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

Weike Feng; Giovanni Nico; Motoyuki Sato

doi:10.1109/LGRS.2018.2866600

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

Weike Feng, Giovanni Nico, Motoyuki Sato

Department of Basic Studies

Research output: Contribution to journal › Article

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 language	English
Article number	8456836
Pages (from-to)	70-74
Number of pages	5
Journal	IEEE Geoscience and Remote Sensing Letters
Volume	16
Issue number	1
DOIs	https://doi.org/10.1109/LGRS.2018.2866600
Publication status	Published - 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

Access to Document

10.1109/LGRS.2018.2866600

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Feng, W., Nico, G., & Sato, M. (2019). GB-SAR Interferometry Based on Dimension-Reduced Compressive Sensing and Multiple Measurement Vectors Model. IEEE Geoscience and Remote Sensing Letters, 16(1), 70-74. [8456836]. https://doi.org/10.1109/LGRS.2018.2866600

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