Engineering Commons^™

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

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

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 …

The Afit Engineer, Volume 5, Issue 4, Graduate School Of Engineering And Management, Air Force Institute Of Technology

AFIT Documents

This issue has a special research feature section by the Autonomy and Navigation Technology Center (ANT) on Demonstration of Alternative Navigation Technologies for Autonomous Aircraft.

Also in this issue:

• ANT Center lowers DOD dependence on GPS
• Record number of female Doctorates awarded at AFIT's Fall Commencement
• D'Azzo Research Library recognized by Library of Congress.
• Hypersonic vehicle flying qualities assessment
• Retirement of Dean Badiru

.... and more.

Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor

Faculty Publications

To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952-2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in a sensor. Recent work has sought to overcome the graphical nature and visual-inspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but …

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl

Faculty Publications

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …

Live-Sky Gnss Signal Processing Using A Dual-Polarized Antenna Array For Multipath Mitigation, Eric Hahn, Sanjeev Gunawardena, Chris Bartone

Faculty Publications

Excerpt: Multipath results from reflections of Global navigation satellite signals (GNSS) signals arriving at a receiver that are delayed with respect to the desired line-of-sight (LOS) signals. The delayed signals distort the received LOS signals, thereby causing pseudorange and carrier phase measurement errors. Traditional multipath mitigation techniques include antenna gain pattern shaping (primarily to reduce ground multipath) and correlator gating techniques (such as narrow correlator and double-delta correlator [1]).

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.

A Comparison Of Correlation-Agnostic Techniques For Magnetic Navigation, Clark N. Taylor, Josh Hiatt

Faculty Publications

Navigation using a Global Navigation Satellite System (GNSS) is common for autonomous vehicles (ground or air). Unfortunately, GNSS-based navigation solutions are often susceptible to jamming, interference, and a limited number of satellites. A proposed technique to aid in navigation when a GNSS-based system fails is magnetic navigation - navigation using the Earth's magnetic anomaly field. This solution comes with its own set of problems including the need for quality magnetic maps in every area in which magnetic navigation will be used. Many of the currently available magnetic maps are generated from a combination of dated magnetic surveys, resulting in maps …

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 …

Ion Gnss Software-Defined Radio Metadata Standard, Sanjeev Gunawardena, Thomas Pany, James Curran

Faculty Publications

The past several years have seen a proliferation of software‐defined radio (SDR) data collection systems and processing platforms designed for or applicable to satellite navigation (satnav) applications. These systems necessarily produce datasets in a wide range of different formats. To correctly interpret this SDR data, essential information such as the packed sample format and sampling rate is needed. Communicating this metadata between creators and users has historically been an ad‐hoc, cumbersome, and error‐prone process. To address this issue, the satnav SDR community developed a metadata standard and normative software library to automate this process, thus simplifying the exchange of datasets …

Resilience For Multi-Filter All-Source Navigation Framework With Integrity, Jonathon S. Gipson, Robert C. Leishman

Faculty Publications

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters, (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.) do not intrinsically meet this requirement.
This paper presents a novel method to monitor real-time overlapping position state observability and introduces an "observability bank" within the ARMAS framework, known as Stable Observability Monitoring (SOM). SOM …

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 …

Operationalized Intent For Improving Coordination In Human-Agent Teams, Michael F. Schneider

Theses and Dissertations

With the increasing capabilities of artificial intelligent agents (AIAs) integrated into multi-agent systems, future concepts include human-agent teams (HATs) in which the members perform fluidly as a coordinated team. Research on coordination mechanisms in HATs is largely focused on AIAs providing information to humans to coordinate better (i.e. coordination from the AIA to the human). We focus on the compliment where AIAs can understand the operator to better synchronize with the operator (i.e. from the human to the AIA). This research focuses specifically on AIA estimation of operator intent. We established the Operationalized Intent framework which captures intent in a …

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

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 …

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 …

Applying Control Abstraction To The Design Of Human–Agent Teams, Clifford D. Johnson, Michael E. Miller, Christina F. Rusnock, David R. Jacques

