RSSI-Based Localization Through Uncertain Data Mapping for Wireless Sensor Networks
RSSI-Based Localization Through Uncertain Data Mapping for Wireless Sensor Networks
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DOI：
10.1109/jsen.2016.2524532
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发表时间：
2016-05-01
影响因子：
4.3
通讯作者：
Peng, Xiyuan
中科院分区：
文献类型：
--
作者：
Luo, Qinghua;Peng, Yu;Peng, Xiyuan
在无线传感器网络中定位未知节点时，通常考虑利用接收信号强度指示（RSSI）值来拟合一个固定的衰减模型和相应的通信距离。然而，由于一些负面因素，在实际的定位环境中，这种关系是不成立的，这导致了相当大的定位误差。因此，我们提出了一种改进的基于RSSI的定位方法，通过不确定的数据映射。从一个先进的RSSI测量开始，RSSI数据元组的分布被确定并以间隔数据表示。然后，在定位过程中，将数据元组模式匹配策略应用于RSSI数据向量。在三种典型无线环境下的实验结果表明了该方法的可行性和有效性。
When localizing the position of an unknown node for wireless sensor networks, the received signal strength indicator (RSSI) value is usually considered to fit a fixed attenuation model with a corresponding communication distance. However, due to some negative factors, the relationship is not valid in the actual localization environment, which leads to a considerable localization error. Therefore, we present a method for improved RSSI-based localization through uncertain data mapping. Starting from an advanced RSSI measurement, the distributions of the RSSI data tuples are determined and expressed in terms of interval data. Then, a data tuple pattern matching strategy is applied to the RSSI data vector during the localization procedure. Experimental results in three representative wireless environments show the feasibility and effectiveness of the proposed approach.