Deep Neural Networks Based End-to-End DOA Estimation System

Ando, Daniel Akira; Kase, Yuya; Nishimura, Toshihiko; Sato, Takanori; Ohganey, Takeo; Ogawa, Yasutaka; Hagiwara, Junichiro

Deep Neural Networks Based End-to-End DOA Estimation System

Ando, Daniel Akira; Kase, Yuya; Nishimura, Toshihiko et al.

IEICE transactions on communications, 2023, E106B(12), 1350-1362

Permalink : https://hdl.handle.net/2115/91226

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論文情報

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アクセス権	open access
URI	https://hdl.handle.net/2115/91226
タイトル	Deep Neural Networks Based End-to-End DOA Estimation System
著者	Ando, Daniel Akira ; Kase, Yuya ; Nishimura, Toshihiko ; Sato, Takanori ; Ohganey, Takeo ; Ogawa, Yasutaka ; Hagiwara, Junichiro
著者名 Ando, Daniel Akira
著者名 Kase, Yuya
著者名 Nishimura, Toshihiko
著者名 Sato, Takanori
著者名 Ohganey, Takeo
著者名 Ogawa, Yasutaka
著者名 Hagiwara, Junichiro
言語	英語
キーワード	antenna array
	DOA estimation
	SNR estimation
	source number estimation
	deep neural network
発行日	2023-12-01
出版者	IEICE - Institute of the Electronics, Information and Communication Engineers
収録物名	IEICE transactions on communications
巻(号)	E106B(12)
ページ	1350-1362
抄録	Direction of arrival (DOA) estimation is an antenna array signal processing technique used in, for instance, radar and sonar systems, source localization, and channel state information retrieval. As new applications and use cases appear with the development of next generation mobile communications systems, DOA estimation performance must be continually increased in order to support the nonstop growing demand for wireless technologies. In previous works, we verified that a deep neural network (DNN) trained offline is a strong candidate tool with the promise of achieving great on-grid DOA estimation performance, even compared to traditional algorithms. In this paper, we propose new techniques for further DOA estimation accuracy enhancement incorporating signal-to-noise ratio (SNR) prediction and an end-to-end DOA estimation system, which consists of three components: source number estimator, DOA angular spectrum grid estimator, and DOA detector. Here, we expand the performance of the DOA detector and angular spectrum estimator, and present a new solution for source number estimation based on DNN with very simple design. The proposed DNN system applied with said enhancement techniques has shown great estimation performance regarding the success rate metric for the case of two radio wave sources although not fully satisfactory results are obtained for the case of three sources.
資源タイプ	学術雑誌論文
出版タイプ	Version of Record
権利情報	copyright©2023 IEICE
PISSN	0916-8516
関連情報 (isIdenticalTo)	出版社版DOI https://doi.org/10.1587/transcom.2023CEP0006