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Articles

Efficient mitigation of atmospheric phase effects in repeat-pass InSAR measurements

, , , , , & show all
Pages 4144-4159 | Received 09 Feb 2015, Accepted 13 Jul 2015, Published online: 10 Aug 2015
 

Abstract

The problem of atmospheric phase effects is currently one of the most important limiting factors for widespread application of repeat-pass interferometric synthetic aperture radar (InSAR) measurements. Due to the extraordinary complexity of the atmospheric inhomogeneity and turbulence, it is generally difficult to obtain satisfactory mitigation of the atmospheric phase effects in repeat-pass InSAR measurements. In recent years, several methods have been developed for mitigating the atmospheric phase effects. An effective approach is interferogram stacking, which is based on stacking independent interferograms. However, as many as 2n images are required to generate n interferograms and the atmospheric delay errors of the stacked interferogram decrease only with the square root of the number of interferograms in the conventional interferogram stacking method, which is not very efficient. In order to efficiently mitigate the atmospheric phase effects on the stacked interferogram in repeat-pass InSAR measurements, we propose a relay-interferogram stacking method. Compared with the conventional method, this method not only can efficiently mitigate atmospheric phase effects on the stacked interferogram, but also greatly decreases the number of required synthetic aperture radar (SAR) images. The key element is that the first and the last SAR images are selected from the periods of similar meteorological conditions. In addition, we present an application of the approach to the study of ground subsidence in the area around Beijing, China.

Acknowledgements

The authors would like to express their gratitude to European Space Agency for delivering part of ENVISAT-1 ASAR data.

Additional information

Funding

This research work was supported by the Natural Science Foundation of Beijing [Grant No. 8142009]; National Natural Science Foundation of China [Grant No. 41201419].

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