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Full-Text Articles in Physical Sciences and Mathematics
Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor
Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor
Faculty Publications
Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …
Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won
Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won
Faculty Publications
Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …
An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban
An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban
Faculty Publications
Achieving precise 6 degrees of freedom (6D) pose estimation of rigid objects from color images is a critical challenge with wide-ranging applications in robotics and close-contact aircraft operations. This study investigates key techniques in the application of YOLOv5 object detection convolutional neural network (CNN) for 6D pose localization of aircraft using only color imagery. Traditional object detection labeling methods suffer from inaccuracies due to perspective geometry and being limited to visible key points. This research demonstrates that with precise labeling, a CNN can predict object features with near-pixel accuracy, effectively learning the distinct appearance of the object due to perspective …
Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch
Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch
Faculty Publications
Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.
Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Joshua Larson, Clark N. Taylor, Thomas Wischgoll
Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Joshua Larson, Clark N. Taylor, Thomas Wischgoll
Faculty Publications
Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding the nearest neighbor of a point in a reference 3D point set is a common operation in ICP and frequently consumes at least 90% of the computation time. We introduce a novel approach to performing the distance-based nearest neighbor step based on Delaunay triangulation. This greedy algorithm finds the nearest neighbor of a query point by traversing the edges of the Delaunay triangulation created from a reference 3D point set. Our work integrates the Delaunay traversal into the correspondences search of …
Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor
Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor
Faculty Publications
This paper presents a method to estimate the covariances of the inputs in a factor-graph formulation for localization under non-line-of-sight conditions. A general solution based on covariance estimation and M-estimators in linear regression problems, is presented that is shown to give unbiased estimators of multiple variances and are robust against outliers. An iteratively re-weighted least squares algorithm is proposed to jointly compute the proposed variance estimators and the state estimates for the nonlinear factor graph optimization. The efficacy of the method is illustrated in a simulation study using a robot localization problem under various process and measurement models and measurement …
Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel
Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel
Theses and Dissertations
In legacy Global Positioning System (GPS) Satellite Navigation (SatNav) payloads, the architecture does not provide the flexibility to adapt to changing circumstances and environments. GPS SatNav payloads have largely remained unchanged since the system became fully operational in April 1995. Since then, the use of GPS has become ubiquitous in our day-to-day lives. GPS availability is now a basic assumption for distributed infrastructure; it has become inextricably tied to our national power grids, cellular networks, and global financial systems. Emerging advancements of easy to use radio technologies, such as software-defined radios (SDRs), have greatly lowered the difficulty of discovery and …
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Theses and Dissertations
Hyperspectral target detection promises new operational advantages, with increasing instrument spectral resolution and robust material discrimination. Resolving surface materials requires a fast and accurate accounting of atmospheric effects to increase detection accuracy while minimizing false alarms. This dissertation investigates deep learning methods constrained by the processes governing radiative transfer to efficiently perform atmospheric compensation on data collected by long-wave infrared (LWIR) hyperspectral sensors. These compensation methods depend on generative modeling techniques and permutation invariant neural network architectures to predict LWIR spectral radiometric quantities. The compensation algorithms developed in this work were examined from the perspective of target detection performance using …
Cyberspace Odyssey: A Competitive Team-Oriented Serious Game In Computer Networking, Kendra Graham [I], James Anderson [I], Conrad Rife [I], Bryce Heitmeyer [I], Pranav R. Patel [*], Scott L. Nykl, Alan C. Lin, Laurence D. Merkle
