WSNS中基于箱线图的误差自校正定位算法

针对基于接收信号强度指示(RSSI)的无线传感器网络(WSNs)节点定位技术易受环境影响、算法运算量大等问题,提出一种基于箱线图的误差自校正定位算法.该算法采用箱线图法处理测距过程中的异常RSSI值,利用自校正最小二乘法消除测距误差进而实现节点定位.仿真和实验结果表明,该算法可以有效抑制异常RSSI值,显著提高节点定位的准确性和稳定性,而且无需建立复杂的数据传播模型或构造RSSI位置指纹分布图.

Boxplot-based Error Self-calibration Localization Algorithm in WSNs

In order to solve the problem of wireless sensor network (WSNs) node location technology based on received signal strength indication (RSSI), which is easy to be influenced by the environment,and the algorithm has a large amount of computation and so on,a boxplot-based error self-calibration localization algorithm is proposed.The algorithm selects an adaptive distance estimation method based on boxplot to deal with outlier RSSI value,and uses a self-calibration least square algorithm to achieve localization by using ranging error self-elimination.The experiment results show that the proposed algorithm can effectively suppress outliers RSSI value and output a high and stable processing result while satisfying the high positioning accuracy requirement.For the above achievement,no hardware modification as well as time consuming RSSI-maps or complex signal propagation models are required.