Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review

The coastal zone offers among the world’s most productive and valuable ecosystems and is experiencing increasing pressure from anthropogenic impacts: human settlements, agriculture, aquaculture, trade, industrial activities, oil and gas exploitation and tourism. Earth observation has great capability to deliver valuable data at the local, regional and global scales and can support the assessment and monitoring of land‐ and water‐related applications in coastal zones. Compared to optical satellites, cloud‐cover does not limit the timeliness of data acquisition with spaceborne Synthetic Aperture Radar (SAR) sensors, which have all‐weather, day and night capabilities. Hence, active radar systems demonstrate great potential for continuous mapping and monitoring of coastal regions, particularly in cloud‐prone tropical and sub‐tropical climates. The canopy penetration capability with long radar wavelength enables L‐band SAR data to be used for coastal terrestrial environments and has been widely applied and investigated for the following geoscientific topics: mapping and monitoring of flooded vegetation and inundated areas; the retrieval of aboveground biomass; and the estimation of soil moisture. Human activities, global population growth, urban sprawl and climate change‐induced impacts are leading to increased pressure on coastal ecosystems causing land degradation, deforestation and land use change. This review presents a comprehensive overview of existing research articles that apply spaceborne L‐band SAR data for geoscientific analyses that are relevant for coastal land applications

Atmospheric artifacts correction for InSAR using empirical model and numerical weather prediction models

