Range Spectral Filtering in SAR Interferometry: Methods and Limitations

A geometrical decorrelation constitutes one of the sources of noise present in Synthetic Aperture Radar (SAR) interferograms. It comes from the different incidence angles of the two images used to form the interferograms, which cause a spectral (frequency) shift between them. A geometrical decorrelation must be compensated by a specific filtering technique known as range filtering, the goal of which is to estimate this spectral displacement and retain only the common parts of the images’ spectra, reducing the noise and improving the quality of the interferograms. Multiple range filters have been proposed in the literature. The most widely used methods are an adaptive filter approach, which estimates the spectral shift directly from the data; a method based on orbital information, which assumes a constant-slope (or flat) terrain; and slope-adaptive algorithms, which consider both orbital information and auxiliary topographic data. Their advantages and limitations are analyzed in this manuscript and, additionally, a new, more refined approach is proposed. Its goal is to enhance the filtering process by automatically adapting the filter to all types of surface variations using a multi-scale strategy. A pair of RADARSAT-2 images that mapped the mountainous area around the Etna volcano (Italy) are used for the study. The results show that filtering accuracy is improved with the new method including the steepest areas and vegetation-covered regions in which the performance of the original methods is limited.This work was supported by the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development (ERFD) under Projects PID2020-117303GB-C21 and PID2020-117303-C22

Improving InSAR geodesy using global atmospheric models

Spatial and temporal variations of pressure, temperature and water vapor content in the atmosphere introduce significant confounding delays in Interferometric Synthetic Aperture Radar (InSAR) observations of ground deformation and bias estimatesof regional strain rates. Producing robust estimates of tropospheric delays remains one of the key challenges in increasing the accuracy of ground deformation measurements using InSAR. Recent studies revealed the efficiency of global atmospheric reanalysis to mitigate the impact of tropospheric delays, motivating further exploration of their potential. Here, we explore the effectiveness of these models in several geographic and tectonic settings on both single interferograms and time series analysis products. Both hydrostatic and wet contributions to the phase delay are important to account for. We validate these path delay corrections by comparing with estimates of vertically integrated atmospheric water vapor content derived from the passive multi-spectral imager MERIS, onboard the ENVISAT satellite. Generally, the performance of the prediction depends on the vigor of atmospheric turbulence. We discuss (1) how separating atmospheric and orbital contributions allows one to better measure long wavelength deformation, (2) how atmospheric delays affect measurements of surface deformation following earthquakes and (3) we show that such a method allows us to reduce biases in multi-year strain rate estimates by reducing the influence of unevenly sampled seasonal oscillations of the tropospheric delay

Advanced pixel selection and optimization algorithms for Persistent Scatterer Interferometry (PSI)

