无线传感器网络中一种改进的目标定位算法

将定位区域网格化,把目标定位问题转化为稀疏搜索问题,建立基于压缩感知的定位模型。为满足压缩感知理论对测量矩阵的约束等距性要求,采用LU分解的方法对测量矩阵进行正交化预处理。同时提出一种改进的正交匹配追踪算法恢复目标位置,并利用加权质心算法进一步提高了定位精度。实验结果表明,该方案平均定位误差小于其它算法。

An Improved Target Localization Algorithm for WSN

Based on the target spatial domain discretion, the target localization problem is formulated as a sparsity-seeking problem which can be solved by compressed sensing(CS) technique. In order to satisfy the robust recovery condition for CS theory requirement, an orthogonalization preprocessing method called LU decomposition is utilized to make the measurement matrix obey the restricted isometry property(RIP).Meanwhile, an improved orthogonal matching pursuit(IOMP) algorithm is proposed to recover the position of target, and the weighted centroid algorithm to enhance the positioning precision was also adopted. The simulation results illustrate that the average localization error of the proposed algorithm is less than other existing algorithms.