Dissertations / Theses on the topic 'Radar sounders'

Radar sounders are spaceborne electromagnetic sensors specifically designed for subsurface investigations. They operate in the HF/VHF part of the electromagnetic spectrum and are widely employed for applications such as monitoring changes to the polar ice sheets of the Earth and for the study of planetary bodies (e.g. Mars) from satellite. Radar sounding of planetary bodies is a relatively young discipline both in terms of system design and data processing architectures. As a result of the current state of the art in system design, the data recorded by radar sounders are typically affected by artifacts, such as off-nadir surface clutter, which hinders its interpretation by scientists. On top of that, the analysis of the very large of amount of data produced by such systems is typically performed manually by experts thus inherently subjective and time-consuming. Therefore the development of automatic high-level processing strategies for reliable, objective and fast extraction of information is needed. Accordingly, this thesis work deals with different aspects of radar sounding namely system design, low-level and high-level processing. The thesis provides three main novel contributions to the state of the art. First, we present a study on system design, performance assessment and 3D electromagnetic simulations of a radar sounding system specifically tailored for detecting lava tubes under the Moon surface. Lava tubes are considered to be important and useful structures. By having a stable temperature and by providing protection against cosmic ray radiation and micrometeorites impacts, they could potentially serve as natural shelter for human outposts on the Moon. The results presented in this thesis show that a multi-frequency radar sounder is the best option for effectively sound most of the lava tube dimension expected from the literature and that they show unique electromagnetic signature which can be used for their detection. The second novel contribution is focused on low-level processing and consists in a bio-inspired clutter detection model based on bats echolocation. Very relevant analogies occur between a bat and radar sounder such as the nadir acquisition geometry. The mathematical model proposed in this thesis adapts the bats frequency diversity strategy (i.e. multi-frequency approach) to solve clutter ambiguities to the radar sounding case. The proposed bio-inspired clutter detection model has been tested and validated on experimental data acquired over Mars. The experimental results showed that the method is able to discriminate in a precise way the radar echoes arising from subsurface targets with respect to off-nadir surface clutter ones. The third novel contribution of this thesis goes in the direction of high-level processing and in particular of automatic data analysis for accurate and fast extraction of relevant information from radar sounding data. To this extent, we propose a novel automatic method for retrieving the spatial position and radiometric properties of the subsurface layers based on Hidden Markov Models for radar response modeling and the Viterbi Algorithm for the inference step. Furthermore, a novel radargram enhancement and denoising technique has been developed to support the detection step. The effectiveness of the technique has been demonstrated on different radargrams acquired over the North Pole of Mars pointing out its superiority with respect to current state of the art techniques.

Spaceborne radar sounders are an important class of remote sensing instruments which operate by recording backscattered electromagnetic waves in the vicinity of a solid planetary body. The incoming waves are generally transmitted by the radar itself (active sounding), although external signals of opportunity can also be used (passive sounding). There are currently two major planetary radar sounders under development, both headed to the Jovian icy moons (Europa, Ganymede and Callisto). Designing a radar sounder is a very challenging process involving careful leveraging of heritage and predictive tools, and in which backscattering simulators play a central role. This is especially true for coherent simulators, due to their higher accuracy and the possibility they offer to apply advanced processing techniques on the resulting simulated data, such as synthetic aperture radar focusing, or any other operation which requires field amplitude, phase and polarisation. For this reason, designing computationally-efficient coherent simulators is an important and active research area. The first contribution of this thesis is a novel multilayer coherent simulator based on the Stratton-Chu equation and the linear phase approximation, which can generate realistic simulated radar data on a wide range of surface and subsurface digital elevation models (DEM), using only a fraction of the computational resources that a finite-difference time-domain method would need. Thorough validation was conducted against both theoretical formulations and real data, which confirmed the accuracy of the method. The method was then generalised to noisy active and passive sounding, which is an important capability in the context of the proposed use of passive sounding on the Jovian icy moons. Provided that representative information about the surface and this external field exists, the simulator could compare the relative scientific value of active and passive sounding of a given target under given conditions. However, quality DEMs of the Jovian icy moons are scarce. For this reason we also present a comparative study of the fractal roughness of Europa and Mars (a much better studied body), where we derive fractal analogue maps of twelve types of Europan terrains on Mars. These maps could be used to guide the choice of Martian DEMs on which to perform representative backscattering simulations for future radar missions on Europa. Finally, we explore the possibility of entirely new radar architectures with the novel concept of the distributed radar. In a distributed sounder, very large across-track antennas can be synthesised from smallsats flying on selected orbits, providing a way to obtain a highly-directive antenna without the need to deploy large and complex structures in space. We develop an analytical formulation to treat the problem of beamforming with an array affected by perturbations on the positions of its array elements, and propose a set of Keplerian parameters that enable the concept.

