Orbital Effects in Spaceborne Synthetic Aperture Radar Interferometry

This book reviews and investigates orbit-related effects in synthetic aperture Radar interferometry (InSAR). The translation of orbit inaccuracies to error signals in the interferometric phase is concisely described; estimation and correction approaches are discussed and evaluated with special focus on network adjustment of redundantly estimated baseline errors. Moreover, the effect of relative motion of the orbit reference frame is addressed

An introduction to the interim digital SAR processor and the characteristics of the associated Seasat SAR imagery

Basic engineering data regarding the Interim Digital SAR Processor (IDP) and the digitally correlated Seasat synthetic aperature radar (SAR) imagery are presented. The correlation function and IDP hardware/software configuration are described, and a preliminary performance assessment presented. The geometric and radiometric characteristics, with special emphasis on those peculiar to the IDP produced imagery, are described

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

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

Orbital Effects in Spaceborne Synthetic Aperture Radar Interferometry

This book reviews and investigates orbit-related effects in synthetic aperture Radar interferometry (InSAR). The translation of orbit inaccuracies to error signals in the interferometric phase is concisely described; estimation and correction approaches are discussed and evaluated with special focus on network adjustment of redundantly estimated baseline errors. Moreover, the effect of relative motion of the orbit reference frame is addressed

Geocoding and stereoscopy of synthetic aperture radar imagery.

This thesis is concerned with the geocoding of Synthetic Aperture Radar (SAR) images and the use of stereo SAR images. The work was carried out as part of the preparation for the launch of the ERS-1 sateffite, due in July 1991, which will carry a SAR sensor. There are two basic approaches to geocoding: image-to-object and object-to-image. Both of these methods have been analysed and assessed on experimental data, namely SIR-B imagery of Mount Shasta. Each type of geocoding requires the solution of nonlinear equations. It has been shown that if the parameters which control the geocoding process are given to a good degree of accuracy, each method can give good results. The effect of inaccuracies in the estimation of these parameters has also been analysed. It was found that there was a predominantly linear response to parameter error in both types of geocoding. Experimental investigations into the effects of the resampling, inherent in operational geocoding, showed that the statistical properties of the resulting image may be severely corrupted with pixel values of less than zero being obtained. This discovery has subsequently been given theoretical support. Height can be determined from stereo pairs of images and digital elevation models can thus be produced, aiding both geocoding and topographic mapping. Existing approaches to SAR/SAR stereo all appear to be based on photograinmetric methods. An alternative, analytic approach, believed to be novel, is described and applied to the same Mount Shasta imagery. Using this method, with accurately-known controlling parameters, correspondence with ground data is excellent. However, an analysis of the sensitivity of the approach to inaccuracies in the controlling parameters shows that the method is extremely sensitive to error. The possibility of combining SAR and optical/infrared imagery for stereometric purposes is also discussed from a theoretical viewpoint

