针对基于粒子群优化算法的粒子滤波精度不高，容易陷入局部最优，难以满足目标跟踪的问题-For particle swarm optimization algorithm based on particle filter accuracy is not high, easy to fall into local optimum, it is difficult to meet the target tracking problem

多目标粒子群算法，最优的解决方案，使用一个外部文件管理，拥塞机制筛选，灰色设计验过滤。-Multi-objective particle swarm algorithm, the optimal solution using an external file management, congestion mechanism screening, gray design posteriori filtering.

简单的粒子群优化程序，模拟鸟群飞行时合作，将每只小鸟比作一个粒子。粒子通过自己的历史最优值和所有粒子的最优值来调整自己的速度和位置，从而达到目的地。-Simple particle swarm optimization procedure, the simulation when flying birds, compared each bird to a particle. Particle optimal value through its own history and the optima