Spaceborne radar sounders are an important class of remote sensing instruments which operate by recording backscattered electromagnetic waves in the vicinity of a solid planetary body. The incoming waves are generally transmitted by the radar itself (active sounding), although external signals of opportunity can also be used (passive sounding). There are currently two major planetary radar sounders under development, both headed to the Jovian icy moons (Europa, Ganymede and Callisto). Designing a radar sounder is a very challenging process involving careful leveraging of heritage and predictive tools, and in which backscattering simulators play a central role. This is especially true for coherent simulators, due to their higher accuracy and the possibility they offer to apply advanced processing techniques on the resulting simulated data, such as synthetic aperture radar focusing, or any other operation which requires field amplitude, phase and polarisation. For this reason, designing computationally-efficient coherent simulators is an important and active research area. The first contribution of this thesis is a novel multilayer coherent simulator based on the Stratton-Chu equation and the linear phase approximation, which can generate realistic simulated radar data on a wide range of surface and subsurface digital elevation models (DEM), using only a fraction of the computational resources that a finite-difference time-domain method would need. Thorough validation was conducted against both theoretical formulations and real data, which confirmed the accuracy of the method. The method was then generalised to noisy active and passive sounding, which is an important capability in the context of the proposed use of passive sounding on the Jovian icy moons. Provided that representative information about the surface and this external field exists, the simulator could compare the relative scientific value of active and passive sounding of a given target under given conditions. However, quality DEMs of the Jovian icy moons are scarce. For this reason we also present a comparative study of the fractal roughness of Europa and Mars (a much better studied body), where we derive fractal analogue maps of twelve types of Europan terrains on Mars. These maps could be used to guide the choice of Martian DEMs on which to perform representative backscattering simulations for future radar missions on Europa. Finally, we explore the possibility of entirely new radar architectures with the novel concept of the distributed radar. In a distributed sounder, very large across-track antennas can be synthesised from smallsats flying on selected orbits, providing a way to obtain a highly-directive antenna without the need to deploy large and complex structures in space. We develop an analytical formulation to treat the problem of beamforming with an array affected by perturbations on the positions of its array elements, and propose a set of Keplerian parameters that enable the concept.

