No description available.

No description available.

No description available.

Radar-based remote sensing is consistently growing, and new technologies and subsequent techniques for characterization are changing the feasibility of understanding the environment. The emergence of easily accessible unmanned aircraft system (UAS) has broadened the scope of possibilities for efficiently surveying the world. The continued development of low-cost sensing systems has greatly increased the accessibility to characterize physical phenomena. In this thesis, we explore the viability and implementation of using UAS as a means of radar-based remote sensing for ground penetrating radar (GPR) and polarimetric scatterometry. Additionally, in this thesis, we investigate the capabilities and implementations of low-cost microwave technologies for applications in radar-based remote sensing compared to higher fidelity and more expensive technologies of similar scope.

The focus of this dissertation is on developing novel methods and extending existing ones to improve the security and reliability of fixed-wing unmanned aircraft systems (UAS). Specifically, we focus on three strands of work: i) designing UAS controllers with performance guarantees using the robust control framework, ii) developing tools for detection and mitigation of physical-layer security threats in UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS. Under the first category, we use the robust H-infinity control approach to design a linear parameter-varying (LPV) path-following controller for a fixed-wing UAS that enables the aircraft to follow any arbitrary planar curvature-bounded path under significant environmental disturbances. Three other typical path-following controllers, namely, a linear time-invariant H-infinity controller, a nonlinear rate-tracking controller, and a PID controller, are also designed. We study the relative merits and limitations of each approach and demonstrate through extensive simulations and flight tests that the LPV controller has the most consistent position tracking performance for a wide array of geometric paths. Next, convex synthesis conditions are developed for control of distributed systems with uncertain initial conditions, whereby independent norm constraints are placed on the disturbance input and the uncertain initial state. Using this approach, we design a distributed controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories. Pertaining to the second strand of this dissertation, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, a probabilistic framework that employs tools from statistical analysis to detect sensor attacks on UAS is proposed. By incorporating knowledge about the physical system and using a Bayesian network, the proposed approach minimizes the false alarm rates, which is a major challenge for UAS that operate in dynamic and uncertain environments. Next, the security vulnerabilities of existing UAS actuators are identified and three different methods of differing complexity and effectiveness are proposed to detect and mitigate the security threats. While two of these methods involve developing algorithms and do not require any hardware modification, the third method entails hardware modifications to the actuators to make them resilient to malicious attacks. The three methods are compared in terms of different attributes such as computational demand and detection latency. As for the third strand of this dissertation, tools from formal methods such as compositional verification are used to design an unmanned multi-aircraft system that is deployed in a geofencing application, where the design objective is to guarantee a critical global system property. Verifying such a property for the multi-aircraft system using monolithic (system-level) verification techniques is a challenging task due to the complexity of the components and the interactions among them. To overcome these challenges, we design the components of the multi-aircraft system to have a modular architecture, thereby enabling the use of component-based reasoning to simplify the task of verifying the global system property. For component properties that can be formally verified, we employ results from Euclidean geometry and formal methods to prove those properties. For properties that are difficult to be formally verified, we rely on Monte Carlo simulations. We demonstrate how compositional reasoning is effective in reducing the use of simulations/tests needed in the verification process, thereby increasing the reliability of the unmanned multi-aircraft system. / Doctor of Philosophy / Given the safety-critical nature of many unmanned aircraft systems (UAS), it is crucial for stake holders to ensure that UAS when deployed behave as intended despite atmospheric disturbances, system uncertainties, and malicious adversaries. To this end, this dissertation deals with developing novel methods and extending existing ones to improve the security and reliability of fixed-wing UAS. Specifically, we focus on three key areas: i) designing UAS controllers with performance guarantees, ii) developing tools for detection and mitigation of security threats to sensors and actuators of UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS. Pertaining to the first area, we design controllers for UAS that would enable the aircraft to follow any arbitrary planar curvature-bounded path under significant atmospheric disturbances. Four different controllers of differing complexity and effectiveness are designed, and their relative merits and limitations are demonstrated through extensive simulations and flight tests. Next, we develop control design tools to improve the transient response of multi-mission UAS networks. Using these tools, we design a controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories. As for the contributions in the second area, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, we propose a framework for detecting sensor attacks on UAS. By judiciously using knowledge about the physical system and techniques from statistical analysis, the framework minimizes the false alarm rates, which is a major challenge in designing attack detection systems for UAS. Then, we focus on another important attack surface of the UAS, namely, the actuators. Here, we identify the security vulnerabilities of existing UAS actuators and propose three different methods to detect and mitigate the security threats. The three methods are compared in terms of different attributes such as computational demand, detection latency, need for hardware modifications, etc. In regard to the contributions in the third area, tools from compositional verification are used to design an unmanned multi-aircraft system that is tasked to track and compromise an aerial encroacher, wherein the multi-aircraft system is required to satisfy a global system property pertaining to collision avoidance and close tracking. A common approach to verifying global properties of systems is monolithic verification where the whole system is analyzed. However, such an approach becomes intractable for complex systems like the multi-aircraft system considered in this work. We overcome this difficulty by employing the compositional verification approach, whereby the problem of verifying the global system property is reduced to a problem of reasoning about the system’s components. That being said, even formally verifying some component properties can be a formidable task; in such cases, one has to rely on Monte Carlo simulations. By suitably designing the components of the multi-aircraft system to have a modular architecture, we show how one can perform focused component-level simulations rather than conduct simulations on the whole system, thereby limiting the use of simulations during the verification process and, as a result, increasing the reliability of the system.

