对称子阵列的近场信号稀疏表示定位方法

针对近场信号源，本文基于对称子阵列提出了两种稀疏信号表示的目标定位方法。首先利用对称阵元导向矢量的关系分离出时延中的方向角和距离两个参数，将一个近场目标定位问题转换为一个类远场的方向角估计问题，再通过稀疏信号重构的方法分步得到方向角和距离两个参数的估计。在参数分离的过程中，方法二通过构造共轭部分，所得到的虚拟远场阵列阵元数等效于原始阵列，故所能估计的信源数约为方法一的两倍。和同类方法相比，本文提出的方法具有较低的计算量。仿真表明，本文两种方法具有更高的分辨率。 

Localization of Near-Field Sources Using the Sparse Signal Representation with Symmetric Subarrays

In this paper, based on sparse signal representation, two novel near-field source localization methods are proposed for symmetric subarrays. By utilizing the relationship between the array steering vector of symmetric sensors and separating the two parameters of directions and ranges in propagation time, the near-field source localization problem is converted into a more convenient far-field one. Then the directions and ranges are estimated by sparse-signal-recovery sequentially. The number of sensors of the virtual array using the second method is equavilent to that of the physical array. Thus the number of sources the second method can detect is two times of that while using the first method. The proposed methods show less computation complexity compared to other sparse-signal-recovery methods. Numerical simulation demonstrates that the proposed methods achieve higher resolution ability compared to other methods.