A considerable amount of research effort has, and continues to be invested into technologies and algorithms for capabilities which are forecast to be needed in future uninhabited vehicles. Much of this research is conducted with the aim of increasing the level of autonomy of these vehicles. However these technologies and capabilities provide only a part of the total system solution and must be integrated into an architecture that covers the entire vehicle system. This total system approach is particularly relevant since this is how airworthiness regulators consider Uninhabited Aircraft Systems. Airworthiness of uninhabited aircraft has been addressed by Australian aviation regulators. While the regulations may be in place, technical challenges still remain for the suppliers of these systems. For example, one of these unresolved technical challenges is the capability of uninhabited aircraft to

Wind observations that are critical for understanding meteorological processes occurring inside of the Earth's atmospheric boundary layer (ABL) are sparse due to limitations of conventional atmospheric sensors. In this dissertation, dynamic systems and estimation theory are combined with experimental methods to exploit the flight envelope of multirotor UAS for wind sensing. The parameters of three quadrotor motion models, consisting of a kinematic particle, a dynamic particle, and a dynamic rigid body models are developed to measure wind velocity in hovering flight. Wind tunnel and steady level flight tests are used to characterize kinematic and dynamic particle models. System identification stepwise regression and output error algorithms are used to determine the model structure and parameter estimates of rigid body models. The comparison of all three models demonstrates the rigid body model to have higher performance resolving slow-varying winds based on a frequency response analysis and field experiments conducted next to a 3-D sonic anemometer. The dissertation also presents an extension of the rigid body wind estimation framework to profile the horizontal components of wind velocity in vertical steady ascending flight. The extension employed system identification to characterize five rigid body models for steady-ascending flight speeds increasing from 0 to 2 m/s in intervals of 0.5~m/s. State observers for wind profiling were synthesized using all five rigid body models. Performance assessments employing wind observations from in situ and remote sensors demonstrated model-based wind profiling results to be be in close agreement with ground-truth wind observations. Finally, the rigid body wind sensing framework developed in this dissertations for multirotor UAS is employed to support science objectives for the Advanced Lagrangian Predictions for Hazards Assessment Project. Quadrotor wind measurements sampled at 10 m above sea level were used to characterize the leeway of a person in water for search and rescue scenarios. Leeway values determined from quadrotor wind measurements were found to be in close to leeway parameters previous published in the literature. This results demonstrates the utility of model-based wind sensing for multirotor UAS for providing wind velocity observations in complex environments where conventional wind observations are not readily available. / Doctor of Philosophy / Wind observations that are critical for understanding meteorological processes occurring inside of the Earth's atmospheric boundary layer (ABL) are sparse due to limitations of conventional atmospheric sensors. In this dissertation, dynamic systems and estimation theory are combined with experimental methods to exploit the flight envelope of multirotor UAS for wind sensing. The parameters of three quadrotor motion models, consisting of a kinematic particle model, a dynamic particle model, and a dynamic rigid body model, are characterized to measure wind velocity in hovering flight. Parameter characterizations are realized using data from wind tunnel, steady level flight tests and system identification experiments. Model-based wind estimations algorithms are developed using the kinematic particle model directly and by synthesizing state observers for the dynamic particle and rigid body models separately. For comparison purposes, the frequency response characteristic of the dynamic particle and rigid body models is examined to determine the range of wind fluctuations that each model can resolve. Performance comparisons demonstrate that the rigid body model to resolve higher wind fluctuations and yield more accurate wind estimates. The dissertation extends the rigid body wind estimation algorithm to estimate wind velocity profiles of the horizontal wind vector. The rigid body wind estimation algorithms is used to answer science questions about about the drift of a person in water.

