The role of atmosphere in SAR interferometry represents a widely investigated topic in remote sensing literature. Space heterogeneities and temporal changes in atmosphere composition lead, unless properly handled, to heavy polarization effects in target position estimation. Nowadays, most advanced techniques exploit the presence in the scene of assumed stable targets, formally addressed as Permanent Scatters, to remove the atmospheric phase screen superimposed to the data. This approach bases on the robustness of the PS selection process and on their distribution in the SAR image. In ground-based techniques a correct identification of stable targets can indeed meet some difficulties in particularly troublesome scenarios. In order to improve the APS evaluation accuracy, we investigated the possibility to exploit the a-prori information represented by the meteo data (pressure, temperature and humidity) gathered by a weather station in the proximity of the monitored area. In this paper a phase delay model based on these data has been implemented and its application performance, either in a pre-processing step for PS selection or as a validation method with respect to PS analisys, is reported.

On the Exploitation of Meteo Information for Atmospheric Phase Screen Compensation in GB-SAR Interferometry

GIUDICI, DAVIDE;MONTI-GUARNIERI, ANDREA VIRGILIO;IANNINI, LORENZO
2010

Abstract

The role of atmosphere in SAR interferometry represents a widely investigated topic in remote sensing literature. Space heterogeneities and temporal changes in atmosphere composition lead, unless properly handled, to heavy polarization effects in target position estimation. Nowadays, most advanced techniques exploit the presence in the scene of assumed stable targets, formally addressed as Permanent Scatters, to remove the atmospheric phase screen superimposed to the data. This approach bases on the robustness of the PS selection process and on their distribution in the SAR image. In ground-based techniques a correct identification of stable targets can indeed meet some difficulties in particularly troublesome scenarios. In order to improve the APS evaluation accuracy, we investigated the possibility to exploit the a-prori information represented by the meteo data (pressure, temperature and humidity) gathered by a weather station in the proximity of the monitored area. In this paper a phase delay model based on these data has been implemented and its application performance, either in a pre-processing step for PS selection or as a validation method with respect to PS analisys, is reported.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/573044
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