As problems in the world become increasingly complex, designers in multiple disciplines have begun to propose swarms as a solution. The espoused benefits include flexibility, resilience, and potential for decentralized control, yet there lacks consensus on what a swarm is, what characteristics they possess, and what applications they are able to address. This study addresses these questions by creating a unified approach for understanding and analyzing swarms, called the Swarm Analysis Framework. The framework pursues three goals: 1) provide extensive analysis on the many characteristics and applications that define a swarm, 2) remain flexible enough to facilitate design, testing, analysis, and other problems in understanding swarms, and 3) outline swarm applications specific to aircraft and spacecraft based swarms. Afterwards, the Swarm Analysis Framework is used to guide a case study in which the application is a swarm was developed to study one of these aerospace applications. Ultimately, the Swarm Analysis Framework, along with its extensions improvements, should be able to act as a guide or roadmap in understanding how swarms behave across multiple disciplines.<br>

Electromagnetic compatibility (EMC), or the field of reducing emissions from and increasing immunity against electromagnetic interference, is an essential part of designing modern electronics. As one would expect, EMC is especially important for things such as aircraft and aviation equipment where outages or disturbances could have severe consequences. The problem presented in this thesis was to consolidate the available legislation regarding EMC for unmanned aircraft and then apply this information onto two commercial systems still under development. Based on the applied rules, pre-compliance measurements were then performed to identify problematic areas of their designs in regards to EMC, or more specifically radiated emissions and electromagnetic immunity. The research process for the legislation involved reading through mainly the official documents and directives published by the European Commission, the European Parliament and the European Aviation Safety Agency (EASA), looking up declarations of conformity made by drone manufacturers and also contacting accredited EMC labs for information on how they usually prove compliance for drones. The conclusion of this research being that (for EMC purposes) drones need to follow either the EMC directive 2014/30/EU, the radio equipment directive 2014/53/EU or the essential requirements of directive 2018/1139/EU depending on the intended usage of the drone and its technical specification. As for application of legislation onto the two commercial systems, because there were no drone-specific EMC standards (i.e voluntary ways to more easily prove conformity) in the EU some simplifications would need to be made. This took the form of applying parts of both the EN 55032 (applicable for multimedia equipment) and EN 301 489-1 (applicable for radio equipment) standards for radiated emissions and immunity testing respectively. While the application of legislation in the end was more simplified than initially planned, the goal of condensing down the available information was still achieved. As for the measurements, it should be noted that while most of the problematic areas that caused the systems to break the limits in the chosen legislation were indeed successfully identified on both systems there are still measurements that should be done in the future. This includes testing conducted emissions and immunity against transient electromagnetic phenomena such as electrostatic discharge (ESD).

The current standard for remote identification of unmanned aircraft does not contain anyform of security considerations, opening up possibilities for impersonation attacks. Thenewly proposed Drone Remote Identification Protocol aims to change this. To fully ensurethat the protocol is secure before real world implementation, we conduct a formal verification using the Tamarin Prover tool, with the goal of detecting possible vulnerabilities. Theunderlying technologies of the protocol are studied and important aspects are identified.The main contribution of this thesis is the formal verification of session key secrecy andmessage authenticity within the proposed protocol. Certain aspects of protocol securityare still missing from the scripts, but the protocol is deemed secure to the extent of themodel. Many features of both the protocol and Tamarin Prover are presented in detail,serving as a potential base for the continued work toward a complete formal verificationof the protocol in the future.

<p>Due to the rapid development of technologies for unmanned aircraft systems (UAS's), the supply and demand market for UAS's is expanding globally. With the great number of UAS's ready to fly in civilian airspace, an UAS aircraft traffic management system that can guarantee the safe, resilient and efficient operation of UAS's is absent. The vast majority of existing literature on UAS traffic lacks of the attention to the fundamental characteristics of UAS operation, which leads to models and methods that are difficult to implement or lacks scalability. Motivated by these challenges, this research aims at achieving three objectives: 1) the proper frameworks that scale well with high-frequency, high-density UAS operations, 2) the models that captures the fundamental characteristics of UAS operations, 3) the methods that can be implemented in practice with guarantees of efficiency, safety, and resilience. In particular, the objectives are studied at low-level UAS traffic congestion control, agent-level UAS configuration control and unknown agent prediction. The proposed frameworks and obtained results offer comprehensive and practical guidelines of real world UAS operations at different levels.</p>

