High-Resolution SAR Interferometry: Estimation of Local Frequencies in the Context of Alpine Glaciers

Synthetic aperture radar (SAR) interferometric data offer the opportunity to measure temperate glacier surface topography and displacement. The increase of the resolution provided by the most recent SAR systems has some critical implications. For instance, a reliable estimate of the phase gradient c...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2008-04, Vol.46 (4), p.1079-1090
Main Authors: Vasile, G., Trouve, E., Petillot, I., Bolon, P., Nicolas, J.-M., Gay, M., Chanussot, J., Landes, T., Grussenmeyer, P., Buzuloiu, V., Hajnsek, I., Andres, C., Keller, M., Horn, R.
Format: Article
Language:English
Subjects:
Adaptive neighborhood
Applied geophysics
Autocorrelation functions
Computer Science
Computer simulation
Displacement
Earth sciences
Earth, ocean, space
Engineering Sciences
Exact sciences and technology
Experimental synthetic aperture radar (E-SAR)
Flattening
Frequency estimation
glacier monitoring
Glaciers
Image Processing
Interferometry
Internal geophysics
Laboratories
local frequencies
Monitoring
Phase estimation
Radar imaging
Radar measurements
SAR interferometry (InSAR)
Signal and Image processing
Spaceborne radar
Studies
Surface topography
Synthetic aperture radar
TerraSAR-X
Topography
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Description
Summary:Synthetic aperture radar (SAR) interferometric data offer the opportunity to measure temperate glacier surface topography and displacement. The increase of the resolution provided by the most recent SAR systems has some critical implications. For instance, a reliable estimate of the phase gradient can only be achieved by using interferogram local frequencies. In this paper, an original two-step method for estimating local frequencies is proposed. The 2-D phase signal is considered to have two deterministic components corresponding to low-resolution (LR) fringes and high-resolution (HR) patterns due to the local microrelief, respectively. The first step of the proposed algorithm consists in the LR phase flattening. In the second step, the local HR frequencies are estimated from the phase 2-D autocorrelation function computed on adaptive neighborhoods. This neighborhood is the set of connected pixels belonging to the same HR spatial feature and respecting the ldquolocal stationarityrdquo hypothesis. Results with both simulated TerraSAR-X interferograms and real airborne E-SAR images are presented to illustrate the potential of the proposed method.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2007.912713