Information retrieval from spaceborne GNSS Reflectometry observations using physics- and learning-based techniques

This dissertation proposes a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The proposed methodology has been built upon the literature review, analyses, and findings from a number of published studies throughout the dissertation research. Namely, a Sig- nals of Opportunity Coherent Bistatic scattering model (SCoBi) has been first developed at MSU and then its simulator has been open-sourced. Simulated GNSS-Reflectometry (GNSS-R) analyses have been conducted by using SCoBi. Significant findings have been noted such that (1) Although the dominance of either the coherent reflections or incoher- ent scattering over land is a debate, we demonstrated that coherent reflections are stronger for flat and smooth surfaces covered by low-to-moderate vegetation canopy; (2) The influ- ence of several land geophysical parameters such as SM, vegetation water content (VWC), and surface roughness on the bistatic reflectivity was quantified, the dynamic ranges of reflectivity changes due to SM and VWC are much higher than the changes due to the surface roughness. Such findings of these analyses, combined with a comprehensive lit- erature survey, have led to the present inversion algorithm: Physics- and learning-based retrieval of soil moisture information from space-borne GNSS-R measurements that are taken by NASA’s CYGNSS mission. The study is the first work that proposes a machine learning-based, non-parametric, and non-linear regression algorithm for CYGNSS-based soil moisture estimation. The results over point-scale soil moisture observations demon- strate promising performance for applicability to large scales. Potential future work will be extension of the methodology to global scales by training the model with larger and diverse data sets

Forward and Inverse Modeling of GPS Multipath for Snow Monitoring

Snowpacks provide reservoirs of freshwater, storing solid precipitation and delaying runoff to be released later in the spring and summer when it is most needed. The goal of this dissertation is to develop the technique of GPS multipath reflectometry (GPS-MR) for ground-based measurement of snow depth. The phenomenon of multipath in GPS constitutes the reception of reflected signals in conjunction with the direct signal from a satellite. As these coherent direct and reflected signals go in and out of phase, signal-to-noise ratio (SNR) exhibits peaks and troughs that can be related to land surface characteristics. In contrast to other GPS reflectometry modes, in GPS-MR the poorly separated composite signal is collected utilizing a single antenna and correlated against a single replica. SNR observations derived from the newer L2-frequency civilian GPS signal (L2C) are used, as recorded by commercial off-the-shelf receivers and geodetic-quality antennas in existing GPS sites. I developed a forward/inverse approach for modeling GPS multipath present in SNR observations. The model here is unique in that it capitalizes on known information about the antenna response and the physics of surface scattering to aid in retrieving the unknown snow conditions in the antenna surroundings. This physically-based forward model is utilized to simulate the surface and antenna coupling. The statistically-rigorous inverse model is considered in two parts. Part I (theory) explains how the snow characteristics are parameterized; the observation/parameter sensitivity; inversion errors; and parameter uncertainty, which serves to indicate the sensing footprint where the reflection originates. Part II (practice) applies the multipath model to SNR observations and validates the resulting GPS retrievals against independent in situ measurements during a 1-3 year period in three different environments - grasslands, alpine, and forested. The assessment yields a correlation of 0.98 and an RMS error of 6-8 cm, with the GPS under-estimating in situ snow depth by approximately 15%. GPS daily site averages were found effective in mitigating random noise without unduly smoothing the sharp transitions as captured in new snow events. This work corroborates the readiness of quality-controlled GPS-MR for snow depth monitoring, reinforcing its maturity for operational usage

Simulation and observations of stratospheric aerosols from the 2009 Sarychev volcanic eruption

