Dissertations / Theses on the topic 'Radar operators'

Thesis (M.S. in Systems Engineering (Electronic Warfare))--Naval Postgraduate School, September 1990.
Thesis Advisor(s): Davidson, Kenneth L. ; Powell, James R. "September 1990." Description based on title screen as viewed on December 29, 2009. DTIC Descriptor(s): Frequency, Electronic Warfare, Aircraft, Airborne, Electronic Equipment, Microwave Equipment, Radar, Profiles, Ducts, Meteorology, Communication And Radio Systems, Refraction, Arabian Sea, Refractometers, Military Operations. DTIC Identifier(s): Radar interference, meteorological phenomena, theses. Author(s) subject terms: Refractivity, Arabian Sea refractive conditions, ESM airborne radar, airborne microwave refractometer (AMR), IREPS, EREPS. Includes bibliographical references (p. 96-97). Also available in print.

This research is an exploratory single case study, which focuses on the interplay between aspects of Clausewitz's theory on war and the practice of aid agencies in Nepal between 1999-2005/06. During which period Nepal was embroiled in an escalating violent contlict between Maoist rebels and the ruling establishment. which had a severe impact on the operations of aid agencies present in Nepal. The study draws primarily on Clausewitz's theory on war to provide analytical tools of help to the aid industry and those in strategizing roles at country level in thinking through the challenges faced in unstable and deteriorating operational contexts, in order to further poverty and contlict reduction efforts. The research reflects on the processes of strategizing and implementing aid operations in turbulent environments from a Clausewitz-inspired perspective and advances two main findings. First, the thesis finds that one key concept used in this retlection process, which shows itself to be of practical help, is the 'aid trinity'. The 'aid trinity' is a normative reflective framework that consists of three interacting layers, being psychological, social and managerial, which facilitates the thinking through and strategizing of aid operations. Second, by borrowing Clausewitz notion of friction, the research demonstrates that the existence of multiple forms of friction present in processes of strategizing and implementing aid operations in turbulent contexts like Nepal, could severely hamper these operations. Friction can be understood as the mediating force between what was perceived as the ideal fonn of conducting aid operations in Nepal and their actual character, resulting in the inability of the international aid community to address appropriately the dynamics of poverty and conflict. The research highlights the need to factor in the reality of these multiple forms of friction and to allow for their impact in policy, strategizing and implementation processes, in the hope of maximizing poverty and contlict reduction efforts in fragile states and other turbulent environments.

Considerable interest has recently been shown in the field of marine traffic engineering. Real life data sources made available for maritime studies are often expensive and inconvenient to collect. The marine radar simulator presents the researcher with a relatively inexpensive and readily available source of navlgatlonal data. With the improvement of remote vessel traffic monitoring systems the potential for inexpensive real life data analysis Is enhanced. The work of this study has been to allow the analysis of data archived from the Channel Navigation Information Service Automatic Data Processing system (CNIS AOP) installed at St. Margarets Bay Dover using contemporary digital computer graphical facilities, and to compare mariners' behaviour In a real life and simulator collision avoidance situation. For this comparison certain navigational situations known as encounters have been automatically detected using an extension of the Range to Domain Over Range Rate (RDRR) method (Colley et al 1983), referred to as the RDRR+ technique. A statistical comparison has been completed using non parametric techniques.

