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2020

Air Force Institute of Technology

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Articles 1 - 30 of 55

Full-Text Articles in Electrical and Computer Engineering

Sparse Bases And Bayesian Inference Of Electromagnetic Scattering, John Lee Dec 2020

Sparse Bases And Bayesian Inference Of Electromagnetic Scattering, John Lee

Theses and Dissertations

Many approaches in CEM rely on the decomposition of complex radiation and scattering behavior with a set of basis vectors. Accurate estimation of the quantities of interest can be synthesized through a weighted sum of these vectors. In addition to basis decompositions, sparse signal processing techniques developed in the CS community can be leveraged when only a small subset of the basis vectors are required to sufficiently represent the quantity of interest. We investigate several concepts in which novel bases are applied to common electromagnetic problems and leverage the sparsity property to improve performance and/or reduce computational burden. The first …

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3-D Fabry–Pérot Cavities Sculpted On Fiber Tips Using A Multiphoton Polymerization Process, Jonathan W. Smith, Jeremiah C. Williams, Joseph S. Suelzer, Nicholas G. Usechak, Hengky Chandrahalim Dec 2020

3-D Fabry–Pérot Cavities Sculpted On Fiber Tips Using A Multiphoton Polymerization Process, Jonathan W. Smith, Jeremiah C. Williams, Joseph S. Suelzer, Nicholas G. Usechak, Hengky Chandrahalim

Faculty Publications

This paper presents 3-D Fabry–Pérot (FP) cavities fabricated directly onto cleaved ends of low-loss optical fibers by a two-photon polymerization (2PP) process. This fabrication technique is quick, simple, and inexpensive compared to planar microfabrication processes, which enables rapid prototyping and the ability to adapt to new requirements. These devices also utilize true 3-D design freedom, facilitating the realization of microscale optical elements with challenging geometries. Three different device types were fabricated and evaluated: an unreleased single-cavity device, a released dual-cavity device, and a released hemispherical mirror dual-cavity device. Each iteration improved the quality of the FP cavity's reflection spectrum. The …

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Deep Learning-Based, Passive Fault Tolerant Control Facilitated By A Taxonomy Of Cyber-Attack Effects, Dean C. Wardell Dec 2020

Deep Learning-Based, Passive Fault Tolerant Control Facilitated By A Taxonomy Of Cyber-Attack Effects, Dean C. Wardell

Theses and Dissertations

In the interest of improving the resilience of cyber-physical control systems to better operate in the presence of various cyber-attacks and/or faults, this dissertation presents a novel controller design based on deep-learning networks. This research lays out a controller design that does not rely on fault or cyber-attack detection. Being passive, the controller’s routine operating process is to take in data from the various components of the physical system, holistically assess the state of the physical system using deep-learning networks and decide the subsequent round of commands from the controller. This use of deep-learning methods in passive fault tolerant control …

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Electromagnetic Interference Estimation Via Conditional Neural Processing, Edgar E. Gomez Dec 2020

Electromagnetic Interference Estimation Via Conditional Neural Processing, Edgar E. Gomez

Theses and Dissertations

The goal of this thesis is to determine the efficacy of employing Machine Learning (ML) to solve Joint Urgent Operational Need (JUON) CC-0575, which aims to develop a Common Operating Picture (COP) of the Global Positioning System (GPS) Electromagnetic Interference (EMI) environment. With the growing popularity of Artificial Neural Networks (ANNs), ML solutions are quickly gaining traction in businesses, academia and government. This in turn allows for problem solutions that were previously inconceivable using the classical programming paradigm. This thesis proposes a method to develop a COP of the battlefield via ANN ingestion of multiple-source signals and sensors. We conduct …

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Temporally Multiplexed Ladar Polarimeter, Christian Keyser, Richard Kenneth Martin Oct 2020

Temporally Multiplexed Ladar Polarimeter, Christian Keyser, Richard Kenneth Martin

AFIT Patents

In a polarimeter, a polarization modulator changes a polarization phase of an output optical pulse with a modulation function that varies in time over the duration of the optical pulse. A static polarization state analyzer, which includes a one or more static polarization component analyzers and detectors, receives the modulated optical pulse after interaction with a target medium and provides time varying intensities of the polarization components of the received pulse. A signal processing module determines a polarization property of the target medium, such as a Mueller matrix, dependent upon time varied intensities over the duration of the received optical …