Energy-shaping techniques are used to expand the range of autonomous motion of unmanned aerial systems without prohibitively {color{black}increasing the computational cost of the resultant controller}. Passivity-based control presents a method to implement a static, nonlinear state feedback control law that stabilizes the motion of an aircraft with a large region of attraction. {color{black} The energy-based control scheme is applied to both multirotor and fixed-wing aircraft}. Multirotor aircraft dynamics are cast into a port-Hamiltonian System and the concept of trajectory tracking using canonical feedback transformation is implemented to construct a cross-track controller. Fixed-wing aircraft dynamics are cast in port-Hamiltonian form and a passivity-based nonlinear control law for steady, wings-level flight of a fixed-wing aircraft to a specified inertial velocity (speed, course, and climb angle) is constructed. Results in simulations and experiments suggest robustness, and a large region of attraction of the controller. The control law extended to support time-varying inertial velocity tracking that incorporates banking to turn. The results are extended by including a line-of-sight guidance law and varying the direction as a function of position relative to a desired path, rather than as a function of time. The control law and the associated proof of stability follow similarly to that of the time-varying directional stabilization problem. The results are supported with simulations as well as experimental flight tests. / Doctor of Philosophy / This dissertation presents an alternative but intuitive approach to regulate unmanned aerial vehicles' flight that would allow for more maneuverability {color{black} than conventional methods}. This scheme relies on modifying the energy of the system to achieve the desired motion and leverages the properties of the aircraft rather than eliminating them and imposing different properties. This approach is applied to both fixed-wing and aircraft and quadcopters. Simulations and experimental flights have show the efficacy of this approach compared to other more established methods.

The current proposed unmanned aircraft system (UAS) detect and avoid standards require the same safety metrics, even when in close proximity to the ground or structures. This requirement has the potential to hinder low altitude small unmanned aircraft operations, such as local package delivery and utility inspection. One of the main safety metrics for UASs to adhere to is a ``well clear" volume that quantifies the vertical and horizontal separation UASs are required to maintain from manned aircraft. The current volume of 2000 feet horizontal and +/- 250 feet vertical does not provide credit for the safety benefit of being close to an obstacle where manned aircraft do not fly and could prove to be too restricting for low-level flight operations (i.e., under 400 feet above ground level). This thesis suggests using smaller safety metric volumes than the well clear volume to demonstrate that operations at lower altitudes can still be proven to be just as safe as if they were held to the larger well clear volume standard by using obstacle and terrain shielding. The research leverages simulation to analyze different safety metrics and provides an example use case in which the methodology of shielded operations is applied to demonstrate how this methodology can be applied for a safety case. / Master of Science / With the development of small unmanned aircraft system (sUAS) technologies have come many practical and regulatory challenges, especially in low altitude airspaces. At lower altitudes, manned aircraft are likely to be operating at lower velocities and restricting standards require UASs to maneuver against aircraft that may not present a significant risk of collision. The excessive avoidance maneuvering can cause the successful execution of even simple operations such as package delivery or survey operations to become difficult. The strict requirements have the potential to specifically inhibit sUAS beyond visual line-of-sight commercial operations, which are of great interest to the industry. This thesis describes a method for demonstrating an equivalent level of safety of small UAS operations when utilizing avoidance algorithms that leverage obstacle and terrain awareness. The purpose of this research is to demonstrate that by remaining close to obstacles, which pose a hazard to other aircraft, an unmanned aircraft can lower the risk of a mid-air collision and to demonstrate an equivalent level of safety for operations using a reduced safety metrics.

The autonomous operation of Uncrewed Aircraft Systems (UAS) beyond the pilot in command's visual line of sight is currently restricted due to a lack of cost-effective surveillance sensors robust enough to operate in low-level airspace. The current sensors available either have have high accuracy of locating targets but are too short of a range to be usable or have long ranges but have gaps in coverage due to varying terrain. Sensor fusion is one possible method of combining the strengths of different sensors to increase the overall airspace surveillance quality to allow for robust detect and avoid (DAA) capabilities; enabling beyond visual line of sight operations. This thesis explores some of the current techniques and challenges to use sensor fusion for collision avoidance between crewed aircraft and UAS. It demonstrates an example method of sensor fusion using data from two radars and an ADS-B receiver. In this thesis, a test bed for ground-based airspace monitoring surveillance is proposed for a low cost method of long-term sensor evaluation. Lastly, an potential method of a heterogeneous, score-based, sensor fusion is presented and simulated. / Master of Science / Long range operations of Uncrewed Aircraft Systems (UAS) are currently restricted due to a lack of cost-effective surveillance sensors that work well enough near the ground in the presence changing terrain. The current sensors available either have have high accuracy of locating targets but are too short of a range to be usable or have long ranges but have gaps in coverage due to varying terrain. Sensor fusion is a solution to this problem by combining the strengths of different sensors to allow for better collision avoidance capabilities; enabling these long range operations. This thesis explores some of the current techniques and challenges to use sensor fusion for collision avoidance between crewed aircraft and UAS. It demonstrates an example method of sensor fusion using data from two radars and an ADS-B receiver. In this thesis, a test bed for ground-based airspace monitoring surveillance is proposed for long-term sensor testing. Lastly, an potential method of a sensor fusion using different types of sensors is presented and simulated.

