure PSO, the DPSO algorithm takes full advantage of the complementary strengths of the particle swarm optimization algorithm, and the algorithm could solve multi-UCAV cooperation mission assignment effectively. The simulation results show that the DPSO algorithm could find the better assignment scheme fleetly and is simple and flexible.