To mitigate atmospheric errors caused by the troposphere, which is a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging, a tropospheric correction method has been developed using data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Global Positioning System (GPS).

The Original InSAR Image (left), the GPS ZTD Difference Correction Map (center), and the corrected InSAR Image (right). The black dots in the middle image correspond to the locations of the GPS stations.
The ECMWF data was interpolated using a Stretched Boundary Layer Model (SBLM), and ground-based GPS estimates of the tropospheric delay from the Southern California Integrated GPS Network were interpolated using modified Gaussian and inverse distance weighted interpolations. The resulting Zenith Total Delay (ZTD) correction maps have been evaluated, both separately and using a combination of the two data sets, for three short-interval InSAR pairs from Envisat during 2006 on an area stretching from northeast from the Los Angeles basin towards Death Valley. Results show that the root mean square (rms) in the InSAR images was greatly reduced, meaning a significant reduction in the atmospheric noise of up to 32 percent. However, for some of the images, the rms increased and large errors remained after applying the tropospheric correction. The residuals showed a constant gradient over the area, suggesting that a remaining orbit error from Envisat was present. The orbit reprocessing in ROI_pac and the plane fitting both require that the only remaining error in the InSAR image be the orbit error. If this is not fulfilled, the correction can be made anyway, but it will be done using all remaining errors assuming them to be orbit errors. By correcting for tropospheric noise, the biggest error source is removed, and the orbit error becomes apparent and can be corrected for.

After reprocessing the InSAR images using re-estimated satellite orbits, the overall rms reduction (using both tropospheric and orbit correction) spanned from 15 to 68 percent. With this tropospheric correction, low-frequency errors can be removed from InSAR images. Additionally, results show that for days with high-quality ECMWF data, the SBLM ZTD correction performs as well as the GPS ZTD correction. Finally, the tropospheric correction enabled orbit correction, and by correcting for both errors, the quality of the InSAR images increased significantly.

By correcting for the troposphere, other errors become visible. The main contributor to the remaining errors is uncertainties with determining the satellite orbit. Because the orbit error is now separated from the tropospheric error, the orbit can be corrected for more accurately.

This work was done by Frank H. Webb, Evan F. Fishbein, Angelyn W. Moore, Susan E. Owen, Eric J. Fielding, and Stephanie L. Granger of Caltech and Fredrik Björndahl and Johan Löfgren of Chalmers University of Technology for NASA’s Jet Propulsion Laboratory. NPO-46918

Topics:
Global positioning systems (GPS) Imaging and visualization Information Technology Navigation and guidance systems Optics
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Tropospheric Correction for InSAR Using Interpolated ECMWF Data and GPS Zenith Total Delay

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NASA Tech Briefs Magazine

This article first appeared in the August, 2011 issue of NASA Tech Briefs Magazine (Vol. 35 No. 8).

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Overview

The document discusses advancements in tropospheric correction for Interferometric Synthetic Aperture Radar (InSAR) data, focusing on the integration of interpolated European Centre for Medium-Range Weather Forecasts (ECMWF) data and Global Positioning System (GPS) Zenith Total Delay (ZTD) measurements. Tropospheric effects can significantly impact the accuracy of InSAR measurements, which are crucial for applications such as land subsidence monitoring, earthquake studies, and infrastructure assessment.

The research highlights the importance of correcting for atmospheric delays caused by water vapor in the troposphere, which can introduce errors in radar signal propagation. The document presents various methodologies for achieving these corrections, including the use of ECMWF data, which provides high-resolution atmospheric information, and GPS data, which offers real-time ZTD measurements.

Key figures in the document illustrate the corrected InSAR results, showcasing the effectiveness of the proposed correction methods. For instance, several pairs of overpasses are analyzed, with specific dates provided for the data used in the corrections. The figures demonstrate the differences between uncorrected and corrected InSAR data, emphasizing the improvements in accuracy achieved through the proposed techniques.

The document also discusses the merging of ECMWF and GPS data to create a more robust correction map, which enhances the reliability of the tropospheric corrections applied to InSAR data. This merging process is crucial for ensuring that the corrections account for spatial and temporal variations in atmospheric conditions.

Overall, the findings suggest that integrating ECMWF and GPS data significantly improves the quality of InSAR measurements by reducing atmospheric errors. The research contributes to the ongoing efforts to enhance remote sensing technologies and their applications in various fields, including environmental monitoring, disaster response, and urban planning.

In conclusion, the document provides valuable insights into the methodologies for tropospheric correction in InSAR applications, highlighting the benefits of using a combination of ECMWF and GPS data. The advancements presented in this research have the potential to improve the accuracy of InSAR measurements, thereby enhancing their utility in scientific and practical applications.