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

Spatiotemporal Analysis of C-band interferometric Phase Anomalies over Sicily

Short temporal SAR interferograms present a phase which is biased with respect to the surface deformation signal. We analyse the anomalies in terms of their spatiotemporal patterns in a C-band Sentinel-1 dataset. The temporal high-pass component can be explained with moisture variations as sensed by the ASCAT scatterometer. The low-pass components need a different explanation. Considering the apparent accumulation of delay, the spatial correlation to land cover types or topographic height, and the seasonality, they are compatible with wet biomass accumulation. The strong decorrelation observed is likely related to strong vegetation extinction in C-band

Analyzing an InSAR short-term systematic phase bias with regards to soil moisture and landcover

This work investigates a systematic phase bias affecting Synthetic Aperture Radar interferograms, in particular at short-term, causing biases in displacement velocity estimates that can reach several mm per year. The analysis relies on the processing of a stack of Single Look Complex SAR images; in our case, the stack consists in 184 Sentinel-1 images acquired regularly between 2014 and 2018 and covering the Eastern part of Sicily. A reference phase history is derived using the EMI method (Eigen-decomposition-based Maximum-likelihood estimator of Interferometric phase), which takes advantage of the full sample covariance matrix built out of all the SAR acquisitions at a given pixel. This phase history has been shown to be equivalent to a persistent scatterer’s phase history over our region of interest. We use it to calibrate the direct multilooked interferograms built out of consecutive acquisitions. The short-term phase bias signal thus obtained is analyzed in time and space, making use in addition of ASCAT soil moisture variations and landcover information from the CORINE dataset. We observe that for certain land classes, the high-frequency part of the signal is correlated with soil moisture variations in both dry and wet seasons. The low-pass trend exhibits strongly seasonal variations, with maxima of comparable value in spring (April-May) of each year. Areas with similar landcover types (forests, vegetated areas, agricultural areas) witness similar phase biases behavior, indicating a physical contribution associated with vegetation effects. By investigating the behavior of the bias, this study contributes towards a future mitigation of this phase error in deformation estimates, or the exploitation of the bias itself as a physically relevant signal

Study on Ionospheric Effects on SAR and their Statistics

The objective of this work is to study the impact of ionospheric disturbances on the Sentinel-1 mission. First we realize an ionospheric statistics database based on global TEC models and maps. Then we process interferometric stacks of Sentinel-1 images using the split-spectrum method to estimate the differential ionosphere and validate the GNSS based statistics. We use the newly developed database to determine the expected average and maximum ionospheric errors on Sentinel-1 SAR measurements. We discuss the possibility to routinely include flags or corrections for ionospheric disturbances in Sentinel-1 products

Influence and Correction of Ionospheric Effects on Sentinel-1 TOPS Interferometry

Synthetic aperture radar (SAR) and interferometric SAR (InSAR) measurements are disturbed by the propagation velocity changes of microwaves that are caused by the high density of free electrons in the ionosphere. Most affected are low-frequency (L- or P-band) radars although higher frequency (C- or X-band) systems, as the recently launched Sentinel-1, are not immune. Since the ionosphere is an obstacle to increasing the precision of SAR systems needed to remotely measure the Earth’s dynamic processes, as ground deformation, it is necessary to estimate and compensate ionospheric propagation delays in SAR signals. In this work we work discuss about the influence of the ionosphere on interferograms and the possible correction methods. The ionospheric error, when measuring ground motion with C-band InSAR systems, is often considered small enough to be ignored. In this work we assess the average ionospheric error level occurring in non-compensated interferograms by using global ionospheric measurements, to show that the correction of ionospheric effects can sensibly increase the measurement accuracy. A statistical analysis of IGS global ionospheric TEC maps is used to calculate the standard deviation of the LOS and along-track error caused by ionospheric effects. IGS global TEC maps are generated assimilating a network of GPS-based TEC measurements with ionospheric models. The resolution and accuracy of these maps are too low to allow the correction of interferograms. Nevertheless, we use them for the statistical analysis to obtain a reasonable assessment of the possible ionospheric error when no correction is applied to interferograms. Firstly, we produce a histogram of the differential ionospheric TEC level considering all possible 12-days interferograms of one year (2015). In fact, a different absolute ionospheric level during the two acquisitions generates a linear phase term in the interferogram range direction due to the incidence angle change. This additional phase term introduces a measurement error. A global map of the expected LOS error can then be produced; an example is reported in Figure 1. Such a map can be used to predict the ionospheric error to ground deformation measurements. Solar cycle, diurnal, seasonal, and geographical variations of the ionosphere influence the error level for different satellites with different orbits, acquisition times, and for different geographical regions. For example, the result shows how the standard deviation of the LOS deformation error for a single Sentinel-1 interferogram in ascending geometry is, in low latitude regions, about 4 cm every 100 ground range km. The latter considers only the effect due to the incidence angle change; a similar analysis has been also realized for the ionospheric gradients in the range and azimuth directions. The analysis indicates that the ionosphere can sensibly reduce the accuracy of ground deformation measurements. To increase such accuracy, the split-spectrum method can be used to estimate and remove the ionospheric phase screen from interferograms. In the second part of the work, the processing workflow of the split-spectrum method, applied to the special case of TOPS images, will be presented. Practical examples of successful correction of ionospheric disturbances, as well as possible issues, will also be presented. Figure 2 shows a disturbed interferogram and its compensated version. The phase screens estimated with the split-spectrum method will then be compared to the ones derived from the global TEC maps, to verify the quality of the statistical analysis. Finally, other ionospheric effects on Sentinel-1 interferograms, such as ionosphere-induced azimuth shifts will also be discussed with some examples, and possible correction strategies proposed

Estimation and Compensation of Ionospheric Propagation Delay in Synthetic Aperture Radar (SAR) Signals

Synthetic aperture radar (SAR) and interferometric SAR (InSAR) measurements are disturbed by the propagation velocity changes of microwaves that are caused by the high density of free electrons in the ionosphere. As the ionosphere is an obstacle to increasing the precision of SAR systems needed to remotely measure the Earth's dynamic processes, this thesis aims to develop methods to estimate and compensate ionospheric propagation delays in SAR signals

Estimation of Ionosphere-Compensated Azimuth Ground Motion with Sentinel-1

This paper deals with the mitigation of ionospheric effects in the estimation of azimuth ground motion using Sentinel-1 images. Thanks to the high accuracy of Sentinel-1 azimuth orbit timings, precise absolute measurements of azimuth ground displacements are possible, nevertheless, variations in the ionosphere electron content can introduce significant errors. Azimuth shifts are usually estimated with the Enhanced Spectral Diversity technique in the burst overlap areas. The ionospheric phase contribution can be estimated with the split-spectrum method. In this paper, the correction of ionospheric errors in azimuth shifts is realized by compensating the ionospheric phase in the burst overlap areas; this is only possible when considering the correct ionospheric height and the squint angles. The technique is thoroughly described in the paper. Experiments shows how this procedure can sensibly mitigate the ionospheric influence on azimuth shifts, improving the measurements of geophysical phenomena as, for example, earthquakes

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