摘要
在目前无线传感器网络中,接收信号强度指示(RSSI)测距模型严重依赖于信号衰减因子。为解决该问题,提出一种环境自适应的无线传感器网络定位算法。该算法利用改进的RSSI测距方法,通过网络中边与边之间的量化关系,消去信号衰减因子对定位算法的影响,从而使算法能实现对环境的认知。仿真实验结果表明,与传统的MDS-MAP定位算法相比,该算法具有较强的环境自适应能力和较好的定位精度。
Aiming at the problem of the Received Signal Strength Indication(RSSI) model depending on the signal attenuation factor,this paper puts forward an environment self-adaptive localization algorithm.With the improved RSSI method,the signal attenuation factor which impacts the precision of the localization algorithm is eliminated through the quantitative relationship between the edges and the algorithm can realize awareness of the environment.Simulation experimental result shows that the improved localization algorithm has higher precision and stronger self-adaptability than traditional MDS-MAP algorithm.
出处
《计算机工程》
CAS
CSCD
2012年第11期104-106,共3页
Computer Engineering
基金
重庆市教委研究计划基金资助项目(KJ10082)
关键词
无线传感器网络
定位算法
自适应
接收信号强度指示
MDS-MAP方法
信号衰减因子
Wireless Sensor Network(WSN)
localization algorithm
self-adaptive
Received Signal Strength Indication(RSSI)
MDS-MAP method
signal attenuation factor