基于棋盘编码粒子群算法的卫星资源调度方法

Multi-satellite scheduling based on chessboard coding and improved particle swarm optimization algorithm

针对卫星多传感器多目标跟踪问题的特殊性,在分析了现有编码方式存在问题的基础上,考虑组合数学中的棋盘多项式概念,提出了一种直接满足多目标跟踪复杂约束处理的棋盘编码方法,方便求解全部的优化目标;在此基础上,将并行粒子群算法和遗传交叉操作相结合,提出了基于改进并行粒子群优化算法的传感器管理算法(improved parallel particle swarm optimization algorithm,IPPSO)。仿真实验表明,基于棋盘编码粒子群算法的传感器管理算法实时性好、搜索质量高,可以有效解决传感器资源分配的冲突消解。

Based on analyzing the disadvantages of old coding methods, a new chessboard coding method is given. Chessboard coding method satisfies the constraints and solves the collision in multi-satellite mission planning. Combining particle swarm opti- mization algorithm with genetic operation, a sensor management method based on improved parallel particle swarm optimization algorithm （IPPSO） is proposed. The simulation experiment analyzes real-time performance and validity of PPSO based on old coding method, PPSO based on chessboard coding method, and IPPSO based on chessboard coding method. Experimental results show that the IPPSO algorithm based on chessboard coding method is a efficient approach to solve the satellite resources schedu- ling problem.