Radar sounders (RS) are active instruments that have proved to be able to profile the subsurface of planetary bodies. The design of RS instruments, as well as the interpretation of the acquired data, is a non-trivial task due to the complexity of the scenario of acquisition and the limited amount of information on the targets (especially in planetary exploration). In this context, data simulations are necessary to support the design of the radar, the development of the related processing chain, and the definition of algorithms for the automatic analysis of data. However, state-of-the-art RS simulation methods are characterized by different trade-offs between simulation accuracy and computational costs. On the one hand, numerical methods, such as the Finite-Difference Time-Domain (FDTD) technique, allow to accurately model the wave-target interaction by exactly solving Maxwell's equations at the cost of very high computational requirements. On the other hand, optical methods, such as the ray-tracing based Multi-layer Coherent Simulator (MCS), rely on approximated solution of Maxwell's equations that allow for a better usage of computational resources at the cost of a less accurate modeling. Moreover, simulators produce raw or range-compressed only data, making it difficult to interpret and analyze them via direct comparison with the real data, which are typically processed also for azimuth compression. In this thesis, we present four main contributions related to the simulation of RS data to address the above-mentioned limitations. The first and second contributions thus present 3D simulations of selected targets of two new RS instruments, i.e., the Radar for Icy Moon Exploration (RIME) and the EnVision Subsurface Radar Sounder (SRS). The simulations are performed with the FDTD and MCS simulators. Despite producing good results in terms of detection probability of the selected targets, these two contributions highlight the above-mentioned gaps in the literature of simulation of RS data. The first main limitation is the lack of methods that can accurately model both large and small-scale scattering phenomena at relatively low computational costs. This problem is addressed by the third contribution of this thesis, which presents a novel integrated simulation technique that models both large and small-scale surface scattering phenomena by combining the advantages of the FDTD and MCS techniques, in an accurate and computationally efficient way. The second problem identified is the lack of SAR processing techniques to be applied to the simulated radargrams. This is addressed in the fourth contribution which presents a range-Doppler method for focusing raw radar sounder data simulated with 3D coherent electromagnetic simulators. The method is general and can be applied to any electromagnetic simulator, and is demonstrated for both the FDTD and MCS methods. The results presented throughout the thesis indicate that the proposed methods advance the state-of-the-art of techniques for both generating and processing simulated RS data.

In the last decade the interest in radar systems for the exploration of planetary bodies and for Earth Observation (EO) from orbit increased considerably. In this context, the main goal of this thesis is to present novel methods for the automatic analysis of planetary radar sounder (RS) signals and very high resolution (VHR) synthetic aperture radar (SAR) images acquired on the Earth. Both planetary RSs and VHR SAR systems are instruments based on relatively recent technology which make it possible to acquire from orbit new types of data that before were available only in limited areas from airborne acquisitions. The use of orbiting platforms allows the acquisition of a huge amount of data on large areas. This calls for the development of effective and automatic methods for the extraction of information tuned on the characteristics of these new systems. The work has been organized in two parts. The first part is focused on the automatic analysis of data acquired by planetary RSs. RS signals are currently mostly analyzed by means of manual investigations and the topic of automatic analysis of such data has been only marginally addressed in the literature. In this thesis we provide three main novel contributions to the state of the art on this topic. First, we present a theoretical and empirical statistical study of the properties of RS signals. Such a study drives the development of two novel automatic methods for the generation of subsurface feature maps and for the detection of basal returns. The second contribution is a method for the extraction of subsurface layering in icy environments, which is capable to detect linear features with sub-pixel accuracy. Moreover, measures for the analysis of the properties of the detected layers are proposed. Finally, the third contribution is a technique for the detection of surface clutter returns in radargrams. The proposed method is based on the automatic matching between real and clutter data generated according to a simulator developed in this thesis. The second part of this dissertation is devoted to the analysis of VHR SAR images, with special focus on urban areas. New VHR SAR sensors allow the analysis of such areas at building level from space. This is a relatively recent topic, which is especially relevant for crisis management and damage assessment. In this context, we describe in detail an empirical and theoretical study carried out on the relation between the double-bounce effect of buildings and their orientation angle. Then, a novel approach to the automatic detection and reconstruction of building radar footprints from VHR SAR images is pre-sented. Unlike most of the methods presented in the literature, the developed method can extract and reconstruct building radar footprints from single VHR SAR images. The technique is based on the detection and combination of primitive features in the image, and introduces the concept of semantic meaning of the primitives. Qualitative and quantitative experimental results obtained on real planetary RS and spaceborne VHR SAR data confirm the effectiveness of the proposed methods.

