压缩感知雷达超分辨率成像

doi:10.3969/j.issn.0255-8297.2014.02.004

Abstract

Abstract: 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.

Key words: compressed sensing (CS), radar image, reconstruction, super-resolution

CLC Number:

TN911

DENG Zhen-miao, YE Lin-mei, FU Mao-zhong, ZHANG Yi-xiong. Radar Super-Resolution Imaging Based on Compressive Sensing[J]. Journal of Applied Sciences, 2014, 32(2): 133-140.

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URL: https://www.jas.shu.edu.cn/EN/10.3969/j.issn.0255-8297.2014.02.004

https://www.jas.shu.edu.cn/EN/Y2014/V32/I2/133

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Radar Super-Resolution Imaging Based on Compressive Sensing

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