加权稀疏信号重构的近场源定位方法

Near-field source localization based on weighted sparse signal recovery

针对近场源定位问题,提出了一种使用加权L1范数优化进行稀疏信号重构的近场源定位方法。该定位方法分步完成目标的方位和距离估计。为了避免二维优化问题出现,首先利用均匀线阵的对称特性,通过菲涅尔近似,将二维参数估计的近场定位问题转换为类远场阵列的一维参数估计问题,接着将该一维参数估计问题转换为稀疏信号重构问题,通过类MUSIC权向量的构造,使用加权L1范数优化方法重构稀疏空间谱得到目标波达方向;在得到信号波达方向之后,再利用稀疏信号重构的思想求解信号源到阵列的距离。最后,通过数字仿真验证了算法在估计精度和分辨率等方面的优良性能。

In this paper, a source localization method is proposed based on sparse signal recovery by utilizing a weighted L1-norm penalty. The direction-of-arrival and range are estimated by two steps. First, the source localization problem, which needs two-dimensional parameter estimation, is transformed into a one-dimensional parameter estimation problem in far-field by use of the symmetry of uniform linear array and Fresnel approximation. After that, the problem is solved by finding the sparse spatial spectrum using weighted L1-norm penalty. Then the idea of sparse signal recovery is employed again to estimate the range between the source and the array. Finally, the superior performance of the method is demonstrated by numerical simulation in terms of accuracy and resolution ability.