Les radars à nuages sont des atouts indéniables pour la Prévision Numérique du Temps (PNT). De par leur petite longueur d’onde, ils possèdent une excellente sensibilité aux particules nuageuses et ils sont facilement déployables à bord de plates-formes mobiles. Cette thèse a permis d’évaluer l’apport des observations de radars à nuages pour la validation et l’initialisation de modèles de PNT à échelle kilométrique. Dans la première partie, un opérateur d’observation pour la réflectivité en bande W a été conçu en cohérence avec le schéma microphysique à un moment d'Arome, le modèle de PNT à échelle kilométrique de Météo-France, mais de façon suffisamment générale pour pouvoir être adapté à un autre modèle de PNT à échelle kilométrique. Il est adaptable pour des radars à visée verticale aéroportés ou au sol. Afin de dissocier les erreurs de positionnement des nuages prévus par Arome, de celles présentes dans l’opérateur d’observation, une nouvelle méthode de validation, appelée "la méthode de la colonne la plus ressemblante (CPR), a été élaborée. Cette méthode a été employée afin de valider et de calibrer l'opérateur d'observation en utilisant les profils de réflectivité collectés par le radar à nuages aéroporté Rasta dans des conditions variées durant la première période d’observations (SOP1) du programme international HyMeX, qui vise à améliorer notre compréhension du cycle de l'eau en méditerranée. La seconde partie s'est intéressée à l'apport respectif de l'assimilation de profils verticaux de réflectivité et de vents horizontaux mesurés par le radar à nuages Rasta dans le système d'assimilation variationnel tridimensionnel (3DVar) d'Arome. Le bénéfice apporté par des conditions thermodynamiques, via l'assimilation de la réflectivité en bande W, et dynamiques, via l'assimilation des profils de vents horizontaux, cohérentes dans l'état initial a également été étudié. Pour assimiler la réflectivité en bande W, la méthode d'assimilation "1D+3DVar", qui est opérationnelle dans Arome pour assimiler les réflectivités des radars de précipitation au sol, a été employée. La méthode de restitution bayésienne 1D de profils d'humidité a été validée avec des mesures d'humidité in situ indépendantes. Puis, les expériences d'assimilation ont été menées sur un événement fortement convectif, ainsi que sur une plus longue période de 45 jours. Les résultats suggèrent notamment que l'assimilation conjointe des profils de réflectivité en bande W et des profils verticaux de vents horizontaux permet d'améliorer les analyses d'humidité, mais suggèrent également une légère amélioration des prévisions des cumuls de précipitation

Cette thèse a permis d'explorer l'apport des variables polarimétriques radar (aux longueurs d'onde centimétriques), sensibles aux propriétés microphysiques des hydrométéores, pour les modèles de prévision numérique à échelle convective. Dans la première partie de la thèse, un opérateur d'observation radar polarimétrique, cohérent avec les paramétrisations microphysiques à 1 moment couramment utilisées par les modèles opérationnels à échelle convective a été développé. Des comparaisons entre données simulées et observées pour tous les types de radar (S, C et X) ont été réalisées pour deux cas d'étude convectifs, et ont permis de valider l'opérateur d'observation. La deuxième partie de cette thèse a été consacrée à la conception et au test d'une méthode d'assimilation des variables polarimétriques, s'appuyant sur la méthode opérationnelle 1D+3D-Var, d'assimilation des réflectivités radar dans le modèle AROME. La méthode de restitution bayésienne 1D des profils d'humidité a été adaptée, afin d'inclure la phase différentielle spécifique et la réflectivité différentielle, en plus de la réflectivité, dans le vecteur d'observation. Plusieurs options de la méthode de restitution ont été testées et évaluées par des comparaisons aux observations radar et GPS. Des expériences d'assimilation menées sur deux cas convectifs ont ensuite été réalisées et ont permis d'évaluer l'impact des observations polarimétriques sur les champs analysés d'humidité ainsi que sur les prévisions de réflectivité et de cumuls de précipitation
This PhD has explored the benefits of polarimetric variables (for centimeter wavelength radars), which are sensitive to the microphysical properties of hydrometeors, for convective scale numerical prediction models. In the first part of the PhD, a radar forward operator, consistent with the bulk 1 moment microphysical schemes typically used by the operational convective scale models, has been designed. Comparisons between observed and simulated variables for all radar types (S, C, X) have been performed for two convective cases, and helped validate the forward operator. Following these comparisons, quality controls have been specified so as to limitate the errors on the polarimetric variables before using them for assimilation. In the second part of the PhD, an assimilation method for polarimetric variables, based on the operational 1D+3D-Var assimilation method used for radar reflectivities in AROME model has been designed. The Bayesian retrieval of 1D humidity profiles has been adapted in order to include differential reflectivity and specific differential phase within the observation vector. Different options of the methodology have been tested and evaluated by comparisons with radar and GPS observations. Assimilation experiments conducted for two convective cases demonstrated an impact on analysed humidity fields. The effect of the assimilation of polarimetric variables on forecasted reflectivities and precipitation accumulations was also evaluated