Unmanned aircraft systems (UAS) often encounter turbulent fields that perturb the aircraft from its desired target trajectory, or in a manner that increases the load factor. The aircraft's fixed dihedral angle, providing passive roll-stiffness, is often selected based on lateral-directional stability requirements for the vehicle. A study to predict the effect of an active dihedral system on lateral-directional stability and vertical gust rejection capability was conducted to assess the performance and feasibility of the system. Traditionally, the dihedral location begins at the root to maintain wing structural requirements, however, the active dihedral system was also evaluated for dynamic stability and gust rejection performance at alternative dihedral breakpoint locations. Simulations were completed using linear parameter-varying (LPV) models, derived from traditional Newtonian aircraft dynamics and associated kinematic equations, to improve the modeling of the nonlinear active dihedral system. The stability of the LPV system was evaluated using Lyapunov stability theory applied to switched linear systems, assessing bounds of operation for the dihedral angle and flapping rate. An ideal feedback controller was developed using a linear–quadratic regulator (LQR) for both a discrete gust model and a continuous gust model, and a gain scheduled LQR controller was implemented to show the benefits of gain scheduling with a parameter varying state and input model. Finally, a cost analysis was conducted to investigate the real-world benefit of altering the dihedral breakpoint location. The effects of the active dihedral system on battery capacity and consumption efficiency were observed and compared with the gust rejection authority. / Master of Science / Unmanned aircraft systems (UAS) often encounter wind disturbances that perturb the aircraft from its desired target trajectory, or in a manner that increases the force encountered on the vehicle. The aircraft's fixed dihedral angle, providing stiffness to roll rotations, is often selected based on stability and control requirements for the vehicle. A study to predict the effect of a flapping wing (active dihedral) system on the stability, control, and wind gust rejection capability is completed to assess the performance and feasibility of such a system. Traditionally, the dihedral location begins at the root to maintain wing structural requirements, however, the active dihedral system was also evaluated for stability and wind gust rejection performance at alternative locations along the wing where the dihedral could begin, with intention of finding the best location. Simulations were completed using a varying set of simplified models, obtained from traditional aircraft mechanics, to improve the modeling of the true complex active dihedral system. The stability of the system was evaluated using various theories applied to the linear systems in attempt to define a bounded operating region for the dihedral angle and flapping motion. An ideal controller for the system was developed using ideas from well documented linear control theory for both a single wind gust and a continuous wind gust model. A controller that varies with vehicle flapping motion was implemented to show the benefits of scheduling the controller with a parameter varying state and input model. Finally, a cost analysis was conducted to investigate the real-world benefit of altering the dihedral starting location. The effects of the active dihedral system on battery capacity and consumption efficiency were observed and compared with the total gust rejection capability.

