X-Band Sea Surface Coherence Time Inferred From Bistatic SAR Interferometry

Coherence time plays an important role in ocean surface observation by means of synthetic aperture radar (SAR). For X-band, the autocorrelation function (ACF) of the backscatter from the sea surface has been predicted using models. Up to now there exist only few experimental data and an empirical an...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2017-07, Vol.55 (7), p.3941-3948
Main Authors: Suchandt, Steffen, Romeiser, Roland
Format: Article
Language:English
Subjects:
Autocorrelation
Backscatter
Backscattering
Bistatic synthetic aperture radar (SAR) along-track interferometry
Coherence
Data acquisition
Data processing
Decorrelation
Doppler sonar
Empirical analysis
Experimental data
Interferometry
Ocean surface
Radar
SAR (radar)
Satellite tracking
Satellites
Sea surface
sea surface coherence time
Sensors
Signal to noise ratio
Statistical analysis
Statistical methods
Superhigh frequencies
Surface waves
Synthetic aperture radar
TanDEM-X
Temperature (air-sea)
Time lag
Time measurement
X-band
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Summary:Coherence time plays an important role in ocean surface observation by means of synthetic aperture radar (SAR). For X-band, the autocorrelation function (ACF) of the backscatter from the sea surface has been predicted using models. Up to now there exist only few experimental data and an empirical analysis of the sea surface coherence time based on a larger amount of data is missing. In this paper, we show how space-based bistatic SAR along-track interferometry is used for the first time to measure the ACF. We achieve this by statistical analysis of the interferometric scene coherence as a function of the along-track interferometric time lag, instead of indirect estimation from the Doppler bandwidth. We use many data acquisitions of opportunity for that purpose, thereby exploiting the diversity of along-track baselines between the two SAR sensors of the TanDEM-X satellite formation. The ACF is related to the temporal decorrelation, which is not directly observable. We extract this component by quantifying and compensating for all other sources of decorrelation that contribute to the observed coherence.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2017.2684259