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| Paper Abstract and Keywords | ||
| Presentation | 2020-03-11 09:30 A fundamental study on identification of various drones using ultra-wideband radar Takumi Mizushima, Ryohei Nakamura, Hisaya Hadama (NDA)  IT2019-115 ISEC2019-111 WBS2019-64 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, Drone technology is developing rapidly and various types of drones are used in many fields such as military, industry and academia. Low price and high performance drones have become spread and easy to get. Along with that, accidents and illegal acts of drones are increasing, and malicious uses such as terrorism are concerned. Therefore, establishing a method to detect and monitor drones is an important issue. We have reported that ultra-wideband (UWB) radar can measure unique echoes from a typical drone, and it is effective for distinguishing from other flying objects such as birds. In this paper, we experimentally clarify the reflection characteristics of three types of drones with different shapes, sizes and the number of rotors and a radio-controlled bird that flaps its wings. In addition, we report the results of a fundamental study on classification of the targets by machine learning. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Ultra-wideband radar / drone / reflection characteristic / classification / machine learning / SVM / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 475, WBS2019-64, pp. 171-176, March 2020. | |
| Paper # | WBS2019-64 | |
| Date of Issue | 2020-03-03 (IT, ISEC, WBS) | |
| ISSN | Print edition: ISSN 0913-5685 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 | IT2019-115 ISEC2019-111 WBS2019-64 |
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| Conference Information | |
| Committee | ISEC IT WBS |
| Conference Date | 2020-03-10 - 2020-03-11 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | University of Hyogo |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | joint meeting of IT, ISEC, and WBS |
| Paper Information | |
| Registration To | WBS |
| Conference Code | 2020-03-ISEC-IT-WBS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A fundamental study on identification of various drones using ultra-wideband radar |
| Sub Title (in English) | |
| Keyword(1) | Ultra-wideband radar |
| Keyword(2) | drone |
| Keyword(3) | reflection characteristic |
| Keyword(4) | classification |
| Keyword(5) | machine learning |
| Keyword(6) | SVM |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Takumi Mizushima |
| 1st Author's Affiliation | National Defense Academy (NDA) |
| 2nd Author's Name | Ryohei Nakamura |
| 2nd Author's Affiliation | National Defense Academy (NDA) |
| 3rd Author's Name | Hisaya Hadama |
| 3rd Author's Affiliation | National Defense Academy (NDA) |
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| Speaker | Author-1 |
| Date Time | 2020-03-11 09:30:00 |
| Presentation Time | 25 minutes |
| Registration for | WBS |
| Paper # | IT2019-115, ISEC2019-111, WBS2019-64 |
| Volume (vol) | vol.119 |
| Number (no) | no.473(IT), no.474(ISEC), no.475(WBS) |
| Page | pp.171-176 |
| #Pages | 6 |
| Date of Issue | 2020-03-03 (IT, ISEC, WBS) |
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