We used a general circulation model of Earth’s climate to conduct simulations of the 12-16 June 2009 eruption of Sarychev volcano (48.1°N, 153.2°E). The model simulates the formation and transport of the stratospheric sulfate aerosol cloud from the eruption and the resulting climate response. We compared optical depth results from these simulations with limb scatter measurements from the Optical Spectrograph and InfraRed Imaging System (OSIRIS), in situ measurements from balloon-borne instruments lofted from Laramie, Wyoming (41.3°N, 105.7°W), and five lidar stations located throughout the Northern Hemisphere. The aerosol cloud covered most of the Northern Hemisphere, extending slightly into the tropics, with peak backscatter measured between 12 and 16 km in altitude. Aerosol concentrations returned to near background levels by Spring, 2010. After accounting for expected sources of discrepancy between each of the data sources, the magnitudes and spatial distributions of aerosol optical depth due to the eruption largely agree. In conducting the simulations, we likely overestimated both particle size and the amount of SO2 injected into the stratosphere, resulting in modeled optical depth values that were a factor of 2-4 too high. Model results of optical depth due to the eruption show a peak too late in high latitudes and too early in low latitudes, suggesting a problem with stratospheric circulation in the model. The model also shows a higher annual decay rate in optical depth than is observed, showing an inaccuracy in seasonal deposition rates. The modeled deposition rate of sulfate aerosols from the Sarychev eruption is higher than the rate calculated for aerosols from the 1991 eruption of Mt. Pinatubo

Vegetation/Forest Effects in Microwave Remote Sensing of Soil Moisture

This thesis includes (1) the distorted Born approximation (DBA) and an improved coherent model for vegetation-covered surfaces at L-band for data-cube based soil moisture retrieval; (2) a unified approach for combined active and passive remote sensing of vegetation-covered surfaces with the same input physical parameters; (3) Numerical Maxwell Model in 3D (NMM3D) simulations of a vegetation canopy comprising randomly distributed dielectric cylinders; and (4) a hybrid method based on the generalized T matrix of single objects and Foldy-Lax equations for NMM3D full-wave simulations of the realistic vegetation/forest with vector spherical, spheroidal and cylindrical wave expansoins. The main contributions and novelty of this thesis are NMM3D full-wave simulations of vegetation/forest canopy using the generalized T matrix of the single object and Foldy-Lax equations of multiple scattering among many objects. Before this work, the large-scale full-wave simulations of vegetation/forst such as many tree trunks were deemed very difficult. The NMM3D full-wave simulation results showed that the results of past models significantly overestimate attenuation in a vegetation/forest canopy. The NMM3D full-wave models predict transmissions that are several times greater than that of past models. A much greater microwave transmission means the microwave can better penetrate a vegetation/forest canopy and thus it can be used to retrieve soil moisture. The thesis starts with the DBA to compute the backscattering coefficients for various kinds of vegetation-covered surfaces such as pasture, wheat and canola fields. For the soybean fields, an improved coherent branching model is used. The novel feature of the analytic coherent model consists of conditional probability functions to eliminate the overlapping effects of branches in the former branching models. In order to make use of complex physical models for real time retrieval for satellite missions, the outputs of the physical model are provided as lookup-tables (data-cubes). By inverting the lookup-tables, time-series retrieval of soil moisture is performed. Next, the DBA is extended to calculate the bistatic scattering coefficients. Emissivities are calculated by integrating the bistatic scattering coefficients over the hemispherical solid angle. The backscattering coefficients and emissivities calculated using this approach form a consistent model for combined active and passive microwave remote sensing. In the analytical physical models mentioned above, as well as in another commonly used approach of the radiative transfer equation (RTE), the attenuation of the wave is accounted for by the attenuation rate per unit distance, which originates from the concept of an “effective medium”. Such a model is unsuitable for a vegetation canopy. Because of these issues, NMM3D full-wave simulations of vegetation are pursued. Firstly, the scattering of a vegetation canopy consisting of cylindrical scatterers is calculated. The approach for solving Maxwell’s equations is based on the Foldy-Lax multiple scattering equations (FL) combined with the body of revolution (BOR). For a layer of extended-cylinders distributed in clusters, the NMM3D simulations at C-band show very different results from DBA/RTE. The method FL-BOR is limited for rotationally symmetric objects such as cylinders and circular disks. To perform NMM3D full-wave simulations for realistic vegetation/forests, a hybrid method is used, which is a hybrid of the off-the-shelf techniques and newly developed techniques. The newly developed techniques are the three key steps of the hybrid method: (1) extracting the generalized T matrix of each single object using vector spheroidal/cylindrical waves, (2) vector wave transformations, and (3) solving FL for all the objects.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153347/1/huanght_1.pd

