Detection of dispersive targets in synthetic aperture radar images with the help of deep learning
DOI10.3934/CAC.2024012MaRDI QIDQ6616139
S. Tsynkov, Sai Naga Vamshi Chidara, Rageeni Sah, Mikhail Gilman
Publication date: 8 October 2024
Published in: Communications on Analysis and Computation (Search for Journal in Brave)
convolutional neural network (CNN)target classificationrange-delay ambiguitycoordinate-delay SAR images (cdSAR)delayed scattering of electromagnetic waves
Inverse problems in geophysics (86A22) Inverse problems for PDEs (35R30) Inverse problems (including inverse scattering) in optics and electromagnetic theory (78A46) Inverse problems for integral equations (45Q05)
Cites Work
- Title not available (Why is that?)
- Transionospheric synthetic aperture imaging
- Spectral estimation of non-stationary white noise
- Statistical characterization of scattering delay in synthetic aperture radar imaging
- Deep learning approach to the detection of scattering delay in radar images
- A mathematical tutorial on synthetic aperture radar
- Time-frequency transforms for radar imaging and signal analysis. With a foreword by William J. Miceli
- Fundamentals of Radar Imaging
- Detection of delayed target response in SAR
- Materials identification synthetic aperture radar: progress toward a realized capability
- Inverse acoustic and electromagnetic scattering theory
- The Elements of Statistical Learning
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