摘要
传统的DV-Hop传感节点定位算法,估计未知节点与各锚节点之间距离是用跳段距离代替直线距离。在实际网络定位环境中,未知节点和锚节点之间多数是折线连接。当平均每跳距离的估计值与实际值的偏差较大时,未知节点到锚节点之间估计距离与实际距离之间的误差会增大。为解决上述问题,提出一种粒子群优化算法修正DV-Hop算法定位误差的传感器节点定位方法。采用DV-Hop算法估计待测节点和锚节点之间距离,通过三边测量法确定节点的位置,并将传感器节点定位问题转换成一个多约束优化问题,最后通过粒子群优化算法对定位误差进行修正,并通过仿真对其性能进行测试。仿真结果表明,相对传统DV-Hop算法可大幅度提高传感器节点定位精度,符合无线传感器网络定位需求,具有较好的应用价值。
DV-Hop algorithm substitute jump distance for linear distance,and the cumulative error is increased with nodes＇ distance.In order to improve the positioning accuracy of sensor node,the DV-Hop algorithm error must be analyzed and improved.This paper proposed a sensor node localization method which improves DV-Hop algorithm with particle swarm optimization algorithm.Firstly,the improved DV-Hop algorithm was used to estimate the sensor node and the anchor node location,and then the location was determined by three side measurement methods,and the node localization problem was converted into a constrained optimization problem.Finally,the particle swarm optimization algorithm was used to correct the localization error to improve the sensor positioning accuracy.The simulation results show that the proposed method greatly improves the sensor node localization accuracy compared with the DV-Hop algorithm and overcomes the shortcomings in DV-Hop algorithm.
出处
《计算机仿真》
CSCD
北大核心
2013年第8期281-284,共4页
Computer Simulation
基金
黑龙江省教育厅科学技术研究项目<无线传感器网络定位技术研究>(12531765)
关键词
节点定位
粒子群优化算法
无线传感
Node localization
Particle swarm optimization （PSO） algorithm
Wireless sensor network （WSN）