Numerical weather modeling can benefit from improved wind sensing in the Earth's atmospheric boundary layer (ABL). Small, low-cost, uncrewed aircraft (drones) can be used to measure wind and a distribution of these vehicles could potentially provide measurements with much greater density and resolution, in both space and time, than current methods allow. To measure wind, a drone could be equipped with dedicated wind-measuring sensors, although these can be costly and obtrusive and must be carefully calibrated to account for interference effects. State estimation algorithms that combine a drone's operational measurements with a flight dynamic model can be used to infer wind without a dedicated wind sensor, although the sensor quality affects measurement accuracy. Previous studies have explored the effects of various sensors on wind estimate accuracy, but the effect of flight dynamic model fidelity has received less attention. This dissertation presents analysis of different aerodynamic model-free and model-based wind estimation methods, comparing six wind estimation formulations using experimental flight data from a small, fixed-wing aircraft. Each formulation is implemented using a Kalman filter, an extended Kalman filter, and an unscented Kalman filter. These filters are designed based on different assumptions related to the flight dynamic model, available sensors, and available measurements. Having identified a promising estimation approach, the dissertation next explores the value of incorporating unsteady effects into a flight dynamic model for model-based wind estimation. An unsteady aerodynamic model for a small, fixed-wing aircraft is developed, identified, and validated using experimental flight data. An extended Kalman filter is then designed and implemented for two motion models -- one that includes unsteady effects and another that does not. Analysis of the wind estimates and the estimation differences show that, while the unsteady flight dynamic model better predicts the aircraft motion, the value of incorporating this model for wind estimation is questionable. / Doctor of Philosophy / Wind velocity sensing is crucial to understanding the meteorological processes at low altitudes. The integration of low-cost drones has allowed them to be used as wind-sensing platforms. This is achieved by equipping small drones with dedicated wind-measuring sensors, often costly and infeasible, or inferring wind velocity from the drone's motion. Algorithms designed to infer wind can be used by combining onboard flight sensor measurements with a drone's flight dynamic model to infer wind. However, low-cost drones are usually equipped with low-cost flight sensors, which frequently lead to higher measurement uncertainty and degrade the accuracy of wind estimates. Previous studies have explored the effects of various sensors on wind estimates, but errors due to low-fidelity dynamic models have received less attention. This dissertation first presents a detailed analysis of different flight dynamic model-free and model-based wind estimation methods. It compares six wind estimation formulations. Each formulation is implemented in wind inferring algorithms called a Kalman filter, an extended Kalman filter, and an unscented Kalman filter. These algorithms are designed based on different assumptions related to the flight dynamic model, available flight sensors, and available measurements. Secondly, the value of incorporating a fixed-wing, unsteady flight dynamic model in a wind estimation scheme is analyzed. To this end, an unsteady flight dynamic model for a fixed-wing drone is developed, identified, and validated from data acquired from the drone's flight history. Furthermore, an extended Kalman filter is designed and implemented for two motion models -- one that includes unsteady effects and another that does not. The analysis of the time histories of the wind estimates and the wind estimate differences show that both model-based estimators perform equally well.

Unmanned combat aircraft systems (UCAS) represent a certain type of modern technology the States use to counter the growing number of security threats coming from the various non-state actors. The thesis focuses on the most common use of UCAS in the fight against these threats, on the practice called targeted killing. The purpose of the thesis is to identify all conditions amongst the norms of international law pertaining to the use of force between States, international human rights law and international humanitarian law, which are relevant for the targeted killing through UCAS. Furthermore, the thesis seeks to set out the circumstances, under which this practice can satisfy the relevant conditions, and when, on the other hand, it is never lawful. The thesis is composed of four chapters. The First Chapter defines the key terms used in the thesis and clarifies the terminology relating to UCAS. It also offers a short overview of their technical specifications and capabilities and identifies the States, which own, develop and sell the technology. The following three chapters represent the analytical core of the thesis and set out the conditions for the use of UCAS found in three systems of international law. The Second Chapter examines the use of UCAS from the perspective of the prohibition on the...

