Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Ionospheric correction of interferometric SAR data with application to the cryospheric sciences

Thesis (Ph.D.) University of Alaska Fairbanks, 2018The ionosphere has been identified as an important error source for spaceborne Synthetic Aperture Radar (SAR) data and SAR Interferometry (InSAR), especially for low frequency SAR missions, operating, e.g., at L-band or P-band. Developing effective algorithms for the correction of ionospheric effects is still a developing and active topic of remote sensing research. The focus of this thesis is to develop robust and accurate techniques for ionospheric correction of SAR and InSAR data and evaluate the benefit of these techniques for cryospheric research fields such as glacier ice velocity tracking and permafrost deformation monitoring. As both topics are mostly concerned with high latitude areas where the ionosphere is often active and characterized by turbulence, ionospheric correction is particularly relevant for these applications. After an introduction to the research topic in Chapter 1, Chapter 2 will discuss open issues in ionospheric correction including processing issues related to baseline-induced spectrum shifts. The effect of large baseline on split spectrum InSAR technique has been thoroughly evaluated and effective solutions for compensating this effect are proposed. In addition, a multiple sub-band approach is proposed for increasing the algorithm robustness and accuracy. Selected case studies are shown with the purpose of demonstrating the performance of the developed algorithm. In Chapter 3, the developed ionospheric correction technology is applied to optimize InSAR-based ice velocity measurements over the big ice sheets in Greenland and the Antarctic. Selected case studies are presented to demonstrate and validate the effectiveness of the proposed correction algorithms for ice velocity applications. It is shown that the ionosphere signal can be larger than the actual glacier motion signal in the interior of Greenland and Antarctic, emphasizing the necessity for operational ionospheric correction. The case studies also show that the accuracy of ice velocity estimates was significantly improved once the developed ionospheric correction techniques were integrated into the data processing flow. We demonstrate that the proposed ionosphere correction outperforms the traditionally-used approaches such as the averaging of multi-temporal data and the removal of obviously affected data sets. For instance, it is shown that about one hundred multi-temporal ice velocity estimates would need to be averaged to achieve the estimation accuracy of a single ionosphere-corrected measurement. In Chapter 4, we evaluate the necessity and benefit of ionospheric-correction for L-band InSAR-based permafrost research. In permafrost zones, InSAR-based surface deformation measurements are used together with geophysical models to estimate permafrost parameters such as active layer thickness, soil ice content, and permafrost degradation. Accurate error correction is needed to avoid biases in the estimated parameters and their co-variance properties. Through statistical analyses of a large number of L-band InSAR data sets over Alaska, we show that ionospheric signal distortions, at different levels of magnitude, are present in almost every InSAR dataset acquired in permafrost-affected regions. We analyze the ionospheric correction performance that can be achieved in permafrost zones by statistically analyzing correction results for large number of InSAR data. We also investigate the impact of ionospheric correction on the performance of the two main InSAR approaches that are used in permafrost zones: (1) we show the importance of ionospheric correction for permafrost deformation estimation from discrete InSAR observations; (2) we demonstrate that ionospheric correction leads to significant improvements in the accuracy of time-series InSAR-based permafrost products. Chapter 5 summarizes the work conducted in this dissertation and proposes next steps in this field of research

Estimation of Forest Biomass and Faraday Rotation using Ultra High Frequency Synthetic Aperture Radar