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End-To-End Direct Digital Synthesis Simulation And Mathematical Model To Minimize Quantization Effects Of Digital Signal Generation, Pranav R. Patel, Richard K. Martin Oct 2020

End-To-End Direct Digital Synthesis Simulation And Mathematical Model To Minimize Quantization Effects Of Digital Signal Generation, Pranav R. Patel, Richard K. Martin

Faculty Publications

Direct digital synthesis (DDS) architectures are becoming more prevalent as modern digital-to-analog converter (DAC) and programmable logic devices evolve to support higher bandwidths. The DDS architecture provides the benefit of digital control but at a cost of generating spurious content in the spectrum. The generated spurious content may cause intermodulation distortion preventing proper demodulation of the received signal. The distortion may also interfere with the neighboring frequency bands. This article presents the various DDS architectures and explores the DDS architecture which provides the most digital reconfigurability with the lowest spurious content. End-to-end analytical equations, numerical and mathematical models are developed …

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Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit Sep 2020

Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit

Faculty Publications

The United States Air Force has implemented a dispersed air base strategy to enhance mission effectiveness for near-peer conflicts. Asset dispersal places many smaller bases across a wide geographic area, which increases resupply requirements and logistical complexity. Hybrid energy systems reduce resupply requirements through sustainable, off-grid energy production. This paper presents a novel hybrid energy renewable delivery system (HERDS) model capable of (1) selecting the optimal hybrid energy system design that meets demand at the lowest net present cost and (2) optimizing the delivery of the selected system using existing Air Force cargo aircraft. The novelty of the model’s capabilities …

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Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung Sep 2020

Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung

Theses and Dissertations

This dissertation focuses on improving the ability to detect dim stellar objects that are in close proximity to a bright one, through statistical image processing using short exposure images. The goal is to improve the space domain awareness capabilities with the existing infrastructure. Two new algorithms are developed. The first one is through the Neighborhood System Blind Deconvolution where the data functions are separated into the bright object, the neighborhood system, and the background functions. The second one is through the Dimension Reduction Blind Deconvolution, where the object function is represented by the product of two matrices. Both are designed …

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Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli Aug 2020

Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli

Faculty Publications

The spectral method is typically applied as a simple and efficient method to solve the parabolic wave equation in phase screen scintillation models. The critical factors that can greatly affect the spectral method accuracy is the uniformity and smoothness of the input function. This paper observes these effects on the accuracy of the finite difference and the spectral methods applied to a wideband SATCOM signal propagation model simulated in the ultra-high frequency (UHF) band. The finite difference method uses local pointwise approximations to calculate a derivative. The spectral method uses global trigonometric interpolants that achieve remarkable accuracy for continuously differentiable …

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Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky Jun 2020

Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky

AFIT Patents

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

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Statistical Photo-Calibration Of Photo-Detectors For Radiometry Without Calibrated Light Sources Comprising An Arithmetic Unit To Determine A Gain And A Bias From Mean Values And Variance Values, Adrian M. Catarius, Nicholas Yielding, Stephen C. Cain, Michael D. Seal Jun 2020

Statistical Photo-Calibration Of Photo-Detectors For Radiometry Without Calibrated Light Sources Comprising An Arithmetic Unit To Determine A Gain And A Bias From Mean Values And Variance Values, Adrian M. Catarius, Nicholas Yielding, Stephen C. Cain, Michael D. Seal

AFIT Patents

Calibration of a radiometry system uses a readout circuit of a photo-detector to provide first and second measurements collected over first and second integration times, respectively, where the first and second measurements are related to a photonic input to the photo-detector by a gain and a bias. First mean and variance values are computed for a plurality of first measurements. Second mean and variance values are computed for a plurality of second measurements. The gain and bias are determined from the first and second mean values and the first and second variance values without the use of a calibrated source. …

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Nondestructive Electromagnetic Characterization Of Uniaxial Sheet Media Using A Two-Flanged Rectangular Waveguide Probe, Neil G. Rogers, Michael J. Havrilla, Milo W. Hyde Iv, Alexander G. Knisely Jun 2020

Nondestructive Electromagnetic Characterization Of Uniaxial Sheet Media Using A Two-Flanged Rectangular Waveguide Probe, Neil G. Rogers, Michael J. Havrilla, Milo W. Hyde Iv, Alexander G. Knisely

Faculty Publications

Excerpt: Recent advancements in fabrication capabilities have renewed interest in the electromagnetic characterization of complex media, as many metamaterials are anisotropic and/or inhomogeneous. Additionally, for composite materials, anisotropy can be introduced by load, strain, misalignment, or damage through the manufacturing process [1], [2]. Methods for obtaining the constitutive parameters for isotropic materials are well understood and widely employed [3]–[8]. Therefore, it is crucial to develop a practical method for the electromagnetic characterization of anisotropic materials.