Aircraft despatch reliability was the main subject of this research in the wider content of aircraft reliability. The factors effecting dispatch reliability, aircraft delay, causes of aircraft delays, and aircraft delay costs and magnitudes were examined. Delay cost elements and aircraft delay scenarios were also studied. It concluded that aircraft dispatch reliability is affected by technical and non-technical factors, and that the former are under the designer's control. It showed that the costs of aircraft delays are very significant and must be reduced. Cont/d.

Aircraft despatch reliability was the main subject of this research in the wider content of aircraft reliability. The factors effecting dispatch reliability, aircraft delay, causes of aircraft delays, and aircraft delay costs and magnitudes were examined. Delay cost elements and aircraft delay scenarios were also studied. It concluded that aircraft dispatch reliability is affected by technical and non-technical factors, and that the former are under the designer's control. It showed that the costs of aircraft delays are very significant and must be reduced. Cont/d.

Made available in DSpace on 2014-06-12T15:59:55Z (GMT). No. of bitstreams: 2 arquivo5803_1.pdf: 2496332 bytes, checksum: b4666e127bf620dbcb7437f9d83c2344 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / Faculdade de Amparo à Ciência e Tecnologia do Estado de Pernambuco / A análise da segurança (Safety Assessment) é um processo bem conhecido que serve para garantir que as restrições de segurança de um sistema crítico sejam cumpridas. Dentro dele, a análise de segurança quantitativa lida com essas restrições em um contexto numérico (probabilístico). Os métodos de análise de segurança, como a tradicional Fault Tree Analysis (FTA), são utilizados no processo de avaliação da segurança quantitativo, seguindo as diretrizes de certificação (por exemplo, a ARP4761 Guia de Práticas Recomendadas da Aviação). No entanto, este método é geralmente custoso e requer muito tempo e esforço para validar um sistema como um todo, uma vez que para uma aeronave chegam a ser construídas, em média, 10.000 árvores de falha e também porque dependem fortemente das habilidades humanas para lidar com suas limitações temporais que restringem o âmbito e o nível de detalhe que a análise e os resultados podem alcançar. Por outro lado, as autoridades certificadoras também permitem a utilização da análise de Markov, que, embora seus modelos sejam mais poderosos que as árvores de falha, a indústria raramente adota esta análise porque seus modelos são mais complexos e difíceis de lidar. Diante disto, FTA tem sido amplamente utilizada neste processo, principalmente porque é conceitualmente mais simples e fácil de entender. À medida que a complexidade e o time-to-market dos sistemas aumentam, o interesse em abordar as questões de segurança durante as fases iniciais do projeto, ao invés de nas fases intermediárias/finais, tornou comum a adoção de projetos, ferramentas e técnicas baseados em modelos. Simulink é o exemplo padrão atualmente utilizado na indústria aeronáutica. Entretanto, mesmo neste cenário, as soluções atuais seguem o que os engenheiros já utilizavam anteriormente. Por outro lado, métodos formais que são linguagens, ferramentas e métodos baseados em lógica e matemática discreta e não seguem as abordagens da engenharia tradicional, podem proporcionar soluções inovadoras de baixo custo para engenheiros. Esta dissertação define uma estratégia para a avaliação quantitativa de segurança baseada na análise de Markov. Porém, em vez de lidar com modelos de Markov diretamente, usamos a linguagem formal Prism (uma especificação em Prism é semanticamente interpretada como um modelo de Markov). Além disto, esta especificação em Prism é extraída de forma sistemática a partir de um modelo de alto nível (diagramas Simulink anotados com lógicas de falha do sistema), através da aplicação de regras de tradução. A verificação sob o aspecto quantitativo dos requisitos de segurança do sistema é realizada utilizando o verificador de modelos de Prism, no qual os requisitos de segurança tornam-se fórmulas probabilísticas em lógica temporal. O objetivo imediato do nosso trabalho é evitar o esforço de se criar várias árvores de falhas até ser constatado que um requisito de segurança foi violado. Prism não constrói árvores de falha para chegar neste resultado. Ele simplesmente verifica de uma só vez se um requisito de segurança é satisfeito ou não no modelo inteiro. Finalmente, nossa estratégia é ilustrada com um sistema simples (um projeto-piloto), mas representativo, projetado pela Embraer