为了克服接收信号强度测量误差对无线传感器网络(WSN)节点自身定位精度的影响,在对极大似然估计定位算法和接收信号强度指示(RSSI)模型分析的基础上,定义了个体差异差分系数、距离差分系数和距离差分定位方程,把离目标节点最近的信标节点作为参考节点对基于RSSJ的测距进行差分修正,并将测距差分修正和极大似然估计相结合提出了一种测距差分修正极大似然估计定位算法。算法通过RSSI进行测距,无需增加额外硬件开销,容易实现,定位精度可达2.5m以下,适合于处理能力和能量有限的WSN节点定位。
To suppress received signal strength indication(RSSI) errors to the positioning precision of localized nodes in wireless sensor networks, difference coefficients of individual diversities, difference coefficients of distances, and positioning difference equations of localized distances are defined based on analytical models of the maximum likelihood estimation and RSSI. The measured distances are corrected through the closest beaconing nodes to object nodes as their reference nodes, using the difference method of RSSI. A positioning algorithm is combined with the modified difference of localized distances and the method of the maximum likelihood estimation. The positioning algorithm is easy to be realized without the additional hardware spending. The positioning error is less than 2.5 m, so it is fit for the positioning of the nodes on wireless sensor networks (WSNs) when their operation abilities and power supplies are restricted.