Middle Atmosphere Program. Handbook for MAP, volume 28

Extended abstracts from the fourth workshop on the technical and scientific aspects of MST (mesosphere stratosphere troposphere) radar are presented. Individual sessions addressed the following topics: meteorological applications of MST and ST radars, networks, and campaigns; dynamics of the equatorial middle atmosphere; interpretation of radar returns from clear air; techniques for studying gravity waves and turbulence; intercomparison and calibration of wind and wave measurements at various frequencies; progress in existing and planned MST and ST radars; hardware design for MST and ST radars and boundary layer/lower troposphere profilers; signal processing; and data management

Interferometric GNSS-R processing : modeling and analysis of advanced processing concepts for altimetry

This PhD dissertation is focused on the use of the opportunity signals from the Global Navigation Satellite Systems (GNSS), that scatter-off the Earth's surface for perform ocean mesoscale altimetry (the so called GNSS-R technique). Specially, this work analyses the capabilities of the interferometric approach (iGNSS-R) originally proposed for PARIS IoD (which will be implemented on GEROS-ISS), comparing its performance with the one obtained by the conventional approach (cGNSS-R). The main content of this PhD dissertation includes: A comprehensive analysis of the GNSS-R cross-correlation waveform properties, analyzing the impact that the observation geometry and system parameters have on the GNSS-R observables, where parameters such as the receiver bandwidth, observation geometry, sea state, and thermal and speckle noises are analyzed. A detailed derivation of the statistics for both the voltage and power cross-correlations (for both conventional and interferometric processing cases) validated all of them with both simulated and real data from ground-based airborne, and spaceborne experiments. Study of the performance model of the altimetry precision based on the Cramer-Rao Bound statistical estimator theory. This study has been carried out for a wide variety of parameters concerning the overall observation system, including instrument, on-board and on-ground processing aspects, for both the conventional and interferometric GNSS-R techniques. Analysis of experimental data from the Typhoon Investigation using GNSS-R Interferometric Signals (TIGRIS) experiment. This analysis has been used to determine and establish the boundaries and capabilities of GNSS-R towards remote sensing of typhoons. In this part, aspects such as the mitigation of the direct cross-talk contamination, GNSS multipath contamination, and preliminary results (including a novel observable) are presented.Este PhD se centra en el uso de la señales GNSS (Global Navigation Satellite Systems) como señales de oportunidad, para realizar altimetría. Es lo que se conoce como GNSS-R (Global Navigation Satellite Systems-Reflectometry). Especialmente este trabajo analiza las principales propiedades del método interferométrico (iGNSS-R) inicialmente propuesto para PARIS-IoD, y que será implementado en GEROS-ISS. comparándolo con el método convencional (cGNSS-R). A continuación se enumeran los principales puntos abordados en esta tesis doctoral: Se ha realizado un exhaustivo y detallado análisis de las propiedades de las waveforms, evaluando la influencia de la geometría (altitud, ángulo de incidencia, estado del mar, etc), y de los principales parámetros a nivel de instrumento sobre las waveforms. Así mismo se ha analizado el impacto del ancho de banda del receptor, y del ruido térmico y speckle. Por otra parte, se han derivado las estadísticas (matrices de covarianzas) tanto para las waveforms complejas, como para las waveforms de potencia, considerando el método convencional, y el interferométrico. Las diferentes estadísticas o matrices de covarianzas han sido validadas usando datos reales procedentes de diferentes experimentos y datos simulados, para diferentes escenarios (.espacio, aerotransportado, ground-base). Dichas matrices de covarianza, posteriormente han sido usadas para calcular la precisión altimétrica, basada en el uso de estimadores estadísticos, como es el Cramer-Rad Bound. Dicho estudio ha sido realizado considerando un amplio número de parámetros, tanto para el método convencional como para el interferométrico, comparando el performance de ambas técnicas, y realizando una primera estimación de la precisión altimétrica que se obtendría para una misión espacial como PARIS-IoD. Por último se han analizado datos de la campaña experimental TIGRIS (Typhoon Investigation using GNSS-R Interferometric Signal). con dicho analisis se han estudio la capacidad de la técnica GNSS-R para monitorizar y detectar huracanes. Este análisis incluye aspectos como la mitigación de la contaminación procendente de la señal directa, y del multipath ocasionado por las diferentes señales GNSS. Al mismo tiempo durante este análisis un nuevo observable se ha propuesto

