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Synthetic aperture radar (SAR) has been widely used in remote sensing. Feature extraction is a crucial step in SAR automatic target recognition (ATR). In this paper, Kernel Marginal Sample Discriminant Embedding (KMSDE) is proposed, which is based on kernel trick and manifold learning theory. In feature extraction via KMSDE, the original dataset is mapped to high dimensional space and manifold learning...
Fast Factorized Back-projection (FFBP) is a new way to fix the high computation problem in Back-projection (BP) but it still keeps high-resolution and strong adaptability in synthetic aperture radar (SAR). However, Applying conventional autofocus methods to both BP and FFBP requires a special consideration. In this letter, we present a new method to solve the phase error problem. We establish a evaluation...
Bistatic synthetic aperture radar (SAR) possesses plenty of unique benefits compared to monostatic SAR. As a key performance parameter for SAR, the spatial resolution for bistatic SAR (BSAR) is much more difficult to measure than that of monostatic SAR due to the complex coupling of the range and azimuth profiles caused by the nonorthogonality of the range and azimuth resolution direction. To address...
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