The main contributions of this work are applications of robust control and analysis methods to complex engineering systems, namely, small fixed-wing unmanned aircraft systems (UAS). Multiple path-following controllers for a small fixed-wing Telemaster UAS are presented, including a linear parameter-varying (LPV) controller scheduled over path curvature. The controllers are synthesized based on a lumped path-following and UAS dynamic system, effectively combining the six degree-of-freedom aircraft dynamics with established parallel transport frame virtual vehicle dynamics. The robustness and performance of these controllers are tested in a rigorous MATLAB simulation environment that includes steady winds, turbulence, measurement noise, and delays. After being synthesized off-line, the controllers allow the aircraft to follow prescribed geometrically defined paths bounded by a maximum curvature. The controllers presented within are found to be robust to the disturbances and uncertainties in the simulation environment. A robust analysis framework for mathematical validation of flight control systems is also presented. The framework is specifically developed for the complete uncertainty characterization, quantification, and analysis of small fixed-wing UAS. The analytical approach presented within is based on integral quadratic constraint (IQC) analysis methods and uses linear fractional transformations (LFTs) on uncertainties to represent system models. The IQC approach can handle a wide range of uncertainties, including static and dynamic, linear time-invariant and linear time-varying perturbations. While IQC-based uncertainty analysis has a sound theoretical foundation, it has thus far mostly been applied to academic examples, and there are major challenges when it comes to applying this approach to complex engineering systems, such as UAS. The difficulty mainly lies in appropriately characterizing and quantifying the uncertainties such that the resulting uncertain model is representative of the physical system without being overly conservative, and the associated computational problem is tractable. These challenges are addressed by applying IQC-based analysis tools to analyze the robustness of the Telemaster UAS flight control system. Specifically, uncertainties are characterized and quantified based on mathematical models and flight test data obtained in house for the Telemaster platform and custom autopilot. IQC-based analysis is performed on several time-invariant H∞ controllers along with various sets of uncertainties aimed at providing valuable information for use in controller analysis, controller synthesis, and comparison of multiple controllers. The proposed framework is also transferable to other fixed-wing UAS platforms, effectively taking IQC-based analysis beyond academic examples to practical application in UAS control design and airworthiness certification. IQC-based analysis problems are traditionally solved using convex optimization techniques, which can be slow and memory intensive for large problems. An oracle for discrete-time IQC analysis problems is presented to facilitate the use of a cutting plane algorithm in lieu of convex optimization in order to solve large uncertainty analysis problems relatively quickly, and with reasonable computational effort. The oracle is reformulated to a skew-Hamiltonian/Hamiltonian eigenvalue problem in order to improve the robustness of eigenvalue calculations by eliminating unnecessary matrix multiplications and inverses. Furthermore, fast, structure exploiting eigensolvers can be employed with the skew-Hamiltonian/Hamiltonian oracle to accurately determine critical frequencies when solving IQC problems. Applicable solution algorithms utilizing the IQC oracle are briefly presented, and an example shows that these algorithms can solve large problems significantly faster than convex optimization techniques. Finally, a large complex engineering system is analyzed using the oracle and a cutting-plane algorithm. Analysis of the same system using the same computer hardware failed when employing convex optimization techniques. / Ph. D.

