摘要
针对RSSI定位中RSSI值容易受外界环境干扰的数据源精度问题,提出一种自适应分簇策略,从锚节点中优选节点形成一个工作簇为定位算法提供可靠观测数据;针对传统的RSSI最小二乘定位算法的不足,提出一种改进的加权最小二乘法.实验结果表明,此算法的准确率和定位精度都有较大提高,具有良好的定位效果.
Focusing on the problem of inaccurate RSSI (Received Signal Strength Indicator) data caused by the environment interference in RSSI localization ,an adaptive clustering strategy is introduced is this paper .Anchor nodes with precise RSSI value are chosen to form a working cluster by using this strategy to provide the node localization algorithm with reliable measurement data .An improved weighted least squares algorithm is proposed to overcome the shortage of traditional least squares algorithm in RSSI localization .In addition ,a positioning experiment platform was built to verify and testify the presented algorithm and strategy .The results show that the improved weighted least squares algorithm based on adaptive clustering greatly improve the positioning accuracy and performance .
出处
《微电子学与计算机》
CSCD
北大核心
2014年第5期103-106,共4页
Microelectronics & Computer
基金
广东省自然科学基金项目(S2012010008462)
国家自然科学基金项目(61273109)
关键词
RSSI
自适应分簇
节点定位
加权最小二乘定位算法
RSSI
RSSI
adaptive clustering
node localization
weighted least squares localization algorithm