In this article, we focus on the bistatic multiple-input multiple-output (MIMO) radar that performs one-bit quantization of received echo data. Based on the one-bit bistatic MIMO radar, we devise an effective algorithm for joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation. By exploiting the signal sparsity, we first formulate a decoupled atomic norm minimization problem to reconstruct two noise-free covariance matrices from one-bit quantized data. Subsequently, we apply the MUSIC algorithm on two reconstructed matrices to estimate the DODs and DOAs of targets, respectively. Furthermore, an additional procedure is proposed to achieve pairing of the estimated DODs and DOAs. The proposed algorithm can achieve satisfactory estimation performance only using single-pulse data. Numerical results demonstrate the effectiveness of the proposed algorithm.

中文翻译：

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通过原子范数最小化使用一位采样的双基地 MIMO 雷达角度估计


在本文中，我们重点关注对接收的回波数据执行一位量化的双基地多输入多输出 (MIMO) 雷达。基于一位双基地 MIMO 雷达，我们设计了一种有效的联合出发方向（DOD）和到达方向（DOA）估计算法。通过利用信号稀疏性，我们首先制定解耦原子范数最小化问题，以从一位量化数据重建两个无噪声协方差矩阵。随后，我们将 MUSIC 算法应用于两个重建矩阵，分别估计目标的 DOD 和 DOA。此外，还提出了一个额外的程序来实现估计的 DOD 和 DOA 的配对。所提出的算法仅使用单脉冲数据即可获得令人满意的估计性能。数值结果证明了该算法的有效性。