摘要： 针对无线传感器网络中节点移动性问题提出一种遗传蒙特卡罗定位算法。将进化理论中的交叉操作与变异操作引入到蒙特卡罗定位算法中，对采样进行优化，使采样向后验密度分布取值较大的区域移动，从而更好地表达后验密度分布。仿真结果表明，该算法可以明显减少所需的采样数，具有更高的定位精度和鲁棒性。

关键词: 无线传感器网络, 移动节点, 定位, 蒙特卡罗

Abstract: In view of the localization in mobile wireless sensor network, a new localization method named genetic Monte Carlo localization is proposed. The crossover and mutation operations in evolutionary theory are introduced into Monte Carlo localization algorithm to make samples move towards regions with large value of posterior density distribution, so the sample set of localization algorithm can represent the desired posterior density distribution better. Simulation results show the algorithm needs fewer samples and is more precise and robust.

Key words: wireless sensor network, mobile node, localization, Monte Carlo

中图分类号: 

• TP312