Radar sounders (RS) are low frequency remote sensing instruments that profile the shallow subsurface of planetary bodies providing valuable scientific information. The prediction of the RS performance and the interpretation of the target properties from the RS data are challenging due to the complex electromagnetic interaction between many acquisition variables. RS simulations address this issue by forward modeling this complex interaction and simulating the radar response. However, existing simulators require detailed and subjective modeling of the target in order to produce realistic radargrams. For less-explored planetary bodies, such information is difficult to obtain with high accuracy. Moreover, the high computational requirements of conventional electromagnetic simulators prohibit the simulation of a large number of radargrams. Thus, it is not possible to generate and analyze a database of simulated radargrams representative of the acquisition scenario that would be very useful for both the RS design and the data analysis phase. To overcome these difficulties and to produce realistic simulated radargrams, this thesis proposes two novel approaches to the simulation and analysis of the radar response. The first contribution is a simulation approach that leverages the data available over geological analogs of the investigated target and reprocesses them to obtain the simulated radargrams. The second contribution is a systematic approach to the generation and analysis of a database of simulated radargrams representing the possible scenarios during the RS acquisition. The database is analyzed to predict the RS performance, to design the instrument parameters, and to support the development of automatic target detection algorithms. To demonstrate the proposed techniques the thesis addresses their use in two future RS instruments, which are at different phases of development: (1) the Radar for Icy Moons Exploration (RIME) and (2) a RS for Earth observation of the polar ice caps. The first contribution focuses on the analysis of the detectability of complex tectonic targets on the icy moons of Jupiter by RIME by simulating the radar response of 3D target models. The second contribution presents a feasibility study for an Earth orbiting RS based on the proposed simulation approaches.

Radar sounders (RS) are low frequency remote sensing instruments that profile the shallow subsurface of planetary bodies providing valuable scientific information. The prediction of the RS performance and the interpretation of the target properties from the RS data are challenging due to the complex electromagnetic interaction between many acquisition variables. RS simulations address this issue by forward modeling this complex interaction and simulating the radar response. However, existing simulators require detailed and subjective modeling of the target in order to produce realistic radargrams. For less-explored planetary bodies, such information is difficult to obtain with high accuracy. Moreover, the high computational requirements of conventional electromagnetic simulators prohibit the simulation of a large number of radargrams. Thus, it is not possible to generate and analyze a database of simulated radargrams representative of the acquisition scenario that would be very useful for both the RS design and the data analysis phase. To overcome these difficulties and to produce realistic simulated radargrams, this thesis proposes two novel approaches to the simulation and analysis of the radar response. The first contribution is a simulation approach that leverages the data available over geological analogs of the investigated target and reprocesses them to obtain the simulated radargrams. The second contribution is a systematic approach to the generation and analysis of a database of simulated radargrams representing the possible scenarios during the RS acquisition. The database is analyzed to predict the RS performance, to design the instrument parameters, and to support the development of automatic target detection algorithms. To demonstrate the proposed techniques the thesis addresses their use in two future RS instruments, which are at different phases of development: (1) the Radar for Icy Moons Exploration (RIME) and (2) a RS for Earth observation of the polar ice caps. The first contribution focuses on the analysis of the detectability of complex tectonic targets on the icy moons of Jupiter by RIME by simulating the radar response of 3D target models. The second contribution presents a feasibility study for an Earth orbiting RS based on the proposed simulation approaches.