The theory of Lagrangian Coherent Structures (LCS) enables prediction of material transport by turbulent winds, such as those observed in the Earth's Atmospheric Boundary Layer. In this dissertation, both theory and experimental methods are developed for utilizing small fixed-wing unmanned aircraft systems (UAS) in detecting these atmospheric coherent structures. The dissertation begins by presenting relevant literature on both LCS and airborne wind estimation. Because model-based wind estimation inherently depends on high quality models, a Flight Dynamic Model (FDM) suitable for a small fixed-wing aircraft in turbulent wind is derived in detail. In this presentation, some new theoretical concepts are introduced concerning the proper treatment of spatial wind gradients, and a critical review of existing theories is presented. To enable model-based wind estimation experiments, an experimental approach is detailed for identifying a FDM for a small UAS by combining existing computational aerodynamic and data-driven approaches. Additionally, a methodology for determining wind estimation error directly resulting from dynamic modeling choices is presented and demonstrated. Next, some model-based wind estimation results are presented utilizing the experimentally identified FDM, accompanied by a discussion of model fidelity concerns and other experimental issues. Finally, an algorithm for detecting LCS from a single circling fixed-wing UAS is developed and demonstrated in an Observing System Simulation Experiment. The dissertation concludes by summarizing these contributions and recommending future paths for continuing research. / Doctor of Philosophy / In a natural or man-made disaster, first responders depend on accurate predictions of where the wind might carry hazardous material. A mathematical theory of Lagrangian Coherent Structures (LCS) has shown promise in ocean environments to improve these predictions, and the theory is also applicable to atmospheric flows near the Earth’s surface. This dissertation presents both theoretical and experimental research efforts towards employing small fixed-wing unmanned aircraft systems (UAS) to detect coherent structures in the Atmospheric Boundary Layer (ABL). These UAS fit several “gaps” in available sensing technology: a small aircraft responds significantly to wind gusts, can be steered to regions of interest, and can be flown in dangerous environments without risking the pilot’s safety. A key focus of this dissertation is to improve the quality of airborne wind measurements provided by inexpensive UAS, specifically by leveraging mathematical models of the aircraft. The dissertation opens by presenting the motivation for this research and existing literature on the topics. Next, a detailed derivation of a suitable Flight Dynamic Model (FDM) for a fixed-wing aircraft in a turbulent wind field is presented. Special attention is paid to the theories for including aerodynamic effects of flying in non-uniform winds. In preparation for wind measurement experiments, a practical method for obtaining better quality FDMs is presented which combines theoretically based and data-driven approaches. A study into the wind-measurement error incurred solely by mathematical modeling is presented, focusing on simplified forms of the FDM which are common in aerospace engineering. Wind estimates which utilize our best available model are presented, accompanied by discussions of the model accuracy and additional wind measurement concerns. A method is developed to detect coherent structures from a circling UAS which is providing wind information, presumably via accurate model based estimation. The dissertation concludes by discussing these conclusions and directions for future research which have been identified during these pursuits.

This thesis presents the development and implementation of a software framework for estimating the position of a drone during flight. This framework is based on an algorithm known as the Unscented Kalman Filter (UKF), a recursive method of estimating the state of a highly nonlinear system, such as an aircraft. In this thesis, we present a UKF formulation specially designed for a quadcopter carrying an Inertial Measurement Unit (IMU) and a downward-facing camera. The UKF fuses data from each of these sensors to track the position of the quadcopter over time. This work supports a number of similar efforts in the robotics and aerospace communities to navigate in GPS-denied environments with minimal hardware and minimal computational complexity. The software framework explored in this thesis provides a means for roboticists to easily implement similar UKF-based state estimators for a wide variety of systems, including surface vessels, undersea vehicles, and automobiles. We test the system's effectiveness by comparing its position estimates to those of a commercial motion capture system and then discuss possible applications. / Master of Science

