基于分跳跳距和粒子群优化算法的DV—Hop定位算法改进

Improved DV—Hop Algorithm Based on Separate—Hop Hop Distance and Particle Swarm Optimization Algorithm

定位技术是无线传感器网络(WSN)应用的基础;针对在DV-Hop定位算法的第2阶段,选取未知节点接收到的第一个平均跳距作为其平均跳距产生的较大偏差,提出的一种分跳跳距的选择方法,既考虑到了距未知节点的所有信标节点的情况,也体现了距未知节点不同的跳数,跳距与误差不同的思想;而且在定位的第3阶段,用粒子群算法代替最小二乘法更近一步精确了坐标值,经Matlab仿真可知,改进算法定位性能优异。

Positioning technology is the basis of the wireless sensor network （WSN）. Proposing an selection method of separate--hop hop distance in allusion to the large deviation in the phase 2 of DV--hop positioning algorithm because of selecting the first average hop dis- tance received by unknown node as the average hop distance, which not only takes into consideration all beacon nodes around the unknown nodes, also reflects the idea that different hop count from unknown node has different hop distance and different error. While in the phase 3 of positioning, using particle swarm algorithm instead of the least square method makes the coordinates precise further. Results attained by Matlab proves that this improved algorithm has good execution efficiency.