Synthetic Aperture Radar (SAR) data in the Ultra High Frequency (UHF; 300 MHz – 3 GHz)) band have been shown to be strongly dependent of forest biomass, which is a poorly estimated variable in the global carbon cycle. In this thesis UHF-band SAR data from the fairly flat hemiboreal test site Remningstorp in southern Sweden were analysed. The data were collected on several occasions with different moisture conditions during the spring of 2007. Regression models for biomass estimation on stand level (0.5-9 ha) were developed for each date on which SAR data were acquired. For L-band (centre frequency 1.3 GHz) the best estimation model was based on HV-polarized backscatter, giving a root mean squared error (rmse) between 31% and 46% of the mean biomass. For P-band (centre frequency 340 MHz), regression models including HH, HV or HH and HV backscatter gave an rmse between 18% and 27%. Little or no saturation effects were observed up to 290 t/ha for P-band. A model based on physical-optics has been developed and was used to predict HH-polarized SAR data with frequencies from 20 MHz to 500 MHz from a set of vertical trunks standing on an undulating ground surface. The model shows that ground topography is a critical issue in SAR imaging for these frequencies. A regression model for biomass estimation which includes a correction for ground slope was developed using multi-polarized P-band SAR data from Remningstorp as well as from the boreal test site Krycklan in northern Sweden. The latter test site has pronounced topographic variability. It was shown that the model was able to partly compensate for moisture variability, and that the model gave an rmse of 22-33% when trained using data from Krycklan and evaluated using data from Remningstorp. Regression modelling based on P-band backscatter was also used to estimate biomass change using data acquired in Remningstorp during the spring 2007 and during the fall 2010. The results show that biomass change can be measured with an rmse of about 15% or 20 tons/ha. This suggests that not only deforestation, but also forest growth and degradation (e.g. thinning) can be measured using P-band SAR data. The thesis also includes result on Faraday rotation, which is an ionospheric effect which can have a significant impact on spaceborne UHF-band SAR images. Faraday rotation angles are estimated in spaceborne L-band SAR data. Estimates based on distributed targets and calibration targets with high signal to clutter ratios are found to be in very good agreement. Moreover, a strong correlation with independent measurements of Total Electron Content is found, further validating the estimates

A generic level 1 simulator for spaceborne GNSS-R missions and application to GEROS-ISS ocean reflectometry

©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In the past decade Global Navigation Satellites System Reflectometry (GNSS-R) has emerged as a new technique for earth remote sensing for various applications, such as ocean altimetry and sea state monitoring. After the success of the GNSS-R demonstrator payloads aboard the UK-DMC or TDS-1 satellites; at present, there are several missions planned to carry GNSS reflectometers. The GNSS rEflectometry, Radio Occultation, and Scatterometry onboard International Space Station (GEROS-ISS) is an innovative ISS experiment exploiting GNSS-R technique to measure key parameters of ocean, land, and ice surfaces. For GEROS-ISS mission, the European Space Agency (ESA) supported the study of GNSS-R assessment of requirements and consolidation of retrieval algorithms (GARCA). For this, it was required to accurately simulate the GEROS-ISS measurements including the whole range of parameters affecting the observation conditions and the instrument, which is called GEROS-SIM. To meet these requirements, the PAU/PARIS end-to-end performance simulator (P$^{2}$EPS) previously developed by UPC BarcelonaTech was used as the baseline building blocks for the level 1 (L1) processor of GEROS-SIM. P$^{2}$EPS is a flexible tool, and is capable of systematically simulating the GNSS-R observations for spaceborne GNSS-R missions. Thanks to the completeness and flexibility, the instrument-to-L1 data module of GEROS-SIM could be implemented by proper modification and update of P$^{2}$EPS. The developed GEROS-SIM was verified and validated in the GARCA study as comparing to the TDS-1 measurements. This paper presents the design, implementation, and results of the GEROS-SIM L1 module in a generic way to be applied to GNSS-R instruments.Peer ReviewedPostprint (author's final draft

Measuring Coseismic Deformation With Spaceborne Synthetic Aperture Radar: A Review

In the past 25 years, space-borne Synthetic Aperture Radar imagery has become an increasingly available data source for the study of crustal deformation associated with moderate to large earthquakes (M > 4.0). Coseismic surface deformation can be measured with several well-established techniques, the applicability of which depends on the ground displacement pattern, on several radar parameters, and on the surface properties at the time of the radar acquisitions. The state-of-the-art concerning the measurement techniques is reviewed, and their application to over 100 case-studies since the launch of the Sentinel-1a satellite is discussed, including the performance of the different methods and the data processing aspects, which still constitute topics of ongoing research

