Synthesis of Micro-Doppler Signatures of Human Activities From Different Aspect Angles Using Generative Adversarial Networks

Synthesis of Micro-Doppler Signatures of Human Activities From Different Aspect Angles Using Generative Adversarial Networks

In this paper, we propose to produce synthesized micro-Doppler signatures from different aspect angles through conditional generative adversarial networks (cGANs). Micro-Doppler signatures of non-rigid human body motions vary considerably as a function of the radar’s aspect angle. Because...

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Bibliographic Details
Main Authors: Ibrahim Alnujaim, Shobha Sundar Ram, Daegun Oh, Youngwook Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Generative adversarial networks (GAN)
deep learning
micro-Doppler signatures
monostatic radar
multistatic radar
human activity
Online Access:https://ieeexplore.ieee.org/document/9383276/

Internet

https://ieeexplore.ieee.org/document/9383276/

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