lnSAR has been proved its unprecedented ability and merits of monitoring ground deformation on large scale with centimeter to millimeter scale accuracy. However, several factors affect the reliability and accuracy of its applications. Among them, atmospheric artifacts due to spatial and temporal variations of atmosphere state often pose noise to interferograms. Therefore, atmospheric artifacts m itigalion remains one of the biggest challenges to be addressed in the In SAR community. State-of-the-art research works have revealed atmospheric artifacts can be partially compensated with empirical models, temporal-spatial filtering approach in lnSAR time series, pointwise GPS zenith path delay and numerical weather prediction models. In this thesis, firstly, we further develop a covariance weighted linear empirical model correction method. Secondly, a realistic LOS direction integration approach based on global reanalysis data is employed and comprehensively compared with the conventional method that integrates along zenith direction. Finally, the realistic integration method is applied to local WRF numerical forecast model data. l'vbreover, detailed comparisons between different global reanalysis data and local WRF model are assessed. In terms of empirical models correcting methods, many publications have studied correcting stratified tropospheric phase delay by assuming a linear model between them and topography. However, most of these studies ha\19 not considered the effect of turbulent atmospheric artefacts when adjusting the linear model to data. In this thesis, an improved technique that minimizes the influence of turbulent atmosphere in the model adjustment has been presented. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its APS covariance estimated from an empirical variogram to reduce in the model adjustment the impact of pixel pairs with significant turbulent atmosphere. The performance of the proposed method has been validated with both simulated and real Sentinel-1 SAR data in Tenerife island, Spain. Considering methods using meteorological observations to mitigate APS, an accurate realistic com puling strategy utilizing global atmospheric reanalysis data has been implemented. With the approach, the realistic LOS path along satellite and the monitored points is considered, rather than converting from zenith path delay. Com pared with zenith delay based method, the biggest advantage is that it can avoid errors caused by anisotropic atmospheric behaviour. The accurate integration method is validated with Sentinel-1 data in three test sites: Tenerife island, Spain, Almeria, Spain and Crete island, Greece. Compared to conventional zenith method, the realistic integration method shows great improvement. A variety of global reanalysis data are available from different weather forecasting organizations, such as ERA-Interim, ERAS, MERRA2. In this study, the realistic integration mitigation method is assessed on these different reanalysis data. The results show that these data are feasible to mitigate APS to some extent in most cases. The assessment also demonstrates that the ERAS performs the best statistically, compared to other global reanalysis data. l'vbreover, as local numerical weather forecast models have the ability to predict high spatial resolution atmospheric parameters, by using which, it has the potential to achieve APS mitigation. In this thesis, the realistic integration method is also employed on the local WRF model data in Tenerife and Almeria test s ites. However, it turns out that the WRF model performs worse than the original global reanalysis data.Las técnicas lnSAR han demostrado su capacidad sin precedentes y méritos para el monitoreo de la deformaci6n del suelo a gran escala con una precisión centimétrica o incluso milimétrica. Sin embargo, varios factores afectan la fiabilidad y precisión de sus aplicaciones. Entre ellos, los artefactos atmosféricos debidos a variaciones espaciales y temporales del estado de la atm6sfera a menudo añaden ruido a los interferogramas. Por lo tanto, la mitigación de los artefactos atmosféricos sigue siendo uno de los mayores desafíos a abordar en la comunidad lnSAR. Los trabajos de investigaci6n de vanguardia han revelado que los artefactos atmosféricos se pueden compensar parcialmente con modelos empíricos, enfoque de filtrado temporal-espacial en series temporales lnSAR, retardo puntual del camino cenital con GPS y modelos numéricos de predicción meteorológica. En esta tesis, en primer lugar, desarrollamos un método de corrección de modelo empírico lineal ponderado por covarianza. En segundo lugar, se emplea un enfoque realista de integracion de dirección LOS basado en datos de reanálisis global y se compara exhaustivamente con el método convencional que se integra a lo largo de la dirección cenital. Finalmente, el método de integraci6n realista se aplica a los datos del modelo de pronóstico numérico WRF local. Ademas, se evalúan las comparaciones detalladas entre diferentes datos de reanálisis global y el modelo WRF local. En términos de métodos de corrección con modelos empíricos, muchas publicaciones han estudiado la corrección del retraso estratificado de la fase troposférica asumiendo un modelo lineal entre ellos y la topografía. Sin embargo, la mayoría de estos estudios no han considerado el efecto de los artefactos atmosféricos turbulentos al ajustar el modelo lineal a los datos. En esta tesis, se ha presentado una técnica mejorada que minimiza la influencia de la atm6sfera turbulenta en el ajuste del modelo. En el algoritmo propuesto, el modelo se ajusta a las diferencias de fase de los pixeles en lugar de utilizar la fase sin desenrollar de cada pixel. Además, las diferentes diferencias de fase se ponderan en función de su covarianza APS estimada a partir de un variograma empírico para reducir en el ajuste del modelo el impacto de los pares de pixeles con una atm6sfera turbulenta significativa. El rendimiento del método propuesto ha sido validado con datos SAR Sentinel-1 simulados y reales en la isla de Tenerife, España. Teniendo en cuenta los métodos que utilizan observaciones meteorológicas para mitigar APS, se ha implementado una estrategia de computación realista y precisa que utiliza datos de reanálisis atmosférico global. Con el enfoque, se considera el camino realista de LOS a lo largo del satélite y los puntos monitoreados, en lugar de convertirlos desde el retardo de la ruta cenital. En comparación con el método basado en la demora cenital, la mayor ventaja es que puede evitar errores causados por el comportamiento atmosférico anisotrópico. El método de integración preciso se valida con los datos de Sentinel-1 en tres sitios de prueba: la isla de Tenerife, España, Almería, España y la isla de Creta, Grecia. En comparación con el método cenital convencional, el método de integración realista muestra una gran mejora.Postprint (published version

