GB-SAR Interferometry Based on Dimension-Reduced Compressive Sensing and Multiple Measurement Vectors Model

Weike Feng, Giovanni Nico, Motoyuki Sato

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

To reduce the data acquisition time and the high-level sidelobes produced by conventional focusing methods for ground-based synthetic aperture radar interferometry, we present a new method to provide accurate displacement maps based on the dimension-reduced compressive sensing (CS) method combined with the multiple measurement vectors (MMVs) model. The proposed CS method consists in selecting the supported area of targets, estimated by the fast conventional method with undersampled data. The following sparse reconstruction is applied only to the selected areas. The MMV-based approach allows increasing the coherence and the precision of displacement estimates. Two experiments are carried out to assess the performance of the proposed method.

Original languageEnglish
Article number8456836
Pages (from-to)70-74
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume16
Issue number1
DOIs
Publication statusPublished - 2019 Jan

Keywords

  • Compressive sensing (CS)
  • SAR
  • SAR interferometry
  • ground-based synthetic aperture radar (GB-SAR)
  • multiple measurement vectors (MMVs) model

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering

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