3-D Satellite Interferometry for Interseismic Velocity Fields

The global interseismic strain rate map is being accomplished rapidly with measurements of the space-based geodetic technique of InSAR. High-resolution measurements of crustal deformation from InSAR can provide crucial constraints on a region's active tectonics, geodynamics, and seismic hazard. However, space-based InSAR usually only provides good constraints on horizontal displacement in the east-west direction, with the north-south component typically provided by low-resolution GNSS measurements. Sentinel-1, on the other hand, has the potential to provide measurements that are sensitive to north-south motion, through exploitation of the burst overlap areas produced by the TOPS acquisition mode. However, the significant noise contributions from decorrelation and propagation through the ionosphere make it challenging to detect surface displacements associated with interseismic deformation needing millimeters per year accuracy. The ionospheric phase advance is a significant nuisance term that can bias InSAR measurements. Although methods have been developed to mitigate the effect, they are not always routinely applied when processing C-band SAR images, for which the effect is generally expected to be small. Nevertheless, the effect can be significant, especially when analyzing low deformation gradients over large areas using time-series analysis. Here, the work in Chapter 3 presents a time-series approach to ionospheric noise mitigation, which improves on existing methods. Firstly, I estimate the ionospheric contribution for each individual acquisition from multiple interferograms, which reduces noise. Secondly, this work improved the identification of unwrapping errors, which can bias the estimation. Thirdly, I introduce a new filtering approach, which gives better results, particularly at image edges and areas with variable density of coherent measurements. Furthermore, the approach is applicable when estimating along-track motion in burst overlap areas. The results show that applying the correction improves velocity accuracy significantly for both conventional line-of-sight and burst overlap interferometry techniques. The application of measuring long-term tectonic signals that concentrate in the north-south component with millimeters per year accuracy is essential to constrain interseismic strain globally. In Chapter 4, I also demonstrate a time-series approach with the burst overlap interferometry appropriate for extracting subtle long-term displacements. The approach includes mitigation of ionospheric noise, and I investigate different filtering approaches to optimize the reduction of decorrelation noise. I present the mean ground velocity in the azimuth direction from data acquired between 2014 and 2019 along the West-Lut Fault, a north-south striking fault in eastern Iran. The chi-square statistic defines a good agreement between the results and independent GNSS measurements. Moreover, the denser coverage of the technique allows to detect the variation in strain accumulation between northern and southern segments of the fault, with our modeling indicating a variation of slip rate from 9.2±0.5 mm/yr in the south to 4.3±0.5 mm/yr in the north. With current efforts to use InSAR to constrain strain rates globally, along-track measurements can fill a crucial gap in north-south sensitivity. With the achievement of that the burst overlap InSAR technique can measure azimuth motions across a slowly deforming area where the surface displacements are concentrated in the north-south component, this results in that, in the TOPS burst overlap region, the number of observations for a ground displacement can reach 3-4 times with different observational components. Measurement redundancy allows for the decomposition of observed velocities into three-dimensional components. In Chapter 5, I apply InSAR observations to estimate a deformation across the Chaman fault in both line-of-sight and along-track components using images from ascending and descending passes. I demonstrate an inversion to estimate the decomposed velocities. The algorithm employs a sparse GNSS network across the region to transform InSAR velocities to the GNSS reference frame. The results show that constraining the long-wavelength signal across the InSAR observations using GNSS data can mitigate the long-wavelength ionospheric disturbance that remains in the observations. The variation in slip rates across the Chaman fault is depicted by two transect profiles. The mean velocity profile at latitude 31˚N, where the Chaman fault is the only tectonic structure to accommodate strain, is consistent with 10.4±0.4 mm/yr of slip rate derived from the interseismic modeling. The optimal fault slip rate to fit with the mean velocity of the southern profile at latitude 29˚N is 5.5±0.8 mm/yr across the Chaman fault and 15.5±0.9 mm/yr across the parallel fault (the Ghazaband fault). I also demonstrate the benefits of high temporal sampling of InSAR observations with TOPS acquisition mode to study time-dependent surface deformation. I present the evolution of fault creeps, including seismic and aseismic fault slip along the Chaman fault during 2014-2018

