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Title: Motion parameter estimation in the SAR system with low PRF sampling
Authors: Wu, Q.
Xing, M.
Qiu, C. 
Liu, B.
Bao, Z.
Yeo, T.-S. 
Keywords: Compressed sensing (CS)
motion parameter estimation
Radon transform (RT)
synthetic aperture radar (SAR)
Issue Date: Jul-2010
Citation: Wu, Q., Xing, M., Qiu, C., Liu, B., Bao, Z., Yeo, T.-S. (2010-07). Motion parameter estimation in the SAR system with low PRF sampling. IEEE Geoscience and Remote Sensing Letters 7 (3) : 450-454. ScholarBank@NUS Repository.
Abstract: A novel approach to motion parameter estimation with low pulse repetition frequency (PRF) sampling based on compressed sensing (CS) theory is introduced. As is known to us, when PRF is less than the Doppler spectrum bandwidth, moving targets suffer both Doppler centroid frequency ambiguity and Doppler spectrum ambiguity. Under this condition, the traditional parameter estimation method in the Doppler domain is out of action. The key of this letter converts motion parameter estimation in the synthetic aperture radar system with low PRF sampling into solving an optimization equation based on CS theory. Because moving targets in the scene can be regarded as sparse signals after clutter cancellation, an optimization algorithm based on CS theory is proposed to reconstruct sparse signals and meanwhile estimate the along-track velocities and azimuth positions of moving targets. Considering the fact that range cell migration of moving targets is not subject to PRF limitations, Radon transform is adopted to obtain unambiguous across-track velocities and range positions. Results on simulation and real data are provided to show the effectiveness of this method. © 2010 IEEE.
Source Title: IEEE Geoscience and Remote Sensing Letters
ISSN: 1545598X
DOI: 10.1109/LGRS.2009.2039113
Appears in Collections:Staff Publications

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