Cyberspace Odyssey: A Competitive Team-Oriented Serious Game In Computer Networking, Kendra Graham [I], James Anderson [I], Conrad Rife [I], Bryce Heitmeyer [I], Pranav R. Patel [*], Scott L. Nykl, Alan C. Lin, Laurence D. Merkle
Faculty Publications
Cyber Space Odyssey (CSO) is a novel serious game supporting computer networking education by engaging students in a race to successfully perform various cybersecurity tasks in order to collect clues and solve a puzzle in virtual near-Earth 3D space. Each team interacts with the game server through a dedicated client presenting a multimodal interface, using a game controller for navigation and various desktop computer networking tools of the trade for cybersecurity tasks on the game's physical network. Specifically, teams connect to wireless access points, use packet monitors to intercept network traffic, decrypt and reverse engineer that traffic, craft well-formed and …
Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei
Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei
Theses and Dissertations
Operation of Unmanned Aerial Vehicles (UAV) support many critical missions in the United State Air Force (USAF). Monitoring abnormal behavior is one of many responsibilities of the operator during a mission. Some behaviors are hard to be detect by an operator, especially when flying one or more autonomous vehicles; as such, detections require a high level of attention and focus to flight parameters. In this research, a monitoring system and its algorithm are designed and tested for a target fixed-wing UAV. The Autonomy Monitoring Service (AMS) compares the real vehicle or simulated Vehicle with a similar simulated vehicle using Software …
Event-Based Visual-Inertial Odometry Using Smart Features, Zachary P. Friedel
Event-Based Visual-Inertial Odometry Using Smart Features, Zachary P. Friedel
Theses and Dissertations
Event-based cameras are a novel type of visual sensor that operate under a unique paradigm, providing asynchronous data on the log-level changes in light intensity for individual pixels. This hardware-level approach to change detection allows these cameras to achieve ultra-wide dynamic range and high temporal resolution. Furthermore, the advent of convolutional neural networks (CNNs) has led to state-of-the-art navigation solutions that now rival or even surpass human engineered algorithms. The advantages offered by event cameras and CNNs make them excellent tools for visual odometry (VO). This document presents the implementation of a CNN trained to detect and describe features within …
Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham
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 …
Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee
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 …
Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki
Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki
Theses and Dissertations
Performing flight tests is a natural part of researching cutting edge sensors and filters for sensor integration. Unfortunately, tests are expensive, and typically take many months of planning. A sensible goal would be to make previously collected data readily available to researchers for future development. The Air Force Institute of Technology (AFIT) has hundreds of data logs potentially available to aid in facilitating further research in the area of navigation. A database would provide a common location where older and newer data sets are available. Such a database must be able to store the sensor data, metadata about the sensors, …
Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev
Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev
Theses and Dissertations
Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. …
Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl
Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl
Theses and Dissertations
The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …
The Impact Of Changing The Size Of Aircraft Radar Displays On Visual Search In The Cockpit, Justin R. Marsh
The Impact Of Changing The Size Of Aircraft Radar Displays On Visual Search In The Cockpit, Justin R. Marsh
Theses and Dissertations
Advances in sensor technology have enabled our fighter aircraft to find, fix, track, target, engage (F2T2E) at greater distances, providing the operator with more data within the battlefield. Modern aircraft are designed with larger displays while our legacy aircraft are being retrofitted with larger cockpit displays to enable display of the increased data. While this modification has been shown to enable improvements in human performance of many cockpit tasks, this effect is often not measured nor fully understood at a more generalizable level. This research outlines an approach to comparing human performance across two display sizes in future F-16 cockpits. …
Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis
Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis
Theses and Dissertations
The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …
Determining Virtual Practicality From Physical Stereo Vision Images And Gps, Bradley S. French
Determining Virtual Practicality From Physical Stereo Vision Images And Gps, Bradley S. French
Theses and Dissertations
