稀疏孔径下的运动补偿及快速超分辨成像方法

发布时间：2018-03-19 10:19

本文选题：稀疏孔径　切入点：逆合成孔径雷达成像　出处：《电子学报》2017年02期 　论文类型：期刊论文

【摘要】：针对稀疏孔径条件下目标运动补偿难和方位稀疏成像算法效率低、分辨率差等问题,本文提出了一种稀疏孔径下的运动补偿和快速超分辨成像方法.首先,通过将运动补偿问题转换为距离频域内的多参数估计问题,基于黄金分割法实现参数的快速估计后同时实现包络对齐和相位校正,从而完成运动补偿;其次,针对补偿后不同距离单元ISAR回波的特征,为实现快速的方位成像,本文提出矩阵形式的Nesterov线性Bregman迭代算法(Matrix form of Nesterov Linearized Bregman Iteration,MNLBI)算法,分析了该算法的基本迭代格式,讨论了加快收敛的原因,并详细分析了该算法的运算量,仿真与实测数据结果验证了本文方法的有效性.
[Abstract]:In order to solve the problems of difficult motion compensation for targets with sparse aperture, low efficiency and poor resolution of azimuth sparse imaging algorithm, a motion compensation method and a fast super-resolution imaging method under sparse aperture are proposed in this paper. By converting the motion compensation problem to the multi-parameter estimation problem in the range frequency domain, the fast estimation of parameters is realized based on the golden section method, and then the envelope alignment and phase correction are realized at the same time. Then, the motion compensation is completed. In order to realize the fast azimuth imaging, the matrix form of Nesterov Linearized Bregman iteration algorithm (MNLBI) is proposed in this paper, and the basic iterative scheme of the algorithm is analyzed, aiming at the characteristics of the ISAR echo of different distance elements after compensation, and in order to realize the fast azimuth imaging, this paper presents the matrix form of Nesterov Linearized Bregman iteration algorithm (MNLBI). The reason of accelerating convergence is discussed and the computational complexity of the algorithm is analyzed in detail. The effectiveness of the proposed method is verified by simulation and measured data.
【作者单位】：空军预警学院研究生队;空军预警学院三系;
【基金】：国家自然科学基金(No.61179014)
【分类号】：TN957.52

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