摘要
在基于RSSI的无线传感网络定位算法中,未知节点定位精度过度依赖于RSSI物理测量的精度和锚节点密度,对此提出一种基于RSSI测距自修正的遗传定位算法.在节点定位的第一阶段,为消除测量误差,在未知节点通信范围内找出接收信号强度最大的锚节点作为误差消除的参考节点;在节点定位的第二阶段,为削弱"虚假适应度"现象提出一种新的适应度函数.在同等的仿真条件下,该算法比GAL定位精度更高.
Aiming at the problem which positioning accuracy of unknown node overly depends on physicat measurement accuracy and anchor nodes density among the loealization algorithms based on RSSI in wireless sensor networks, an error self-calibration genetic localization algorithm based on RSSI is proposed in this paper. In the first period of positioning, in order to eliminate the measurement error, the maximum received signal strength indicator anchor node within communication range of the unknown node is selected as the bias reduction reference minutiae; In the second period of positioning, a modified fitness function is introduced, which weaken the phenomenon of unreal fitness. The simulation results show that the positioning accuracy of the proposed algorithm is higher than that of genetic localization algorithm under the same simulation condition,
出处
《微电子学与计算机》
CSCD
北大核心
2016年第10期82-86,共5页
Microelectronics & Computer
关键词
遗传定位算法
锚节点
自修正
定位精度
genetic localization algorithm
anchor node
self-calibration
positioning accuracy
