Giorgio Gomba

Toward Operational Compensation of Ionospheric Effects in SAR Interferograms: The Split-Spectrum Method

The differential ionospheric path delay is a major error source in L-band interferograms. It is superimposed to topography and ground deformation signals, hindering the measurement of geophysical processes. In this paper, we proceed toward the realization of an operational processor to compensate the ionospheric effects in interferograms. The processor should be robust and accurate to meet the scientific requirements for the measurement of geophysical processes, and it should be applicable on a global scale. An implementation of the split-spectrum method, which will be one element of the processor, is presented in detail, and its performance is analyzed. The method is based on the dispersive nature of the ionosphere and separates the ionospheric component of the interferometric phase from the nondispersive component related to topography, ground motion, and tropospheric path delay. We tested the method using various Advanced Land Observing Satellite Phased-Array type L-band synthetic aperture radar interferometric pairs with different characteristics: high to low coherence, moving and nonmoving terrains, with and without topography, and different ionosphere states. Ionospheric errors of almost 1 m have been corrected to a centimeter or a millimeter level. The results show how the method is able to systematically compensate the ionospheric phase in interferograms, with the expected accuracy, and can therefore be a valid element of the operational processor.

Ionospheric Phase Screen Compensation for the Sentinel-1 TOPS and ALOS-2 ScanSAR Modes

Variations of the ionosphere can significantly disrupt synthetic aperture radar (SAR) acquisitions and interferometric measurements of ground deformation. In this paper, we show how the ionosphere can also strongly modify C-band interferograms despite its smaller influence at higher frequencies. Thus, ionospheric phase screens should not be neglected: their compensation improves the estimation of ground deformation maps. The split-spectrum method is able to estimate the dispersive ionospheric component of the interferometric phase; we describe the implementation of this method for the burst modes TOPS and ScanSAR to estimate and remove ionospheric phase screens. We present Sentinel-1 interferograms of the 2016 Taiwan earthquake and ALOS-2 interferograms of the 2015 Nepal earthquake, which show strong ionospheric phase gradients, and their corrected versions. Finally, to validate the results and better understand the origin of these ionospheric variations, we compare the estimated differential ionosphere with global Total Electron Content maps and local Global Positioning System measurements.

High-resolution estimation of ionospheric phase screens through semi-focusing processing

Ionosphere irregularities along the synthetic aperture generate shifts and blurring that cause decorrelation. In this paper it is shown how, by partially focusing SAR images to the height of the ionosphere, it is possible to reduce the ionospheric azimuth effects and increase the coherence. This permits, even in case of turbulent ionosphere, to obtain better accuracies when separating the deformations phase from the ionospheric phase using the delta-k split-band interferometry method.

Estimation of ionospheric height variations during an aurora event using multiple semi-focusing levels

Many methods, to estimate the ionospheric effects on SAR images and interferograms, have been proposed and studied in the past years. However, depending on the conditions of the ionosphere, different methods can or should be applied. The effects that an aurora event has on SAR images and interferograms possibly have some differences with respect to the effects generated by a more normal ionospheric state. This work shows one of these differences, which is supposed to be a change in the ionosphere vertical profile, and propose and demonstrates a method to deal with it. This method improves the integrated-azimuth-shifts method, and permits to obtain a better estimate of the ionospheric phase screen.

Bayesian Data Combination for the Estimation of Ionospheric Effects in SAR Interferograms

The ionospheric propagation path delay is a major error source in synthetic aperture radar (SAR) interferograms and, therefore, has to be estimated and corrected. Various methods can be used to extract different kinds of information about the ionosphere from SAR images, with different accuracies. This paper presents a general technique, based on a Bayesian inverse problem, that combines various information sources in order to increase the estimation accuracy, and thus the correction. A physically realistic fractal modeling of the ionosphere turbulence and a data-based estimation of the model parameters allow the avoidance of arbitrary filtering windows and coefficients. To test the technique, the differential ionospheric phase screen was estimated by combining the split-spectrum method with the azimuth mutual shifts between interferometric pair images. This combination is convenient since it can benefit from the strengths of both sources: range and azimuth variations from the split-spectrum method and small-scale azimuth variations from more sensitive azimuth shifts. Therefore, the two methods can recover the long and short wavelength components of the ionospheric phase screen, respectively. A theoretical comparison between the Faraday rotation method and the split-spectrum method is also reported. For the use in the combination, precedence was then given to the split-spectrum method because of the comparable precision level, lower susceptibility to biases, and wider applicability. Finally, Advanced Land Observing Satellite Phased Array type L-band SAR L-band images are used to show how the combined result is more accurate than that obtained with the simple split-spectrum method.

Correction of ionospheric and tropospheric path delay for L-band interferograms

The differential atmospheric path delay is a major error source in L-band interferograms. Refractivity index variations with respect to the nominal value, in the troposphere and in the ionosphere, delay the propagation of radio waves changing the slant range distance. This additional delay is superimposed to topography and ground deformation signals, hindering the measure of geophysical processes. Therefore, it needs to be corrected. In this work we present the correction results for two test cases. We mitigate the impact of height-dependent tropospheric effects (stratified delay) with a method based on the direct integration using numerical weather prediction data. We compensate the ionospheric delay using the split-spectrum method, which is based on the dispersive nature of the ionosphere and estimates the delay from the SAR data itself. Errors are reduced from almost one meter to a centimeter level.

Simulation of ionospheric effects on L-band Synthetic Aperture Radar images

A procedure to simulate the effects of the ionosphere on Synthetic Aperture Radar (SAR) images is presented. The propagation delay errors induced by the ionosphere have to be compensated to millimeter level in order to meet the scientific requirements for an L-band mission dedicated to deformation measurements, which are summarized in [1]. The simulator presented in this paper can be used to study the effects of an arbitrary ionospheric state on SAR images and to generate disrupted raw and focused images starting from ionospherefree real SAR images and use them to validate ionosphere estimation methods.