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

Precise orbit determination of LEO satellites : a systematic review

The need for precise orbit determination (POD) has grown significantly due to the increased amount of space-based activities taking place at an accelerating pace. Accurate POD positively contributes to achieving the requirements of Low-Earth Orbit (LEO) satellite missions, including improved tracking, reliability and continuity. This research aims to systematically analyze the LEO–POD in four aspects: (i) data sources used; (ii) POD technique implemented; (iii) validation method applied; (iv) accuracy level obtained. We also present the most used GNSS systems, satellite missions, processing procedures and ephemeris. The review includes studies on LEO–POD algorithms/methods and software published in the last two decades (2000–2021). To this end, 137 primary studies relevant to achieving the objective of this research were identified. After the investigation of these primary studies, it was found that several types of POD techniques have been employed in the POD of LEO satellites, with a clear trend observed for techniques using reduced-dynamic model, least-squares solvers, dual-frequency signals with undifferenced phase and code observations in post-processing mode. This review provides an understanding of the various POD techniques, dataset utilized, validation techniques, and accuracy level of LEO satellites, which have interest to developers of small satellites, new researchers and practitioners.© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.fi=vertaisarvioitu|en=peerReviewed

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

IMPROVING AND EXPANDING PRECISION ORBIT DERIVED ATMOSPHERIC DENSITIES

Atmospheric drag is the most uncertain non-conservative force acting on a low Earth orbiting satellite. The existing atmospheric density models are not accurate enough to model the variations in density, which significantly affect the drag on satellites since drag is directly proportional to atmospheric density. In this research, precision orbit ephemerides (POE) are used as measurements in an optimal orbit determination scheme to estimate corrections to baseline atmospheric density models. These corrections improve the drag estimates, which in turn improve orbit determination and prediction and also provide a better understanding of the upper atmosphere. The POE are used as measurements in a sequential measurement and filtering scheme using the Orbit Determination Tool Kit (ODTK) software, which provides the orbit determination. Five atmospheric density models are available in ODTK, which are used as baseline atmospheric density models to which corrections are made in the orbit determination. These density models are Jacchia 1971, Jacchia-Roberts, CIRA 1972, MSISE 1990, and NRLMSISE 2000. The user has the option to specify the ballistic coefficient (BC) correlated half-life and density correlated half-life. These half-lives are usually given values of 1.8, 18, or 180 minutes. If all five baseline density models are used along with three different combinations of ballistic coefficient and density correlated half-lives, then this would result in forty-five different cases. All the forty-five cases are examined in some studies and only a selected few are examined in others, the details of which are given in the appropriate sections. The POE derived densities are validated by comparing them with accelerometer derived densities for satellites which have accelerometers onboard, such as the Challenging Minisatellite Payload (CHAMP) and the Gravity Recovery and Climate Experiment (GRACE). The trend in the variation is compared quantitatively by calculating the cross correlation between the POE and accelerometer derived densities, and the magnitude is compared by calculating the root mean square between the two. The accelerometer derived densities for both CHAMP and GRACE are available from Sean Bruinsma of CNES and also from Eric Sutton of the United States Air Force Research Laboratory, and are used in this research. The effect of different functions of geomagnetic planetary amplitude (ap) as an input in orbit determination to estimate atmospheric density was investigated. The three different functions of input are 3-hourly ap step functions, linear interpolated ap functions, and ap osculating spline functions. These three different types of functions were used as inputs for all the forty-five different combinations obtained by using the five different baseline atmospheric density models and three different combinations of ballistic coefficient and density correlated half-lives as stated earlier, and POE derived density was estimated for both CHAMP and GRACE. The POE derived densities were compared with the accelerometer derived densities by calculating the CC and RMS. To create continuous data sets of POE derived densities that span a period of one week, the linear weighted blending technique was used to blend the 14 hour POE derived densities in their overlap periods. CIRA 1972 was used as the baseline atmospheric density model and a BC correlated half-life of 1.8 minutes and density correlated half-life of 180 minutes were used as inputs in ODTK to generate these POE derived density estimates. These one week continuous POE derived densities showed better correlation with accelerometer derived densities than HASDM densities for both CHAMP and GRACE. The average cross-sectional area of the satellite that is normal to the velocity vector, the area facing the Sun, and the area facing the Earth, were determined so that these areas could be used to estimate the atmospheric drag, the force due to solar radiation pressure, and the force due to Earth radiation pressure (infrared and Earth albedo). This was done for both TerraSAR-X and ICESat. For TerraSAR-X, the area normal to the velocity vector was assumed be a constant and equal to the frontal area, and the area facing the Earth was also assumed to be constant. However, the area facing the Sun varied with time. The average area facing the Sun for a period of 14 hours and also the annual average area were calculated and used to calculate the POE derived densities. The POE derived densities calculated using these two different average areas facing the Sun were found to be very similar. Since TerraSAR-X does not have an accelerometer onboard, the POE derived densities could not be compared with accelerometer derived densities, but instead were compared with Jacchia-71 densities since this was also one of the outputs from ODTK. The POE derived densities were also compared with NRLMSISE 2000 densities. The attitude of ICESat as a function of beta angle was given in the literature and so was the average area of each side of the satellite when it was modeled as a rectangular box with two solar panels. This information was used to estimate the 30-hour average area normal to the velocity vector, area facing the Earth, and area facing the Sun, for ICESat. The POE derived densities using these areas were estimated by ODTK and compared with the Jacchai-71 density model

