基于改进OMP算法的无线传感器网络节点定位

Unknown node location in wireless sensor networks based on improved OMP algorithm

定位问题是无线传感器网络中极具前景的钻研课题。解决定位问题的根本是提高目标的定位精度和加快目标的定位速度。为了解决无线传感器网络定位方法可以优化定位的精度。以压缩感知为研究方法。首先对被检测区域划分网格,传感器节点和未知节点散布在网格中,然后计算出区域中锚节点与网格的距离得到压缩感知模型的测量矩阵,并采用改进的OMP重构算法,通过测量矩阵对未知节点进行初步定位,接下来运用质心算法对目标进行估计定位,最后运用Matlab做仿真实验。实验结果表明,算法降低了无线传感器网络的系统通信量,提高了目标定位的工作效率,在定位精度上符合实际运用的要求。

The positioning problem is a very promising research topic in wireless sensor networks. To solve the positioning problem is to improve the positioning accuracy of the target and speed up the target＇s positioning speed. In order to solve the wireless sensor network positioning method, the positioning accuracy can be optimized. Compressive sensing is the research method. Firstly, the detected area is divided into grids, and the sensor nodes and unknown nodes are scattered in the grid.Then the distance between the anchor nodes and the grid in the area is calculated to obtain the measurement matrix of the compressed sensing model, and the improvement is adopted. The OMP reconstruction algorithm uses the measurement matrix to initially locate the unknown node, then uses the centroid algorithm to estimate and locate the target, and finally uses Matlab as the simulation experiment. The experimental results show that the algorithm reduces the system traffic of the wireless sensor network, improves the work efficiency of the target positioning, and meets the requirements of practical application in positioning accuracy.