An Adaptive Spatial Filtering Algorithm Based On Nonlocal Mean Filtering For GNSS-based InSAR

Runze Shang*, Feifeng Liu, Zhanze Wang, Jian Gao, Jingtian Zhou, Di Yao*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

3D deformation retrieval can be achieved through joint using different navigation satellites as the transmitters in Global navigation satellite system(GNSS)-based InSAR systems. However, multi-source errors will seriously reduce the deformation retrieval accuracy. In this paper, an adaptive spatial filtering algorithm based on nonlocal mean filtering is proposed for GNSS-based InSAR system. First, the search area is introduced to describe the areas where deformations interact with each other based on the persistent scatter point. Then, the 3D deformation retrieval accuracy is improved based on the nonlocal mean filtering for the selected Permanent Scatterers. The raw data from eight Beidou satellites are used to prove the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665469722
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022 - Xi'an, China
Duration: 25 Oct 202227 Oct 2022

Publication series

Name2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022

Conference

Conference2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
Country/TerritoryChina
CityXi'an
Period25/10/2227/10/22

Keywords

  • 3D deformation retrieval
  • Adaptive spatial filtering
  • GNSS-based InSAR
  • search area

Fingerprint

Dive into the research topics of 'An Adaptive Spatial Filtering Algorithm Based On Nonlocal Mean Filtering For GNSS-based InSAR'. Together they form a unique fingerprint.

Cite this