Presentation 2018-07-11
A Fundamental Study on Direction of Arrival Estimation with Deep Learning
Yuya Kase, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Direction of arrival (DOA) estimation of radio waves is applicable to localization of wireless terminals and radar systems. In addition to MUSIC and ESPRIT, which are well-known traditional algorithms, compressed sensing has been applied to DOA estimation. Compressed sensing has a higher accuracy compared with MUSIC in general but requires larger computational load. If such a large computational load is acceptable, we can consider to apply deep learning to DOA estimation. In this paper, we propose an estimation method using deep learning, especially with an additional network designed for closely located sources, and examine its basic characteristics in the case where two narrow-band signals impinge on a linear array. The simulation results show that high estimation accuracy is obtained and that the performance depends on the learning data sets.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) DOA estimation / deep learning
Paper # RCC2018-33,NS2018-46,RCS2018-88,SR2018-27,ASN2018-27
Date of Issue 2018-07-04 (RCC, NS, RCS, SR, ASN)

Conference Information
Committee ASN / NS / RCS / SR / RCC
Conference Date 2018/7/11(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Hakodate Arena
Topics (in Japanese) (See Japanese page)
Topics (in English) Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc.
Chair Hiraku Okada(Nagoya Univ.) / Yoshikatsu Okazaki(NTT) / Tomoaki Otsuki(Keio Univ.) / Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Kazunori Hayashi(Osaka City Univ.)
Vice Chair Koji Yamamoto(Kyoto Univ.) / Jin Nakazawa(Keio Univ.) / Kazuya Monden(Hitachi) / Akihiro Nakao(Univ. of Tokyo) / Eisuke Fukuda(Fujitsu Labs.) / Satoshi Suyama(NTT DoCoMo) / Fumiaki Maehara(Waseda Univ.) / Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) / Shunichi Azuma(Nagoya Univ.) / HUAN-BANG LI(NICT)
Secretary Koji Yamamoto(NICT) / Jin Nakazawa(Sophia Univ.) / Kazuya Monden(Kanagawa Inst. of Tech.) / Akihiro Nakao(NTT) / Eisuke Fukuda(Osaka Pref Univ.) / Satoshi Suyama(Hokkaido Univ.) / Fumiaki Maehara(NTT) / Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) / Shunichi Azuma(Univ. of Electro-Comm.) / HUAN-BANG LI(Kagawa Univ.)
Assistant Masafumi Hashimoto(Osaka Univ.) / Tomoyuki Ota(Hiroshima City Univ.) / Tatsuya Kikuzuki(Fujitu Lab.) / Ryo Nakano(HITACHI) / Yoshifumi Hotta(Mitsubishi Electric) / Kenichi Kashibuchi(NTT) / Kazushi Muraoka(NTT DOCOMO) / Shinsuke Ibi(Osaka Univ.) / Hiroshi Nishimoto(Mitsubishi Electric) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(Mie Univ.) / Koji Ohshima(Kozo Keikaku Engineering) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Toshinori Kagawa(NICT) / Masateru Ogura(NAIST)

Paper Information
Registration To Technical Committee on Ambient intelligence and Sensor Networks / Technical Committee on Network Systems / Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Reliable Communication and Control
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Fundamental Study on Direction of Arrival Estimation with Deep Learning
Sub Title (in English)
Keyword(1) DOA estimation
Keyword(2) deep learning
1st Author's Name Yuya Kase
1st Author's Affiliation Hokkaido University(Hokkaido Univ.)
2nd Author's Name Toshihiko Nishimura
2nd Author's Affiliation Hokkaido University(Hokkaido Univ.)
3rd Author's Name Takeo Ohgane
3rd Author's Affiliation Hokkaido University(Hokkaido Univ.)
4th Author's Name Yasutaka Ogawa
4th Author's Affiliation Hokkaido University(Hokkaido Univ.)
Date 2018-07-11
Paper # RCC2018-33,NS2018-46,RCS2018-88,SR2018-27,ASN2018-27
Volume (vol) vol.118
Number (no) RCC-123,NS-124,RCS-125,SR-126,ASN-127
Page pp.pp.51-55(RCC), pp.57-61(NS), pp.51-55(RCS), pp.39-43(SR), pp.67-71(ASN),
#Pages 5
Date of Issue 2018-07-04 (RCC, NS, RCS, SR, ASN)