L'exploitation des données radar météorologiques utilisées pour estimer la lame d'eau est souvent compliquée par la hauteur de la mesure. C'est tout particulièrement le cas en zone montagneuse où le faisceau est très éloigné du sol du fait que les radars sont installés en haute altitude et queles élévations les plus basses sont partiellement ou totalement masquées. La méthode classiquement utilisée en opérationnel (et notamment à Météo-France) pour extrapoler les réflectivités à hauteur du sol, ne permet pas de considérer certains processus trop complexes pour être modélisés simplement, comme l'évaporation ou le renforcement des précipitations sous le faisceau. De plus, la variabilité spatiale des profils de précipitations n'est pas prise en compte, limitant considérablement les performances de l'algorithme d'estimation de la lame d'eau en plaine comme en régions montagneuses. C'est en identifiant ces lacunes et limitations que s'est inscrite cette thèse, avec pour but le développement d'une méthode novatrice d'estimation de la lame d'eau. L'idée est de tirer partie de la capacité du modèle numérique de prévision immédiate à haute résolution de Météo-France (AROME-PI) à produire des profils de précipitations réalistes, pour établir les profils les plus probables compte tenu des observations volumiques disponibles et les utiliser pour estimer la précipitation au sol. On s'appuie sur un simulateur radar qui, à partir des variables pronostiquées par le modèle (contenus en hydrométéores, température...), simule la réflectivité, tout en respectant la géométrie du faisceau du radar. La première partie de la thèse se concentre sur la mise en place d'une méthode bayésienne de recherche des profils de réflectivitéssimulés les plus pertinents par rapport à l'observation et ensuite utilisés pour la restitution des taux de précipitations et de la lame d'eau. Deux cas d'études stratiformes complexes ont été étudiés pour tester les performances du nouveau schéma et souligner les limitations de la correction des réflectivités actuellement utilisée à Météo-France. Une étude de sensibilité sur le poids donné aux élévations les plus basses dans la méthode ainsi que sur le nombre de profils simulés utilisés a été menée. La deuxième partie de cette thèse présente des améliorations apportées à la paramétrisation de la bande brillante de ce simulateur en cohérence avec le schéma microphysique ICE3 utilisé dans AROME. Les réflectivités ainsi simulées ont été évaluées sur différents cas d'études. Les biais identifiés ont été en partie corrigés grâce au développement d'une méthode statistique adaptée, permettant l'élaboration d'un jeu de données simulées plus robuste. Enfin, le dernier volet du travail se focalise sur l'évaluation du potentiel de la méthode à mieux estimer les précipitations en zone montagneuse. Des premiers tests ont été effectués sur un cas idéalisé de plaine pour lequel on a volontairement masqué l'élévation la plus basse. On a ensuite reconstitué les réflectivité masquées pour les comparer avec les réflectivités réellement observées. La nouvelle méthode a ensuite été appliquée sur un cas convectif et un cas stratiforme en zone montagneuse. Une évaluation tri-dimensionnelle des résultats a été faite à partir des profils quasi-verticaux du radar Xport de l'IGE, des pluviomètres ainsi que des profils de référence issus des réanalyses SAFRAN, un modèle d'analyse et de prévision de grandeurs météorologiques adapté pour la montagne. Elle a permis de montrer tout le potentiel que représente cette nouvelle approche pour l'estimation de la lame d'eau en montagne
The use of weather radar data to estimate rainfall accumulations is often complicated by the heightof the measurement. This is particularly true in mountainous areas where the beam is very farfrom the ground either because the radar are installed at high altitude or because the lowest elevations are partially or totally hidden or both. The method conventionally used in operationalsystems (and in particular at Météo-France) to extrapolate reflectivities to ground level, does notallow to consider some processes too complex to be modeled easily, such as evaporation orstrengthening of precipitation under the radar beam. In addition, the spatial variability of theprecipitation profiles is not taken into account, limiting considerably the performance of the rainfallestimation by the algorithm in both plains and mountainous regions. It is by identifying these gapsand limitations that this thesis was written, with the aim of developing an innovative method forestimating the rainfall accumulations. The idea is to take advantage of the ability of MétéoFrance's high-resolution nowcasting model (AROME-PI) to produce realistic precipitation profiles.These profiles are used to estimate the most probable one according to the available volume observations, and to use it to estimate the precipitation at the ground. In order to do so, we relie ona radar simulator that simulates the reflectivity from the model prognostic variables (hydrometeorcontents, temperature ...), and that takes into acount the radar beam geometry. The first part ofthe thesis focused on the implementation of a Bayesian method to retrieve the most relevantsimulated profiles of reflectivity which are then used to estimate the rainfall rates and accumulations. Two complex stratiform situations were studied to test the performance of the newscheme and to highlight the limitations of the correction currently used at Météo-France. Thesensitivity of the results to the weight given to the lowest elevations in the method as well as to thenumber of simulated profiles used was conducted. The second part of this thesis presentsimprovements brought to the parametrization of the bright band in the radar simulator while keeping the coherence with the microphysics scheme ICE3 implemented in AROME model. Thesimulated reflectivities were evaluated on different case studies. The biases identified have beenpartially corrected through the development of a suitable statistical method, allowing thedevelopment of a more robust simulated dataset. Finally, the last part of the work focused onevaluating the potential of the method in mountainous areas. First tests were carried out on anidealized case over flat areas for which the lowest elevation was deliberately hidden. There flectivity behind this fictive mask was then reconstructed and compared with the reflectivitiesactually observed. Next, the new method was applied to a convective case and a stratiform caseover mountainous areas. A three-dimensional evaluation of the performances from the quasivertical profiles of the Xport radar from IGE, the rain gauges as well as the SAFRAN reanalysis (amodel producing analysis and forecast of meteorological quantities adapted for the mountain),helped to evaluate the full potential of this new approach for estimating the rainfall accumulationsin complex terrain