Combining Multitemporal Microwave and Optical Remote Sensing Data. Mapping of Land Use / Land Cover, Crop Type, and Crop Traits

Humanity has changed the earth’s surface to a dramatic extent. This is especially true for the area used for agricultural production. Against the background of a growing world population and the associated increased demand for food, it is precisely this area that will become even more important in the future. In order not to have to allocate even more land to agricultural use, optimization and intensification is the only way out of the dilemma. In this context, precise Geoinformation of the agriculturally used area is of central importance. It is utilized for improving land use, producing yield forecasts for more stable food security, and optimizing agricultural management. Rapid developments in the field of satellite-based remote sensing sensors make it possible to monitor agricultural areas with increased spatial, spectral and temporal resolution. However, to retrieve the needed information from this data, new methods are needed. Furthermore, the quality of the data has to be verified. Only then can the presented geodata help to grow crops more sustainably and more efficiently. This thesis develops new approaches for monitoring agricultural areas using the technology of microwave remote sensing in combination with optical remote sensing and existing geodata. It is framed by the overall objective to obtain knowledge on how this combination of data can provide the necessary geoinformation for land use studies, precision farming, and agricultural monitoring systems. Hundreds of remote sensing images from more than eight different satellites were analyzed in six research studies from two different Areas of Interest (AOIs). The studies guide through various spatial scales. First, the general Land Use / Land Cover (LULC) on a regional level in a multi-sensor scenario is derived, evaluating different sensor combinations of varying resolutions. Next, an innovative method is proposed, through which the high geometric accuracy of radar-imaging satellite sensors is exploited to update the spatial accuracy of any external geodata of lower spatial accuracy. Such external data is then used in the next two studies, which focus on cost-effective crop type mapping using Synthetic Aperture Radar (SAR) images. The resulting enhanced LULC maps present the annually changing crop types of the region alongside external, official geoinformation that is not retrievable from remote sensing sensors. The last two research studies deal with a single maize field, on which high resolution optical WorldView-2 images and experimental bistatic SAR observations from TanDEM-X are assessed and combined with ground measurements. As a result, this thesis shows that, depending on the AOI and the application, different resolution demands need to be fulfilled before LULC, crop type, and crop traits mapping can be performed with adequate accuracy. The spatial resolution needs to be adapted to the particularities of the AOI. Evaluation of the sensors showed that SAR sensors proved beneficial for the study objective. Processing the SAR images is complicated, and the images are unintuitive at first sight. However, the advantage of SAR sensors is that they work even in cloudy conditions. This results in an increased temporal resolution, which is particularly important for monitoring the highly dynamic agricultural area. Furthermore, the high geometric accuracy of the SAR images proved ideal for implementing the Multi-Data Approach (MDA). Thus information-rich external geodata could be used to lower the remote sensing resolution needs, improve the accuracy of the LULC-maps, and to provide enhanced LULC-maps. The first study of the maize field demonstrates the potential of the WorldView-2 data in predicting in-field biomass variations, and its increased accuracy when fused with plant height measurements. The second study shows the potential of the TanDEM-X Constellation (TDM) to retrieve plant height from space. LULC, crop type and information on the spatial distribution of biomass can thus be derived efficiently and with high accuracy from the combination of SAR, optical satellites and external geodata. The shown analyses for acquiring such geoinformation represent a high potential for helping to solve the future challenges of agricultural production

