Travelling Ionospheric Disturbances (TIDs) are said to be produced by atmospheric gravitational waves propagating through the neutral ionosphere. These are smaller in amplitude and period when compared to most ionospheric disturbances and hence more difficult to measure. Very little is known about the properties of the travelling ionospheric disturbances (TIDs) over the Southern Hemisphere regions since studies have been conducted mostly over the Northern Hemisphere regions. This study presents a framework, using a High Frequency (HF) Doppler radar to investigate the physical properties and the possible driving mechanisms of TIDs. This research focuses on studying the characteristics of the TIDs, such as period, velocity and temporal variations, using HF Doppler measurements taken in South Africa. By making use of a Wavelet Analysis technique, the TIDs’ characteristics were determined. A statistical summary on speed and direction of propagation of the observed TIDs was performed. The winter medium scale travelling ionospheric disturbances (MSTIDs) observed are generally faster than the summer MSTIDs. For all seasons, the MSTIDs had a preferred south-southwest direction of propagation. Most of the large scale travelling ionospheric disturbances (LSTIDs) were observed during the night and of these, the spring LSTIDs were fastest when compared to autumn and summer LSTIDs. The general direction of travel of the observed LSTIDs is south-southeast. Total Electron Content (TEC), derived from Global Positioning System (GPS) measurements, were used to validate some of the TID results obtained from the HF Doppler data. The Horizontal Wind Model (HWM07), magnetic K index, and solar terminators were used to determine the possible sources of the observed TIDs. Only 41% of the observed TIDs were successfully linked to their possible sources of excitation. The information gathered from this study will be valuable in future radio communications and will serve as means to improve the existing ionospheric models over the South African region.

As objects move, their changing shape produces a signature that can be measured by a radar system. That signature is called the micro-Doppler signature. The micro-Doppler signature of an object is a distinguishing characteristic for certain classes of objects. In this thesis features are extracted from the micro-Doppler signature and are used to classify objects. The scope of the objects is limited to humans walking and traveling vehicles. The micro-Doppler features are able to distinguish the two classes of objects. With a sufficient amount of training data, the micro-Doppler features may be used with learning algorithms to predict unknown objects detected by the radar with high accuracy.

Cette étude traite de la dynamique des éruptions volcaniques explosives, depuis les mécanismes de sub-surface jusqu’aux processus d’émission et de dispersion des pyroclastes. A cet effet un radar Doppler sol est utilisé (VOLDORAD), lequel renseigne sur la charge / vitesse des ejectas. Les données sont intégrées avec d’autres techniques géophysiques, et des modèles numériques sont développés afin de simuler les émissions pyroclastiques, générer des signaux radar synthétiques, pour finalement améliorer notre compréhension des processus qui leurs sont sous-jacents. L’Arenal (Costa Rica) est utilisé comme volcan cible, où de fréquentes éruptions de faible magnitude émettent des panaches de cendres et des projections balistiques jusqu’à quelques centaines de mètres au-dessus de l’évent. Dans un premier temps, nous combinons des données sismiques et radar afin d’explorer la relation entre les processus de conduit et les émissions pyroclastiques. Leurs interactions complexes sont interprétées via un modèle conceptuel, lequel décrit les fractures parsemant le bouchon de lave comme responsables du dégazage du système, et en retour des signaux sismiques et radar collectés (ces derniers dépendants de la charge en cendres des émissions de gaz). Par ailleurs, nous investiguons la dynamique des émissions pyroclastiques à travers l’étude de radargrammes Doppler. La distribution spatio-temporelle de la vitesse des ejectas indique l’existence de deux phénomènes aux dynamiques distinctes. Des modélisations numériques permettant la reconstruction de signaux synthétiques indiquent qu’il s’agit de l’émission simultanée de blocs balistiques et de panaches de cendres. Une procédure d’inversion de type Monte Carlo couplée d’un algorithme d’optimisation permet de retrouver les radargrammes synthétiques qui reproduisent au mieux ceux observés. Les résultats apportent des contraintes sur divers paramètres éruptifs, tels que les tailles, trajectoires, vitesses des ejectas et des gaz, ainsi que la vitesse / direction de dispersion des panaches de cendres par le vent. Enfin, nous discutons du potentiel des radars Doppler appliqués à la surveillance opérationnelle des émissions volcaniques. En particulier, la possibilité de quantifier les masses éjectées dans l’atmosphère ou retombant sur les flancs du volcan, fournit des paramètres éruptifs à la source pouvant alimenter les modèles de dispersion de panaches de cendres. / This study investigates the dynamics of explosive volcanic eruptions, from the sub-surface source mechanisms through to the emission dynamics and downwind dispersal of tephra. To this end, we use a ground-based Doppler radar (VOLDORAD) which informs on the loading / velocimetry of the expelled ejecta. Data are integrated with complementary geophysical techniques, and numerical models are developed to simulate pyroclastic emissions, generate synthetic radar data, and in turn enhance our understanding of the underlying dynamical processes. Arenal (Costa Rica) is used as a case study volcano, where frequent mildly-explosive eruptions commonly expel ash plumes and ballistic projections up to a few hundred meters above the vent. Firstly, we combine seismic and radar data to investigate the link between conduit processes and pyroclastic emissions. A conceptual model is proposed to account for their complex interplay, whereby fractures through a rigid lava cap control the system’s degassing, which in turn governs both the seismic and radar signals (the latter depending on the ash load carried by the gas). Secondly, we investigate the dynamics of pyroclastic emissions from the analysis of Doppler radargrams. Time-velocity distribution of the expelled tephra shows the signature of two distinct phenomena. Numerical modeling and computation of synthetic radargrams show that these are consistent with both ballistic projections and ash plume crossing the beam simultaneously, whose respective mass load can be derived. Inverse modeling using a nearneighborhood Monte Carlo procedure was used to find synthetic Doppler radargrams which best matched the observed ones. The results give constrains on eruptive parameters, such as the size, trajectory, exit velocities and source gas velocities of the ballistics, as well as the speed / direction of the ash cloud drifted by trade winds. Lastly, because Doppler radars are powerful tool for real-time allweather monitoring of volcanic activity, we address issues relative to the operational radar monitoring of ash plumes. In particular, the ability to remotely quantify the mass proportions of ejecta either falling on the slopes of the volcano or prone to be ejected into the atmosphere, gives source eruptive parameters which may feed volcanic ash dispersal models.