The purpose of this thesis is the exploration of the relationship and interaction between Electronic Warfare (EW) and Information Operations (IO) core, supporting and related competencies. Understanding the definitions of information and its value, information superiority, and the decision making cycle provides the foundation for the thesis. Investigation of the historical transformation of EW from the U.S. Civil War to the First Gulf War, and also examining how the concept of IO has developed and evolved contributes to this study by helping to comprehend the modern day interaction between EW and each IO competency separately. This interaction is constructed upon the guidance and standards provided by the latest U.S. Joint Chiefs of Staff Publication Joint Publication 3-13 Information Operations. This study concludes that the relationship between EW and IO is increasingly interactive and consists of two aspects: limiting and interfering, and reinforcing and supporting. Also, the relationship between EW and each IO competency is not consistent between the core and supporting competencies. In addition to these conclusions, this study expresses some considerations for EW and IO applications with respect to the unique environment and requirements of the Turkish Republic.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2006.
Thesis Advisor(s): Gerald Brown. "September 2006." Includes bibliographical references (p. 51-52). Also available in print.

Autonomous Vehicle are coming. But mass adoption is at least ten years away according to consensus compiled from interviews conducted with industry thought lenders. Questions remain as to what technology those vehicles will contain as there is no universal platform for autonomous vehicle technology, since manufacturers, hardware and software companies are developing their own proprietary products. A/V technology is expected to improve productivity, and provide a plethora of societal benefits, but while we await the closure of the time gap the US will lose almost 40,000 citizens each year with traffic fatalities. Connected vehicle technology, which is currently completing pilot studies, has been shown to reduce automobile accidents. This technology is not as complex as autonomous vehicle technology and is available now. Semi-autonomous vehicles which is Level 1 through Level 3 on the Society of Automobile Executives (SAE) scale is available on American automobiles today and has proven to be very popular amongst consumers. Technology convergence of semi-autonomous vehicle and connected vehicles can bridge the time gap until mass adoption of autonomous vehicle and contribute to reducing annual traffic fatalities. Combining these technologies will give drivers additional safety features thus providing them with the opportunity of making better decisions.

International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California
An increasing number of satellite users and manufacturers are looking to lightweight, inexpensive satellites as substitutes to traditional large, expensive satellites with multiple payloads. Neither the Department of Defense nor the commercial sector can bear the financial or reputational consequences associated with massive program failures. With the low cost and weight of these new satellites, users can achieve mission success without great risk. One example of this new class of inexpensive spacecraft is the RADCAL (RADar CALibration) satellite. Detachment 2, Space & Missile Systems Center at Sunnyvale, CA operates the satellite. RADCAL is a 200-pound polar orbiting satellite with an average altitude of 450 miles. It is primarily used by 77 worldwide radars to calibrate their systems to within five meter accuracy. Also flying on board RADCAL is a communication payload for remote field users with small radios. The RADCAL program has satisfied all mission requirements. However, with the limited size and cost come certain challenges, both in the satellite and on the ground. Pre-launch testing was not as comprehensive as with more expensive programs; anomalies have arisen that require extensive workarounds. Data management is not a straightforward task, and it is sometimes difficult and inexact to track satellite performance. These challenges are presented with their solutions in the following discussion; this paper addresses the functional, operational, and testing aspects associated with the RADCAL satellite.

We describe major enhancements to the missile defense planning aid "JOINT DEFENDER" (JDEF). JDEF is the first system that shows how to evaluate and exploit new and anticipated improvements in interceptors, long-range surveillance and tracking capabilities, networked communications, and the ability of detecting platforms to cue intercepting ones downrange. We want to improve system-wide effectiveness, gauged here by the reduction of expected damage inflicted. We defend an asset list (DAL) of targets, characterized by their locations and values to us. Our defenders include pure "LOOKERs," radars and sensors of enemy missile launches, and "SHOOTERs," platforms with means to both detect and intercept enemy launches. JDEF optimally positions platforms that can be moved, and prescribes what each platform should do. JDEF can estimate the value to either opponent of secrecy, deception, or intelligence. JDEF is the only missile defense planning system using formal optimization. Among many advantages this conveys, JDEF is able to unambiguously quantify the difference among disparate plans. Although the JDEF planner can manually control any detail, the planner is well advised to let optimization suggest where to start.

Rainfall affects the performance of traffic operations and endangers safety. A common and conventional method (rain gauges) for rainfall measurements mostly provide precipitation records in hourly and 15-minute intervals. However, reliability, continuity, and wide area coverage pose challenges with this data collection method. There is also a greater likelihood for data misrepresentation in areas where short duration rainfall is predominant, i.e., reported values may not reflect the actual equivalent rainfall intensity during subintervals over the entire reporting period. With recent weather and climate patterns increasing in severity, there is a need for a more effective and reliable way of measuring rainfall data used for traffic analyses. This study deployed the use of precipitation radar data to investigate the spatiotemporal effect of rainfall on freeways in Jacksonville, Florida. The linear regression analysis suggests a speed reduction of 0.75%, 1.54%, and 2.25% for light, moderate, and heavy rainfall, respectively. Additionally, headways were observed to increase by 0.26%, 0.54%, and 0.79% for light, moderate, and heavy rainfall, respectively. Measuring precipitation from radar data in lieu of using rain gauges has potential for improving the quality of weather data used for transportation engineering purposes. This approach addresses limitations experienced with conventional rain data, especially since conventional collection methods generally do not reflect the spatiotemporal distribution of rainfall.

