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To overcome the contradiction between wide swath and high resolution in synthetic aperture radar systems, a multichannel azimuth reconstruction method is investigated to unambiguously recover the Doppler spectrum. The proposed method is derived from the least squares principle by exploiting a Vandermonde component of the system matrix. The Vandermonde matrix is Doppler independent and data independent...
Subspace learning plays a key role in pattern recognition and machine learning. However, its performance would be degraded when data are corrupted by various occlusions. Low-rank representation (LRR) can recover the corrupted data and explore low-dimensional subspace structures embedded in data. Inspired by low-rank representation and subspace learning, in this paper, we propose a regularized low-rank...
To overcome the contradiction between wide unambiguous swath and high azimuth resolution in synthetic aperture radar (SAR) system, a multi-channel reconstruction method is investigated to unambiguously recover the azimuth signal even for nonuniform spatial samplings. This reconstruction method is derived from matrix inversion method under least square principle. By taking the system additive noise...
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