Tesi amb diferents seccions retallades per dret de l'editorPremi Extraordinari de Doctorat, promoció 2018-2019. Àmbit de les TICGround deformation measurements can provide valuable information for minimization of associated loss and damage caused by natural and environmental hazards. As a kind of remote sensing technique, Persistent Scatterer Interferometry (PSI) SAR is able to measure ground deformation with high spatial resolution, efficiently. Moreover, the ground deformation monitoring accuracy of PSI techniques can reach up to millimeter level. However, low coherence could hinderthe exploitation of SAR data, and high-accuracy deformation monitoring can only be achieved by PSI for high quality pixels. Therefore, pixel optimization and identification of coherent pixels are crucial for PSI techniques. In this thesis, advanced pixel selection and optimization algorithms have been investigated. Firstly, a full-resolution pixel selection method based on the Temporal Phase Coherence (TPC) has been proposed. This method first estimates noise phase term of each pixel at interferogram level. Then, for each pixel, its noise phase terms of all interferograms are used to assess this pixel’s temporal phase quality (i.e., TPC). In the next, based on the relationship between TPC and phase Standard Deviation (STD), a threshold can be posed on TPC to identify high phase quality pixels. This pixel selection method can work with both Deterministic Scatterers (PSs) and Distributed Scatterers (DSs). To valid the effectiveness of the developed method, it has been used to monitor the Canillo (Andorra) landslide. The results show that the TPC method can obtained highest density of valid pixels among the employed three approaches in this challenging area with X-band SAR data. Second, to balance the polarimetric DInSAR phase optimization effect and the computation cost, a new PolPSI algorithm is developed. This proposed PolPSI algorithm is based on the Coherency Matrix Decomposition result to determine the optimal scattering mechanism of each pixel, thus it is named as CMD-PolPSI. CMDPolPSI need not to search for solution within the full space of solution, it is therefore much computationally faster than the classical Equal Scattering Mechanism (ESM) method, but with lower optimization performance. On the other hand, its optimization performance outperforms the less computational costly BEST method. Third, an adaptive algorithm SMF-POLOPT has been proposed to adaptive filtering and optimizing PolSAR pixels for PolPSI applications. This proposed algorithm is based on PolSAR classification results to firstly identify Polarimetric Homogeneous Pixels (PHPs) for each pixel, and at the same time classify PS and DS pixels. After that, DS pixels are filtered by their associated PHPs, and then optimized based on the coherence stability phase quality metric; PS pixels are unfiltered and directly optimized based on the DA phase quality metric. SMF-POLOPT can simultaneously reduce speckle noise and retain structures’ details. Meanwhile, SMF-POLOPT is able to obtain much higher density of valid pixels for deformation monitoring than the ESM method. To conclude, one pixel selection method has been developed and tested, two PolPSI algorithms have been proposed in this thesis. This work make contributions to the research of “Advanced Pixel Selection and Optimization Algorithms for Persistent Scatterer InterferometryLes mesures de deformació del sòl poden proporcionar informació valuosa per minimitzar les pèrdues i els danys associats causats pels riscos naturals i ambientals. Com a tècnica de teledetecció, la interferometria de dispersors persistents (Persistent Scatter Interferometry, PSI) SAR és capaç de mesurar de forma eficient la deformació del terreny amb una alta resolució espacial. A més, la precisió de monitorització de la deformació del sòl de les tècniques PSI pot arribar a arribar a nivells del mil·límetre. No obstant això, una baixa coherència pot dificultar l’explotació de dades SAR i el control de deformació d’alta precisió només es pot aconseguir mitjançant PSI per a píxels d’alta qualitat. Per tant, l’optimització de píxels i la identificació de píxels coherents són crucials en les tècniques PSI. En aquesta tesi s¿han investigat algorismes avançats de selecció i optimització de píxels. En primer lloc, s'ha proposat un mètode de selecció de píxels de resolució completa basat en la coherència temporal de fase (Temporal Phase Coherence, TPC). Aquest mètode estima per primera vegada el terme de fase de soroll de cada píxel a nivell d’interferograma. A continuació, per a cada píxel, s'utilitzen els termes de la fase de soroll de tots els interferogrames per avaluar la qualitat de fase temporal d'aquest píxel (és a dir, TPC). A la següent, basant-se en la relació entre el TPC i la desviació estàndard de fase (STD), es pot plantejar un llindar de TPC per identificar píxels de qualitat de fase alta. Aquest mètode de selecció de píxels es capaç de detectar tant els dispersors deterministes (PS) com els distribuïts (DS). Per validar l’eficàcia del mètode desenvolupat, s’ha utilitzat per controlar l’esllavissada de Canillo (Andorra). Els resultats mostren que el mètode TPC pot obtenir la major densitat de píxels vàlids, comparat amb els mètodes clàssics de selecció, en aquesta àrea difícil amb dades de SAR de banda X. En segon lloc, per equilibrar l’efecte d’optimització de fase DInSAR polarimètrica i el cost de càlcul, es desenvolupa un nou algorisme de PolPSI. Aquest algorisme proposat de PolPSI es basa en el resultat de la descomposició de la matriu de coherència per determinar el mecanisme de dispersió òptim de cada píxel, de manera que es denomina CMD-PolPSI. CMDPolPSI no necessita buscar solucions dins de l’espai complet de la solució, per tant, és molt més eficient computacionalment que el mètode clàssic de mecanismes d’igualtat de dispersió (Equal Scattering Mechanism, ESM), però amb un efecte d’optimització no tant òptim. D'altra banda, el seu efecte d'optimització supera el mètode BEST, el que te un menor cost computacional. En tercer lloc, s'ha proposat un algoritme adaptatiu SMF-POLOPT per al filtratge adaptatiu i l'optimització de píxels PolSAR per a aplicacions PolPSI. Aquest algorisme proposat es basa en els resultats de classificació PolSAR per identificar primer els píxels homogenis polarimètrics (PHP) per a cada píxel i, alhora, classificar els píxels PS i DS. Després d'això, els píxels DS es filtren pels seus PHP associats i, a continuació, s'optimitzen en funció de la mètrica de qualitat de la fase d'estabilitat de coherència; els píxels classificats com PS no es filtren i s'optimitzen directament en funció de la mètrica de qualitat de la fase DA. SMF-POLOPT pot reduir simultàniament el soroll de la fase interferomètrica i conservar els detalls de les estructures. Mentrestant, SMF-POLOPT aconsegueix obtenir una densitat molt més alta de píxels vàlids per al seguiment de la deformació que el mètode ESM. Per concloure, en aquesta tesi s’ha desenvolupat i provat un mètode de selecció de píxels, i s’han proposat dos algoritmes PolPSI. Aquest treball contribueix a la recerca en "Advanced Pixel Selection and Optimization Algorithms for Persistent Scatterer Interferometry"Postprint (published version

