节点文献
WSNS中基于箱线图的误差自校正定位算法
Boxplot-based Error Self-calibration Localization Algorithm in WSNs
【摘要】 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。
【Abstract】 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.
【Key words】 wireless sensor networks; boxplot; error self-calibration; localization algorithm;
- 【文献出处】 单片机与嵌入式系统应用 ,Microcontrollers & Embedded Systems , 编辑部邮箱 ,2017年07期
- 【分类号】TN929.5;TP212.9
- 【下载频次】179