GNSS reflectometry for land remote sensing applications

Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological and carbon cycle. On the other hand, soil moisture is essential for agricultural applications and water management, and vegetation biomass is crucial for regional development programs. Several remote sensing techniques have been used to measure these two parameters. However, retrieving soil moisture and vegetation biomass with the required accuracy, and the appropriate spatial and temporal resolutions still remains a major challenge. The use of Global Navigation Satellite Systems (GNSS) reflected signals as sources of opportunity for measuring soil moisture and vegetation biomass is assessed in this PhD Thesis. This technique, commonly known as GNSS-Reflectometry (GNSS-R), has gained increasing interest among the scienti c community during the last two decades due to its unique characteristics. Previous experimental works have already shown the capabilities of GNSS-R to sense small reflectivity changes on the surface. The use of the co- and cross-polarized reflected signals was also proposed to mitigate nuisance parameters, such as soil surface roughness, in the determination of soil moisture. However, experimental evidence of the suitability of that technique could not be demonstrated. This work analyses from a theoretical and an experimental point of view the capabilities of polarimetric observations of GNSS reflected signals for monitoring soil moisture and vegetation biomass. The Thesis is structured in four main parts. The fi rst part examines the fundamental aspects of the technique and provides a detailed review of the GNSS-R state of the art for soil moisture and vegetation monitoring. The second part deals with the scattering models from land surfaces. A comprehensive description of the formation of scattered signals from rough surfaces is provided. Simulations with current state of the art models for bare and vegetated soils were performed in order to analyze the scattering components of GNSS reflected signals. A simpli ed scattering model was also developed in order to relate in a straightforward way experimental measurements to soil bio-geophysical parameters. The third part reviews the experimental work performed within this research. The development of a GNSS-R instrument for land applications is described, together with the three experimental campaigns carried out in the frame of this PhD Thesis. The analysis of the GNSS-R and ground truth data is also discussed within this part. As predicted by models, it was observed that GNSS scattered signals from natural surfaces are a combination of a coherent and an incoherent scattering components. A data analysis technique was proposed to separate both scattering contributions. The use of polarimetric observations for the determination of soil moisture was demonstrated to be useful under most soil conditions. It was also observed that forests with high levels of biomass could be observed with GNSS reflected signals. The fourth and last part of the Thesis provides an analysis of the technology perspectives. A GNSS-R End-to-End simulator was used to determine the capabilities of the technique to observe di erent soil reflectivity conditions from a low Earth orbiting satellite. It was determined that high accuracy in the estimation of reflectivity could be achieved within reasonable on-ground resolution, as the coherent scattering component is expected to be the predominant one in a spaceborne scenario. The results obtained in this PhD Thesis show the promising potential of GNSS-R measurements for land remote sensing applications, which could represent an excellent complementary observation for a wide range of Earth Observation missions such as SMOS, SMAP, and the recently approved ESA Earth Explorer Mission Biomass.La humedad del suelo y la biomasa de la vegetaci on son dos parametros clave desde un punto de vista tanto cient co como econ omico. Por una parte son esenciales para el estudio del ciclo del agua y del carbono. Por otra parte, la humedad del suelo es esencial para la gesti on de las cosechas y los recursos h dricos, mientras que la biomasa es un par ametro fundamental para ciertos programas de desarrollo. Varias formas de teledetección se han utilizado para la observaci on remota de estos par ametros, sin embargo, su monitorizaci on con la precisi on y resoluci on necesarias es todav a un importante reto tecnol ogico. Esta Tesis evalua la capacidad de medir humedad del suelo y biomasa de la vegetaci on con señales de Sistemas Satelitales de Posicionamiento Global (GNSS, en sus siglas en ingl es) reflejadas sobre la Tierra. La t ecnica se conoce como Reflectometr í a GNSS (GNSS-R), la cual ha ganado un creciente inter es dentro de la comunidad científ ca durante las dos ultimas d ecadas. Experimentos previos a este trabajo ya demostraron la capacidad de observar cambios en la reflectividad del terreno con GNSS-R. El uso de la componente copolar y contrapolar de la señal reflejada fue propuesto para independizar la medida de humedad del suelo de otros par ametros como la rugosidad del terreno. Sin embargo, no se pudo demostrar una evidencia experimental de la viabilidad de la t ecnica. En este trabajo se analiza desde un punto de vista te orico y experimental el uso de la informaci on polarim etrica de la señales GNSS reflejadas sobre el suelo para la determinaci on de humedad y biomasa de la vegetaci on. La Tesis se estructura en cuatro partes principales. En la primera parte se eval uan los aspectos fundamentales de la t ecnica y se da una revisi on detallada del estado del arte para la observaci on de humedad y vegetaci on. En la segunda parte se discuten los modelos de dispersi on electromagn etica sobre el suelo. Simulaciones con estos modelos fueron realizadas para analizar las componentes coherente e incoherente de la dispersi on de la señal reflejada sobre distintos tipos de terreno. Durante este trabajo se desarroll o un modelo de reflexi on simpli cado para poder relacionar de forma directa las observaciones con los par ametros geof sicos del suelo. La tercera parte describe las campañas experimentales realizadas durante este trabajo y discute el an alisis y la comparaci on de los datos GNSS-R con las mediciones in-situ. Como se predice por los modelos, se comprob o experimentalmente que la señal reflejada est a formada por una componente coherente y otra incoherente. Una t ecnica de an alisis de datos se propuso para la separacióon de estas dos contribuciones. Con los datos de las campañas experimentales se demonstr o el bene cio del uso de la informaci on polarim etrica en las señales GNSS reflejadas para la medici on de humedad del suelo, para la mayor a de las condiciones de rugosidad observadas. Tambi en se demostr o la capacidad de este tipo de observaciones para medir zonas boscosas densamente pobladas. La cuarta parte de la tesis analiza la capacidad de la t ecnica para observar cambios en la reflectividad del suelo desde un sat elite en orbita baja. Los resultados obtenidos muestran que la reflectividad del terreno podr a medirse con gran precisi on ya que la componente coherente del scattering ser a la predominante en ese tipo de escenarios. En este trabajo de doctorado se muestran la potencialidades de la t ecnica GNSS-R para observar remotamente par ametros del suelo tan importantes como la humedad del suelo y la biomasa de la vegetaci on. Este tipo de medidas pueden complementar un amplio rango de misiones de observaci on de la Tierra como SMOS, SMAP, y Biomass, esta ultima recientemente aprobada para la siguiente misi on Earth Explorer de la ESA

Opportunistic radar imaging using a multichannel receiver

Bistatic Synthetic Aperture Radars have a physically separated transmitter and receiver where one or both are moving. Besides the advantages of reduced procurement and maintenance costs, the receiving system can sense passively while remaining covert which offers obvious tactical advantages. In this work, spaceborne monostatic SARs are used as emitters of opportunity with a stationary ground-based receiver. The imaging mode of SAR systems over land is usually a wide-swath mode such as ScanSAR or TOPSAR in which the antenna scans the area of interest in range to image a larger swath at the expense of degraded cross-range resolution compared to the conventional stripmap mode. In the bistatic geometry considered here, the signals from the sidelobes of the scanning beams illuminating the adjacent sub-swath are exploited to produce images with high cross-range resolution from data obtained from a SAR system operating in wide-swath mode. To achieve this, the SAR inverse problem is rigorously formulated and solved using a Maximum A Posteriori estimation method providing enhanced cross-range resolution compared to that obtained by classical burst-mode SAR processing. This dramatically increases the number of useful images that can be produced using emitters of opportunity. Signals from any radar satellite in the receiving band of the receiver can be used, thus further decreasing the revisit time of the area of interest. As a comparison, a compressive sensing-based method is critically analysed and proves more sensitive to off-grid targets and only suited to sparse scene. The novel SAR imaging method is demonstrated using simulated data and real measurements from C-band satellites such as RADARSAT-2 and ESA’s satellites ERS-2, ENVISAT and Sentinel-1A. In addition, this thesis analyses the main technological issues in bistatic SAR such as the azimuth-variant characteristic of bistatic data and the effect of imperfect synchronisation between the non-cooperative transmitter and the receiver

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