This work studies the near-field localization problem using a symmetry uniform linear array (ULA). To decouple the range and direction of arrival (DOA), by exploiting the symmetry property of the array, two spatial correlation sequences are constructed, where each sequence only corresponds to one parameter, i.e., DOA or range. After decoupling, an attractive property is that the resulting sequences still share the similar ULA spatial structure. To perform DOA estimation, two approaches have been developed. The first one is based on the power of R (POR) method, which obtains the noise subspace without the eigendecomposition and prior information of the number of sources. The second one is developed using atomic norm minimization, which eliminates the off-grid issue. For range estimation, since the constructed sequence that corresponds to the range parameter shares the same spatial structure with the DOA sequence, the developed approaches are readily applied to obtain the range estimates. The proposed approach is also studied under one-bit measurement to show its robustness. The numerical studies including simulation and real-world data demonstrate the performance of the proposed method.

这项工作研究使用对称均匀线性阵列（ULA）的近场定位问题。为了分离距离和到达方向（DOA），通过利用阵列的对称特性，构造了两个空间相关序列，其中每个序列仅对应一个参数，即DOA或距离。解耦后，一个吸引人的特性是所得序列仍共享相似的ULA空间结构。为了执行DOA估计，已经开发了两种方法。第一种是基于R的幂（POR）方法，该方法获得了没有特征分解和源数量先验信息的噪声子空间。第二个是使用原子规范最小化开发的，它消除了离网问题。对于范围估算，由于对应于距离参数的构造序列与DOA序列共享相同的空间结构，因此可以轻松应用已开发的方法来获得距离估计。还对所提出的方法进行了一位测量，以显示其鲁棒性。包括仿真和现实世界数据在内的数值研究证明了该方法的性能。