Radar Sounders (RSs) are active sensors that transmit in the nadir electromagnetic (EM) waves with a low frequency in the range of High-Frequency and Very-High-Frequency and relatively wide bandwidth. Such a signal penetrates the surface and propagates in the subsurface, interacting with dielectric interfaces. This interaction yields to backscattered echoes detectable by the antenna that are coherently summed and stored in radargrams. RSs are used for planetary exploration and Earth observation for their value in investigating subsurface geological structures and processes, which reveal the past geomorphological history and possible future evolution. RS instruments have several parameter configurations that have to be designed to achieve the mission science goals. On Mars, radargram visual analyses revealed the icy layered deposits and liquid water evidence in the poles. On the Earth, RSs showed relevant structures and processes in the cryosphere and the arid areas that help to monitor the subsurface geological evolution, which is critical for climate change. Despite the valuable results, visual analysis is subjective and not feasible for processing a large amount of data. Therefore, a need emerges for automatic methods extracting fast and reliable information from radargrams. The thesis addresses two main open issues of the radar-sounding literature: i) assessing target detectability in simulated orbiting radargrams to guide the design of RS instruments, and ii) designing automatic methods for information extraction from RS data. The RS design is based on assessing the performance of a given instrument parameter configuration in achieving the mission science goals and detecting critical targets. The assessment guides the parameter selection by determining the appropriate trade-off between the achievable performance and technical limitations. We propose assessing the detectability of subsurface targets (e.g., englacial layering and basal interface) from satellite radar sounders with novel performance metrics. This performance assessment strategy can be applied to guide the design of the SNR budget at the surface, which can further support the selection of the main EORS instrument parameters. The second contribution is designing automatic methods for analyzing radargrams based on fuzzy logic and deep learning. The first method aims at identifying buried cavities, such as lava tubes, exploiting their geometric and EM models. A fuzzy system is built on the model that detects candidate reflections from the surface and the lava tube boundary. The second and third proposed methods are based on deep learning, as they showed groundbreaking results in several applications. We contributed with an automatic technique for analyzing radargram acquired in icy areas to investigate the basal layer. To this end, radargrams are segmented with a deep learning network into literature classes, including englacial layers, bedrock, and echo-free zone (EFZ) and thermal noise, as well as new classes of basal ice and signal perturbation. The third method proposes an unsupervised segmentation of radargrams with deep learning for detecting subsurface features. Qualitative and quantitative experimental results obtained on planetary and terrestrial radargrams confirm the effectiveness of the proposed methods, which investigate new subsurface targets and allow an improvement in terms of accuracy when compared to other state-of-the-art methods.

Radar Sounders (RSs) are active sensors that transmit in the nadir electromagnetic (EM) waves with a low frequency in the range of High-Frequency and Very-High-Frequency and relatively wide bandwidth. Such a signal penetrates the surface and propagates in the subsurface, interacting with dielectric interfaces. This interaction yields to backscattered echoes detectable by the antenna that are coherently summed and stored in radargrams. RSs are used for planetary exploration and Earth observation for their value in investigating subsurface geological structures and processes, which reveal the past geomorphological history and possible future evolution. RS instruments have several parameter configurations that have to be designed to achieve the mission science goals. On Mars, radargram visual analyses revealed the icy layered deposits and liquid water evidence in the poles. On the Earth, RSs showed relevant structures and processes in the cryosphere and the arid areas that help to monitor the subsurface geological evolution, which is critical for climate change. Despite the valuable results, visual analysis is subjective and not feasible for processing a large amount of data. Therefore, a need emerges for automatic methods extracting fast and reliable information from radargrams. The thesis addresses two main open issues of the radar-sounding literature: i) assessing target detectability in simulated orbiting radargrams to guide the design of RS instruments, and ii) designing automatic methods for information extraction from RS data. The RS design is based on assessing the performance of a given instrument parameter configuration in achieving the mission science goals and detecting critical targets. The assessment guides the parameter selection by determining the appropriate trade-off between the achievable performance and technical limitations. We propose assessing the detectability of subsurface targets (e.g., englacial layering and basal interface) from satellite radar sounders with novel performance metrics. This performance assessment strategy can be applied to guide the design of the SNR budget at the surface, which can further support the selection of the main EORS instrument parameters. The second contribution is designing automatic methods for analyzing radargrams based on fuzzy logic and deep learning. The first method aims at identifying buried cavities, such as lava tubes, exploiting their geometric and EM models. A fuzzy system is built on the model that detects candidate reflections from the surface and the lava tube boundary. The second and third proposed methods are based on deep learning, as they showed groundbreaking results in several applications. We contributed with an automatic technique for analyzing radargram acquired in icy areas to investigate the basal layer. To this end, radargrams are segmented with a deep learning network into literature classes, including englacial layers, bedrock, and echo-free zone (EFZ) and thermal noise, as well as new classes of basal ice and signal perturbation. The third method proposes an unsupervised segmentation of radargrams with deep learning for detecting subsurface features. Qualitative and quantitative experimental results obtained on planetary and terrestrial radargrams confirm the effectiveness of the proposed methods, which investigate new subsurface targets and allow an improvement in terms of accuracy when compared to other state-of-the-art methods.

