基于压缩感知的宽带成像雷达Chirp信号回波的压缩和重构

针对宽带成像雷达chirp信号回波按照带通采样定理采样得到的数据量大所导致的存储压力大的问题，本文提出基于压缩感知的chirp信号回波压缩和重构方法，首先就回波是否可压缩，利用chirplet变换分析了chirp信号回波的稀疏性，在信号稀疏的基础上，应用chirplet变换给出了可应用于压缩感知的稀疏字典及其简化形式，并证明了所给出的简化形式稀疏字典满足信号重构的条件。最后给出了回波的压缩和重构方法并结合ISAR成像进行了数字实验，先在目标转动加平动模型下，进行了数据的压缩和重构，通过比较重构信号和原信号的时域波形、高分辨距离像和ISAR成像结果，验证了本文的方法。最后仿真分析了重构误差随信噪比的变化曲线，说明了本文的方法对信噪比的要求。 

Compression and Reconstruction of Chirp Echo of Broadband Imaging Radar Based on Compressed Sensing

Under Band-Pass sampling theorem, the chirp echo of broadband imaging radar brings large data quantity and it is hard to store. In order to solve this problem, this paper put forward the compression and reconstruction method under the compressed sensing theory. Firstly, the sparseness of echo is researched using chirplet transform for whether the echo is compressible. Secondly, under the sparseness of the echo, the practicable sparsity dictionary and its compact form in compressed sensing is given based on chirplet transform and the qualification of sparse dictionary in compact form for recovery is proved. In the end, the compression and reconstruction method for the echo is given and the numerical experiment under the inverse synthetically aperture radar (ISAR) is done. In the model of rotation with movement, the data is compressed and reconstructed. From the comparison of time-domain waveform, high resolution range profile (HRRP) and ISAR image between original and the recovered data, the efficiency of compressing method is validated. In the end, the curve of error for reconstruction corresponding to signal-noise-ratio (SNR) is analyzed and the demand of the method put forward in this paper to SNR is shown.