Interferometric synthetic aperture radar atmospheric correction using a GPS-based iterative tropospheric decomposition model

REMOTE SENSING OF ENVIRONMENT

卷:204

Article

Yu, Chen¹  Li, Zhenhong¹  Penna, Nigel T.¹ 

[1] Newcastle Univ, Sch Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

关键词: InSAR;    GPS;    Tropospheric delay;    Atmospheric correction;    Performance indicator;    Station spacing;   

DOI  :  10.1016/j.rse.2017.10.038

来源: Elsevier

【 摘 要 】

Atmospheric effects represent one of the major error sources of repeat-pass Interferometric Synthetic Aperture Radar (InSAR), and could mask actual displacements due to tectonic or volcanic deformation. The tropospheric delays vary both vertically and laterally and can be considered as the sum of (i) a vertically stratified component highly correlated with topography and (ii) a turbulent component resulting from turbulent processes in the troposphere varying both in space and time. In this paper, we outline a framework to routinely use pointwise GPS data to reduce tropospheric effects on satellite radar measurements. An Iterative Tropospheric Decomposition (ITD) model is used and further developed to separate tropospheric stratified and turbulent signals and then generate high-resolution correction maps for SAR interferograms. Cross validation is employed to assess the performance of the ITD model and act as an indicator to users of when and where correction is feasible. Tests were carried out to assess the impact of GPS station spacing on the ITD model InSAR correction performance, which provides insights into the trade-off between station spacing and the achievable accuracy. The appliCation of this framework to Sentinel-1A interferograms over the Southern California (USA) and Southern England (UK) regions shows approximately 45-78% of noise reduction even with a sparse (similar to 50-80 km station spacing) GPS network and/or with strong and non-random tropospheric turbulence. This is about a 50% greater improvement than previous methods. It is believed that this framework could lead to a generic InSAR atmospheric correction model while incorporating continuous and global tropospheric delay datasets, e.g. numerical weather models.

【 授权许可】

Free