Atmospheric artifacts correction for InSAR using empirical model and numerical weather prediction models

lnSAR has been proved its unprecedented ability and merits of monitoring ground deformation on large scale with centimeter to millimeter scale accuracy. However, several factors affect the reliability and accuracy of its applications. Among them, atmospheric artifacts due to spatial and temporal variations of atmosphere state often pose noise to interferograms. Therefore, atmospheric artifacts m itigalion remains one of the biggest challenges to be addressed in the In SAR community. State-of-the-art research works have revealed atmospheric artifacts can be partially compensated with empirical models, temporal-spatial filtering approach in lnSAR time series, pointwise GPS zenith path delay and numerical weather prediction models. In this thesis, firstly, we further develop a covariance weighted linear empirical model correction method. Secondly, a realistic LOS direction integration approach based on global reanalysis data is employed and comprehensively compared with the conventional method that integrates along zenith direction. Finally, the realistic integration method is applied to local WRF numerical forecast model data. l'vbreover, detailed comparisons between different global reanalysis data and local WRF model are assessed. In terms of empirical models correcting methods, many publications have studied correcting stratified tropospheric phase delay by assuming a linear model between them and topography. However, most of these studies ha\19 not considered the effect of turbulent atmospheric artefacts when adjusting the linear model to data. In this thesis, an improved technique that minimizes the influence of turbulent atmosphere in the model adjustment has been presented. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its APS covariance estimated from an empirical variogram to reduce in the model adjustment the impact of pixel pairs with significant turbulent atmosphere. The performance of the proposed method has been validated with both simulated and real Sentinel-1 SAR data in Tenerife island, Spain. Considering methods using meteorological observations to mitigate APS, an accurate realistic com puling strategy utilizing global atmospheric reanalysis data has been implemented. With the approach, the realistic LOS path along satellite and the monitored points is considered, rather than converting from zenith path delay. Com pared with zenith delay based method, the biggest advantage is that it can avoid errors caused by anisotropic atmospheric behaviour. The accurate integration method is validated with Sentinel-1 data in three test sites: Tenerife island, Spain, Almeria, Spain and Crete island, Greece. Compared to conventional zenith method, the realistic integration method shows great improvement. A variety of global reanalysis data are available from different weather forecasting organizations, such as ERA-Interim, ERAS, MERRA2. In this study, the realistic integration mitigation method is assessed on these different reanalysis data. The results show that these data are feasible to mitigate APS to some extent in most cases. The assessment also demonstrates that the ERAS performs the best statistically, compared to other global reanalysis data. l'vbreover, as local numerical weather forecast models have the ability to predict high spatial resolution atmospheric parameters, by using which, it has the potential to achieve APS mitigation. In this thesis, the realistic integration method is also employed on the local WRF model data in Tenerife and Almeria test s ites. However, it turns out that the WRF model performs worse than the original global reanalysis data.Las técnicas lnSAR han demostrado su capacidad sin precedentes y méritos para el monitoreo de la deformaci6n del suelo a gran escala con una precisión centimétrica o incluso milimétrica. Sin embargo, varios factores afectan la fiabilidad y precisión de sus aplicaciones. Entre ellos, los artefactos atmosféricos debidos a variaciones espaciales y temporales del estado de la atm6sfera a menudo añaden ruido a los interferogramas. Por lo tanto, la mitigación de los artefactos atmosféricos sigue siendo uno de los mayores desafíos a abordar en la comunidad lnSAR. Los trabajos de investigaci6n de vanguardia han revelado que los artefactos atmosféricos se pueden compensar parcialmente con modelos empíricos, enfoque de filtrado temporal-espacial en series temporales lnSAR, retardo puntual del camino cenital con GPS y modelos numéricos de predicción meteorológica. En esta tesis, en primer lugar, desarrollamos un método de corrección de modelo empírico lineal ponderado por covarianza. En segundo lugar, se emplea un enfoque realista de integracion de dirección LOS basado en datos de reanálisis global y se compara exhaustivamente con el método convencional que se integra a lo largo de la dirección cenital. Finalmente, el método de integraci6n realista se aplica a los datos del modelo de pronóstico numérico WRF local. Ademas, se evalúan las comparaciones detalladas entre diferentes datos de reanálisis global y el modelo WRF local. En términos de métodos de corrección con modelos empíricos, muchas publicaciones han estudiado la corrección del retraso estratificado de la fase troposférica asumiendo un modelo lineal entre ellos y la topografía. Sin embargo, la mayoría de estos estudios no han considerado el efecto de los artefactos atmosféricos turbulentos al ajustar el modelo lineal a los datos. En esta tesis, se ha presentado una técnica mejorada que minimiza la influencia de la atm6sfera turbulenta en el ajuste del modelo. En el algoritmo propuesto, el modelo se ajusta a las diferencias de fase de los pixeles en lugar de utilizar la fase sin desenrollar de cada pixel. Además, las diferentes diferencias de fase se ponderan en función de su covarianza APS estimada a partir de un variograma empírico para reducir en el ajuste del modelo el impacto de los pares de pixeles con una atm6sfera turbulenta significativa. El rendimiento del método propuesto ha sido validado con datos SAR Sentinel-1 simulados y reales en la isla de Tenerife, España. Teniendo en cuenta los métodos que utilizan observaciones meteorológicas para mitigar APS, se ha implementado una estrategia de computación realista y precisa que utiliza datos de reanálisis atmosférico global. Con el enfoque, se considera el camino realista de LOS a lo largo del satélite y los puntos monitoreados, en lugar de convertirlos desde el retardo de la ruta cenital. En comparación con el método basado en la demora cenital, la mayor ventaja es que puede evitar errores causados por el comportamiento atmosférico anisotrópico. El método de integración preciso se valida con los datos de Sentinel-1 en tres sitios de prueba: la isla de Tenerife, España, Almería, España y la isla de Creta, Grecia. En comparación con el método cenital convencional, el método de integración realista muestra una gran mejora

