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Paper Abstract and Keywords
Presentation 2021-07-29 13:30
[Invited Lecture] A Study on Wi-Fi RTT Indoor Positioning Method By Using Machine Learning
Ryohei Hayashi, Yuto Nakagawa, Takashi Izumi (PSNRD), Abe Shinya, Yamauchi Hiroki (Panasonic) AP2021-38
Abstract (in Japanese) (See Japanese page) 
(in English) As a position estimation method using wireless LAN and Bluetooth, there is a method using Received Signal Strength Indicator (RSSI), but this method is a low positioning accuracy. Another method using Wi-Fi RTT (Round Trip Time) is capable of highly accurate positioning compared to RSSI based one, but the accuracy deteriorates in a multipath environment or NLOS environment. In this paper, we evaluate the positioning performance by machine learning using Wi-Fi RTT. In the experiment, we obtain the self-position and RTT from 6 APs by driving a megarover equipped with SLAM in the office. As a result, we show that the positioning can be performed with an accuracy of 1m or less by using machine learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Wi-FI RTT / Indoor positioning / Machine learning / Deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 126, AP2021-38, pp. 81-85, July 2021.
Paper # AP2021-38 
Date of Issue 2021-07-21 (AP) 
ISSN 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 AP2021-38

Conference Information
Committee AP SANE SAT  
Conference Date 2021-07-28 - 2021-07-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Remote sensing, Sattelite Communication, Radio propagation, Antennas and Propagation 
Paper Information
Registration To AP 
Conference Code 2021-07-AP-SANE-SAT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Wi-Fi RTT Indoor Positioning Method By Using Machine Learning 
Sub Title (in English)  
Keyword(1) Wi-FI RTT  
Keyword(2) Indoor positioning  
Keyword(3) Machine learning  
Keyword(4) Deep learning  
1st Author's Name Ryohei Hayashi  
1st Author's Affiliation Panasonic System Networks R&D Lab.Co., Ltd (PSNRD)
2nd Author's Name Yuto Nakagawa  
2nd Author's Affiliation Panasonic System Networks R&D Lab.Co., Ltd (PSNRD)
3rd Author's Name Takashi Izumi  
3rd Author's Affiliation Panasonic System Networks R&D Lab.Co., Ltd (PSNRD)
4th Author's Name Abe Shinya  
4th Author's Affiliation Panasonic (Panasonic)
5th Author's Name Yamauchi Hiroki  
5th Author's Affiliation Panasonic (Panasonic)
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Speaker Author-1 
Date Time 2021-07-29 13:30:00 
Presentation Time 25 minutes 
Registration for AP 
Paper # AP2021-38 
Volume (vol) vol.121 
Number (no) no.126 
Page pp.81-85 
Date of Issue 2021-07-21 (AP) 

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