In this paper, a space-time adaptive processing (STAP) method is proposed for the airborne radar with the array amplitude-phase error considered, which is based on atomic norm minimization (ANM). In the conventional ANM-based STAP method, the influence of the array amplitude-phase error is not considered and restrained, which inevitably causes performance deterioration. To solve this problem, the array amplitude-phase error is firstly estimated. Then, by pre-estimating the array amplitude-phase error information, a modified ANM model is built, in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix (CCM) to improve the estimation accuracy of the CCM. To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error, the clutter sparsity is analyzed in this paper. Meanwhile, simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method. Moreover, the measured data is used to verify the effectiveness of the proposed method.

中文翻译：

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基于原子范数最小化和阵列幅度相位误差标定的STAP方法

本文提出了一种基于原子范数最小化（ANM）的考虑阵列幅度-相位误差的机载雷达空时自适应处理（STAP）方法。在传统的基于ANM的STAP方法中，没有考虑和限制阵列幅度相位误差的影响，这不可避免地导致性能下降。为了解决这个问题，首先估计阵列幅度相位误差。然后，通过预先估计阵列幅度相位误差信息，建立了改进的ANM模型，其中将阵列幅度相位误差因子与杂波响应和杂波协方差矩阵（CCM）分开以提高估计的准确性。 CCM。为了证明原子范数理论适用于存在阵列幅度相位误差的情况，本文对杂波稀疏性进行了分析。同时，仿真结果表明，该方法优于最新的STAP方法。此外，实测数据用于验证所提出方法的有效性。