中文摘要：

针对DV-Hop算法在节点随机分布的网络拓扑环境中存在较大误差的问题，提出了一种基于跳距修正粒子群优化的定位算法WPDV-Hop（weight PSO DV-Hop）。本算法通过对锚节点广播的数据分组结构进行了改进，对参考锚节点的平均每跳距离的误差进行加权处理以及用改进的粒子群（PSO）算法对定位中的迭代过程进行优化，实现WPDV-Hop定位算法的全面改进，以提高定位精度。仿真结果表明，改进的算法与原始算法相比，定位精度和算法的稳定性有明显提高。。

英文摘要：

Regarding the relatively big errors with running the DV-hop localization algorithm in a network topology scenario, with which nodes randomly distributes, a particle swarm optimization localization algorithm for WSN nodes based on modifying average hop distance was proposed. By changing the structure of data packets sent by anchor nodes with broadcasting, weighting the average hop distance error of reference anchor nodes to modify the average hop distance, and using an improved particle swarm algorithm to optimize iteration process for localization, thus, WPDV-Hop localization algorithm improvements were carried out. The simulation results indicate that the localization accuracy and the stability of the WPDV-Hop localization algorithm are significantly improved compared with the original algorithm.