摘要
针对无线传感网中的节点定位问题,采用RSSI测距技术测量未知节点之间的距离,并采用粒子群算法进行优化,针对粒子群算法的不足,首先通过引入动态扰动因子和惩罚函数提高算法的性能,其次采用距离误差修正和修正定位误差模型来优化节点定位的效果。通过仿真实验将所提算法与基本粒子群算法进行比较,结果表明所提算法在算法的收敛性能和定位精度上取得了比较好的效果,提高了节点的定位效果。
Aiming at node positioning in wireless sensor network,this paper adopts RSSI measuring technology to measure the distance between unknown nodes,and uses particle swarm algorithm for optimization. Aiming at the deficiency of particle swarm algorithm,this paper firstly introduces dynamic disturbance factors and penalty functions to improve the performance of the algorithm,and then it adopts the distance error modification and modification positioning error model to optimize the effect of node optimization. Through comparing basic particle swarm algorithm in the simulation experiment,good effects have been achieved in the algorithm's convergence performance and positioning accuracy,improving the positioning effect of the node.
出处
《微型机与应用》
2017年第8期63-66,共4页
Microcomputer & Its Applications
关键词
无线传感网
动态扰动因子
惩罚函数
wireless sensor network
dynamic disturbance factor
penalty function
