二维稀疏采样下的双通道SAR地面运动目标检测方法

多通道合成孔径雷达(synthetic aperture radar, SAR)地面运动目标检测系统具有良好的主瓣杂波抑制能力,但是其采样数据量过大的问题给数据存储与传输系统带来沉重负担。针对该问题,提出一种二维稀疏采样下的双通道SAR运动目标检测方法。该方法首先在距离和方位两维域进行随机稀疏采样，然后利用压缩感知技术对双通道的SAR回波数据进行联合处理，构造变换矩阵将目标能量支撑区从所有场景散射点的能量支撑区中进行分离，采用基于加权的最小l₁范数优化模型进行杂波抑制与运动目标成像。所提算法能够有效降低原始数据量，在杂波散射点的空间分布稀疏性较差的情况下，仍可以较好地检测地面运动目标。仿真实验验证了所提算法的有效性。

Dual-channel SAR-GMTI method based on sparse sampling in 2-dimensional domain

Multi-channel synthetic aperture radar (SAR) system has an excellent performance of main-lobe clutter suppression, but the resulting enormous amount of sampling raw data increases storage and transmission load. To alleviate this problem, a dual-channel SAR ground moving target indication (GMTI) method based on sparse sampling in 2-dimensional (2-D) domain is proposed. In this method, the signal is randomly and sparsely sampled in the range and azimuth 2-D directions, and then compressive sensing is utilized to process jointly the two channel raw data. A transform matrix is firstly constructed to separate the energy support areas of moving targets from the energy support areas of all scattering centers. Then, clutter suppression and moving target imaging are obtained by solving a weighted l₁ norm optimization. The proposed method performs well even if only a few SAR raw data are acquired and clutter scattering centers have a low sparse level. Simulation results demonstrate the effectiveness of the method.