用局部保持典型相关分析定位无线传感器网络节点

Localization in Wireless Sensor Network Using Locality Preserving Canonical Correlation Analysis

在分析了无线传感器网络的布局基本符合流形(manifold)特点的基础上,借助所提出的局部保持的典型相关分析(locality preserving canonical correlation analysis,简称LPCCA)进行建模,以建立从信号强度空间到现实物理空间的映射;进而提出了一种能够体现网络拓扑结构局部信息的无线传感器网络定位算法——LE-LPCCA(location estimation-locality preserving canonical correlation analysis).与现有同类算法在benchmark上的实验结果相比,LE-LPCCA具有更高的定位精度和稳定性.

In this paper,the deployment of wireless network is analyzed in accordance with the manifold distribution.Next,the previous Locality Preserving Canonical Correlation Analysis（LPCCA） algorithm is used to build a mapping from the signal-vector space to the physical location space and develop a location algorithm,Location Estimation-Locality Preserving Canonical Correlation Analysis（LE-LPCCA,for short）,which sufficiently takes the local structure of the network topology into account.Finally,experimental results on benchmark show that this method achieves a higher accuracy and stability than other location algorithms.