In this study, the authors take further insight into the sparse geometry which offers a larger array aperture than uniform linear array with the same number of physical sensors. A novel direction of arrivals (DOAs) estimation model with flexible sparse geometry, which possesses the potential to significantly improve the estimation performance especially when the placed space and the weight of carrier such as airborne radar are restricted, is proposed to offer a larger aperture compared with co-prime array. The proposed algorithm can estimate DOAs by solving phase ambiguity. To improve the capability of spectrum analysis in frequency domain, all phase discrete Fourier transform (DFT), which can effectively alleviate spectrum leakage compared with traditional DFT, is proposed to apply into DOAs estimation. Additionally, the performance on degrees of freedom can be considerably improved compared with the state of the art where all the targets can be distinguished by Doppler information of received echo signal. More importantly, the proposed algorithm can effectively deal with DOA-closely-spaced targets because the proposed algorithm does not require to estimate signal subspace with ill-conditioned steering matrices. Both the theoretical analysis and simulation results demonstrate that the proposed algorithm significantly improves DOAs estimation precision with less computation cost.

中文翻译：

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稀疏阵列中多目标的基于多普勒辅助中文余数定理全相位DFT的DOA估计新方法

在这项研究中，作者进一步了解了稀疏的几何形状，该几何形状比具有相同数量的物理传感器的均匀线性阵列具有更大的阵列孔径。提出了一种新颖的具有稀疏几何形状的到达方向（DOA）估计模型，该模型具有显着提高估计性能的潜力，尤其是在受限于机载雷达等载物的放置空间和重量时，可以提供更大的孔径与互素数组。该算法可以通过求解相位模糊度来估计DOA。为了提高频域频谱分析的能力，提出了与传统DFT相比可以有效减轻频谱泄漏的全相位离散傅里叶变换（DFT），将其应用于DOA估计中。另外，与现有技术中的所有目标都可以通过接收到的回波信号的多普勒信息进行区分的现有技术相比，可以大大提高自由度的性能。更重要的是，由于所提出的算法不需要估计病态转向矩阵的信号子空间，因此所提出的算法可以有效地处理DOA密集的目标。理论分析和仿真结果均表明，该算法显着提高了DOA估计精度，且计算成本较低。由于该算法不需要用病态控制矩阵来估计信号子空间，因此该算法可以有效地处理DOA密集的目标。理论分析和仿真结果均表明，该算法显着提高了DOA估计精度，且计算成本较低。由于该算法不需要用病态控制矩阵来估计信号子空间，因此该算法可以有效地处理DOA密集的目标。理论分析和仿真结果均表明，该算法显着提高了DOA估计精度，且计算成本较低。