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Author:

Xu, Ben (Xu, Ben.) | Lang, Shinan (Lang, Shinan.) | Cui, Xiangbin (Cui, Xiangbin.) | Li, Lin (Li, Lin.) | Liu, Xiaojun (Liu, Xiaojun.) | Guo, Jingxue (Guo, Jingxue.) | Sun, Bo (Sun, Bo.)

Indexed by:

EI Scopus SCIE

Abstract:

The spatial correlation of ice-sounding data can be used to trace internal isochronic layers and synchronize the age-depth relationship between different ice core sites, which is difficult using existing imaging methods. In this study, we propose a new algorithm to address the opportunity that applying spatial correlation to ice-sheet imaging offers. The algorithm is a spatial-correlation-based ice-sounding imaging method using fast back projection (FBP) that successfully improves the spatial correlation of imaging results with high efficiency. We give the specific steps to implement the algorithm and apply it to simulate both point targets and ice-sounding radar data to demonstrate its validity in imaging ice sheets. Furthermore, compared with two previous methods, the proposed algorithm improves the spatial correlation without degrading the ability of signal-to-noise ratio (SNR) improvement and processing efficiency. © 1980-2012 IEEE.

Keyword:

Signal to noise ratio Glaciers Time domain analysis Ice Efficiency Synthetic aperture radar Radar imaging

Author Community:

  • [ 1 ] [Xu, Ben]Polar Research Institute of China, Shanghai; 200136, China
  • [ 2 ] [Xu, Ben]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 3 ] [Lang, Shinan]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 4 ] [Cui, Xiangbin]Polar Research Institute of China, Shanghai; 200136, China
  • [ 5 ] [Cui, Xiangbin]Zhejiang University, Technology and Equipment Engineering Centre for Polar Observations, Zhoushan; 316000, China
  • [ 6 ] [Li, Lin]Polar Research Institute of China, Shanghai; 200136, China
  • [ 7 ] [Liu, Xiaojun]Chinese Academy of Sciences, Key Laboratory of Electromagnetic Radiation and Sensing Technology, Beijing; 100190, China
  • [ 8 ] [Liu, Xiaojun]Chinese Academy of Sciences (AIRCAS), Aerospace Information Research Institute, Beijing; 100190, China
  • [ 9 ] [Guo, Jingxue]Polar Research Institute of China, Shanghai; 200136, China
  • [ 10 ] [Sun, Bo]Polar Research Institute of China, Shanghai; 200136, China

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Source :

IEEE Transactions on Geoscience and Remote Sensing

ISSN: 0196-2892

Year: 2022

Volume: 60

8 . 2

JCR@2022

8 . 2 0 0

JCR@2022

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:38

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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