El Instituto Geofísico del Perú ha desarrollado un proyecto, financiado por INNOVATE Perú, llamado “Diseño e implementación de un radar perfilador de vientos que opera en UHF para estudios de turbulencias y precipitación en el territorio peruano”, este proyecto es la propuesta de solución a una limitación presentada por la comunidad científica del Perú y otras entidades para hacer estudios climáticos de vientos y precipitación. Parte del desarrollo de este radar, es el procesamiento de los datos recibidos. En esta tesis se ha hecho un análisis del diseño, frecuencia y tipo de radar que fue diseñado para luego seleccionar los algoritmos de procesamiento necesarios. Los algoritmos que se desarrollaron para el procesamiento del radar UHF permiten estimar vientos troposféricos y turbulencia con la técnica de análisis espectral total. Además de medir la intensidad de precipitación y el factor de reflectividad obtenido de las lluvias con la relación del diámetro de gotas y el factor de reflectividad. Los resultados de estas estimaciones, posteriormente son comparados con otros instrumentos para su validación y su posterior aplicación.
The Geophysical Institute of Peru (IGP) has developed a project called "Design and implementation of a radar profiler that operates in UHF for studies of turbulence and precipitation in the Peruvian territory", this project is the proposed solution to a limitation presented by the scientific community of Peru and other entities to conduct climate studies of winds and precipitation. Part of the development of this radar is the processing of received data. In this thesis an analysis of the design, frequency and type of the designed radar was done to then select the appropriate processing algorithms. The algorithms that were developed for the UHF radar processing allows the estimation of tropospheric winds and turbulence with the full spectral analysis technique. In addition to measuring the intensity of precipitation and the reflectivity factor obtained from rainfall related to the diameter of drops and the reflectivity factor. The results of these estimates are then compared with other instruments for validation and subsequent application.
Tesis

Adverse weather is considered as one of the important factors contributing to injuries and severe crashes. During rainy conditions, it can reduce travel visibility, increase stopping distance, and create the opportunity hydroplaning. This study quantified the relative crash risk on Oregon 217 southbound direction under rainy conditions by using a match-paired approach, applied one-year traffic data, crash data and NEXRAD Level II radar weather data. There are 26 crashes occurred in match-paired weather conditions for Oregon 217 in year 2007. The results of this study indicate that a higher crash risk and a higher property-damage-only crash risk occurred during rainy days. The crash risk level varies by the location of the highway, at milepost 2.55 station SW Allen Blvd has the highest driving risks under rainy conditions.

Dans le cadre de la surveillance maritime, les opérationnels ont de plus en plus recours à l'imagerie radar pour classifier à grande distance un objet marin. Le traitement ISAR (Inverse Synthetic Aperture Radar) répond à ce besoin. Il repose en particulier sur l'analyse des mouvements propres de l'objet marin. Une fois l'objet détecté, il s'agit d'afficher sur la console tactique la représentation de la fréquence Doppler en fonction de la distance, aussi appelée image range-Doppler. Le travail présenté dans ce mémoire s'inscrit dans une perspective d'évolution opérationnelle de la chaîne de traitement existante. Il vise à produire de manière automatique la « meilleure » image range-Doppler. Dans cette thèse, nos contributions s'appuient sur l'idée de reconsidérer la chaîne de traitement en tenant compte de l'a priori que l'objet marin est un objet rigide dont la géométrie structure l'évolution du signal radar. Ainsi, dans une première contribution, nous proposons une nouvelle méthode d'analyse temps-fréquence du signal radar afin d'obtenir une image instantanée où l'opérationnel peut distinguer « au mieux » les superstructures de l'objet marin. Cette dernière est fondée sur la fusion de plusieurs représentations temps-fréquence issues de la classe de Cohen en faisant l'hypothèse que les composantes temps-fréquence sont des trajectoires structurées 2D dans le plan temps-fréquence, contrairement aux termes d'interférences induits par la propriété de bilinéarité des membres de cette classe. Une étude comparative sur données synthétiques et ISAR est menée pour confirmer la pertinence de notre approche, notamment du point de vue de la résolution temps-fréquence et de la suppression des termes d'interférences.Dans une seconde contribution, nous établissons une nouvelle procédure pour qualifier chaque image range-Doppler, obtenue à l'issue de l'analyse temps-fréquence, avec des mesures d'irrégularité de formes que nous fusionnons à l'aide d'un opérateur d'agrégation. Des simulations sur données réelles sont réalisées. Les résultats concordent avec une analyse subjective menée par des opérationnels, ce qui confirme l'efficacité de notre méthode
In maritime surveillance, radar imaging plays a key role to classify a maritime object. ISAR processing is one of the solutions, which takes advantage of the object rotational motion to provide a range-Doppler image.The work, presented in this report, is an evolution of the existing ISAR processing chain. Therefore, our contributions are based on the processing chain reconsideration by taking into account the fact that the maritime object is a rigid object, the geometry of which influences the radar signal evolution.In a first contribution, we propose a new time-frequency analysis method based on the aggregation of some time-frequency representations obtained with Cohen class members. It consists in differentiating the signal, assumed to be characterized by 2-D near-linear stable trajectories in the time-frequency plane, and the cross-terms, assumed to be geometrically unstructured. A comparative study is then carried out on ISAR synthetic data to confirm the efficiency of our approach.In a second contribution, we present a new procedure to characterize each range-Doppler image, obtained from a time-frequency analysis, by means of shape irregularity measures that are combined with a fuzzy logic operator. To validate our approach, simulations on real data are done. The results are compared to a subjective analysis carried out with practionners

