基于交替迭代的压缩感知多目标定位算法

针对目前的多目标定位算法在定位精度等方面的不足,将交替迭代应用于压缩感知多目标定位方法。该方法首先利用压缩感知理论将传感器感知到的目标信号强度矩阵表示为测量矩阵与稀疏向量的乘积,将多目标定位问题转换为对稀疏信号的重构问题;然后运行传统压缩感知定位算法得到目标的粗略位置估计;最后通过交替迭代对定位结果不准确的目标进行精确定位。交替迭代过程中,采用菱形搜索寻找目标的精确位置。仿真结果表明:与传统的基于压缩感知的定位算法相比,该算法提高了不在网格中心的目标定位精度,改善了多目标间相互影响对定位干扰大的问题,具有较高的多目标定位精度。最后,以重庆某电力公司的室内运维巡检区域作为实验场所,将该方法应用于实际的巡检定位,取得了较好的室内定位结果。

Multiple target localization algorithm based on alternate iteration using compressive sensing

In view of the shortcomings in localization accuracy of current multiple target localization algorithm, a method of multi-object localization based on compressive sensing (CS) and alternate iteration is proposed. Firstly, the measurement matrix of received signal strength (RSS) is expressed as the product of measurement matrix and sparse vector according to CS theory, which transforms multiple target localization problem to the reconstruction of sparse vector. Next, traditional localization algorithm based on CS is presented to obtain rough estimation of target positions. Finally, alternate iteration method is employed to further refine positions when localization results are not accurate. During the alternate iteration process, the diamond search is used to find the exact target locations. Simulation results show that the proposed algorithm overcomes the limitation of traditional compressive sensing localization techniques which can only locate targets in the center of grid, and improves the localization interference of the interaction between objects with high localization accuracy. The indoor operation and maintenance inspection area of a power company in Chongqing is chosen as an experimental site and the proposed method is applied to the actual inspection localization, and good results are achieved in the indoor localization.