The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Resolution Enhancement for Inversed Synthetic Aperture Radar Imaging Under Low SNR via Improved Compressive Sensing
Abstract
The theory of compressed sampling (CS) indicates that exact recovery of an unknown sparse signal can be achieved from very limited samples. For inversed synthetic aperture radar (ISAR), the image of a target is usually constructed by strong scattering centers whose number is much smaller than that of pixels of an image plane. This sparsity of the ISAR signal intrinsically paves a way to apply CS to the reconstruction of high-resolution ISAR imagery. CS-based high-resolution ISAR imaging with limited pulses is developed, and it performs well in the case of high signal-to-noise ratios. However, strong noise and clutter are usually inevitable in radar imaging, which challenges current high-resolution imaging approaches based on parametric modeling, including the CS-based approach. In this paper, we present an improved version of CS-based high-resolution imaging to overcome strong noise and clutter by combining coherent projectors and weighting with the CS optimization for ISAR image generation. Real data are used to test the robustness of the improved CS imaging compared with other current techniques. Experimental results show that the approach is capable of precise estimation of scattering centers and effective suppression of noise.
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Cites
Donoho, D. L. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2006.871582 · Cited by 23,994
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An Introduction To Compressive Sampling
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Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
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Stable signal recovery from incomplete and inaccurate measurements
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Atomic Decomposition by Basis Pursuit
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Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
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Enhancing Sparsity by Reweighted ℓ 1 Minimization
Candès, E. J., Wakin, M. B., & Boyd, S. P. (2008) · Journal of Fourier Analysis and Applications · doi:10.1007/s00041-008-9045-x · Cited by 4,863
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Metadata
- Authors
- Zhang, L., Xing, M., Qiu, C.-W., Li, J., Sheng, J., Li, Y., & Bao, Z.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2010-10
- Volume
- 48
- Issue
- 10
- Pages
- 3824-3838
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2161035945
- Cited by
- 317
- References
- 14
- FWCI
- 30.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, L., Xing, M., Qiu, C.-W., Li, J., Sheng, J., Li, Y., & Bao, Z. (2010). Resolution Enhancement for Inversed Synthetic Aperture Radar Imaging Under Low SNR via Improved Compressive Sensing. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/tgrs.2010.2048575
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