Flygfotografering med Unmanned Aircraft System (UAS) är i jämförelse med traditionell fotogrammetri effektivare, billigare och säkrare vilket har medfört att denna teknik föredras av många aktörer. Ett tidskrävande arbete som varit svårt att kringgå är att etablera flygsignaler på marken som används för att georeferera och kontrollera flygbilderna med. Under 2018 presenterade UAS-tillverkaren DJI sin nya quadcopter med integrerad Real-Time Kinematic (RTK)-modul. I samband med detta kan kontinuerliga och noggranna positioner levereras via Nätverks-RTK (NRTK) och behovet av markstödpunkter reduceras. I denna studie undersöktes lägesosäkerheterna i plan för ortofoton som framställdes med hjälp av en DJI Phantom 4 RTK där flygbilderna georefererades med begränsat antal eller utan markstödpunkter. Lägesosäkerheterna beräknades och kontrollerades enligt Handbok i mät- och kartfrågor (HMK) – Ortofoto, vilket är ett stöddokument inom ämnet. Vid framställning av ett ortofoto krävs även en digital terrängmodell (DTM) eller en digital ytmodell (Digital Surface Model, DSM) och kvaliteten av denna har stor inverkan på ortofotots kvalitet. I denna studie kontrollerades och utvärderades därför en del av den DSM som användes vid ortofotoframställning för respektive uppsättning enligt den tekniska specifikationen SIS-TS 21144:2016. Resultatet från studien visar att ett ortofoto går att framställas utan markstödpunkter och samtidigt klara kraven på specificerad lägesosäkerhet enligt HMK-standardnivå 3. Den sammanlagda lägesosäkerheten beräknades till 0,029 m vilket är 5 mm högre i jämförelse med ett ortofoto som baserats på traditionell georefereringsmetod, dvs. med markstödpunkter. Kravet på kvalitet i höjddata uppfylldes också för ortofotoframställning trots att en systematisk effekt i höjd uppkom. Denna effekt påverkade inte ortofotots koordinater i plan då standardosäkerheterna i höjd var låga. Resultatet visade att om två markstödpunkter adderades i vardera änden av området, kunde de systematiska effekterna i höjd minimeras och det var då möjligt att skapa en DSM som uppfyller kraven för detaljprojektering (noggrannhetsklass 1–3) enligt SIS-TS 21144:2016. / Aerial photography with UAS is in comparison with traditional photogrammetry more efficient, cheaper and safer which has led to this technology being preferred by many performers. A time-consuming job that has been difficult to avoid is to establish signals at the ground that are used for georeferencing and evaluate the results. In 2018, the UAS manufacturer DJI presented its new quadcopter with integrated Real-Time Kinematic (RTK) module. This allows continuous and accurate positions delivered via Network RTK (NRTK) and the need of ground control points can be reduced. In this study, investigations of the position uncertainties in orthophotos produced using a DJI Phantom 4 RTK carried out where the aerial images were georeferenced with limited numbers or without ground control points. The position uncertainties were calculated and controlled according to the Swedish HMK – Ortofoto (Orthophoto) which is a document within the subject. When producing an orthophoto, a digital terrain model (DTM) or a digital surface model (DSM) is also required and the quality of this has a great impact on the result. Therefore, a part of the DSM used for orthophoto production for each set was checked and evaluated according to the Swedish technical specification, SIS-TS 21144:2016. The result of the study shows that an orthophoto can be produced without ground control points and at the same time meet the requirements for specified position uncertainty according to HMK standard level 3. The total position uncertainty was calculated to be 0,029 m, which is 5 mm higher compared to the orthophoto based on the traditional georeferencing method, i.e. with ground control points. The requirement for quality in height data was also met for orthophoto production even though a systematic effect in height occurred. This effect did not affect the plane coordinates in the orthophoto because of the low standard uncertainties in height. The result showed that if two ground control points were added at each end of the area, the systematic effects were minimized, and it was possible to produce a DSM that fulfils the requirements for accuracy class 1-3 according to SIS-TS 21144:2016.