The World Climate Research Programme (WCRP) has recently reconfirmed the importance of a better understanding of the Cryosphere for advancing the analysis, modeling and prediction of climate change and its impact on the environment and society. One of the most complete collection of information about the ice sheets and glaciated areas is contained in the data (radargrams) acquired by Radar Sounder (RS) instruments. The need to better understand the structure of the ice sheets and the availability of enourmous quantities of radargrams call for the development of automatic techniques for an efficient extraction of information from RS data. This topic has been only marginally addressed in the literature. Thus, in this thesis we address this challenge by contributing with four novel automatic techniques for the analysis of radargrams acquired at the ice sheets. The first contribution of this thesis presents a system for the automatic classification of ice subsurface targets in RS data. The core of the system is represented by the extraction of a set of features for target discrimination. The features are based on both the specific statistical properties of the RS signal and the spatial distribution of the ice subsurface targets. The second contribution is an unsupervised model-based technique for the automatic detection and property estimation of ice subsurface targets. This is done by using the parameters of the RS system combined with the output of an automatic image segmentation algorithm. The third contribution presents an automatic technique for the local 3D reconstruction of the ice sheet. It is based on the use of RS and altimeter (ALT) data, and relies on the use of a geostatistical interpolation method and on several statistical measures for validating the interpolation results and the quality of interpolation. The fourth contribution presents a technique for the automatic estimation of radar power losses in ice as a continuous non-linear function of depth, by using RS and ice core data. The technique relies on the detection of ice layers in the RS data, the computation of their reflectivity from the ice core data and the use of the radar equation for loss estimation. Qualitative and quantitative experimental results obtained on real RS data confirm the effectiveness of the first three techniques. Also, preliminary results have been obtained by applying the fourth technique to real RS and ice core data acquired in Greenland. Due to their advantages over the traditional manual approach, e.g., efficiency, objectivity, possibility of jointly analyzing multisensor data (e.g., RS, ALT), the proposed methods can support the scientific community to enhance the data usage for a better modeling and understanding of the ice sheets. Moreover, they will become even more important in the near future, since the volume of data is expected to grow from the increase in airborne and possible Earth Observation spaceborne RS missions.

On se propose dans un premier temps d'étudier des jeux de données topographiques sur la lune glacée de Jupiter Ganymède et d'estimer l'impact de la topographie sur les performances du futur radar sondeur. Les principaux résultats sont présentés dans [1]. Une seconde partie est dédiée à l'expression mathématique du problème direct du sondage radar planétaire (physique et instrumentation). On rappelle ainsi comment dériver à partir des formulations de Stratton-Chu les formulations volumiques classiques et surfaciques (i.e. Huygens-Fresnel). On s'attache ensuite à détailler un algorithme performant basé sur la formulation surfacique pour simuler des échos radar à partir d'une surface planétaire maillée. Cette approche est largement inspirée par le travail de J.-F. Nouvel [2]. Une troisième partie s'intéresse à l'inversion des paramètres géophysiques de surface à partir des mesures radar. On écrit ainsi le problème dans un cadre probabiliste (c.f. [3]) et on présente trois grandes familles d'algorithmes : (i) une approche avec une linéarisation du problème, (ii) une approche itérative basée sur une méthode de gradient et (iii) une approche statistique pour estimer les densités de probabilités a posteriori. Ces algorithmes sont appliqués à des jeux de données synthétiques pour illustrer leurs performances. [1] Y. Berquin, W. Kofman, A. Herique, G. Alberti, and P. Beck. A study on ganymede's surface topography: Perspectives for radar sounding. Planetary and Space Science, (0), 2012. [2] J.-F. Nouvel, A. Herique, W. Kofman, and A. Safaeinili. Radar signal simulation: Surface modeling with the Facet Method. Radio Science, 39:RS1013, February 2004. [3] A. Tarantola. Inverse problem theory and methods for model parameter estimation. SIAM, 2005
The manuscript details the work performed in the course of my PhD on planetary sounding radar. The main goal of the study is to help designing and assessing the sounding radar performances. This instrument will be embarked on the ac{ESA}'s large class mission ac{JUICE} to probe Jupiter's environment and Jupiter's icy moons Callisto, Ganymede and Europa. As an introduction to the problem, a study on Ganymede's surface ac{DEM} and its implications with regard to the radar performances was performed. The results of this work put forward issues due to a hostile environment with important surface clutter which eventually lead to a decrease in the radar signal bandwidth to 8--10 MHz. A first section is then dedicated to the formulation of the direct problem of sounding radar with a focus on surface formulations. This section eventually leads to a novel algorithm for radar surface echo computation from meshed surfaces which proves to be both efficient and accurate. A second section studies the possibility to use surface formulation to recover geophysical surface parameters from sounding radar data. For that purpose, three main approaches are discussed namely (i) a linear approach, (ii) a gradient-based approach and (iii) a statistical approach. These techniques rely on a probabilistic view of the inverse problem at hand and yield good result with different setups. Although we mainly focus on surface reflectivity, we also discuss surface topography inversion. Finally, a last section discusses the work presented in the manuscript and provides perspectives for future work