Image Restoration for Remote Sensing: Overview and Toolbox

Remote sensing provides valuable information about objects or areas from a distance in either active (e.g., RADAR and LiDAR) or passive (e.g., multispectral and hyperspectral) modes. The quality of data acquired by remotely sensed imaging sensors (both active and passive) is often degraded by a variety of noise types and artifacts. Image restoration, which is a vibrant field of research in the remote sensing community, is the task of recovering the true unknown image from the degraded observed image. Each imaging sensor induces unique noise types and artifacts into the observed image. This fact has led to the expansion of restoration techniques in different paths according to each sensor type. This review paper brings together the advances of image restoration techniques with particular focuses on synthetic aperture radar and hyperspectral images as the most active sub-fields of image restoration in the remote sensing community. We, therefore, provide a comprehensive, discipline-specific starting point for researchers at different levels (i.e., students, researchers, and senior researchers) willing to investigate the vibrant topic of data restoration by supplying sufficient detail and references. Additionally, this review paper accompanies a toolbox to provide a platform to encourage interested students and researchers in the field to further explore the restoration techniques and fast-forward the community. The toolboxes are provided in https://github.com/ImageRestorationToolbox.Comment: This paper is under review in GRS

Reliable estimation of orbit errors in spaceborne SAR interferometry. The network approach

An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates

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

Time Series Analysis of Surface Deformation Associated With Fluid Injection and Induced Seismicity in Timpson, Texas Using DInSAR Methods

In recent years, a rise in unconventional oil and gas production in North America has been linked to an increase in seismicity rate in these regions (Ellsworth, 2013). As fluid is pumped into deep formations, the state of stress within the subsurface changes, potentially reactivating pre-existing faults and/or causing subsidence or uplift of the surface. Therefore, hydraulic fracturing and/or fluid disposal injection can significantly increase the seismic hazard to communities and structures surrounding the injection sites (Barnhart et al., 2014). On 17th May 2012 an Mw4.8 earthquake occurred near Timpson, TX and has been linked with wastewater injection operations in the area (Shirzaei et al., 2016). This study aims to spatiotemporally relate, wastewater injection operations to seismicity near Timpson using differential interferometric synthetic aperture radar (DInSAR) analysis. Results are presented as a set of time series, produced using the Multidimensional Small Baseline Subset (MSBAS) InSAR technique, revealing two-dimensional surface deformation

Design and implementation of an SDR-based multi-frequency ground-based SAR system

