Geolocation of RF Emitters Using a Low-Cost UAV-Based Approach

The proliferation of unmanned aerial vehicles (UAVs) in both military and civilian settings has prompted great interest in finding new and innovative ways to utilize these tools. One such application is to locate ground-based radio emitters from a UAV platform. The goal of this research is to study the feasibility of a low-cost (on the order of $1000) UAV geolocation platform. To accomplish this goal, a series of both real-world flight testing and computer simulated scenarios were conducted. Simulations for different sensor uncertainties and approach path scenarios such as loiter and button hook patterns were investigated. Results showed that a high uncertainty sensor of ±10 degrees was able to reliably geolocate the target provided it could fly sufficiently close to the emitter location. For the physical testing, a commercial-off-the-shelf Doppler direction finding unit was chosen as the method of performing the geolocation. Ground testing proved promising, locating the emitter to within 20 meters. However, flight testing showed poor results and was unable to locate the target. Areas of future work that could improve upon these results include investigating how altitude and antenna orientation variations caused by the movement of the aircraft affect the performance of the direction finding unit

Air Force Institute of Technology Research Report 2014

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Localisation d'une source d'interférence dans un système satellitaire

RÉSUMÉ Lorsqu’une source d’interférence génère un signal qui est envoyé vers un satellite, cela a˙ecte les performances du système satellitaire. Afin de faire cesser l’envoi du signal interférant, le fournisseur de service doit géolocaliser la source de l’interférence. Les systèmes de géolocalisation implémentés actuellement ne sont pas en mesure de géolocaliser la source d’interférence si celle-ci est en mouvement ou, dans le cas contraire, si la vélocité n’est pas connue à l’avance. De plus, les algorithmes de géolocalisation de source d’interférence mobile présentés dans la littérature sont difficilement implémentables dû au mauvais conditionnement des matrices générées par le problème de géolocalisation. Ainsi, le but de ce mémoire est de proposer un algorithme de géolocalisation d’une source d’interférence mobile dont on ne connaît ni la position, ni la vélocité à l’avance et dont on veut estimer les valeurs dans le temps. L’algorithme proposé utilise un filtre de Kalman de Gauss-Hermite (GHKF) pour e˙ectuer le suivi de la source d’interférence à l’aide des mesures des différences des temps d’arrivée (TDoA), différences des fréquences d’arrivée (FDoA) et différences des taux de Doppler d’arrivée (DDRoA) extraites des signaux reçus à la station de base du fournisseur de service, alors que les algorithmes actuels se limitent aux mesures de TDoA et FDoA seulement et à l’utilisation du filtre de Kalman sans-parfum(UKF). Un algorithme d’optimisation, l’algorithme des mauvaises herbes avec évolution différentielle, est utilisé au commencement du processus de géolocalisation afin de géolocaliser grossièrement la position de la source d’interférence afin de démarrer le filtre GHKF. Les simulations de l’algorithme ont permis de confirmer le fonctionnement de l’algorithme et de caractériser ses performances selon divers paramètres, dont le bruit sur les mesures et les paramètres internes de l’algorithme et du système satellitaire. Les systèmes de communication satellitaire Iridium et Globalstar ont été choisis pour simuler l’algorithme et le logiciel STK d’AGI a été utilisé afin de générer les éphémérides des satellites, afin d’obtenir des résultats réalistes. Les résultats obtenus ont permis de confirmer le fonctionnement de l’algorithme des mauvaises herbes avec évolution différentielle, du GHKF et du couplage entre les deux modules. De plus, cela montre qu’il est possible en ajoutant la mesure du DDRoA d’obtenir des estimés de la position de la source d’interférence qui soient inférieures à 3km qui est la précision minimale moyenne des systèmes de géolocalisation déjà existants, et ce, dans un cas avec une source d’interférence en mouvement. Cette recherche a donc permis d’obtenir un algorithme capable de géolocaliser précisément une source d’interférence mouvante affectant une liaison satellitaire en utilisant un module de démarrage utilisant l’algorithme d’optimisation des mauvaises herbes, ainsi qu’un filtre GHKF afin d’en effectuer le suivi.----------ABSTRACT When an interference source generates a signal that is sent to a satellite, it affects the performance of the satellite communication system. In order to stop the sending of the interfering signal, the service provider owning the satellite communication system must geolocate the source of the interference. The geolocation systems currently implemented cannot geolocate the source of interference if it is in motion or if the velocity is not known in advance in the other case. In addition, the mobile interference source geolocation algorithms presented in the literature are difficult to implement due to the poor conditioning of the matrices generated by the geolocation problem. Thus, the purpose of this thesis is to propose an algorithm to geolocate a mobile interference source whose position and velocity are not known in advance and whose values are to be estimated. The proposed algorithm uses a Gauss-Hermite Kalman filter (GHKF) to track the source of interference using time difference of arrival (TDoA), frequency difference of arrival (FDoA) and difference of doppler rates of arrival (DDRoA) measurements retrieved from signals received at the service provider base station, while the current algorithms are limited to TDoA and FDoA measurements only and the use of unscented Kalman filter (UKF). An optimization algorithm, the invasive weed algorithm with differential evolution, is used at the beginning of the geolocation process to roughly geolocate the position of the interference source in order to initialize the GHKF filter. The simulations of the algorithm have made possible to confirm the functionality of the algorithm and to characterize its performances according to various parameters, including the noise on the measurements and the internal parameters of the algorithm and the satellite system. The Iridium and Globalstar satellite communication systems were chosen to simulate the algorithm and the STK software from AGI was used to generate the satellites ephemeris in order to obtain realistic results. The results obtained confirmed the functionality of the invasive weed algorithm with differential evolution algorithm, of the GHKF and the coupling between the two modules. In addition, this shows that it is possible to obtain position estimates of the interference source with a precision less than 3km by adding the measurement of the DDRoA, which is the average maximum accuracy of the current geolocation systems. This research allowed to obtain an algorithm able to precisely geolocate a moving interference source affecting a satellite link by using a startup module using the the invasive weed algorithm with differential evolution, as well as a GHKF filter for tracking purposes

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity