Bridging a Gap in SAR-ATR: Training on Fully Synthetic and Testing on Measured Data

Bridging a Gap in SAR-ATR: Training on Fully Synthetic and Testing on Measured Data

Obtaining measured synthetic aperture radar (SAR) data for training automatic target recognition (ATR) models can be too expensive (in terms of time and money) and complex of a process in many situations. In response, researchers have developed methods for creating synthetic SAR data for targets usi...

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Bibliographic Details
Main Authors: Nathan Inkawhich, Matthew J. Inkawhich, Eric K. Davis, Uttam K. Majumder, Erin Tripp, Chris Capraro, Yiran Chen
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Automatic target recognition (ATR)
deep learning
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/9356129/

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