The Extended Timing Annotation Dataset for Sentinel-1 - Product Description and First Evaluation Results

This article introduces the extended timing annotation dataset (ETAD) product for Sentinel-1 (S-1) which was developed in a joint effort of German Aerospace Center (DLR) and European Space Agency (ESA). It allows to correct range and azimuth timing of S-1 images for geophysical effects and for inaccuracies in synthetic aperture radar (SAR) image focusing. In combination with the precise orbit solution, these effects determine the absolute geolocation accuracy of S-1 SAR images and the relative collocation accuracy of repeat pass image stacks. ETAD contains the gridded timing corrections for the tropospheric and ionospheric path delays, the tidal-based surface displacements, and the SAR processing effects, all of which are computed for each data taken using standard models from geodesy and auxiliary atmospheric data. The ETAD product helps S-1 users to significantly improve the geolocation accuracy of the S-1 SAR products to better than 0.2 m and offers a potential solution for correcting large-scale interferometric phase variations. The product layout and product generation are described schematically. This article also reports first the results for different SAR techniques: first, the improvement in geolocation accuracy down to a few centimeters by verification of accurately surveyed corner reflector positions in the range–azimuth plane; second, the well-established offset-tracking technique, which is used for systematic ice velocity monitoring of ice sheets and glaciers, where ETAD can reduce velocity biases down to subcentimetric values; and third, the correction of atmospheric phase contributions in wide-area interferograms used for national and European ground motion services. These early results proof the added value of the ETAD corrections and that the product design is well-suited to be integrated into the processing flows of established SAR applications such as absolute ranging of targets, speckle/feature tracking, and interferometry

In-depth verification of Sentinel-1 and TerraSAR-X geolocation accuracy using the Australian Corner Reflector Array

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques—also called imaging geodesy—can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improve�ment of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy

Research progress on geosynchronous synthetic aperture radar

Based on its ability to obtain two-dimensional (2D) high-resolution images in all-time and all-weather conditions, spaceborne synthetic aperture radar (SAR) has become an important remote sensing technique and the study of such systems has entered a period of vigorous development. Advanced imaging modes such as radar interferometry, tomography, and multi-static imaging, have been demonstrated. However, current in-orbit spaceborne SARs, which all operate in low Earth orbits, have relatively long revisit times ranging from several days to dozens of days, restricting their temporal sampling rate. Geosynchronous SAR (GEO SAR) is an active research area because it provides significant new capability, especially its much-improved temporal sampling. This paper reviews the research progress of GEO SAR technologies in detail. Two typical orbit schemes are presented, followed by the corresponding key issues, including system design, echo focusing, main disturbance factors, repeat-track interferometry, etc, inherent to these schemes. Both analysis and solution research of the above key issues are described. GEO SAR concepts involving multiple platforms are described, including the GEO SAR constellation, GEO-LEO/airborne/unmanned aerial vehicle bistatic SAR, and formation flying GEO SAR (FF-GEO SAR). Due to the high potential of FF-GEO SAR for three-dimensional (3D) deformation retrieval and coherence-based SAR tomography (TomoSAR), we have recently carried out some research related to FF-GEO SAR. This research, which is also discussed in this paper, includes developing a formation design method and an improved TomoSAR processing algorithm. It is found that GEO SAR will continue to be an active topic in the aspect of data processing and multi-platform concept in the near future