InSAR Data Processing in Digital Elevation Models Creating Tasks: State-of-Art and Issues

Поступила: 10.07.2020. Принята в печать: 30.07.2020.Received: 10.07.2020. Accepted: 30.07.2020.Представлена ретроспектива и обзор современного состояния технологий интерферометрической обработки радиолокационных данных, получаемых космическими радиоэлектронными системами дистанционного зондирования Земли, в задачах построения цифровых моделей рельефа. Рассмотрены вопросы моделирования интерферометрической обработки радиолокационных данных и практических способов ее реализации, а также ошибок способы оценивания точности восстановления абсолютной фазы и рельефа местности.The paper presents a retrospective review and current state-of-art of radar data interferometric processing techniques (InSAR) in space-based radio-electronic systems of the remote sensing of the Earth in the tasks of digital elevation models (DEM) constructing. History of InSAR systems development and trends in the development of data processing methods are considered. It is shown, that InSAR systems take their origin from radio astronomic tasks, related to the Moon and planets’ surface investigations, carried out by the USA and the USSR in 1960th. Since 1980th the InSAR techniques are widely used for the Earth remote sensing tasks (digital elevation models creation, surface displacements detection, recognition of vegetation features, etc.), but the problems of absolute phase restoration inhibit the wide utilization of such systems in the Earth monitoring and mapping tasks, because the accuracy of digital elevation models obtained by such systems remains disputable. The mathematical model and principles of interferometric processing of data from satellite synthetic aperture radar are reviewed in conjunction with problems of absolute phase restoration errors measurement. We demonstrate, that despite the existing diversity of interferometric algorithms (i.e. phase noise filtration algorithms, phase unwrapping algorithms), the existing ways of accuracy assessment of the obtained result implies an end-to-end DEM validation, which complicates the comparative study of InSAR processing algorithms efficiency analysis. So, the author’s proposals for such analysis, based on reference DEM backward geocoding and error functions analysis, are reviewed. This approach allows identifying optimal values and combinations of parameters for interferometric algorithms at each processing stage, and it is applicable for remote sensing radar data obtained by different radar systems in different imaging modes

Интерферометрическая обработка данных космических радиолокаторов с синтезированной апертурой при создании цифровых моделей рельефа земной поверхности: состояние и проблемы