Current research efforts for Automated Aerial Refueling (AAR) at The Air Force Institute of Technology (AFIT) utilize Stereo Computer Vision to compute a relative pose between a tanker and receiver aircraft. Due to costs, time, and availability, it can be onerous to test these algorithms using actual Air Force (AF) aircraft. Our solution to this problem consists of using a 3D Graphics Engine to simulate AAR endeavors. However, the question then arises, “Does the virtual world accurately represent the physical world?” This can be explored by comparing a set of truth data to a similar set of virtual data. First, …
Ion Software-Defined Radio Metadata Standard Final Report, Sanjeev Gunawardena, Alexander Rugamer, Muhammad Subhan Hameed, Markel Arizabaleta, Thomas Pany, Javier Arribas
Ion Software-Defined Radio Metadata Standard Final Report, Sanjeev Gunawardena, Alexander Rugamer, Muhammad Subhan Hameed, Markel Arizabaleta, Thomas Pany, Javier Arribas
Faculty Publications
The ION GNSS SDR Metadata Standard describes the formatting and other essential PNT-related parameters of sampled data streams and files. This allows processors to seamlessly consume such data without the need to input these parameters manually. The technical development phase of the initial version of the standard has now been deemed complete and is currently undergoing the last remaining procedural steps towards adoption as a formal standard by the Institute of Navigation. This paper reports on the activities of the working group since September 2018 and summarizes the final products of the standard. It also reports on examples of early …
Improving Optimization Of Convolutional Neural Networks Through Parameter Fine-Tuning, Nicholas C. Becherer, John M. Pecarina, Scott L. Nykl, Kenneth M. Hopkinson
Improving Optimization Of Convolutional Neural Networks Through Parameter Fine-Tuning, Nicholas C. Becherer, John M. Pecarina, Scott L. Nykl, Kenneth M. Hopkinson
Faculty Publications
In recent years, convolutional neural networks have achieved state-of-the-art performance in a number of computer vision problems such as image classification. Prior research has shown that a transfer learning technique known as parameter fine-tuning wherein a network is pre-trained on a different dataset can boost the performance of these networks. However, the topic of identifying the best source dataset and learning strategy for a given target domain is largely unexplored. Thus, this research presents and evaluates various transfer learning methods for fine-grained image classification as well as the effect on ensemble networks. The results clearly demonstrate the effectiveness of parameter …
The Trust-Based Interactive Partially Observable Markov Decision Process, Richard S. Seymour
The Trust-Based Interactive Partially Observable Markov Decision Process, Richard S. Seymour
Theses and Dissertations
Cooperative agent and robot systems are designed so that each is working toward the same common good. The problem is that the software systems are extremely complex and can be subverted by an adversary to either break the system or potentially worse, create sneaky agents who are willing to cooperate when the stakes are low and take selfish, greedy actions when the rewards rise. This research focuses on the ability of a group of agents to reason about the trustworthiness of each other and make decisions about whether to cooperate. A trust-based interactive partially observable Markov decision process (TI-POMDP) is …
Integrity Monitoring For Automated Aerial Refueling: A Stereo Vision Approach, Thomas R. Stuart
Integrity Monitoring For Automated Aerial Refueling: A Stereo Vision Approach, Thomas R. Stuart
Theses and Dissertations
Unmanned aerial vehicles (UAVs) increasingly require the capability to y autonomously in close formation including to facilitate automated aerial refueling (AAR). The availability of relative navigation measurements and navigation integrity are essential to autonomous relative navigation. Due to the potential non-availability of the global positioning system (GPS) during military operations, it is highly desirable that relative navigation can be accomplished without the use of GPS. This paper develops two algorithms designed to provide relative navigation measurements solely from a stereo image pair. These algorithms were developed and analyzed in the context of AAR using a stereo camera system modeling that …
Physical Layer Defenses Against Primary User Emulation Attacks, Joan A. Betances
Physical Layer Defenses Against Primary User Emulation Attacks, Joan A. Betances
Theses and Dissertations
Cognitive Radio (CR) is a promising technology that works by detecting unused parts of the spectrum and automatically reconfiguring the communication system's parameters in order to operate in the available communication channels while minimizing interference. CR enables efficient use of the Radio Frequency (RF) spectrum by generating waveforms that can coexist with existing users in licensed spectrum bands. Spectrum sensing is one of the most important components of CR systems because it provides awareness of its operating environment, as well as detecting the presence of primary (licensed) users of the spectrum.