Satellite Formation-Flying and Rendezvous

GNSS has come to play an increasingly important role in satellite formation-flying and rendezvous applications. In the last decades, the use of GNSS measurements has provided the primary technique for determining the relative position of cooperative co-orbiting satellites in low Earth orbit

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

Ice dynamics and mass balance in the grounding zone of outlet glaciers in the Transantarctic Mountains

The Antarctic grounding zone has a disproportionately large effect on glacier dynamics and ice sheet stability relative to its size but remains poorly characterised across much of the continent. Accurate ice velocity and thickness information is needed in the grounding zone to determine glacier outflow and establish to what extent changing ocean and atmospheric conditions are affecting the mass balance of individual glacier catchments. This thesis describes new satellite remote sensing techniques for measuring ice velocity and ice thickness, validated using ground measurements collected on the Beardmore, Skelton and Darwin Glaciers and applied to other Transantarctic Mountain outlet glaciers to determine ice discharge. Outlet glaciers in the Transantarctic Mountains provide an important link between the East and West Antarctic Ice Sheets but remain inadequately studied. While long-term velocities in this region are shown here to be stable, instantaneous velocities are sensitive to stresses induced by ocean tides, with fluctuations of up to 50% of the mean observed in GPS measurements. The potential error induced in averaged satellite velocity measurements due to these effects is shown to be resolvable above background noise in the grounding zone but to decrease rapidly upstream. Using a new inverse finite-element modelling approach based on regularization of the elastic-plate bending equations, tidal flexure information from differential InSAR is used to calculate ice stiffness and infer thickness in the grounding zone. This technique is shown to be successful at reproducing the thickness distribution for the Beardmore Glacier, eliminating current issues in the calculation of thickness from freeboard close to the grounding line where ice is not in hydrostatic equilibrium. Modelled thickness agrees to within 10% of ground penetrating radar measurements. Calibrated freeboard measurements and tide-free velocities in the grounding zones of glaciers in the western Ross Sea are used to calculate grounding zone basal melt rates, with values between 1.4 and 11.8 m/a⁻¹ in this region. While strongly dependent on grounding line ice thickness and velocity, melt rates show no latitudinal trend between glaciers, although detailed error analysis highlights the need for much improved estimates of firn density distribution in regions of variable accumulation such as the Transantarctic Mountains

Daylight Measurement Acquisition of Defunct Resident Space Objects Combining Active and Passive Electro-Optical Systems.

The uncontrolled growing number of resident space objects (RSOs) threatens the safe operation of space-related activities. Since the beginning of the Space Age, outer space is getting populated by objects emerging after breakup events; spare components through launching, orbiting, and aging of satellite missions; collisions between functional or defunct RSOs; or by missions that either completed or began their life cycle. One potential measure toward the sustainable use of outer space may start by preventing collisions between existing RSOs. Collisions between existing RSOs will only exacerbate the current situation, which could lead to a cascade effect known as the Kessler syndrome. In the context of such collisions, the enabling of optical daylight tracking has the potential to reduce the uncertainty of the estimated state vector for each RSO, thus aiding the planning and execution of efficient avoidance maneuvers when a collision is foreseeable, as well as benefiting just-in-time collision avoidance strategies in the future. This study starts by analyzing the impact of optical daylight observations, within the domain of defunct RSOs, with respect to the currently restricted nighttime observation windows, the type of observable acquired by the observing station, and the relative geometry between the Sun,the RSO, and the ground station. We highlight the role of key hardware components on each observing system deemed critical for current observing optical ground stations to enable daylight measurement acquisition. Once we have inspected all factors deemed crucial for daylight observations in our system, we present successful daylight observations, from which we derived angular observables, ranges, and apparent brightness. We additionally provide an example where the combination of measurements acquired by the different systems, operating in the optical regime only, contributed to partial disambiguation of the tumbling motion of a selected rocket body. All observations were conducted using a scientific complementary-metal-oxide-semiconductor (CMOS) sensor and a geodetic laser ranging system. Both systems make use of the 1-m Zimmerwald laser and astrometry telescope (ZIMLAT) for measurement acquisition and target RSO tracking at the Swiss Optical Ground Station and Geodynamics Observatory Zimmerwald (SwissOGS), operated by the Astronomical Institute of the University of Bern, Switzerland

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel