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Air Force Institute of Technology

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Articles 91 - 120 of 2678

Full-Text Articles in Physical Sciences and Mathematics

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens Mar 2023

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens

Theses and Dissertations

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate …

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Monocular Vision And Machine Learning For Pose Estimation, Quang Ngoc Tran Mar 2023

Monocular Vision And Machine Learning For Pose Estimation, Quang Ngoc Tran

Theses and Dissertations

This thesis introduces a monocular vision-based approach for 6 DoF pose estimation on a known object. The proposed solution is to use a CNN to find known features of an object in an image. These known features, together with their known locations, are used by a PnP algorithm to estimate the pose of the target object with respect to the camera. The primary difficulty with CNN-based methods is needing to generate a large amount of training data to effectively create the CNN. To overcome this difficulty, a 3D model of the real-world object is created and used in a visualization …

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Effectiveness Of A Timing Side Channel For Deriving Neural Network Depth, Matthew P. Weeks Mar 2023

Effectiveness Of A Timing Side Channel For Deriving Neural Network Depth, Matthew P. Weeks

Theses and Dissertations

From facial recognition on cell phones to vehicle traffic modeling for city planning, integrating ML models can be an expensive investment in resources. Protecting that investment is difficult, as information about the model and how it was built can be leaked through multiple channels, such as timing and memory access. In this thesis, one method of extracting data through a timing side-channel is examined across multiple hardware and software configurations to determine its reliability for general use. While attempting to determine the layer count of a target model solely from its inference time, the research determined that it is not …

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Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler Mar 2023

Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler

Theses and Dissertations

Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.

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Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino Mar 2023

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino

Theses and Dissertations

Generative Adversarial Networks (GANs) have received increasing attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. While this research has yielded GAN variants robust to training set shrinkage and corruption, our research focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to determine empirically the effects of 10 fundamental …

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Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston Mar 2023

Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston

Theses and Dissertations

Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …

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Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian Mar 2023

Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian

Theses and Dissertations

Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …

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Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia Mar 2023

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.

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Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid Mar 2023

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

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Analysis And Optimization Of Contract Data Schema, Franklin Sun Mar 2023

Analysis And Optimization Of Contract Data Schema, Franklin Sun

Theses and Dissertations

agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …

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Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore Mar 2023

Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore

Theses and Dissertations

As the threat of near-peer adversaries has increased, the DoD has increased its emphasis on Joint All-Domain Operations (JADO). This emphasis on JADO highlights the need for hands-on training that can engage military members at all levels. The serious game Battlespace Next (BSN) was designed to teach high-level JADO concepts by modeling real-world military assets in the context of a strategic card game. To keep pace with the evolving landscape of warfare as well as fit the needs of a variety of Department of Defense (DoD) communities, this research introduces the Battlespace Next Education Framework (BSNEF). The BSNEF allows JADO …

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A Method For Monte Carlo Neutral Particle Radiation Transport In A Variable Density Atmosphere, Aidan B. Edens Mar 2023

A Method For Monte Carlo Neutral Particle Radiation Transport In A Variable Density Atmosphere, Aidan B. Edens

Theses and Dissertations

This study focuses on accurately simulating the transport of radiation in the atmosphere to better understand the effects of nuclear weapons. The variable nature of the atmosphere poses a challenge in accurately simulating the prompt radiation following a nuclear explosion. To address this challenge, the Mass Integral Scaling technique is integrated with the Monte Carlo method to perform calculations in a variable density atmosphere. In addition to previous free-field estimates, this work also enables the simulation of transport calculations with other media, such as clouds. Results of neutron and photon fluence have been verified against the standard version of MCNP …

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Coupling To Quantum Topological Order In Superconducting Qubit Systems, Seth T. Hyra Mar 2023

Coupling To Quantum Topological Order In Superconducting Qubit Systems, Seth T. Hyra

Theses and Dissertations

The coupling of superconducting qubits to non-trivial topological phases offers a means of improving existing quantum computational capabilities in lieu of a fully realized topological quantum computer. I will show that although such systems do not completely avoid the necessary errors associated with an energetic qubit basis, they do provide a potential avenue for decoherence free quantum memory. Further, the physics behind such systems enables exploration of the nature of non-Abelian anyons, as well as the remaining challenges in realization of true topological quantum computation.

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Towards An Understanding Of The Thermodynamic Properties Of Crtao4: A Computational Perspective, Tanner B. Gordon Mar 2023

Towards An Understanding Of The Thermodynamic Properties Of Crtao4: A Computational Perspective, Tanner B. Gordon

Theses and Dissertations

Materials that can withstand higher temperatures are paramount for next-generation aircraft design. Hypersonic capabilities and jet-turbine engines operate in extreme environments. Choosing materials that have high thermal stability and oxidation resistance for these applications can increase engine efficiency, reduce size, weight and power (SWaP), and increase the maneuverability of the aircraft. The mixed oxide CrTaO4 has been experimentally observed to significantly contribute to oxidation resistance at high temperatures. However, and despite its significance, its properties remain largely unknown. This work explores the thermal properties of this material from a multi-scale approach, by obtaining an accurate description of the thermodynamics …

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Characterizing Gesn Alloys By Sem/Eds And Photoluminescence Spectroscopy, Christopher M. Sutphin Mar 2023

Characterizing Gesn Alloys By Sem/Eds And Photoluminescence Spectroscopy, Christopher M. Sutphin

Theses and Dissertations

Germanium tin (GeSn) alloys are being studied as potential transition metal (Group IV) photoelectric semiconductors or optical detectors. GeSn alloys could be employed as an optically active material within a computer. Compared to current technologies, a direct band gap GeSn alloy can be engineered to operate with higher thermal stability and efficiency. The GeSn alloy studied was composed of Ge and Si substrates with various Sn percentages grown using remote plasma-enhanced chemical vapor deposition (RPECVD). Photoluminescence spectroscopy (PL) techniques were initially used to determine the GeSn properties, including the band gap. The Ge91.2Sn8.8 PL spectra suggested the …

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Simulation Of Neutron Generation From Laser-Driven Fusion In A Liquid D2o Sheet Using Novel Warpx Module, Colton R. Stoner Mar 2023

Simulation Of Neutron Generation From Laser-Driven Fusion In A Liquid D2o Sheet Using Novel Warpx Module, Colton R. Stoner

Theses and Dissertations

Using WarpX’s new nuclear fusion module, this work attempts to model an experimental system at the ELL at the AFIT with WarpX and draw conclusions about fusion products from resulting simulations. Recently, a table-top, high repetition rate, mixed radiation source was demonstrated at the ELL employing a HIL to fuse the deuterium nuclei present in a unique liquid target of heavy water. Analysis of the simulations predicted an isotropic output of neutrons from deuterium-deuterium fusion. These simulated neutrons were created in tens of femtoseconds from dense bodies of deuterons that were perturbed by the laser. However, it was found that …

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A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor Mar 2023

A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor

Theses and Dissertations

A one-versus-one air combat maneuvering problem is considered wherein a friendly autonomous aircraft must engage and defeat an adversary autonomous aircraft in a beyond visual range environment. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) is leveraged to model the complex and interdependent operations of aircraft, sensors, and weapons utilized in beyond visual range air combat. We formulate a Markov decision process to obtain high-quality decision policies wherein our autonomous aircraft makes maneuvering and missile firing decisions. We utilize a reinforcement learning solution procedure that implements a linear value function approximation to represent state-decision pairs due to the high …

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Net Zero Water Air Force Installations, Kenneth R. Mcknight Mar 2023

Net Zero Water Air Force Installations, Kenneth R. Mcknight

Theses and Dissertations

The United States continues to face problems of a reduction in quality and quantity of groundwater sources because water extraction exceeds natural source recharge. The Air Force has recognized the importance of these groundwater sources but has put minimal effort into determining their contribution to the depletion of these sources. The purpose of this study is to determine this contribution by determining whether Air Force installations are net zero water. This is done using a geospatial information system to determine the volume of water recharging groundwater sources associated with an Air Force installation. This volume is then compared to the …