Представлена ретроспектива и обзор современного состояния технологий интерферометрической обработки радиолокационных данных, получаемых космическими радиоэлектронными системами дистанционного зондирования Земли, в задачах построения цифровых моделей рельефа. Рассмотрены вопросы моделирования интерферометрической обработки радиолокационных данных и практических способов ее реализации, а также ошибок способы оценивания точности восстановления абсолютной фазы и рельефа местности. Сосновский А. В. Интерферометрическая обработка данных космиче- ских радиолокаторов с синтезированной апертурой при создании циф- ровых моделей рельефа земной поверхности: состояние и проблемы. Ural Radio Engineering Journal. 2020;4(2):198–233. DOI: 10.15826/ urej.2020.4.2.004

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Generic interferometric synthetic aperture radar atmospheric correction model and its application to co- and post-seismic motions

PhD ThesisThe tremendous development of Interferometric Synthetic Aperture Radar (InSAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses more challenges for correcting atmospheric effects due to the spatial-temporal variability of atmospheric delays. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate the atmospheric delays, but they are limited by (i) the availability (and distribution) of GPS stations; (ii) the time difference between NWM and radar observations; and (iii) the difficulties in quantifying their performance. To overcome the abovementioned limitations, we have developed the Iterative Tropospheric Decomposition (ITD) model to reduce the coupling effects of the troposphere turbulence and stratification and hence achieve similar performances over flat and mountainous terrains. Highresolution European Centre for Medium-Range Weather Forecasts (ECMWF) and GPS-derived tropospheric delays were properly integrated by investigating the GPS network geometry and topography variations. These led to a generic atmospheric correction model with a range of notable features: (i) global coverage, (ii) all-weather, all-time usability, (iii) available with a maximum of two-day latency, and (iv) indicators available to assess the model’s performance and feasibility. The generic atmospheric correction model enables the investigation of the small magnitude coseismic deformation of the 2017 Mw-6.4 Nyingchi earthquake from InSAR observations in spite of substantial atmospheric contamination. It can also minimize the temporal correlations of InSAR atmospheric delays so that reliable velocity maps over large spatial extents can be achieved. Its application to the post-seismic motion following the 2016 Kaikoura earthquake shows a success to recover the time-dependent afterslip distribution, which in turn evidences the deep inactive subduction slip mechanism. This procedure can be used to map surface deformation in other scenarios including volcanic eruptions, tectonic rifting, cracking, and city subsidence.This work was supported by a Chinese Scholarship Council studentship. Part of this work was also supported by the UK NERC through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET)

Monitoring Snow Cover and Snowmelt Dynamics and Assessing their Influences on Inland Water Resources

Snow is one of the most vital cryospheric components owing to its wide coverage as well as its unique physical characteristics. It not only affects the balance of numerous natural systems but also influences various socio-economic activities of human beings. Notably, the importance of snowmelt water to global water resources is outstanding, as millions of populations rely on snowmelt water for daily consumption and agricultural use. Nevertheless, due to the unprecedented temperature rise resulting from the deterioration of climate change, global snow cover extent (SCE) has been shrinking significantly, which endangers the sustainability and availability of inland water resources. Therefore, in order to understand cryo-hydrosphere interactions under a warming climate, (1) monitoring SCE dynamics and snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced waterbodies, and (3) assessing the causal effect of snowmelt conditions on inland water resources are indispensable. However, for each point, there exist many research questions that need to be answered. Consequently, in this thesis, five objectives are proposed accordingly. Objective 1: Reviewing the characteristics of SAR and its interactions with snow, and exploring the trends, difficulties, and opportunities of existing SAR-based SCE mapping studies; Objective 2: Proposing a novel total and wet SCE mapping strategy based on freely accessible SAR imagery with all land cover classes applicability and global transferability; Objective 3: Enhancing total SCE mapping accuracy by fusing SAR- and multi-spectral sensor-based information, and providing total SCE mapping reliability map information; Objective 4: Proposing a cloud-free and illumination-independent inland waterbody dynamics tracking strategy using freely accessible datasets and services; Objective 5: Assessing the influence of snowmelt conditions on inland water resources

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