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| Presentation | 2022-06-17 10:25 A Study on Support Vector Classification-Aided Regression with Ensemble Learning for GNSS Positioning Shugo Maruyama, Shinsuke Ibi (Doshisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doshisha Univ.)  RCS2022-60 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In Global Navigation Satellite System (GNSS) positioning, the receiver position is estimated by solving the nonlinear simultaneous equations using the approximated iterative method; however, the position error occurs due to the approximation and ranging errors.In order to deal with the error appropriately, we propose the positioning method combined a regression learner with the aid of a classification learner in this paper.Using the prior information obtained from a classification learner, we apply ensemble learning as a regression problem.Training data to create a learner and test data are collected by positioning experiments in open-sky and multipath environments.We conducted positioning experiments in open-sky and multipath environments, collected training data for training the learner and test data for evaluation, and confirmed the effectiveness of the proposed GNSS positioning learner. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | GNSS positioning / pseudo range / ensemble learning / support vector classification / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 73, RCS2022-60, pp. 212-217, June 2022. | |
| Paper # | RCS2022-60 | |
| Date of Issue | 2022-06-08 (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 | RCS2022-60 |
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| Conference Information | |
| Committee | RCS |
| Conference Date | 2022-06-15 - 2022-06-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | University of the Ryukyus, Senbaru Campus and online |
| 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 | 2022-06-RCS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on Support Vector Classification-Aided Regression with Ensemble Learning for GNSS Positioning |
| Sub Title (in English) | |
| Keyword(1) | GNSS positioning |
| Keyword(2) | pseudo range |
| Keyword(3) | ensemble learning |
| Keyword(4) | support vector classification |
| Keyword(5) | |
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| 1st Author's Name | Shugo Maruyama |
| 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 | Takumi Takahashi |
| 3rd Author's Affiliation | Osaka University (Osaka Univ.) |
| 4th Author's Name | Hisato Iwai |
| 4th Author's Affiliation | Doshisha University (Doshisha Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-06-17 10:25:00 |
| Presentation Time | 10 minutes |
| Registration for | RCS |
| Paper # | RCS2022-60 |
| Volume (vol) | vol.122 |
| Number (no) | no.73 |
| Page | pp.212-217 |
| #Pages | 6 |
| Date of Issue | 2022-06-08 (RCS) |
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