| Presentation | 2019-01-24 Accuracy Comparisons between Deep-Learning Based Angle of Arrival Estimation and MUSIC method Toyosaka Yamasaki, Taichi Ohtsuji, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Direction of arrival estimation techniques are used for radio localization of radio transmitters. As a representative localization method, there is a method of obtaining the intersection point from the angle of arrival (AOA) of the radio wave estimated by each of the two radio sensors. In this report, we compare a deep-learning based AOA estimation method and multiple signal classification (MUSIC) method. As is the case with MUSIC method, the deep-learning based method requires to separate multiple and different angle of arrival signals. This report shows the results of study on the case of changing the number of incident signals of learning data and that of estimating data. The theoretical characteristics of array antenna depend on the geometric arrangement of the antenna elements. However, the practical characteristics are affected by antenna element coupling and the other non-ideal phenomena. We show approximation formulae of the characteristics of antenna element coupling, and the effects on the AOA estimation results. These studies clarified that the performance of the deep-learning based AOA estimation method is better than that of MUSIC method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | AOA / DOA / Deep Learning / MUSIC |
| Paper # | SR2018-104 |
| Date of Issue | 2019-01-17 (SR) |
| Conference Information | |
| Committee | SR |
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| Conference Date | 2019/1/24(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Corasse, Fukushima city (Fukushima prefecture) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | cognitive radio, machine learning application, heterogeneous network, SDN, IoT etc. |
| Chair | Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) |
| Vice Chair | Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) |
| Secretary | Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) |
| Assistant | Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(Mie Univ.) / Koji Ohshima(Kozo Keikaku Engineering) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) |
| Paper Information | |
| Registration To | Technical Committee on Smart Radio |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Accuracy Comparisons between Deep-Learning Based Angle of Arrival Estimation and MUSIC method |
| Sub Title (in English) | Impact to Estimation Accuracy of Antenna Element Coupling |
| Keyword(1) | AOA |
| Keyword(2) | DOA |
| Keyword(3) | Deep Learning |
| Keyword(4) | MUSIC |
| 1st Author's Name | Toyosaka Yamasaki |
| 1st Author's Affiliation | NEC Platforms, Ltd(NECPF) |
| 2nd Author's Name | Taichi Ohtsuji |
| 2nd Author's Affiliation | NEC Corporation(NEC) |
| Date | 2019-01-24 |
| Paper # | SR2018-104 |
| Volume (vol) | vol.118 |
| Number (no) | SR-421 |
| Page | pp.pp.49-56(SR), |
| #Pages | 8 |
| Date of Issue | 2019-01-17 (SR) |