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| Computing method of RSSI probability centroid for location in WSN |
| CHENG Sen-lin, LI Lei, ZHU Bao-wei, CHAI Yi |
| College of Automation, Chongqing University, Chongqing 400044, China |
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Abstract A probability-centroid locating method based on RSSI was presented aiming at the low comprehensive locating precision in the least square locating method and large computing amount in maximum likelihood estimation locating. The algorithm adopted the overlapping area, which should be locating ring of anchor node under a certain outstanding degree, replacing the whole distribution area in wireless sensor network (WSN). Then the probability-density-centroid of overlapping area was figured out as the estimated value of unknown node. Locating error curves of the two methods were obtained under the existing differences of standard deviation of anchor nodes. The comparative results demonstrated that the locating precision of the method was higher than that of least square locating method, which validated that the algorithm would excel the least square locating algorithm. Results show that the method is provided with the same locating precision as maximum likelihood estimation, and the computing amount is reduced by 95%～97.5%．
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Published: 01 January 2014
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WSN定位中的RSSI概率质心计算方法
针对最小二乘综合定位精度不高与极大似然估计定位计算量大的问题,提出基于接收信号强度指示（RSSI）模型概率质心的定位方法.该方法采用在一定显著度下的锚节点定位环重叠区域代替整个无线传感网络（WSN）的分布区域,以重叠区域概率密度质心作为未知节点位置的估计.通过实验仿真获得2种方法在锚节点标准差存在差异时的定位误差曲线,对比结果显示,该方法的定位精度高于最小二乘定位方法,验证了该算法优于最小二乘定位算法.研究表明,该方法具有与极大似然估计相同数量级的定位精度,但计算量减少95%～97.5%.
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