Small unmanned aircraft systems (sUAS) will become a disruptive force on the modern battlefield. In recent years, sUAS size and cost have decreased while their capability has increased. They have forced a reconsideration of the air superiority paradigm held since the First World War. Perhaps their most attractive, and worrisome, feature is the huge range of combat roles that they might fulfill. The presence of sUAS on future battlefields is certain, but the role they will play and their impact on those battlefields are not. This work presents a decision support framework for sUAS deployment in small infantry units. The framework is designed to explore and evaluate multiple sUAS-small-unit deployment concepts' impact on small unit effectiveness in a combat scenario of interest. The framework helps decision makers identify high-level sUAS deployment principles for testing and validation in physical experiments before sUAS are implemented on the battlefield. The decision support framework comprises the following: 1) a definition of the sUAS-small-unit deployment concept design space and combat scenario, 2) an agent-based computer model for exploring sUAS deployment concepts, 3) a set of analysis tools for evaluating sUAS deployment impact on combat effectiveness, and 4) suggestions for synthesizing high-level sUAS deployment principles from the analysis. In this work, the decision support framework for sUAS-small-unit deployment is used to explore and evaluate the impact of deploying an infantry platoon with between one and nine unmanned aerial vehicles (UAV) operating in a reconnaissance role while executing one of several sUAS patrol pattern variants. In a scenario in which a defending platoon uses sUAS to intercept and aid in indirect fires targeting against a platoon of attacking infantry, the sUAS were shown to markedly improve the defending platoon's combat effectiveness. The framework is used to synthesize several key principles for sUAS deployment in the scenario. It shows that, when fewer UAVs are deployed, short-range sUAS patrols improve defender combat effectiveness. Conversely, when more UAVs are deployed, long-range sUAS patrols improve the defenders' ability to target attacking units with indirect fires, increasing the firepower concentrated against opponents. The analysis also shows that increasing the number of deployed UAVs improves the likelihood of defending warfighters surviving the engagement and the defenders' ability to detect and engage the attackers with indirect fires. Finally, the framework shows that sUAS can force alterations in attacker behavior, removing them from combat by non-violent, but highly effective, means.

No description available.

A finite element model was developed for a range of human head-sUAS impacts to provide multiple case scenarios of impact severity at two response regions of interest: global and local. The hypothesis was that for certain impact scenarios, local response injuries of the brain (frontal, parietal, occipital, temporal lobes, and cerebellum) have a higher severity level compared to global response injury, the response at the Center of Gravity (CG) of the head. This study is the first one to predict and quantify the influence of impact parameters such as impact velocity, location, offset, and angle of impact to severity of injury. The findings show that an sUAS has the potential of causing minimal harm under certain impact scenarios, while other scenarios cause fatal injuries. Additionally, results indicate that the human head’s global response as a less viable response region of interest when measuring injury severity for clinical diagnosis. It is hoped that the results from this research can be useful to assist decision making for treatments and may offer different perspectives in sUAS designs or operation environments.

Modern prosumer small unmanned aircraft systems (sUAS) have eliminated many historical barriers to aerial remote sensing and photogrammetric survey data generation. The relatively low cost and operational ease of these platforms has driven their adoption for numerous geospatial applications including professional surveying and mapping. However, significant debate exists among geospatial professionals and academics regarding prosumer sUAS ability to achieve “survey-grade” geospatial accuracy ≤ 0.164 ft. in their derivative survey data. To address this debate, a controlled accuracy test experiment was conducted in accordance with federal standards whereby prosumer sUAS geospatial accuracies were reported between 15.367 ft. – 0.09 ft. horizontally and 496.734 ft. – 0.330 ft. vertically at the 95% confidence level. These results suggest prosumer sUAS derived survey data fall short of “survey-grade” accuracy in this experiment. Therefore, traditional surveying instruments and methods should not be relinquished in favor of prosumer sUAS for complex applications requiring “survey-grade” accuracy at this time.

No description available.

To operate, autonomous systems of necessity employ a variety of sensors to perceive their environment. Many small unmanned aerial vehicles (UAV) are unable to carry redundant sensors due to size, weight, and power (SWaP) constraints. Faults in these sensors can cause undesired behavior, including system instability. Thus, detection of faults in these non-redundant sensors is of paramount importance.The problem of detecting sensor faults in non-redundant sensors on board autonomous aircraft is non-trivial. Factors that make development of a solution difficult include both an inability to perfectly characterize systems and sensors as well as the SWaP constraints inherent with small UAV. An additional challenge is the ability of a fault-detection method to strike a balance between false-alarm rate and detection rate.This thesis explores two model-based methods of fault-detection for non-redundant sensors, a Kalman filter based method and a particle filter based method. The Kalman filter based method employs tests of mean and covariance on the normalized innovation sequence to detect faults, while the particle filter based method uses a function of the average particle weights.The Kalman filter based approach was implemented in real time on board an autonomous rotorcraft using an extended Kalman Filter (EKF). Faults tested included varied levels of bias, drift, and increased noise. Metrics included false-alarm rate, detection rate, and delay to detection. The particle filter based approach was implemented on a simulated system. This was then compared with an implementation of the EKF based approach for the same system. The same fault types and metrics were also used for these tests.The EKF based method of fault-detection performed well onboard the autonomous rotorcraft and should be generalizable to other systems for which an EKF or Kalman filter can be implemented. The theory indicates that the particle filter based algorithm should have performed better, though the simulations showed poor detection characteristics in comparison to the Kalman filter based method. Future work should be performed to explore improvements to the particle filter based method.