遗传算法的DV-Hop算法改进

DV-Hop算法中，平均每跳距离是影响定位精度的因素之一。针对平均每跳距离带来的定位误差，对锚节点和未知节点的平均每跳距离进行了改进和优化。首先引入遗传算法计算锚节点的平均每跳距离；然后利用跳数小于等于3的锚节点的平均每跳距离加权处理未知节点的平均每跳距离，减少平均每跳距离带来的误差。仿真结果表明，在不增加硬件开销的基础上，改进算法能够有效提高算法的定位精度，并且具有较好的稳定性。

An improved DV-Hop algorithm based on genetic algorithm

The average per-hop distance is one of the factors which affect the positioning accuracy in DV-Hop algorithm. Aiming at positioning errors caused by the average distance per hop, the average distance per hop of anchor nodes and unknown nodes have been improved and optimized in this paper. First, the average per hop distance of anchor nodes is computed by introducing genetic algorithm; Then the average distance per hop of the unknown node is weighted by using the average distance per hop of anchor nodes which hop count is less than or equal to 3 to reduce errors caused average distance per hop. Ultimately the accuracy of positioning is improved. Simulation results show that without additional hardware cost, the improved algorithm can effectively improve the positioning accuracy of the algorithm and has good stability.