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| Presentation | 2022-12-14 11:30 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 (NDA)  WBS2022-46 ITS2022-22 RCC2022-46 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (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) |
| (in English) | Millimeter-wave radar / fast chirp modulation / drone classification / micro doppler / deep learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 307, WBS2022-46, pp. 65-70, Dec. 2022. | |
| Paper # | WBS2022-46 | |
| Date of Issue | 2022-12-06 (WBS, ITS, RCC) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | WBS2022-46 ITS2022-22 RCC2022-46 |
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| Conference Information | |
| Committee | RCC ITS WBS |
| Conference Date | 2022-12-13 - 2022-12-14 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Ritsumeikan Univ. BKC |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | WBS |
| Conference Code | 2022-12-RCC-ITS-WBS |
| Language | Japanese |
| 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 |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 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) |
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| Speaker | Author-1 |
| Date Time | 2022-12-14 11:30:00 |
| Presentation Time | 25 minutes |
| Registration for | WBS |
| Paper # | WBS2022-46, ITS2022-22, RCC2022-46 |
| Volume (vol) | vol.122 |
| Number (no) | no.307(WBS), no.308(ITS), no.309(RCC) |
| Page | pp.65-70 |
| #Pages | 6 |
| Date of Issue | 2022-12-06 (WBS, ITS, RCC) |
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