压缩感知雷达超分辨率成像

Radar Super-Resolution Imaging Based on Compressive Sensing

研究压缩感知理论在逆合成孔径雷达(inverse synthetic aperture radar,ISAR)成像中的应用.雷达发射方位稀疏的探测脉冲,对满足Nyquist采样定理的雷达去斜回波数据进行稀疏采样,再利用压缩感知重构算法分别重构距离向和方位向的完整的目标特性回波信号.为了得到高分辨的雷达ISAR像,对重构的数据在距离向和方位向分别进行超分辨率处理.实际雷达数据和仿真数据表明ISAR像的分辨率有较大提高,所给出的综合方法可以降低数据量,节省雷达的时间资源,具有良好的应用价值.

Application of compressed sensing （CS） in inverse synthetic aperture radar is investigated in this paper. The radar transmits sparse probing pulses and dechirped radar echo samples that satisfy the Nyquist sampling theorem are resampled sparsely. Reconstruction is performed to these sparse samples both in range and cross-range directions to recover the whole radar echo signals containing the target characteristics. To obtain high resolution ISAR images, super-resolution processing on both range and cross-range directions is conducted on the reconstructed data. Results of processing on real radar data and simulated data show that the resolution of ISAR image can be enhanced significantly. The proposed algorithm can reduce data size and time consumption, and is valuable for super-resolution radar image applications.