This thesis presents the design and implementation of a multifunctional radar sensor. Utilising microstrip transmission line technology, a front-end receiver has been designed based upon a six-port architecture. Additionally, digital signal processing has been implemented on a microcontroller, enabling processing and extraction of information from the down converted quadrature signals. Results have show that the sensor is capable of operating as both a continuous wave radar and frequency modulated continuous wave radar. Through measurements, it has been established that the sensor is capable of wireless measurements, such as vital signs and vibrations. Furthermore, a graphical user interface has been design, allowing a way of switching between different radar configurations and the presentation of measured data to the user.

National security needs dictate the development of new radar systems capable of identifying and tracking exoatmospheric threats to aid our defense. These new radar systems feature reduced noise floors, electronic beam steering, and ultra-wide bandwidths, all of which facilitate threat discrimination. However, in order to identify missile attributes such as RF reflectivity, distance, and velocity, many existing processing algorithms rely upon narrow bandwidth assumptions that break down with increased signal bandwidth. We present a fresh investigation into these algorithms for removing bandwidth limitations and propose novel state-space and direct-data factoring formulations such as * the multidimensional extension to the Eigensystem Realization Algorithm, * employing state-space models in place of interpolation to obtain a form which admits a separation and isolation of solution components, * and side-stepping the joint diagonalization of state transition matrices, which commonly plagues methods like multidimensional ESPRIT. We then benchmark our approaches and relate the outcomes to the Cramer-Rao bound for the case of one and two adjacent reflectors to validate their conceptual design and identify those techniques that compare favorably to or improve upon existing practices.

Bibliography: leaves 163-172 / x, 173 leaves : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, 1986

Thesis (MScEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: This work entails the development and performance analysis of a human gait detection system based on radar micro-Doppler signals. The system consists of a tracking functionality and a target classifier. Target micro-Doppler signatures are extracted with Short-Time Fourier Transform (STFT) based spectrogram providing a high-resolution signatures with the radar that is used. A feature extraction mechanism is developed to extract six features from the signature and an artificial neural network (A-NN) based classifier is designed to carry out the classification process. The system is tested on real X-band radar data of human subjects performing six activities. Those activities are walking and speed walking, walking with hands in pockets, marching, running, walking with a weapon, and walking with arms swaying. The multiclass classifier was designed to discriminate between those activities. High classification accuracy of 96% is demonstrated. / AFRIKAANSE OPSOMMING: Hierdie werk behels die ontwikkeling, en analise van werksverrigting, van ’n menslike stapdetekor gebaseer op radar-mikrodoppleranalise. Die stelsel bestaan uit ’n teikenvolger en -klassifiseerder. Die mikrodoppler-kenmerke van ’n teiken word met behulp van die korttyd-Fourier-transform onttrek, en verskaf hoe-resolusie-kenmerke met die radar wat vir die implementering gebruik word. ’n Kenmerkontrekkingstelsel is ontwikkel om ses kenmerke vanuit die spektrogram te onttrek, en ’n kunsmatige neurale netwerk word as klassifiseerder gebruik. Die stelsel is met ’n X-band radar op werklike menslike beweging getoets, terwyl vrywilligers ses aktiwiteite uitgevoer het: loop, loop (hand in die sakke), marsjeer, hardloop, loop met ’n wapen, loop met arms wat swaai. Die multiklas-klassifiseerder is ontwerp om tussen hierdie aktiwiteite te onderskei. ’n Hoe klassifiseringsakkuraatheid van 96% word gedemonstreer.

This dissertation is focused on target trajectory identification using CW radar sensor network measuring. An omni-directional radar based on single mixing is considered for measurement in ballistic tunnel, where information about direction of target approaching is a priory known. Applied experimental radar network setup with system controller and acquisition units is demonstrated. Mathematical models and optimized structures have been developed for fitting of system parameters and presented in the theoretical part. The second part is aimed to the multi-trajectory identification. New methodical techniques of this work consist in identification of the points of the closest approach with V model function and utilizing gradient methods for path identification.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24212号 / 工博第5040号 / 新制||工||1787(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 中北 英一, 准教授 山口 弘誠, 准教授 佐山 敬洋 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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