Unsupervised Unknown Radar Waveform Detection

This paper proposes a high-accuracy method for detecting unknown radar waveforms using an unsupervised denoising network. The proposed method integrates a Deep Shrinkage Autoencoder (DSAE) and a Memory-Augmented Additional Autoencoder (MAAE). The increasing deployment of radar systems in military su...

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Veröffentlicht in:	IEEE transactions on aerospace and electronic systems S. 1 - 12
Hauptverfasser:	Yoon, Jaehyeok, Nam, Haewoon
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	Accuracy Autoencoders Deep learning Deep shrinkage autoencoder Feature extraction Low SNR environments Memory-based additional autoencoder Noise reduction Radar Radar detection Radar imaging Signal to noise ratio Training Unknown radar waveform detection Unsupervised denoising
ISSN:	0018-9251, 1557-9603
Online-Zugang:	Volltext
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