Synthetic Aperture Radar (SAR) has proven a valuable tool in the monitoring of the Earth, either at a global or local scales. SAR is a coherent radar system able to image extended areas with high resolution, and finds applications in many areas such as forestry, agriculture, mining, structure inspection or security operations. Although space-borne SAR systems can image extended areas, their main limitation is the long revisit times, which are not suitable for applications where the target experiments rapid changes, in the scale of minutes to few days. GBSAR systems have proven useful to fill this revisit time gap by imaging relatively small areas continuously, with extensions usually smaller than a few square kilometers. Ground Based SAR (GBSAR) systems have been used extensively for the monitoring of slope instability, and are a common tool in the mining sector. The development of the GBSAR is relatively recent, and various developments have taken place since the 2000s, transitioning from the usage of Vector Network Analyzers (VNAs) to custom radar cores tailored for this application. This transition is accompanied by a reduction in cost, but at the same time is accompanied by a loss of operational flexibility. Specifically, most GBSAR sensors now operate at a single frequency, losing the value of the multi-band operation that VNAs provided. This work is motivated by the idea that it is worth to use the value of multi-frequency GBSAR measurements, while maintaining a limited system cost. In order to implement a GBSAR with these characteristics, it is realized that Software Defined Radio (SDR) devices are a good option for fast and flexible implementation of broadband transceivers. This thesis details the design and implementation process of an SDR-based Frequency Modulated Continuous Wave (FMCW) GBSAR system from the ground up, presenting the main issues related with the usage of the most common SDR analog architecture, the Zero-IF transceiver. The main problem is determined to be the behavior of spurs related to IQ imbalances of the analog transceiver with the FMCW demodulation process. Two effective techniques to overcome these issues, the Super Spatial Variant Apodization (SSVA) and the Short Time Fourier Transform (STFT) signal reconstruction techniques, are implemented and tested. The thesis also deals with the digital implementation of the signal generator and digital receiver, which are implemented on top of an RF Network-on-Chip (RFNoC) architecture in the SDR Field Programmable Gate Array (FPGA). Another important aspect of this work is the development of an radiofrequency front-end that extends the capabilities of the SDR, implementing filtering, amplification, leakage mitigation and up-conversion to X-band. Finally, a set of test campaigns is described, in which the operation of the system is verified and the value of multi-frequency GBSAR observations is shown.El radar d'obertura sintètica (SAR) ha demostrat ser una eina valuosa en el monitoratge de la Terra, sigui a escala global o local. El SAR és un sistema de radar coherent capaç d’obtenir imatges de zones extenses amb alta resolució i té aplicacions en moltes àrees com la silvicultura, l’agricultura, la mineria, la inspecció d’estructures o les operacions de seguretat. Tot i que els sistemes SAR embarcats en plataformes orbitals poden obtenir imatges d'àrees extenses, la seva principal limitació és el temps de revisita, que no són adequats per a aplicacions on l'objectiu experimenta canvis ràpids, en una escala de minuts a pocs dies. Els sistemes GBSAR han demostrat ser útils per omplir aquesta bretxa de temps, obtenint imatges d'àrees relativament petites de manera contínua, amb extensions generalment inferiors a uns pocs quilòmetres quadrats. Els sistemes SAR terrestres (GBSAR) s’han utilitzat àmpliament per al control de la inestabilitat de talussos i esllavissades i són una eina comuna al sector miner. El desenvolupament del GBSAR és relativament recent i s’han produït diversos desenvolupaments des de la dècada de 2000, passant de l’ús d’analitzadors de xarxes vectorials (VNA) a nuclis de radar personalitzats i adaptats a aquesta aplicació. Aquesta transició s’acompanya d’una reducció del cost, però al mateix temps d’una pèrdua de flexibilitat operativa. Concretament, la majoria dels sensors GBSAR funcionen a una única freqüència, perdent el valor de l’operació en múltiples bandes que proporcionaven els VNA. Aquesta tesi està motivada per la idea de recuperar el valor de les mesures GBSAR multifreqüència, mantenint un cost del sistema limitat. Per tal d’implementar un GBSAR amb aquestes característiques, s’adona que els dispositius de ràdio definida per software (SDR) són una bona opció per a la implementació ràpida i flexible dels transceptors de banda ampla. Aquesta tesi detalla el procés de disseny i implementació d’un sistema GBSAR d’ona contínua modulada en freqüència (FMCW) basat en la tecnologia SDR, presentant els principals problemes relacionats amb l’ús de l’arquitectura analògica de SDR més comuna, el transceptor Zero-IF. Es determina que el problema principal és el comportament dels espuris relacionats amb el balanç de les cadenes de fase i quadratura del transceptor analògic amb el procés de desmodulació FMCW. S’implementen i comproven dues tècniques efectives per minimitzar aquests problemes basades en la reconstrucció de la senyal contaminada per espuris: la tècnica anomenada Super Spatial Variant Apodization (SSVA) i una tècnica basada en la transformada de Fourier amb finestra (STFT). La tesi també tracta la implementació digital del generador de senyal i del receptor digital, que s’implementen sobre una arquitectura RF Network-on-Chip (RFNoC). Un altre aspecte important d’aquesta tesi és el desenvolupament d’un front-end de radiofreqüència que amplia les capacitats de la SDR, implementant filtratge, amplificació, millora de l'aïllament entre transmissió i recepció i conversió a banda X. Finalment, es descriu un conjunt de campanyes de prova en què es verifica el funcionament del sistema i es mostra el valor de les observacions GBSAR multifreqüència

Bistatic SAR data acquisition and processing using SABRINA-X, with TerraSAR-X as the opportunity transmitter

This thesis investigates the acquisition and processing of Bistatic SAR data using SABRINA-X, and with TerraSAR-X as the transmitter of opportunity. SABRINA-X is an X-band receiver system that has been recently designed at the UPC Remote-Sensing Laboratory, while TerraSARX is a German satellite for SAR-based active remote-sensing. Prior to the particular case of acquiring TerraSAR-X signals, the hardware aspects of SABRINAX have been investigated further, and improved as necessary (or suggested for up-gradation in future). Two successful data acquisitions have been carried out, to obtain bistatic SAR images of the Barcelona harbor, with the receiver set-up at the close-by Montjuïc hill. Each acquisition campaign necessitated an accurate prediction of the satellite overpass time and precise orientation of the antennas to acquire the direct signal from the satellite and the backscattered signals off the viewed terrain. The thesis also investigates the characteristics of the acquired signals, which is critical as regards the subsequent processing for imaging and interferometric applications. The hardware limitations, combined with ‘off-nominal’ transmissions of the satellite, necessitate improved range processing of the acquired signals. The thesis expounds the possible range compression techniques, and suggests ways for improved compression, thereby improving the quality of the subsequently processed images