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Securing Photovoltaic (Pv) System Deployments With Data Diodes, Robert D. Larkin, Torrey J. Wagner, Barry E. Mullins Jun 2020

Securing Photovoltaic (Pv) System Deployments With Data Diodes, Robert D. Larkin, Torrey J. Wagner, Barry E. Mullins

Faculty Publications

A survey of a typical photovoltaic (PV) system with and without the cybersecurity protections of a data diode is explored. This survey includes a brief overview of Industrial Control Systems (ICS) and their relationship to the Internet of Things (IoT), Industrial Internet of Things (IIoT), and Industry 4.0 terminology. The cybersecurity features of eight data diodes are compared, and the cyber attack surface, attack scenarios, and mitigations of a typical PV system are discussed. After assessing cybersecurity, the economic considerations to purchase a data diode are considered. At 13.19 cents/kWh, the sale of 227,445 kWh is needed to fund one …

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Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery Jun 2020

Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery

Theses and Dissertations

This thesis takes the Scotland Yard board game and modifies its rules to mimic important aspects of space in order to facilitate the creation of artificial intelligence for space asset pursuit/evasion scenarios. Space has become a physical warfighting domain. To combat threats, an understanding of the tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence and machine learning models can use simulations to develop proper defensive and offensive tactics, techniques, and procedures capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based …

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A Multi-Criteria Logistics Analysis Of Photovoltaic Modules For Remote Applications, Nathan Thomsen [*], Dimitri Papazoglou, Torrey J. Wagner, Andrew J. Hoisington, Steven J. Schuldt Jun 2020

A Multi-Criteria Logistics Analysis Of Photovoltaic Modules For Remote Applications, Nathan Thomsen [*], Dimitri Papazoglou, Torrey J. Wagner, Andrew J. Hoisington, Steven J. Schuldt

Faculty Publications

Reliable electrical power grids are frequently unavailable or inaccessible in remote locations, including developing nation communities, humanitarian relief camps, isolated construction sites, and military contingency bases. This often requires sites to rely on costly generators and continuous fuel supply. Renewable energy systems (RES) in the form of photovoltaic (PV) arrays and energy storage present a rapidly improving alternative to power these remote locations. Previous RES literature and PV optimization models focused on economics, reliability, and environmental concerns, neglecting the importance of logistics factors in remote installations. This paper proposes additional optimization variables applicable to remote PV systems and compares PV …

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Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan May 2020

Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan

Faculty Publications

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …

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Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola Apr 2020

Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola

Faculty Publications

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …

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Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides Apr 2020

Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides

Faculty Publications

We present a novel light detection and ranging (LiDAR) polarimeter that enables measurement of 12 of 16 sample Mueller matrix elements in a single, 10 ns pulse. The new polarization state generator (PSG) leverages Kerr phase modulation in a birefringent optical fiber, creating a probe pulse characterized by temporally varying polarization. Theoretical expressions for the Polarization State Generator (PSG) Stokes vector are derived for birefringent walk-off and no walk-off and incorporated into a time-dependent polarimeter signal model employing multiple polarization state analyzers (PSA). Polarimeter modeling compares the Kerr effect and electro-optic phase modulator–based PSG using a single Polarization State Analyzer …

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One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data For Spatially Separable Objects, Marc R. Brown Mar 2020

One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data For Spatially Separable Objects, Marc R. Brown

Theses and Dissertations

Blind deconvolution is used to complete missions to detect adversary assets in space and to defend the nation's assets. A new algorithm was developed to perform blind deconvolution for objects that are spatially separable using multiple frames of data. This new one-dimensional approach uses the expectation-maximization algorithm to blindly deconvolve spatially separable objects. This object separation reduces the size of the object matrix from an NxN matrix to two singular vectors of length N. With limited knowledge of the object and point spread function the one-dimensional algorithm successfully deconvolved the objects in both simulated and laboratory data.

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Characterization And Sensitivity Analysis Of 6 Meter Cassegrain Antenna, James L. Harris Mar 2020

Characterization And Sensitivity Analysis Of 6 Meter Cassegrain Antenna, James L. Harris

Theses and Dissertations

This paper will characterize a 6 meter in diameter cassegrain antenna. The cassegrain antenna is a special form of a dual reflector antenna which uses a main reflector following a parabolic curve and a sub reflector which follows a hyperbolic curve. Cassegrain style antennas have multiple parameters which can be tuned to achieve specific design goals. Performing a sensitivity analysis will establish relationships between design parameters, directivity, side lobe levels, and effects of strut geometry. The initial design parameters will be assumed based on typical values. Results from the sensitivity analysis will be used to provide a performance band for …

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Characterization Of Reactive Ion Etch Chemistries Using Direct Write Lithography, Dylan T. Martin-Abood Mar 2020

Characterization Of Reactive Ion Etch Chemistries Using Direct Write Lithography, Dylan T. Martin-Abood

Theses and Dissertations

The DoD requires a variety of COTS and number of custom microelectronics to provide important functionality to critical military systems. Photolithography and DRIE are two techniques commonly used in the development of deep anisotropic features for the fabrication and modification of microelectronics and MEMS. However, standard photolithography techniques are ineffective for unique substrate geometries and DRIE processes require a chemical passivation step only applicable to Si substrates. This work confirmed the capability of RIE using DWL to perform deep, highly selective, anisotropic etching on elevated, non-circular substrates.

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A Non-Destructive Evaluation Application Using Software Defined Radios And Bandwidth Expansion, Nicholas J. O'Brien Mar 2020

A Non-Destructive Evaluation Application Using Software Defined Radios And Bandwidth Expansion, Nicholas J. O'Brien

Theses and Dissertations

The development of low-complexity, lightweight and low-cost Non-Destructive Evaluation (NDE) equipment for microwave device testing is desirable from a maintenance efficiency and operational availability perspective. Current NDE equipment tends to be custom-designed, cumbersome and expensive. Software Defined Radio (SDR) technology, and a bandwidth expansion technique that exploits a priori transmit signal knowledge and auto-correlation provides a solution. This research investigated the reconstruction of simultaneous SDR receiver instantaneous bandwidth (sub-band) collections using single, dual and multiple SDR receivers. The adjacent sub-bands, collectively spanning a transmit signal bandwidth were auto-correlated with a replica transmit signal to restore frequency and phase offsets. The …

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Signal Quality Monitoring Of Gnss Signals Using A Chip Shape Deformation Metric, Nicholas C. Echeverry Mar 2020

Signal Quality Monitoring Of Gnss Signals Using A Chip Shape Deformation Metric, Nicholas C. Echeverry

Theses and Dissertations

The Global Navigation Satellite System continues to become deeply em-bedded within modern civilization, and is depended on for confident, accurate navigation information. High precision position and timing accuracy is typically achieved using differential processing, however these systems provide limited compensation for distortions caused by multi-path or faulty satellite hardware. Signal Quality Monitoring (SQM) aims to provide confidence in a receivers Position, Navigation, and Timing solution and to offer timely warnings in the event that signal conditions degrade to unsafe levels. The methods presented in this document focus on implementing effective SQM using low-cost Commercial Off-the-Shelf equipment, a Software Defined Radio, …

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Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee Mar 2020

Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee

Theses and Dissertations

Remotely piloted aircraft (RPAs) cannot currently refuel during flight because the latency between the pilot and the aircraft is too great to safely perform aerial refueling maneuvers. However, an AAR system removes this limitation by allowing the tanker to directly control the RP A. The tanker quickly finding the relative position and orientation (pose) of the approaching aircraft is the first step to create an AAR system. Previous work at AFIT demonstrates that stereo camera systems provide robust pose estimation capability. This thesis first extends that work by examining the effects of the cameras' resolution on the quality of pose …

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Dynamic Micromechanical Fabry-Perot Cavity Sensors Fabricated By Multiphoton Absorption Onto Optical Fiber Tips, Jeremiah C. Williams Mar 2020

Dynamic Micromechanical Fabry-Perot Cavity Sensors Fabricated By Multiphoton Absorption Onto Optical Fiber Tips, Jeremiah C. Williams

Theses and Dissertations

This research leveraged two-photon polymerization microfabrication to integrate dynamic mechanical components with Fabry-Perot resonators onto the ends of low-loss optical fibers to prototype 3 micro-optic devices. The first device featured a multi-positional mirror that enabled thin-film deposition onto cavities of any length with mirrors of significant curvature, for refractive index sensing. The second device combined an FP cavity with a spring body featuring easily scalable stiffness for pressure sensing. The third device presented a high-speed rotating micro-anemometer for measuring a wide range of gas flows. All devices represent a significant reduction in size and weight over commercially available devices.

