A Three-dimensional ray tracing simulation of a synthetic aperture ground penetrating radar system

Ground Penetrating Radar (GPR) is a useful tool for imaging the area below the Earth\u27s surface. GPR works on the same principle as traditional radar, evaluating the electromagnetic returns reflected from an object or scene of interest to determine characteristics of the object that reflected the signal. Synthetic Aperture Radar (SAR) is a technique which combines radar returns of a given scene collected at several positions. By compiling the information contained in the returns, an image of a scene can be generated. Combining these two concepts allows us to create an image of an underground scene. Air Force Research Lab, Rome, NY developed a ground penetrating, SAR system with a resolution of approximately three feet capable of penetrating to depths of 150-160 feet into the ground. In order to assess the results obtained from this system, a simulation was needed to generate expected returns from a user-defined synthetic scene. Ray-tracing is a simulation technique that is frequently used to model radar and imaging systems. In the ray-tracing model, the transmitted radar signal is simulated by a number of straight lines, or rays, which propagate through the scene according to the principles of electromagnetic theory. The data carried with each ray can be used to generate a simulated radar return at the receiver. This thesis describes a ray-tracing simulator, which was created to work in conjunction with the Rome Labs GPR system. The ray-tracing simulation models the transmissions and reflections from faceted target models using Snell\u27s law and the Law of Reflection. The results obtained demonstrate the effects that different scene orientations have upon the images generated by the Rome Labs system

Geodetic monitoring of complex shaped infrastructures using Ground-Based InSAR

In the context of climate change, alternatives to fossil energies need to be used as much as possible to produce electricity. Hydroelectric power generation through the utilisation of dams stands out as an exemplar of highly effective methodologies in this endeavour. Various monitoring sensors can be installed with different characteristics w.r.t. spatial resolution, temporal resolution and accuracy to assess their safe usage. Among the array of techniques available, it is noteworthy that ground-based synthetic aperture radar (GB-SAR) has not yet been widely adopted for this purpose. Despite its remarkable equilibrium between the aforementioned attributes, its sensitivity to atmospheric disruptions, specific acquisition geometry, and the requisite for phase unwrapping collectively contribute to constraining its usage. Several processing strategies are developed in this thesis to capitalise on all the opportunities of GB-SAR systems, such as continuous, flexible and autonomous observation combined with high resolutions and accuracy. The first challenge that needs to be solved is to accurately localise and estimate the azimuth of the GB-SAR to improve the geocoding of the image in the subsequent step. A ray tracing algorithm and tomographic techniques are used to recover these external parameters of the sensors. The introduction of corner reflectors for validation purposes confirms a significant error reduction. However, for the subsequent geocoding, challenges persist in scenarios involving vertical structures due to foreshortening and layover, which notably compromise the geocoding quality of the observed points. These issues arise when multiple points at varying elevations are encapsulated within a singular resolution cell, posing difficulties in pinpointing the precise location of the scattering point responsible for signal return. To surmount these hurdles, a Bayesian approach grounded in intensity models is formulated, offering a tool to enhance the accuracy of the geocoding process. The validation is assessed on a dam in the black forest in Germany, characterised by a very specific structure. The second part of this thesis is focused on the feasibility of using GB-SAR systems for long-term geodetic monitoring of large structures. A first assessment is made by testing large temporal baselines between acquisitions for epoch-wise monitoring. Due to large displacements, the phase unwrapping can not recover all the information. An improvement is made by adapting the geometry of the signal processing with the principal component analysis. The main case study consists of several campaigns from different stations at Enguri Dam in Georgia. The consistency of the estimated displacement map is assessed by comparing it to a numerical model calibrated on the plumblines data. It exhibits a strong agreement between the two results and comforts the usage of GB-SAR for epoch-wise monitoring, as it can measure several thousand points on the dam. It also exhibits the possibility of detecting local anomalies in the numerical model. Finally, the instrument has been installed for continuous monitoring for over two years at Enguri Dam. An adequate flowchart is developed to eliminate the drift happening with classical interferometric algorithms to achieve the accuracy required for geodetic monitoring. The analysis of the obtained time series confirms a very plausible result with classical parametric models of dam deformations. Moreover, the results of this processing strategy are also confronted with the numerical model and demonstrate a high consistency. The final comforting result is the comparison of the GB-SAR time series with the output from four GNSS stations installed on the dam crest. The developed algorithms and methods increase the capabilities of the GB-SAR for dam monitoring in different configurations. It can be a valuable and precious supplement to other classical sensors for long-term geodetic observation purposes as well as short-term monitoring in cases of particular dam operations

Measurement Uncertainties in Fibre-coupled Spectrographs

The signal quality of fibre-coupled spectrographs can be limited by the inherent properties of the optical fibre. This is especially the case for applications that require high signal-to-noise performance and high spectral resolution. Examples include metallicity and age of star clusters, as well as investigations of Lyman-alpha absorbers. Extra-solar planet research in particular encounters its limitations due to the non-repeatability of the fibre response. Initially, a limited signal quality due to fibres seems counter-intuitive, since one of the most remarkable advantages of fibres is their signal stabilizing property, called image scrambling, which refers to the effect that the fibre output signal is largely insensitive to variations at the input side. However, the fibre photometric and barycentre response is sub ject to external parameters like stress, seeing and guiding variations. State-of-the-art instrumentation has attained a level of sensitivity where these effects will impact upon instrument performance, especially when advancing to a regime of spectral resolving powers where the quantized character of the standard optical fibre can be resolved, which manifests itself in modal noise. Unprecedented effort will be required in order to accomplish high resolving powers in the spectral and spatial domains with 40 m class telescopes. It is therefore essential to predict these fibre-related measurement uncertainties so that the performance of current and future instruments can be optimized. This thesis starts out with a phenomenological description of the different effects that give rise to fibre-related noise and its influence on the observables relevant to astrophysics, such as barycentre and photometric stability. Special emphasis is given to the photometric uncertainties related to modal noise, where first a theoretical model is outlined which in later chapters will be sub ject to experimental investigations. Subsequently, the barycentre repeatability due to incomplete scrambling is the subject of detailed investigation. The remaining sources of noise are estimated using experimental data as well as simulations and put in contrast with the other effects. Alongside the quantitative prediction of instrument instabilities, mitigation strategies will be presented and discussed. I conclude with a brief discussion of the impact of incomplete scrambling and modal noise on current instrumentation, the implications for future instrument pro jects as well as future work that will help to further understand and obviate the underlying mechanisms