采用WSVM的三维无线传感器网络节点定位

为了提高无线传感器网络三维节点的定位精度,针对SVM的核函数构建问题,提出一种基于小波支持向量机(WSVM)的定位算法.首先,收集三维传感器锚节点信号强度,构建支持向量机学习样本;然后,将其输入到小波支持向量机进行学习,建立三维传感器节点定位模型;最后,采用仿真实验对模型性能进行测试.研究结果表明:与传统三维定位算法对比,使用小波支持向量机中的三维传感器节点进行定位时,精度水平得到有效提升,获得更加稳定的节点定位结果,可以广泛应用于实际无线传感器网络系统中.

A Node Localization for Three-Dimension Wireless Sensor Network on Wavelet Support Vector Machine

Node localization is one of the key technologies in high three-dimension(3D)wireless sensor networks.In order to improve the three dimensional positioning accuracy of wireless sensor networks. This paper proposed a three-dimension location algorithm based on wavelet support vector machine. Firstly, the signal intensity of three-dimension wireless sensor anchor nodes is collected to build a support vector machine(SVM)learning samples. Then, the samples are input into wavelet support vector machine to establish the 3D sensor nodes locolization model. Finally, the simulation experiment is carried out to test the performance of location model. The results show that, compared with the traditional 3D location algorithm, the proposed method uses the wavelet support vector can improve the positioning accuracy for three-dimension wireless sensor network, and got a more stable node localization result, so the proposed method can be widely applied in the actual wireless sensor network system.