Understanding Effects Of Autonomous Agent Timing On Human-Agent Teams Using Iterative Modeling, Simulation And Human-In-The-Loop Experimentation, Tyler J. Goodman
Understanding Effects Of Autonomous Agent Timing On Human-Agent Teams Using Iterative Modeling, Simulation And Human-In-The-Loop Experimentation, Tyler J. Goodman
Theses and Dissertations
Recent U.S. Air Force Research Laboratory strategy documents have suggested the need for research in human-agent teaming. Teaming supports a dynamic shift in roles between the human and the agent, depending upon human performance and mission needs. Further, because the performance of these agents will be highly dependent upon the state of the human and the mission, this strategy suggests the need for increased use of modeling to provide a broader understanding of the automated agent’s behavior. This thesis applies a combination of static modeling in SysML activity diagrams, dynamic modeling of human and agent behavior in IMPRINT, and human …
Adaptive Automation Design And Implementation, Jason M. Bindewald
Adaptive Automation Design And Implementation, Jason M. Bindewald
Theses and Dissertations
Automations allow us to reduce the need for humans in certain environments, such as auto-pilot features on unmanned aerial vehicles. However, some situations still require human intervention. Adaptive automation is a research field that enables computer systems to adjust the amount of automation by taking over tasks from or giving tasks back to the user. This research develops processes and insights for adaptive automation designers to take theoretical adaptive automation ideas and develop them into real-world adaptive automation system. These allow developers to design better automation systems that recognize the limits of computers systems, enabling better designs for systems in …
Distributed Kernelized Locality-Sensitive Hashing For Faster Image Based Navigation, Scott A. Hutchison
Distributed Kernelized Locality-Sensitive Hashing For Faster Image Based Navigation, Scott A. Hutchison
Theses and Dissertations
Content based image retrieval (CBIR) remains one of the most heavily researched areas in computer vision. Different image retrieval techniques and algorithms have been implemented and used in localization research, object recognition applications, and commercially by companies such as Facebook, Google, and Yahoo!. Current methods for image retrieval become problematic when implemented on image datasets that can easily reach billions of images. In order to process extremely large datasets, the computation must be distributed across a cluster of machines using software such as Apache Hadoop. There are many different algorithms for conducting content based image retrieval, but this research focuses …
The Dynamic Multi-Objective Multi-Vehicle Covering Tour Problem, Joshua S. Ziegler
The Dynamic Multi-Objective Multi-Vehicle Covering Tour Problem, Joshua S. Ziegler
Theses and Dissertations
This work introduces a new routing problem called the Dynamic Multi-Objective Multi-vehicle Covering Tour Problem (DMOMCTP). The DMOMCTPs is a combinatorial optimization problem that represents the problem of routing multiple vehicles to survey an area in which unpredictable target nodes may appear during execution. The formulation includes multiple objectives that include minimizing the cost of the combined tour cost, minimizing the longest tour cost, minimizing the distance to nodes to be covered and maximizing the distance to hazardous nodes. This study adapts several existing algorithms to the problem with several operator and solution encoding variations. The efficacy of this set …
Mobile Network Defense Interface For Cyber Defense And Situational Awareness, James C. Hannan
Mobile Network Defense Interface For Cyber Defense And Situational Awareness, James C. Hannan
Theses and Dissertations
Today's computer networks are under constant attack. In order to deal with this constant threat, network administrators rely on intrusion detection and prevention services (IDS) (IPS). Most IDS and IPS implement static rule sets to automatically alert administrators and resolve intrusions. Network administrators face a difficult challenge, identifying attacks against a vast number of benign network transactions. Also after a threat is identified making even the smallest policy change to the security software potentially has far-reaching and unanticipated consequences. Finally, because the administrator is primarily responding to alerts they may lose situational awareness of the network. During this research a …
Decentralized Riemannian Particle Filtering With Applications To Multi-Agent Localization, Martin J. Eilders
Decentralized Riemannian Particle Filtering With Applications To Multi-Agent Localization, Martin J. Eilders
Theses and Dissertations
The primary focus of this research is to develop consistent nonlinear decentralized particle filtering approaches to the problem of multiple agent localization. A key aspect in our development is the use of Riemannian geometry to exploit the inherently non-Euclidean characteristics that are typical when considering multiple agent localization scenarios. A decentralized formulation is considered due to the practical advantages it provides over centralized fusion architectures. Inspiration is taken from the relatively new field of information geometry and the more established research field of computer vision. Differential geometric tools such as manifolds, geodesics, tangent spaces, exponential, and logarithmic mappings are used …