Abstract
Synthetic Aperture Radar Interferometry (SAR, InSAR) is increasingly being used for deformation monitoring. Uncertainty in satellite state vectors is considered to be one of the main sources of errors in applications such as this. In this paper, we present frequency and spatial domain based algorithms to model orbital errors in InSAR interferograms. The main advantage of this method, when applied to the spatial domain, is that the order of the polynomial coefficient is automatically determined according to the features of the orbital errors, using K-cross validation. In the frequency domain, a maximum likelihood fringe rate estimate is deployed to resolve linear orbital patterns in strong noise interferograms, where spatial-domain-based algorithms are unworkable. Both methods were tested and compared with synthetic data and applied to historical Environmental Satellite Advanced Synthetic Aperture Radar (ENVISAT ASAR) sensor and modern instruments such as Gaofen-3 (GF-3) and Sentinel-1. The validation from the simulation demonstrated that an accuracy of ~1mm can be obtained under optimal conditions. Using an independent GPS measurement that is discontinuous from the InSAR measurement over the Tohoku-Oki area, we found a 31.45% and 73.22% reduction in uncertainty after applying our method for ASAR tracks 347 and 74, respectively.
Highlights
The precise orbiting position information of space-borne Synthetic Aperture Radar (SAR) systems is of great significance in many Interferometric Synthetic Aperture Radar (InSAR) applications, especially in the case of ground motion monitoring [1,2,3]
Three phase components, including deformation, random noise, and orbital errors were simulated according to the ENVISAT ASAR geometry
The linear and non-linear phase ramps were added to the orbital errors (Figure 1c,d)
Summary
The precise orbiting position information of space-borne Synthetic Aperture Radar (SAR) systems is of great significance in many Interferometric Synthetic Aperture Radar (InSAR) applications, especially in the case of ground motion monitoring [1,2,3]. The theoretical accuracy can be as high as a centimeter to as low as a millimeter. This technique has been widely used to identify many geophysical processes that usually cause long-wavelength crustal deformation, including strain accumulation along locked continental faults, coseismic deformation caused by the occurrence of faulting in the lithosphere, and postseismic deformation caused by afterslip and viscoelastic relaxation [4,5,6]. The influence of orbital errors on the final accuracy of deformation products is largely contingent on the SAR instruments, i.e., the trajectory of the satellite orbit, the radar frequency, and the degree of overlap between the phase ramp and the deformation signals
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