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Paper Abstract and Keywords
Presentation 2026-06-18 10:55
A Study on Optimal Satellite Selection in Multi-GNSS Systems Using Machine Learning
Shota Kamada, Shinsuke Ibi, Hisato Iwai (Doshisha Univ.) RCS2026-55
Abstract (in Japanese) (See Japanese page) 
(in English) Multi-GNSS systems, which utilize multiple global navigation satellite systems (GNSS) simultaneously, are susceptible to degradation in positioning accuracy due to multipath effects and the geometric relationship between the satellites and the receiver. Focusing on improving positioning accuracy by excluding satellites that may induces errors, this study proposes a positioning model that applies a satellite selection mask based on a neural network (hereafter referred to as an NN mask). Multiple NN masks are constructed by varying the thresholds of a predefined signal strength mask. The positioning accuracy of each method is then compared with that of conventional methods. Furthermore, this study aims to construct a highly generalizable satellite selection model by applying ensemble learning to these multiple NN masks, thereby enabling of automatically and flexibly selecting satellites according to the positioning environment.
Keyword (in Japanese) (See Japanese page) 
(in English) Multi-GNSS positioning / satellite selection / neural network / ensemble learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 72, RCS2026-55, pp. 170-175, June 2026.
Paper # RCS2026-55 
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 RCS2026-55

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 Optimal Satellite Selection in Multi-GNSS Systems Using Machine Learning 
Sub Title (in English)  
Keyword(1) Multi-GNSS positioning  
Keyword(2) satellite selection  
Keyword(3) neural network  
Keyword(4) ensemble learning  
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1st Author's Name Shota Kamada  
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 2026-06-18 10:55:00 
Presentation Time 10 minutes 
Registration for RCS 
Paper # RCS2026-55 
Volume (vol) vol.126 
Number (no) no.72 
Page pp.170-175 
#Pages 6 
Date of Issue 2026-06-10 (RCS) 

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