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Title: Achieving higher resolution ISAR imaging with limited pulses via compressed sampling
Authors: Zhang, L.
Xing, M.
Qiu, C.-W. 
Li, J.
Bao, Z.
Keywords: Compressed sampling (CS)
High resolution
Inverse synthetic aperture radar (ISAR)
Sparse signal reconstruction
Issue Date: Jul-2009
Citation: Zhang, L., Xing, M., Qiu, C.-W., Li, J., Bao, Z. (2009-07). Achieving higher resolution ISAR imaging with limited pulses via compressed sampling. IEEE Geoscience and Remote Sensing Letters 6 (3) : 567-571. ScholarBank@NUS Repository.
Abstract: Recent theory of compressed sampling (CS) suggests that exact recovery of an unknown sparse signal with overwhelming probability can be achieved from very limited number of samples. In this letter, we adapt this idea and present a framework of high-resolution inverse synthetic aperture radar imaging with limited measured data. During the framework, we mathematically convert the imaging into a problem of signal reconstruction with orthogonal basis; hence, a conceptive upper bound of the cross-range resolution is presented based on the CS theory. Real data results show that the CS imaging approach outperforms the conventional range-Doppler one in resolution. © 2006 IEEE.
Source Title: IEEE Geoscience and Remote Sensing Letters
ISSN: 1545598X
DOI: 10.1109/LGRS.2009.2021584
Appears in Collections:Staff Publications

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