强地杂波下基于压缩感知的稀疏子脉冲高分辨雷达成像方法

High Resolution Radar Imaging Method Based on Compressed Sensing in Strong Ground Clutter with Sparse Sub-pulses

  • 摘要: 针对稀疏雷达孔径数据处理与成像问题,本文提出了一种强地杂波背景下基于压缩感知(CS)的线性调频步进信号(SFCS)稀疏子脉冲高分辨雷达成像方法。在对稀疏回波数据解线调时,采用填零一次相消技术剔除地杂波,对粗分辨距离像序列二次采样后获得高信杂比的目标高分辨回波信号;再利用该信号的频域稀疏特性,结合各脉冲簇中随机丢失不同子脉冲的情况,构造相应的部分傅里叶基矩阵实现雷达数据的稀疏化表征,然后利用正交匹配追踪(OMP)算法对目标高分辨距离像(HRRP)进行重构处理,实现对目标的高分辨成像。仿真结果验证了本文方法的有效性。

     

    Abstract: In the face of the question of sparse aperture data imaging, a method for high resolution radar imaging based on compressed sensing in strong ground clutter using sparse stepped frequency chirp signal (SFCS) is proposed in this letter. Firstly, the zero-padding one-order canceller method is utilized to filter out the ground clutter in the signal stretching process, high resolution target echo can be acquired through second sample for the coarse resolution range profile, and then making use of the sparsity of the signal in the spectrogram, we can construct a reasonable partial fourier sparse basis matrix to realize the sparseness of radar data. Next, the high resolution range profile (HRRP) is recovered by using the orthogonal matching pursuit (OMP) algorithm, and the high resolution target imaging can be gained. Finally, simulation results validate the superiority of the approach.

     

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