| Presentation | 2022-12-14 A fundamental study of a drone classification method applying CNN to range and Doppler images obtained by a millimeter-wave fast chirp MIMO radar Masashi Kurosaki, Kenshi Ogawa, Ryohei Nakamura, Hisaya Hadama, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we propose a method to classifying various drones from range profile and micro Doppler images of a drone obtained by a millimeter-wave fast chirp MIMO radar by using a convolutional neural network (CNN) model. We investigate the classification performance for four types of drones with different shapes, sizes, and the number of rotor blades (Matrice 600, Phantom3, Mavic pro, and Mavic mini) and radio-controlled flapping bird (Bionic bird). As a result, we have confirmed that our proposed method can classified each target with high accuracy of 94.7 % or more. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Millimeter-wave radar / fast chirp modulation / drone classification / micro doppler / deep learning |
| Paper # | WBS2022-46,ITS2022-22,RCC2022-46 |
| Date of Issue | 2022-12-06 (WBS, ITS, RCC) |
| Conference Information | |
| Committee | RCC / ITS / WBS |
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| Conference Date | 2022/12/13(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Ritsumeikan Univ. BKC |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Shunichi Azuma(Nagoya Univ.) / Masahiro Fujii(Utsunomiya Univ.) / Takashi Shono(INTEL) |
| Vice Chair | Shunichi Azuma(Hokkaido Univ.) / Koji Ishii(Kagawa Univ.) / Kohei Ohno(Meiji Univ.) / Naohisa Hashimoto(AIST) / Hiroyasu Ishikawa(Nihon Univ.) / Hideki Ochiai(Yokohama National Univ.) |
| Secretary | Shunichi Azuma(CRIEPI) / Koji Ishii(Ritsumeikan Univ.) / Kohei Ohno(Toyama Prefectural Univ.) / Naohisa Hashimoto(NIT, Tsuruoka College) / Hiroyasu Ishikawa(Okayama Prefectural Univ.) / Hideki Ochiai(Chiba Univ. of Tech.) |
| Assistant | SHAN LIN(NICT) / Ryosuke Adachi(Yamaguchi Univ.) / Msataka Imao(Mitsubishi Electric) / Taishi Swabe(NAIST) / Keiji Jimi(Gunma Univ.) / Sun Ran(Ibaraki Univ.) / Chen Na(NAIST) |
| Paper Information | |
| Registration To | Technical Committee on Reliable Communication and Control / Technical Committee on Intelligent Transport Systems Technology / Technical Committee on Wideband System |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A fundamental study of a drone classification method applying CNN to range and Doppler images obtained by a millimeter-wave fast chirp MIMO radar |
| Sub Title (in English) | |
| Keyword(1) | Millimeter-wave radar |
| Keyword(2) | fast chirp modulation |
| Keyword(3) | drone classification |
| Keyword(4) | micro doppler |
| Keyword(5) | deep learning |
| 1st Author's Name | Masashi Kurosaki |
| 1st Author's Affiliation | National Defense Academy of Japan(NDA) |
| 2nd Author's Name | Kenshi Ogawa |
| 2nd Author's Affiliation | National Defense Academy of Japan(NDA) |
| 3rd Author's Name | Ryohei Nakamura |
| 3rd Author's Affiliation | National Defense Academy of Japan(NDA) |
| 4th Author's Name | Hisaya Hadama |
| 4th Author's Affiliation | National Defense Academy of Japan(NDA) |
| Date | 2022-12-14 |
| Paper # | WBS2022-46,ITS2022-22,RCC2022-46 |
| Volume (vol) | vol.122 |
| Number (no) | WBS-307,ITS-308,RCC-309 |
| Page | pp.pp.65-70(WBS), pp.65-70(ITS), pp.65-70(RCC), |
| #Pages | 6 |
| Date of Issue | 2022-12-06 (WBS, ITS, RCC) |