An Error Prediction Framework for Interferometric SAR Data

Abstract

Abstract-Three of the major error sources in interferometric synthetic aperture radar measurements of terrain elevation and displacement are baseline errors, atmospheric path length errors, and phase unwrapping errors. In many processing schemes, these errors are calibrated out by using ground control points (GCPs) (or an external digital elevation model). In this paper, a simple framework for the prediction of error standard deviation is outlined and investigated. Inputs are GCP position, a priori GCP accuracy, baseline calibration method along with a closed-form model for the covariance of atmospheric path length disturbances, and a model for phase unwrapping errors. The procedure can be implemented as a stand-alone add-on to standard interferometric processors. It is validated by using a set of single-frame interferograms acquired over Rome, Italy, and a double difference data set over Flevoland, The Netherlands.Index Terms-Atmospheric disturbances, baseline error, calibration, interferometry, phase unwrapping error, synthetic aperture radar (SAR), systematic errors.

The February 2014 Cephalonia Earthquake (Greece): 3D Deformation Field and Source Modeling from Multiple SAR Techniques

“…Application of the above-mentioned techniques to the COSMO-SkyMed and TanDEM-X datasets provided eight measurements of four independent displacement components, namely along the descending and ascending LoS and azimuth directions. Predicted error variances were generated with the method of Mohr and Merryman Boncori (2008), which provides a framework to exploit available models for the secondorder statistics of error sources. We generalized the original method, which was proposed for DInSAR, extending it also to offset tracking and MAI.…”

The 2013 Lunigiana (Central Italy) earthquake: Seismic source analysis from DInSAR and seismological data, and geodynamical implications for the northern Apennines

“…1). Based on the error estimation procedure of Mohr and Merryman Boncori (2008) and on a mean-latitude atmospheric turbulence model (Merryman , the expected LoS displacement uncertainty (1σ) in the epicentral area is less than 1 cm (Fig. S1).…”

Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry

“…Although multichannel algorithms like the one in [36] promote a successful phase unwrapping, the ill-posed nature of the unwrapping problem can still cause residual errors. A typical challenging case is when large incoherent areas cross the whole swath, e.g., due to the presence of flooded areas or forests in the scene, potentially leading to large-scale unwrapping errors [24], [36], [44].…”

“…For example, [23] proposed a strategy to detect and correct remaining 2π ambiguities in a baseline calibration step. The approach was later extended in [24], where morphological filters to improve the detection were included. More recently, Lachaise et al [25] developed the correction strategy of the TanDEM-X operational processor profiting from the mission dual-baseline global coverage to detect and correct unwrapping inconsistencies.…”