面向多平台多目标协同跟踪的指派问题

针对多平台多目标协同跟踪中要求多个无人地面平台尽可能均匀地协同跟踪多个目标的特点,提出了改进的离散粒子群优化算法。首先采用连续型粒子群优化算法中的速度和位置迭代公式,然后对粒子位置进行离散编码,使粒子编码对应于可行的指派方案;其次,在优化算法中引入局部搜索,提高算法寻优性能。最后将所提算法应用于多平台多目标协同跟踪中的指派问题,并与未加入局部搜索的粒子群优化算法比较,仿真结果表明,加入局部搜索后的离散粒子群优化算法具有较好的寻优性能。

Research on Assignment Problem for Coordinated Tracking of Multi-platform Multi-target

Aiming at the characteristics of requiring multiple unmanned ground vehicles tracking multiple targets as evenly as possible in the coordinated tracking system of multi-platform multi-target, an improved discrete particle swarm optimization algorithm is proposed. Firstly,the iterative formula of speed and position of the particle swarm optimization algorithm in the continuous space are adopted, and then a discrete particle coding scheme is designed to the particle position,making the particle coding corresponding to the feasible assignment solution; Secondly, a local search is introduced, providing better optimization performance. Finally,the proposed algorithm is applied to the assignment problem of coordinated tracking for the multi-platform multi-target,and compared with particle swarm optimization algorithm without the local search. The simulation results show that the discrete particle swarm optimization algorithm with a local search has better optimization performance.