Robust DoA Estimation Using Denoising Autoencoder and Deep Neural Networks

As one of the most critical technology in array signal processing, direction of arrival (DoA) estimation has received a great deal of attention in many areas. Traditional methods perform well when the signal-to-noise ratio (SNR) is high and the receiving array is perfect, which are quite different f...

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Veröffentlicht in:	IEEE access Jg. 10; S. 52551 - 52564
Hauptverfasser:	Chen, Dawei, Shi, Shuo, Gu, Xuemai, Shim, Byonghyo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Array signal processing Arrays Artificial neural networks Covariance matrices deep neural networks denoising autoencoder Direction of arrival Direction-of-arrival estimation DoA Estimation Feature extraction Machine learning Mutual coupling Neural networks Noise reduction Robustness Signal processing Signal to noise ratio SNR
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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