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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >
Deep Neural Networks Based End-to-End DOA Estimation System
| Title: | Deep Neural Networks Based End-to-End DOA Estimation System |
| Authors: | Ando, Daniel Akira Browse this author | | Kase, Yuya Browse this author | | Nishimura, Toshihiko Browse this author | | Sato, Takanori Browse this author | | Ohganey, Takeo Browse this author | | Ogawa, Yasutaka Browse this author | | Hagiwara, Junichiro Browse this author |
| Keywords: | antenna array | | DOA estimation | | SNR estimation | | source number estimation | | deep neural network |
| Issue Date: | 1-Dec-2023 |
| Publisher: | IEICE - Institute of the Electronics, Information and Communication Engineers |
| Journal Title: | IEICE transactions on communications |
| Volume: | E106B |
| Issue: | 12 |
| Start Page: | 1350 |
| End Page: | 1362 |
| Publisher DOI: | 10.1587/transcom.2023CEP0006 |
| Abstract: | 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. |
| Rights: | copyright©2023 IEICE |
| Type: | article |
| URI: | http://hdl.handle.net/2115/91226 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 大鐘 武雄
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