Localization with Incompletely Paired Data in Complex Wireless Sensor Network
Localization with Incompletely Paired Data in Complex Wireless Sensor Network
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DOI：
10.1109/twc.2011.070511.100270
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发表时间：
2011-07
影响因子：
10.4
通讯作者：
Jingjing Gu;Songcan Chen;Tingkai Sun
中科院分区：
文献类型：
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作者：
Jingjing Gu;Songcan Chen;Tingkai Sun
无线传感器网络中基于RSSI （Received Signal Strength Indicator，接收信号强度指示器）定位技术的传感器定位可以看作是在信号和物理空间之间建立映射，该映射是由一组给定的成对信号强度和已知传感器的物理位置数据建立的。然而，在一些现实场景中，这样一组完全配对的传感器数据并不总是可访问的，这给传感器的定位带来了很大的挑战。这种场景下的本地化研究目前几乎被忽视。在本文中，我们开发了一种新的算法，通过适应我们之前提出的局部相关分析模型来解决配对和许多未配对数据的定位问题；新算法被命名为部分配对局部相关分析（PPLCA）。在室外和室内环境下的实验结果均表明了该算法的可行性和有效性。
Localizing sensors based on Received Signal Strength Indicator (RSSI) localization technique in wireless sensor network can be treated as building a mapping between signal and physical spaces, and the mapping is established from a set of given paired signal strengths and physical location data of known sensors. However, in some realistic scenarios, such a set of completely-paired sensor data is not always accessible, which brings a big challenge for localization of sensors. The localization research in such a scenario is currently almost ignored. In this paper, we develop a novel algorithm to tackle this problem in localization with paired as well as many unpaired data by adapting our previously-proposed Locality Correlation Analysis model; the new algorithm is named as Partially Paired Locality Correlation Analysis (PPLCA). Experimental results in both outdoor and indoor environments do show the feasibility and effectiveness of the proposed algorithm.