This PhD submission contains a select portfolio of practical works that have been created in answer to my research questions. This Thesis contextualises those works in a theoretical framework, linking them explicitly to the academic discourses with which they are inexorably bound. The introduction of this Thesis examines the research context in which research questions were formed. Evaluating a complicated previous project and describing a seminal, difficult encounter with the realm of sound art, this section explores some of the problems involved with presenting everyday sounds to audiences and proposes that these problems might in part be solved by forming new presentational strategies. Problems discussed include the difficulty of presenting everyday sounds to audiences who do not have access to the same information and knowledge that the work’s creator(s) have; presenting everyday sounds to audiences in conditions which offer limited scope for interaction and participation; and presenting everyday sounds to audiences which rely specifically on the primacy of those sounds alone to communicate a message to listeners. The questions that are formed in order to begin solving these problems include looking to feminist art practices of the 1960s/70s for inspiration regarding how theories concerning the value of everyday sounds might be practically applied to artmaking in domestic contexts; exploring ethnographic or Anthropological models to see how everyday sounds might be presented to audiences through investigative, participatory formats; investigating the possibilities for subverting or expanding the frameworks through which sound art is typically disseminated so that that territory might better accommodate the specific resonances and associations of everyday sounds; and proposing Internet-based strategies for presenting everyday sounds to audiences which are inherently intertextual, participatory, and social. The first Chapter of this Thesis examines how the home might be re-envisioned as a sound art site and brings the theories of John Cage together with feminist art thought to reinvent that space as a specifically sonic site. In the second Chapter, investigative anthropological approaches to the everyday are the focus of the discussion. This Chapter explores the context of radio as an inherently domestic medium, and discusses how it might be used as such for the presentation of everyday sounds to audiences. In the third Chapter of this thesis, I position my research in relation to the established tenets of contemporary sound art. Exploring ideas of subversion and critique, this Chapter looks at the proposed revisions to those established tenets which I have offered throughout my research. The final Chapter explores how I have used the Internet both in specific instances and more generally within my practice, connecting my research with emergent recording technologies and Internet platforms which allow everyday sounds to be socially shared. In the conclusion, I discuss what the key findings of exploring these questions have been.

