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Paper Abstract and Keywords
Presentation 2026-06-19 14:30
A Study on Data-Driven Tuning of Extended Weighted Least Squares for UWB Indoor Positioning
Ryoichi Kawaguchi, Shinsuke Ibi, Hisato Iwai (Doshisha Univ) RCS2026-84
Abstract (in Japanese) (See Japanese page) 
(in English) Ultra-wideband (UWB) communications are expected to be used for indoor positioning technology owing to their wide bandwidth and low power consumption.
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In particular, the time difference of arrival (TDoA) method can provide highly accurate positioning, and the transmitter position is estimated using methods such as the least squares (LS) and weighted LS (WLS) methods.
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However, positioning accuracy unavoidably suffers from degradation caused by non-line of sight (NLOS) and multipath.
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Therefore, this study introduces neural network (NN)-optimized correction values to mitigate NLOS and multipath effects in WLS and extended WLS methods.
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We use two NN models: a simple model, the multi-layer perceptron (MLP), and a model specialized for time-series data, the long-short-term memory (LSTM).
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To ensure practicality, we conduct 3D mobile positioning using multiple transmitters.
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Using measured data, we first compare conventional algorithms (LS, Chan, and Cuckoo Search (CS)), and subsequently demonstrate the effectiveness of our proposed method against them.
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Furthermore, by comparing the proposed methods with each other, we verify the effect of extending the positioning method on improving accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) UWB / indoor positioning / neural network / time difference of arrival / weighted least squares / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 72, RCS2026-84, pp. 331-336, June 2026.
Paper # RCS2026-84 
Date of Issue 2026-06-10 (RCS) 
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 RCS2026-84

Conference Information
Committee RCS  
Conference Date 2026-06-17 - 2026-06-19 
Place (in Japanese) (See Japanese page) 
Place (in English) The Ohama Nobumoto Memorial Hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English) First Presentation in IEICE Technical Committee, Resource Control, Scheduling, Wireless Communications, etc. 
Paper Information
Registration To RCS 
Conference Code 2026-06-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Data-Driven Tuning of Extended Weighted Least Squares for UWB Indoor Positioning 
Sub Title (in English)  
Keyword(1) UWB  
Keyword(2) indoor positioning  
Keyword(3) neural network  
Keyword(4) time difference of arrival  
Keyword(5) weighted least squares  
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1st Author's Name Ryoichi Kawaguchi  
1st Author's Affiliation Doshisha University (Doshisha Univ)
2nd Author's Name Shinsuke Ibi  
2nd Author's Affiliation Doshisha University (Doshisha Univ)
3rd Author's Name Hisato Iwai  
3rd Author's Affiliation Doshisha University (Doshisha Univ)
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Speaker Author-1 
Date Time 2026-06-19 14:30:00 
Presentation Time 20 minutes 
Registration for RCS 
Paper # RCS2026-84 
Volume (vol) vol.126 
Number (no) no.72 
Page pp.331-336 
#Pages
Date of Issue 2026-06-10 (RCS) 


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