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Mismatched Filter Effects On Synthetic Aperture Radar Image Quality Metrics, Jerrod M. Kempf Mar 2020

Mismatched Filter Effects On Synthetic Aperture Radar Image Quality Metrics, Jerrod M. Kempf

Theses and Dissertations

Detection of targets across a wide dynamic range is an enduring challenge in radar. This work formulates a modified least-squares mismatched filter that greatly reduces these sidelobes in order to enable the detection of small radar cross section targets in the presence of considerably larger scatterers, increasing the dynamic range. Unlike previous mismatched filters, the proposed filter is applicable to noisy, oversampled signals with no requirements on signal structure. Range profiles and images are presented to demonstrate the superior sidelobe suppression of the modified least-squares mismatched filter in comparison to the commonly employed matched filter. Various weighting vectors are introduced …

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Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham Mar 2020

Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham

Theses and Dissertations

Visual Simultaneous Localization and Mapping (VSLAM) algorithms have evolved rapidly in the last few years, however there has been little research evaluating current algorithm's effectiveness and limitations when applied to tracking the position of a fixed-wing aerial vehicle. This research looks to evaluate current monocular VSLAM algorithms' performance on aerial vehicle datasets using the SLAMBench2 benchmarking suite. The algorithms tested are MonoSLAM, PTAM, OKVIS, LSDSLAM, ORB-SLAM2, and SVO, all of which are built into the SLAMBench2 software. The algorithms' performance is evaluated using simulated datasets generated in the AftrBurner Engine. The datasets were designed to test the quality of each …

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Wideband Metasurface Antenna, Thomas A. Lepley Mar 2020

Wideband Metasurface Antenna, Thomas A. Lepley

Theses and Dissertations

This effort explored design of metasurface antennas and evaluated their suitability for ultra-wideband applications (2 to 18 GHz). Six unit cell types were characterized. Eigenmode simulations produced frequency vs. phase data for the unit cells, from which impedance vs. gap size data was computed. A holographic design equation was used to generate the metasurface antenna designs. The unit cell simulations revealed that the assumption of single mode operation is a constraint for wideband designs. An 8" by 8" metasurface antenna with a Rogers 3010 dielectric and a design frequency of 10 GHz was fabricated and tested. It had a 1.5:1 …

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Extracting Range Data From Images Using Focus Error, Erik M. Madden Mar 2020

Extracting Range Data From Images Using Focus Error, Erik M. Madden

Theses and Dissertations

Air-to-air refueling (AAR) has become a staple when performing long missions with aircraft. With modern technology, however, people have begun to research how to perform this task autonomously. Automated air-to-air refueling (A3R) is this exact concept. Combining many different systems, the idea is to allow computers on the aircraft to link up via the refueling boom, refuel, and detach before resuming pilot control. This document lays out one of the systems that is needed to perform A3R, namely, the system that extracts range data. While stereo cameras perform such tasks, there is interest in finding other ways of accomplishing the …

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Near Real-Time Zigbee Device Discrimination Using Cb-Dna Features, Yousuke Z. Matsui Mar 2020

Near Real-Time Zigbee Device Discrimination Using Cb-Dna Features, Yousuke Z. Matsui

Theses and Dissertations

Currently, Low-Rate Wireless Personal Area Networks (LR-WPAN) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard are at risk due to open-source tools which allow bad actors to exploit unauthorized network access through various cyberattacks by falsifying bit-level credentials. This research investigates implementing a Radio Frequency (RF) air monitor to perform Near RealTime (NRT) discrimination of Zigbee devices using the IEEE 802.15.4 standard. The air monitor employed a Multiple Discriminant Analysis/Euclidean Distance classifier to discriminate Zigbee devices based upon Constellation-Based Distinct Native Attribute (CB-DNA) fingerprints. Through the use of CB-DNA fingerprints, Physical Layer (PHY) characteristics unique to …

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