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 |
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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 | |
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