Multi-Temporal Small Baseline Interferometric SAR Algorithms: Error Budget and Theoretical Performance

Antonio Pepe

doi:10.3390/rs13040557

Abstract

Multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques are well recognized as useful tools for detecting and monitoring Earth’s surface temporal changes. In this work, the fundamentals of error noise propagation and perturbation theories are applied to derive the ground displacement products’ theoretical error bounds of the small baseline (SB) differential interferometric synthetic aperture radar algorithms. A general formulation of the least-squares (LS) optimization problem, representing the SB methods implementation’s core, was adopted in this research study. A particular emphasis was placed on the effects of time-uncorrelated phase unwrapping mistakes and time-inconsistent phase disturbances in sets of SB interferograms, leading to artefacts in the attainable InSAR products. Moreover, this study created the theoretical basis for further developments aimed at quantifying the error budget of the time-uncorrelated phase unwrapping mistakes and studying time-inconsistent phase artefacts for the generation of InSAR data products. Some experiments, performed by considering a sequence of synthetic aperture radar (SAR) images collected by the ASAR sensor onboard the ENVISAT satellite, supported the developed theoretical framework.

Highlights

IntroductionOver the last twenty years, the Differential synthetic aperture radar interferometry (DInSAR) technology gradually evolved towards new advanced multi-temporal interferometric synthetic aperture radar (SAR) (MT-InSAR) techniques [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35], for the generation of ground displacement time-series
Note that S-1 is intrinsically an small baseline (SB) system because the S-1 orbital tube is narrow. This is beneficial for the achievable results, as demonstrated by this research study, because a highly time-redundant network of SB interferograms is characterized by enhanced coherence and low values of the design matrix condition number κ and both conditions have a beneficial effect on the expected theoretical accuracy of the InSAR products
In recent years, new challenges are emerging related to the development of novel efficient processing chains of large sets of synthetic aperture radar (SAR) data and for the extraction of ancillary information in large sets of InSAR data, see for instance [55,56,74], which could be potentially used to enhance the use of present-day InSAR methodologies. In this context, integrated approaches based on the use of radar data at different wavelengths, potentially complemented with multi-spectral data collected in the optical/infrared bands, might help in having new information on the state of the Earth’s environment, including the Earth’s surface, the atmosphere, the oceans, and the coastal regions

Summary

Introduction

Over the last twenty years, the DInSAR technology gradually evolved towards new advanced multi-temporal interferometric SAR (MT-InSAR) techniques [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35], for the generation of ground displacement time-series In this context, the two main classes of the Persistent Scatterers (PS) [21,36] and the Small Baseline (SB) [16,25,26,27,37,38,39] methods emerged, and were principally used for the detection of the displacements affecting point-wise persistent scatterers (PS) and distributed scatterers (DS) on the terrain, respectively. The SB interferograms are usually multi-looked (complex averaged) [3] to mitigate the decorrelation phase noise effects

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Discussion

Conclusion