| Presentation | 2019-04-19 A Study on DOA Estimation Using Deep Learning Yuya Kase, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Daisuke Kitayama, Yoshihisa Kishiyama, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Direction of arrival (DOA) estimation of radio waves is applicable tolocalization of users in mobile communication and radar systems. In addition to MUSIC and ESPRIT, which are well-known traditional algorithms, compressed sensing has been applied to DOA estimation with the development of computing resources. Although compressed sensing requires larger computational load, it has a higher accuracy compared with MUSIC in general. If such a large computational load is acceptable, it is expected that we can obtain the higher estimation accuracy by applying deep learning. In this paper, we consider an estimation method using deep learning and examine its characteristicsin the case where two narrow-band signals impinge on a linear array. The simulation results show that high estimation accuracy comparable to MUSIC is obtainedand that the performance highly depends on the training parameters. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | DOA estimation / array antenna / deep learning / deep neural network |
| Paper # | RCS2019-17 |
| Date of Issue | 2019-04-11 (RCS) |
| Conference Information | |
| Committee | RCS |
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| Conference Date | 2019/4/18(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Noboribetsu Grand Hotel |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Railroad Communications, Inter-Vehicle Communications, Road to Vehicle Communications, Radio Access Technologies, Wireless Communications, etc. |
| Chair | Tomoaki Otsuki(Keio Univ.) |
| Vice Chair | Eisuke Fukuda(Fujitsu Labs.) / Satoshi Suyama(NTT Docomo) / Fumiaki Maehara(Waseda Univ.) |
| Secretary | Eisuke Fukuda(Hokkaido Univ.) / Satoshi Suyama(NTT) / Fumiaki Maehara |
| Assistant | Kazushi Muraoka(NTT DocomoO) / Shinsuke Ibi(Osaka Univ.) / Hiroshi Nishimoto(Mitsubishi Electric) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) |
| Paper Information | |
| Registration To | Technical Committee on Radio Communication Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on DOA Estimation Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | DOA estimation |
| Keyword(2) | array antenna |
| Keyword(3) | deep learning |
| Keyword(4) | deep neural network |
| 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.) |
| 5th Author's Name | Daisuke Kitayama |
| 5th Author's Affiliation | NTT DOCOMO, INC.(NTT DOCOMO) |
| 6th Author's Name | Yoshihisa Kishiyama |
| 6th Author's Affiliation | NTT DOCOMO, INC.(NTT DOCOMO) |
| Date | 2019-04-19 |
| Paper # | RCS2019-17 |
| Volume (vol) | vol.119 |
| Number (no) | RCS-8 |
| Page | pp.pp.79-84(RCS), |
| #Pages | 6 |
| Date of Issue | 2019-04-11 (RCS) |