Most localization methods for mixed far-field (FF) and near-field (NF) sources are based on uniform linear array (ULA) rather than sparse linear array (SLA). In this paper, we propose a localization method for mixed FF and NF sources based on the generalized symmetric linear arrays, which include ULAs, Cantor array, Fractal array and many other SLAs. Our method consists of two steps. In the first step, the high-order statistics of the array output is exploited to increase the degree of freedom. Then the direction-of-arrivals (DOAs) of the FF and NF sources are jointly estimated by using the recently proposed atomic norm minimization (ANM), which belongs to the gridless super-resolution method since the discretization of the parameter space is not required. In the second step, the ranges are given by MUSIC-like one-dimensional searching. Simulations results are provided to demonstrate the advantages of our method.
翻译:在本文件中,我们提议了一种基于通用对称线性阵列的混合远场和近场源的本地化方法,其中包括ULAs、Cantor阵列、Fractal阵列和许多其他SLAs。我们的方法由两步组成。第一步,利用阵列输出的高等级统计数据来增加自由程度。然后,通过使用最近提议的原子规范最小化(ANM),对FF和NF混合源的本地化方法进行联合估计,后者属于无网格超分辨率方法,因为不需要参数空间的离散。第二步,范围由类似于MUSIC的一维搜索提供。提供了模拟结果,以显示我们方法的优点。