In recent years the boost in operations by mini- and micro-UAS (Unmanned Aircraft Systems, also known as Remotely Piloted Aircraft Systems - RPAS - or simply drones) and the successful miniaturization of electronic components were experienced. Radar sensors demonstrated to have favorable features for these operations. However, despite their ability to provide meaningful information for navigation, sense-and-avoid, and imaging tasks, currently very few radar sensors are exploited onboard or developed for autonomous operations with mini- and micro-UAS. Exploration of indoor complex, dangerous, and not easily accessible environments represents a possible application for mini-UAS based on radar technology. In this scenario, the objective of the thesis is to develop design strategies and processing approaches for a novel ultralight radar sensor able to provide the miniaturized platform with Simultaneous Localization and Mapping (SLAM) capabilities, mainly but not exclusively indoors. Millimeter-wave Interferometric Synthetic Aperture Radar (mmw InSAR) technology has been identified as a key asset. At the same time, testing of commercial lightweight radar is carried out to assess potentialities towards autonomous navigation, sense-and-avoid, and imaging. The two main research lines can be outlined as follows: - Long-term scenario: Development of very compact and ultralight Synthetic Aperture Radar able to provide mini- or micro-UAS with very accurate 3D awareness in indoor or GPS-denied complex and harsh environments. - Short-term scenario: Assessment of true potentialities of current commercial radar sensors in a UAS-oriented scenario. Within the framework of long-term scenario, after a review of state-of-art SAR sensors, Frequency-Modulated Continuous Wave (FMCW) SAR technology has been selected as preferred candidate. Design procedure tailored to this technology and software simulator for operations have been developed in MATLAB environment. Software simulator accounts for the analysis of ambiguous areas in a three-dimensional environment, different SAR focusing algorithms, and a Ray-Tracing algorithm specifically designed for indoor operations. The simulations provided relevant information on actual feasibility of the sensor, as well as mission design characteristics. Additionally, field tests have been carried out at Fraunhofer Institute FHR with a mmw SAR. Processing approaches developed from simulations proved to be effective when dealing with field tests. A very lightweight FMCW radar sensor manifactured by IMST GmbH has been tested for short-term scenario operations. The codes for data acquisition were developed in Python language both for Windows-based and GNU/Linux-based operative systems. The radar provided information on range and angle of targets in the scene, thus being interesting for radar-aided UAS navigation. Multiple-target tracking and radar odometry algorithms have been developed and tested on actual field data. Radar-only odometry provided to be effective under specific circumstances.

Over the past decades, peace missions of the United Nations on the African continent succeed and failed. This thesis attempts to ascertain how success or failure can be explained. For assessment, the success criteria are derived from the academic literature and subsequently implemented into the hypotheses. Relevant indicators concerning peacekeeping success are used in African cases. The effectiveness of UN missions is fully investigated on UNOCI in Côte d'Ivoire, MONUC in the Democratic Republic of Congo, and UNMIL in Liberia. Then the results were compared in tested hypotheses. The findings show that host country's consent and willingness to cooperate, alongside the active engagement of major power, a clear, appropriate and achievable mandate, and the consistency of the UN's commitment to conflict resolution proved to be the most important factors for the peacekeeping effectiveness. The diplomacy and attention, given to underlying causes of conflicts, also contributed to the successful outcomes. The ethnic component and participating regional organisations, in contrast, overcomplicated the peace efforts but did not have a direct impact on missions' effectiveness. The effect of the missions' duration was found to be irrelevant, while ties to success with criteria of national ownership and...

