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. 2015 Feb 12;15(2):4176-92.
doi: 10.3390/s150204176.

Compressive SAR imaging with joint sparsity and local similarity exploitation

Fangfang Shen  1 , Guanghui Zhao  2 , Guangming Shi  3 , Weisheng Dong  4 , Chenglong Wang  5 , Yi Niu  6
Affiliations

Compressive SAR imaging with joint sparsity and local similarity exploitation

Fangfang Shen et al. Sensors (Basel). .

Abstract

Compressive sensing-based synthetic aperture radar (SAR) imaging has shown its superior capability in high-resolution image formation. However, most of those works focus on the scenes that can be sparsely represented in fixed spaces. When dealing with complicated scenes, these fixed spaces lack adaptivity in characterizing varied image contents. To solve this problem, a new compressive sensing-based radar imaging approach with adaptive sparse representation is proposed. Specifically, an autoregressive model is introduced to adaptively exploit the structural sparsity of an image. In addition, similarity among pixels is integrated into the autoregressive model to further promote the capability and thus an adaptive sparse representation facilitated by a weighted autoregressive model is derived. Since the weighted autoregressive model is inherently determined by the unknown image, we propose a joint optimization scheme by iterative SAR imaging and updating of the weighted autoregressive model to solve this problem. Eventually, experimental results demonstrated the validity and generality of the proposed approach.

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Figures

Figure 1.
Figure 1.
(a) SAR image; (b) non-stationary patch; (c) distribution of the SSP.
Figure 2.
Figure 2.
The spatial configuration of the weighted AR model.
Figure 3.
Figure 3.
(a) Full SAR echo; (b) Undersampled return.
Figure 4.
Figure 4.
Image recovered from full data.
Figure 5.
Figure 5.
Reconstruction comparison from undersampled SAR echoes. (a) Imaging by [9]; (b) Imaging by [10]; (c) Imagingby [4]; (d) Imaging by ASR-CS-SAR.
Figure 6.
Figure 6.
Comparison of the reconstruction performance. (a)33% sampling rate in range; (b) 25% sampling rate in azimuth.
Figure 7.
Figure 7.
Test images. (a) Image 1; (b) Image 2; (c) Image 3; (d) Image 4; (e) Image 5; (f) Image 6; (g) Image 7.
Figure 8.
Figure 8.
Comparison of the reconstructed images: (a) The defocus image; (b) RD imaging with motion compensation; (c) CS-SAR imaging with motion compensation [18]; and (d) ASR-CS-SAR imaging with motion compensation.
See this image and copyright information in PMC

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