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Validation Of Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Density, Dylan J. Shaver Mar 2023

Validation Of Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Density, Dylan J. Shaver

Theses and Dissertations

An in-depth validation of a new bottom-up approach using GNSS Radio Occultation (GNSS-RO) data to generate electron density profiles in the D- and E-region ionosphere. This comparison was completed using daytime ionosonde profiles when sporadic-E (Es) was not present, and corresponding FIRI profiles. The average GNSS-RO profile is a few kilometers higher in altitude than the ionosonde profiles at the minimum frequency, f min. When the ionosonde profiles are shifted so that the altitudes match at f min, they are in good agreement up to the E-region peak altitude, hmE. Below f min, the …

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Assessment Of Gnss Radio Occultation Data Assimilation In Numerical Weather Prediction Wind Forecasts, Gregory A. Egger Mar 2023

Assessment Of Gnss Radio Occultation Data Assimilation In Numerical Weather Prediction Wind Forecasts, Gregory A. Egger

Theses and Dissertations

A crucial component of weather forecasting in numerical weather prediction (NWP) is the analysis of the initial state of the atmosphere. Inaccurate analysis of the environment can lead to amplifying errors in the forecast which can cause devastating effects to the population and its resources. In this study, a weather model simulation was performed over the Pacific Northwest to evaluate wind speed forecast performance by assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) data. Two separate events were examined: 24 - 26 October 2021 during which a strong extratropical cyclone struck the area, and 7 - 9 November 2021 …

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Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick Mar 2023

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick

Theses and Dissertations

This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …

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Distributed Reconnaissance Deception Using Software-Defined Networking In A Dynamic Network Environment, Richard Hunter Feustel Mar 2023

Distributed Reconnaissance Deception Using Software-Defined Networking In A Dynamic Network Environment, Richard Hunter Feustel

Theses and Dissertations

This research outlines the design and implementation of a DRDS, which is a RDS distributed across multiple controllers that is capable of deploying reconnaissance deception across multiple switches to mitigate network enumeration by a compromised host. This research outlines the design and development of the DRDS as well as tests its functional abilities and routing performance when compared to a two other network routing solutions: a legacy network solution and centralized ONOS controller scheme deploying layer 2 forwarding. The functional tests proved the system can properly route traffic across 100% of the tested scenarios carrying traffic that includes IP, ARP, …

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Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas Tian Sheng Goo Mar 2023

Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas Tian Sheng Goo

Theses and Dissertations

While more attention is generally focused on software security, computer hardware security remains an important effort. Should an attacker gain direct physical access, computers with little to no hardware security can quickly be compromised via a manner of methods. One such attacker method is to steal information directly from the active memory of a locked, powered-on computer. To counter this attack, a hardware security method was developed called memory encryption. Memory encryption, as the name suggests, protects against adversary methods like cold boot attacks by encrypting all of memory. This research evaluates the efficacy and performance specifically of Intel TME. …

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Characterizing Location-Based Electromagnetic Leakage Of Computing Devices Using Convolutional Neural Networks To Increase The Effectiveness Of Side-Channel Analysis Attacks, Ian C. Heffron Mar 2023

Characterizing Location-Based Electromagnetic Leakage Of Computing Devices Using Convolutional Neural Networks To Increase The Effectiveness Of Side-Channel Analysis Attacks, Ian C. Heffron

Theses and Dissertations

SCA attacks aim to recover some sort of secret information, often in the form of a cipher key, from a target device. Some of these attacks focus on either power-based leakage, or EM-based leakage. Neural networks have recently gained in popularity as tools in SCA attacks. Near-field EM probes with high-spatial resolution enable attackers to isolate physical locations above a processor. This enables attackers to exploit the spatial dependencies of algorithms running on said processor. These spatial dependencies result in different physical locations above a chip emanating different signal strengths. The strengths of different locations can be mapped using the …

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Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash Mar 2023

Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash

Theses and Dissertations

Research towards improving the performance of artificial intelligence networks has found that larger and more complex networks tends to yield better results, and continuous hardware upgrades enables the development of larger, more complicated, and better performing neural networks. However, many devices that are widely available and more practical to everyday use, such as drones or smartphones, are unable to use the state-of-the-art neural networks because they simply do not have the processing capabilities to run them in addition to their normal function. It is possible to overcome this lower performance by using a variety of these smaller neural networks as …

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Spectral Material Classification Of Orbital Objects - Applying Machine Learning To Visible And Near-Infrared Spectral Scenes, Stephen M. Stumpf Mar 2023

Spectral Material Classification Of Orbital Objects - Applying Machine Learning To Visible And Near-Infrared Spectral Scenes, Stephen M. Stumpf

Theses and Dissertations

MSI and HSI techniques allow users to determine the material composition of an object at range. To avoid labor-intensive manual classification, ML is used to determine the most likely material contained in a given pixel of a target image. Previous work primarily focuses on terrestrial applications; this paper extends these techniques into the low-illumination space situational awareness domain, which is of critical importance to national security. HSI datacubes are preprocessed with RL deconvolution as a means of reducing the effects of the optical PSF; then, statistical ML techniques, including k-NN, LDA, QDA, and SVMs are implemented as means of assigning …

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Detection Algorithms And Clutter Metrics Comparison For Long Wave Infrared Point-Source Targets, Rudolf N. Vonniederhausern Mar 2023

Detection Algorithms And Clutter Metrics Comparison For Long Wave Infrared Point-Source Targets, Rudolf N. Vonniederhausern

Theses and Dissertations

In Infrared Search and Track (IRST) systems, clutter in the image hinders target detection especially in point-source target scenarios. Currently there is not a standardized metric for quantifying background clutter. Many clutter metrics have been proposed, but none have demonstrated effectiveness or compatibility for point-source targets. Factors such as environment conditions, detection algorithm, and correlation coefficient to probability of detection (PD) and false alarm (PFA) are the main considerations in determining the effectiveness of clutter metrics. Determining the most successful metric will increase Air Force Test and Evaluation (T&E) units’ capability by providing additional information on test conditions and environments …

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Safe And Reliable Software And The Formal Verification Of Prim's Algorithm In Spark, Brian S. Wheelhouse Mar 2023

Safe And Reliable Software And The Formal Verification Of Prim's Algorithm In Spark, Brian S. Wheelhouse

Theses and Dissertations

Despite evidence that formal verification helps produce highly reliable and secure code, formal methods, i.e., mathematically based tools and approaches for software and hardware verification, are not commonly used in software and hardware development. The limited emphasis on formal verification in software education and training suggests that many developers have never considered the benefits of formal verification. Despite the challenging nature of their mathematical roots, software verification tools have improved; making it easier than ever to verify software. SPARK, a programming language and a formal verification toolset, is of particular interest for the AFRL, and will be a primary focus …

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Strategic Action Execution Through Regret Matching In Press Diplomacy, Leif D. White Mar 2023

Strategic Action Execution Through Regret Matching In Press Diplomacy, Leif D. White

Theses and Dissertations

To take most advantage of collaboration, negotiation is paramount to succeed in press Diplomacy. Humans use this construct to work towards self victory or sometimes towards an alternative strategic objective undefined in the game’s rules. To emulate this behavior, this thesis examines how to use communication to enable the victory or defeat of any other player in the game. This research develops a press Diplomacy agent, Lyre, that can work to attain these specific objectives in Diplomacy through the regret matching algorithm (RM). We also study how Lyre can begin Diplomacy with the goal to win, then shift strategies to …

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Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson Mar 2023

Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson

Theses and Dissertations

The goal of automated aerial refueling (AAR) is to extend the range of unmanned aircraft. Control latency prevents a human from remotely controlling the receiving aircraft as it approaches a tanker. To conform with the size, weight, and power constraints of a small unmanned aircraft, an AAR system must execute in real-time on an embedded platform. This thesis explores the timing and computational performance of a NVIDIA Jetson AGX Orin to a state-of-the-art general-purpose computer using existing AAR algorithms. It also constructs an augmented reality framework as an intermediate step for testing vision-based AAR algorithms between virtual testing and expensive …

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