High-resolution ab initio three-dimensional X-ray diffraction microscopy

Coherent X-ray diffraction microscopy is a method of imaging non-periodic isolated objects at resolutions only limited, in principle, by the largest scattering angles recorded. We demonstrate X-ray diffraction imaging with high resolution in all three dimensions, as determined by a quantitative analysis of the reconstructed volume images. These images are retrieved from the 3D diffraction data using no a priori knowledge about the shape or composition of the object, which has never before been demonstrated on a non-periodic object. We also construct 2D images of thick objects with infinite depth of focus (without loss of transverse spatial resolution). These methods can be used to image biological and materials science samples at high resolution using X-ray undulator radiation, and establishes the techniques to be used in atomic-resolution ultrafast imaging at X-ray free-electron laser sources.Comment: 22 pages, 11 figures, submitte

Scattering Analysis and Ultra-Wideband Radar for High-Throughput Phenotyping of Wheat Canopies

Rising the yield of wheat crops is essential to meet the projected demands of future consumption and it is expected that most yield increases will be associated to improvements in biomass accumulation. Cultivars with canopy architectures that focus the light interception where photosynthetic-capacity is greater achieve larger biomass accumulation rates. Identifying varieties with improved traits could be performed with modern breeding methods, such as genomic-selection, which depend on genotype-phenotype mappings. Developing a non-destructive sensor with the capability of efficiently phenotyping wheat-canopy architecture parameters, such as height and vertical distribution of projected-leaf-area-density, would be useful for developing architecture-related genotype-phenotype maps of wheat cultivars. In this dissertation, new scattering analysis tools and a new 2-18 GHz radar system are presented for efficiently phenotyping the architecture of wheat canopies. The radar system presented was designed with the objective to measure the RCS profile of wheat canopies at close range. The frequency range (2-18 GHz), topology (Frequency-modulated-continuous-wave) and other radar parameters were chosen to meet that goal. Phase noise of self-interference signals is the main source of coherent and incoherent noise in FMCW radars. A new comprehensive noise analysis is presented, which predicts the power-spectral-density of the noise at the output of FMCW radars, including those related to phase noise. The new 2-18 GHz chirp generator is based on a phase-locked-loop that was designed with large loop bandwidth to suppress the phase noise of the chirp. Additionally, the radar RF front-end was designed to achieve low levels of LO-leakage and antenna feed-through, which are the main self-interference signals of FMCW radars. In addition to the radar system, a new efficient radar simulator was developed to predict the RCS waveforms collected from wheat canopies over the 2-18 GHz frequency range. The coherent radar simulator is based on novel geometric and fully-polarimetric scattering models of wheat canopies. The scattering models of wheat canopies, leaves with arbitrary orientation and curvature, stems and heads were validated using a full-wave commercial simulator and measurements. The radar simulator was used to derive retrieval algorithms of canopy height and projected-leaf-area-density from RCS profiles, which were tested with field-collected measurements. The retrieved heights and projected-leaf-area densities compare well against ruler measurements and image-based retrievals, respectively