Faculty Publications

Levels of Automation (LOA) provide a method for describing authority granted to automated system elements to make individual decisions. However, these levels are technology-centric and provide little insight into overall system operation. The current research discusses an alternate classification scheme, referred to as the Level of Human Control Abstraction (LHCA). LHCA is an operator-centric framework that classifies a system’s state based on the required operator inputs. The framework consists of five levels, each requiring less granularity of human control: Direct, Augmented, Parametric, Goal-Oriented, and Mission-Capable. An analysis was conducted of several existing systems. This analysis illustrates the presence of each …

Timely Near-Optimal Path Generation For An Unmanned Aerial System In A Highly Constrained Environment, Kyle J. Matissek

Theses and Dissertations

A current challenge in path planning is the ability to efficiently calculate a near-optimum path solution through a highly-constrained environment in near-real time. In addition, computing performance on a small unmanned aerial vehicle is typically limited due to size and weight restrictions. The proposed method determines a solution quickly by first mapping a highly constrained three-dimensional environment to a two-dimensional weighted node surface in which the weighting accounts for both the terrain gradient and the vehicle's performance. The 2D surface is then discretized into triangles which are sized based upon the vehicle maneuverability and terrain gradient. The shortest feasible path …

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 …

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, …

Flight Characteristic Verification Of The Variable Camber Compliant Wing, Sharee B. Acosta

Theses and Dissertations

Morphing wing technology gives aircraft the ability to change wing shape to control the aircraft and flight performance characteristics. AFIT, AFRL and USU Aero Lab have collaborated to design and test a variable camber compliant wing (VCCW) on a small unmanned aerial vehicle (UAV). Flight tests demonstrated the wing performance and provided data to refine a VCCW flight simulator. Work was completed with the USU AeroLab-generated MachUp and the actual flight data to improve the simulator to provide results close to those of the actual flight test. The research provides a tool to reduce time and cost for future flight …

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, …

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 …

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 …

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. …

Hybrid Tri-Objective Optimization Of F-15 Fleet Modernization Scheduling, Richard S. Danaher

Theses and Dissertations

The F-15 weapons system is vital to the Air Forces efforts to obtain air supremacy during conflict. Originally produced almost 50 years ago, technological advancement through systems modifications is necessary to ensure the Eagles lethality and survivability against next-generation adversarial threats. The F-15 Systems Program Office faces challenges to plan aircraft inductions for five fleet modernization programs. Optimal induction schedules are developed using binary-integer linear programming models. Diverse constraints such as manpower, equipment, modification kit availability, minimum operational flight levels, and integration of scheduled depot maintenance reveal that no feasible schedule exists. Two competing objectives representing the value of fully …

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 …

Trade-Space Analysis Of A Small Unmanned Vehicle System For Radiological Search Missions, Sam B. Harriger

Theses and Dissertations

Nuclear and radiological terrorism is a persistent threat to United States national security. The research and development of new technological capabilities is vital to bolstering emergency response and prevention capabilities in support of national security initiatives. This research characterized the applicable trade-space for a system of unmanned vehicles deployed for search, detection, and identification of radiological source material. Exploration included the development of a CONOPS, a functional decomposition and physical allocation, design considerations, and an analysis of feasibility and utility. The concept system comprises of a ground control station, ground vehicle, hybrid-electric multirotor, and fixed-wing vehicle with an open architecture …

Verifying And Improving A Flight Reference System's Performance, Loren E. Myers

Theses and Dissertations

The 746th Test Squadron (746 TS) at Holloman AFB, NM operates the Ultra High Accuracy Reference System (UHARS) as part of its mission positioning and navigation test. This research presents a method for verifying the performance of a flight reference system using a Delta-Position velocity derived from radio navigation positioning measurements. The algorithm presented may utilize Global Positioning System (GPS) or the Locata ground based positioning system. In the latter case, Locata provides a velocity truth independent from GPS. The accuracy of Locata and GPS are assessed and UHARS velocity measurements are characterized both in nominal and GPS denied applications.