This thesis presents observations of the dynamical features of the stratosphere, mesosphere and lower thermosphere. These are made from various observational techniques and model comparisons. A focus of the work is the two-day wave at high latitudes in the MLT region. This has revealed significant wave amplitudes in both summer and winter. However, these waves are shown to have very different origins. Using satellite data, the summertime wave is found to be the classic quasi-two-day wave which maximises at mid-latitudes in the MLT region. The wintertime wave is found to be a mesospheric manifestation of an eastward-propagating wave originating in the stratosphere and likely generated by barotropic and baroclinic instabilities in the polar night jet. The horizontal winds from Meteor and MF radars have been used to measure and produce climatologies of the Lunar M2 tide at Esrange in the Arctic (68°N), Rothera and Davis in the Antarctic (68°S), Castle Eaton at mid-latitude (52°N) and Ascension Island at Equatorial latitudes (8°S). These observations present the longest period of lunar semi-diurnal tidal observations in the MLT region to date, with a 16-year dataset from the UK meteor radar. Comparisons with the Vial and Forbes (1994) lunar tidal model are also made which reveal generally good agreement. Non-migrating lunar tides have been investigated. This uses lunar tidal results from equatorial stations, including the Ascension Island (8°S) meteor radar. Also lunar tidal results from the Rothera meteor wind radar (68°S, 68°W) and the Davis MF radar (68°S, 78°E) are considered. Both of these stations are on the edge of the Antarctic continent. It is demonstrated that there are often consistent tidal phase offsets between similar latitude stations. This suggests that non-migrating modes are likely to be present in the lunar semi-diurnal tidal structure and have significant amplitudes.

Parce que l’incertitude des mesures des précipitations solides est importante en Arctique, les taux de chutes de neige montrent des différences marquées entre les jeux de données disponibles. Afin de caractériser plus précisément les précipitations arctiques, la télédétection spatiale micro-ondes s’avère être un outil idéal. Les observations collectées par le radar à bord du satellite CloudSat ont permis d’obtenir les taux de chutes de neige à la surface pour quatre années complètes. Ces estimations ont été validées avec des données de stations météorologiques, et comparées à diverses climatologies. Malgré un bon accord qualitatif, d’importantes différences sont observées, particulièrement au Groenland. La réanalyse régionale ASR montre un meilleur accord avec les restitutions de CloudSat que la réanalyse globale ERA-Interim, notamment concernant la distribution saisonnière des taux de chutes de neige. Les observations CloudSat ont ensuite été utilisées comme référence afin d’évaluer la capacité des sondeurs passifs micro-ondes proches de 183 GHz à détecter les chutes de neige arctiques. Nous avons montré que la détection est possible et repose principalement sur les températures de brillance à 190 et 183 ± 3 GHz ainsi que la température proche de la surface et la vapeur d’eau intégrée. La détection est limitée dans le cas de conditions environnementales trop froides et pour des chutes de neige faibles. En dépit de ces limitations, l’algorithme développé permet un apport en information concernant les chutes de neige intenses, avec un bon échantillonnage grâce à sa large fauchée et sa longue série temporelle. Ainsi les résultats de ces travaux illustrent notamment l’apport des observations passives micro-ondes, disponibles pour les 20 dernières années, pour la caractérisation de l’occurrence des chutes de neige
Because solid precipitation measurements at the surface are complex in Arctic, snowfall rates present significant differences between recent datasets. To further characterize arctic precipitation, microwave remote sensing is an appropriate tool. The radar observations onboard CloudSat provides rates of snowfall at the surface for a 4-years period. These retrievals are validated with in situ data, and compared to various datasets. Despite a good qualitative agreement, significant differences are observed, especially over Greenland. The regional reanalysis shows a better agreement with CloudSat retrievals than the global reanalysis, especially regarding the seasonnal distribution of snowfall rates. Then, CloudSat observations are used as a reference to evaluate the ability of passive microwave sounders to detect arctic snowfall for frequencies around 183 GHz. Detection is possible and relies mainly on brightness temperatures at 190 and 183 ± 3 GHz as well as the temperature near the surface and the integrated water vapor. A poor detection capability is observed in cold conditions and for light snowfall. Despite these limitations, the algorithm provides significant information for intense snowfalls, with good sampling due to its wide swath and long time series. Available for the last 20 years, passive microwave observations show a notable ability for a better characterization of arctic snowfall

Thesis (M.S.)--University of Wisconsin--Madison, 2003.
Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 32-33).