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Paper Abstract and Keywords
Presentation 2018-08-10 11:40
Object Identification with Time Series of Millimeter-wave Radar Information
Takashi Nakamura, Kentaroh Toyoda, Tomoaki Ohtsuki (Keio Univ.), Osamu Isaji, Kazuaki Hamada, Toshiyuki Miyazaki (DENSO TEN) RCS2018-145
Abstract (in Japanese) (See Japanese page) 
(in English) Identifying objects with radar is in great demand for avoiding road accidents. Recent research tried to identify moving objects on a road by inputting radar information to a machine learning classifier. In the conventional method, the features used in the machine learning are extracted from the observed radar information with a short time interval. Since the movement of the objects is different depending on the objects, time series information is effective for classification, which has not been exploited before. In this report, we propose a machine learning-based object identification using time series of radar information obtained from the time window that contains series of features. We extract features from a series of features by calculating the mean and variance of object information, i.e., velocity, signal power, and distance. Some experiments were carried out, and the classification performance was evaluated. From the classification results, it is shown that our method outperforms the conventional one of which features are extracted with a short time slice. It is also shown how much each feature contributes to the object identification in our method.
Keyword (in Japanese) (See Japanese page) 
(in English) millimeter-wave radar / object identification / automotive system / pedestrian detection / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 177, RCS2018-145, pp. 75-80, Aug. 2018.
Paper # RCS2018-145 
Date of Issue 2018-08-02 (RCS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 RCS2018-145

Conference Information
Committee SAT RCS  
Conference Date 2018-08-09 - 2018-08-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Iwate University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Wireless Communications, etc. 
Paper Information
Registration To RCS 
Conference Code 2018-08-SAT-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Object Identification with Time Series of Millimeter-wave Radar Information 
Sub Title (in English)  
Keyword(1) millimeter-wave radar  
Keyword(2) object identification  
Keyword(3) automotive system  
Keyword(4) pedestrian detection  
1st Author's Name Takashi Nakamura  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Kentaroh Toyoda  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Tomoaki Ohtsuki  
3rd Author's Affiliation Keio University (Keio Univ.)
4th Author's Name Osamu Isaji  
4th Author's Affiliation DENSO TEN Limited (DENSO TEN)
5th Author's Name Kazuaki Hamada  
5th Author's Affiliation DENSO TEN Limited (DENSO TEN)
6th Author's Name Toshiyuki Miyazaki  
6th Author's Affiliation DENSO TEN Limited (DENSO TEN)
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Date Time 2018-08-10 11:40:00 
Presentation Time 25 
Registration for RCS 
Paper # IEICE-RCS2018-145 
Volume (vol) IEICE-118 
Number (no) no.177 
Page pp.75-80 
#Pages IEICE-6 
Date of Issue IEICE-RCS-2018-08-02 

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