The purpose of this research is to study the detection of temporal changes between two (or more) multimodal images satellites, i.e., between two different imaging modalities acquired by two heterogeneous sensors, giving for the same scene two images encoded differently and depending on the nature of the sensor used for each acquisition. The two (or multiple) multimodal satellite images are acquired and coregistered at two different dates, usually before and after an event. In this study, we propose new models belonging to different categories of multimodal change detection in remote sensing imagery. As a first contribution, we present a new constraint scenario expressed on every pair of pixels existing in the before and after image change. A second contribution of our work is to propose a spatio-temporal textural gradient operator expressed with complementary norms and also a new filtering strategy of the difference map resulting from this operator. Another contribution consists in constructing an observation field from a pair of pixels and to infer a solution maximum a posteriori sense. A fourth contribution is proposed which consists to build a common feature space for the two heterogeneous images. Our fifth contribution lies in the modeling of patterns of change by anomalies and on the analysis of reconstruction errors which we propose to learn a non-supervised model from a training base consisting only of patterns of no-change in order that the built model reconstruct the normal patterns (non-changes) with a small reconstruction error. In the sixth contribution, we propose a pairwise learning architecture based on a pseudosiamese CNN network that takes as input a pair of data instead of a single data and constitutes two partly uncoupled CNN parallel network streams (descriptors) followed by a decision network that includes fusion layers and a loss layer in the sense of the entropy criterion. The proposed models are enough flexible to be used effectively in the monomodal change detection case.
Cette recherche a pour objet l’étude de la détection de changements temporels entre deux (ou plusieurs) images satellitaires multimodales, i.e., avec deux modalités d’imagerie différentes acquises par deux capteurs hétérogènes donnant pour la même scène deux images encodées différemment suivant la nature du capteur utilisé pour chacune des prises de vues. Les deux (ou multiples) images satellitaires multimodales sont prises et co-enregistrées à deux dates différentes, avant et après un événement. Dans le cadre de cette étude, nous proposons des nouveaux modèles de détection de changement en imagerie satellitaire multimodale semi ou non supervisés. Comme première contribution, nous présentons un nouveau scénario de contraintes exprimé sur chaque paire de pixels existant dans l’image avant et après changement. Une deuxième contribution de notre travail consiste à proposer un opérateur de gradient textural spatio-temporel exprimé avec des normes complémentaires ainsi qu’une nouvelle stratégie de dé-bruitage de la carte de différence issue de cet opérateur. Une autre contribution consiste à construire un champ d’observation à partir d’une modélisation par paires de pixels et proposer une solution au sens du maximum a posteriori. Une quatrième contribution est proposée et consiste à construire un espace commun de caractéristiques pour les deux images hétérogènes. Notre cinquième contribution réside dans la modélisation des zones de changement comme étant des anomalies et sur l’analyse des erreurs de reconstruction dont nous proposons d’apprendre un modèle non-supervisé à partir d’une base d’apprentissage constituée seulement de zones de non-changement afin que le modèle reconstruit les motifs de non-changement avec une faible erreur. Dans la dernière contribution, nous proposons une architecture d’apprentissage par paires de pixels basée sur un réseau CNN pseudo-siamois qui prend en entrée une paire de données au lieu d’une seule donnée et est constituée de deux flux de réseau (descripteur) CNN parallèles et partiellement non-couplés suivis d’un réseau de décision qui comprend de couche de fusion et une couche de classification au sens du critère d’entropie. Les modèles proposés s’avèrent assez flexibles pour être utilisés efficacement dans le cas des données-images mono-modales.