Sparse Three-dimensional Imaging Based on Hough Transform for Forward-looking Array SAR in Low SNR

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Abstract The performance of sparse reconstruction algorithm of compressive sensing in low Signal-to-Noise Ratio (SNR) is lower, and the quality of sparse three-dimensional imaging for forward-looking array synthetic aperture radar in low SNR is reduced greatly. To solve this problem, a validate method of reconstruction algorithm of compressive sensing based on Hough transform is proposed, in which the continuity of the scattering coefficient vector in the two-dimensional space of range direction and slant range direction and the straight line detection method of Hough transform is used, and thus the reconstruction quality of compressive sensing is increased effectively. Also, the simulation experiments indicate that this method can improve the sparse three-dimensional imaging for forward-looking array SAR in low SNR effectively.

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	Articles by authors
	Liu Xiangyang
	Yang Jungang
	Meng Jin
	Zhang Xiao
	Niu Dezhi

Key words： Forward-looking array Synthetic Aperture Radar (SAR) Three-dimensional imaging Compressive sensing Sparse imaging Hough transform

Received: 2017-01-23; Published: 2017-06-22

Fund: The National Natural Science Foundation of China (61640006), The Natural Science Foundation of Shaanxi Province (2015JM6307)

Cite this article:

Liu Xiangyang,Yang Jungang,Meng Jin et al. Sparse Three-dimensional Imaging Based on Hough Transform for Forward-looking Array SAR in Low SNR[J]. JOURNAL OF RADARS, 2017, 6(3): 316-323.

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