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Paper Abstract and Keywords
Presentation 2021-12-16 11:20
Mitigation of Atmospheric Phase Screen effect in InSAR based on Complex Deep Learning Model
YuFan Cai, Josaphat Tetuko Sri Sumantyo, KeDi Chen (Chiba Univ.) SANE2021-68
Abstract (in Japanese) (See Japanese page) 
(in English) The effect of the atmospheric phase screen seriously affects the DEM quality. The mainstream method is to use meteorological parameters and combine them with GPS information to calculate the atmospheric elevation error. However, it is limited by the number of calibrated points and the addition of multi-view processing and filtering in InSAR will bring a certain difference between the atmospheric phase screen carried by the processed results and the results calculated by the physical model. Therefore, this paper aims to mitigate the effect of APS by using a deep learning method without reducing the DEM resolution but obtaining higher accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) InSAR / Atmospheric Phase Screen / Deep Learning / GACOS / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 306, SANE2021-68, pp. 29-34, Dec. 2021.
Paper # SANE2021-68 
Date of Issue 2021-12-09 (SANE) 
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 SANE2021-68

Conference Information
Committee SANE  
Conference Date 2021-12-16 - 2021-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Chiba University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Radar, Remote Sensing and general issues 
Paper Information
Registration To SANE 
Conference Code 2021-12-SANE 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Mitigation of Atmospheric Phase Screen effect in InSAR based on Complex Deep Learning Model 
Sub Title (in English)  
Keyword(1) InSAR  
Keyword(2) Atmospheric Phase Screen  
Keyword(3) Deep Learning  
Keyword(4) GACOS  
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1st Author's Name YuFan Cai  
1st Author's Affiliation Chiba University (Chiba Univ.)
2nd Author's Name Josaphat Tetuko Sri Sumantyo  
2nd Author's Affiliation Chiba University (Chiba Univ.)
3rd Author's Name KeDi Chen  
3rd Author's Affiliation Chiba University (Chiba Univ.)
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Speaker Author-1 
Date Time 2021-12-16 11:20:00 
Presentation Time 20 minutes 
Registration for SANE 
Paper # SANE2021-68 
Volume (vol) vol.121 
Number (no) no.306 
Page pp.29-34 
#Pages 6 
Date of Issue 2021-12-09 (SANE) 

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