Radar Target Classification Using Deep Learning

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초록

This chapter describes various applications of deep learning algorithms to radar images. In particular, the classification of micro-Doppler spectrograms, range-Doppler diagrams, and synthetic aperture radar images is addressed in terms of convolutional neural networks and recurrent neural networks. The applications discussed include human motion classification, hand gesture recognition, drone detection, vehicle detection, ship detection, and more. Advanced deep learning techniques, such as transfer learning, generative adversarial networks, and continual learning, are also applied to radar images, and their performance is evaluated. © 2023 by The Institute of Electrical and Electronics Engineers, Inc.

키워드

continual learningconvolutional neural networksdeep learninggenerative adversarial networksmicro-Doppler signaturesradar imagerecurrent neural networkssynthetic aperture radartransfer learning
제목
Radar Target Classification Using Deep Learning
저자
Kim, Youngwook
DOI
10.1002/9781119853923.ch16
발행일
2023-01-01
유형
Book Chapter
저널명
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning
페이지
487 ~ 514