ABSTRACT

In view of inverse synthetic aperture radar (ISAR) imaging, sparse aperture not only affects the imaging quality of traditional range Doppler (RD) algorithm but also increases the difficulty of translational motion compensation (TMC). For the purpose of reducing the influence of motion errors on the target imaging, reweighted alternating direction method of multipliers (RADMM) is proposed to realize the joint processing of phase adjustment and ISAR imaging. Combined with pattern-coupled sparse structure (PCSS) information of the target, the reweighted $l_1$ norm minimization problem is established first. Then, the minimum entropy method is adopted to estimate the phase error, and the iterative process of RADMM is deduced. Finally, the experimental results based on two sets of measured data demonstrate the validity of the proposed algorithm under the conditions of noise and sparse aperture.

摘要

针对逆合成孔径雷达（ISAR）成像，稀疏孔径不仅影响传统距离多普勒（RD）算法的成像质量，而且增加了平移运动补偿（TMC）的难度。为减少运动误差对目标成像的影响，提出了重加权乘法器交替方向法（RADMM）实现相位调整和ISAR成像的联合处理。结合目标的模式耦合稀疏结构（PCSS）信息，重新加权$l_1$首先建立范数最小化问题。然后，采用最小熵法估计相位误差，推导出RADMM的迭代过程。最后，基于两组实测数据的实验结果证明了所提算法在噪声和稀疏孔径条件下的有效性。