Navigation, Guidance, Control and Dynamics 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 …

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.

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 …

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 …

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 …

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.

Semantic Segmentation Of Aerial Imagery Using U-Nets, Terence J. Yi

Theses and Dissertations

In situations where global positioning systems are unavailable, alternative methods of localization must be implemented. A potential step to achieving this is semantic segmentation, or the ability for a model to output class labels by pixel. This research aims to utilize datasets of varying spatial resolutions and locations to train a fully convolutional neural network architecture called the U-Net to perform segmentations of aerial images. Variations of the U-Net architecture are implemented and compared to other existing models in order to determine the best in detecting buildings and roads. A final dataset will also be created combining two datasets to …

Improved Ground-Based Monocular Visual Odometry Estimation Using Inertially-Aided Convolutional Neural Networks, Josiah D. Watson

Theses and Dissertations

While Convolutional Neural Networks (CNNs) can estimate frame-to-frame (F2F) motion even with monocular images, additional inputs can improve Visual Odometry (VO) predictions. In this thesis, a FlowNetS-based [1] CNN architecture estimates VO using sequential images from the KITTI Odometry dataset [2]. For each of three output types (full six degrees of freedom (6-DoF), Cartesian translation, and transitional scale), a baseline network with only image pair input is compared with a nearly identical architecture that is also given an additional rotation estimate such as from an Inertial Navigation System (INS). The inertially-aided networks show an order of magnitude improvement over the …

Magslam: Aerial Simultaneous Localization And Mapping Using Earth's Magnetic Anomaly Field, Taylor N. Lee, Aaron J. Canciani

Faculty Publications

Instances of spoofing and jamming of global navigation satellite systems (GNSSs) have emphasized the need for alternative navigation methods. Aerial navigation by magnetic map matching has been demonstrated as a viable GNSS‐alternative navigation technique. Flight test demonstrations have achieved accuracies of tens of meters over hour‐long flights, but these flights required accurate magnetic maps which are not always available. Magnetic map availability and resolution vary widely around the globe. Removing the dependency on prior survey maps extends the benefits of aerial magnetic navigation methods to small unmanned aerial systems (sUAS) at lower altitudes where magnetic maps are especially undersampled or …

Magnetic Field Aided Indoor Navigation, William F. Storms

Theses and Dissertations

This research effort examines inertial navigation system aiding using magnetic field intensity data and a Kalman filter in an indoor environment. Many current aiding methods do not work well in an indoor environment, like aiding using the Global Positioning System. The method presented in this research uses magnetic field intensity data from a three-axis magnetometer in order to estimate position using a maximum – likelihood approach. The position measurements are then combined with a motion model using a Kalman filter. The magnetic field navigation algorithm is tested using a combination of simulated and real measurements. These tests are conducted using …

First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman

Faculty Publications

Numerical lifting-line is a computationally efficient method for calculating aerodynamic forces and moments on aircraft. However, its potential has yet to be tapped for use in guidance, navigation, and control (GN&C). Linear covariance analysis is becoming a popular GN&C design tool and shows promise for pairing with numerical lifting-line. Pairing numerical lifting-line with linear covariance analysis allows for forward propagation of state uncertainty for real-time decision making. We demonstrate this for select state variables in a drone aerial recapture situation. Linear covariance analysis uses finite difference derivatives obtained from numerical lifting-line to calculate force and moment variances. These show agreement …

Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman

Faculty Publications

A key enabler of autonomous vehicles is the ability to plan the path of the vehicle to accomplish mission objectives. To be robust to realistic environments, path planners must account for uncertainty in the trajectory of the vehicle as well as uncertainty in the location of obstacles. The uncertainty in the trajectory of the vehicle is a difficult quantity to estimate, and is influenced by coupling between the vehicle dynamics, guidance, navigation, and control system as well as any disturbances acting on the vehicle. Monte Carlo analysis is the conventional approach to determine vehicle dispersion, while accounting for the coupled …

Navigation With Artificial Neural Networks, Joseph A. Curro Ii

Theses and Dissertations

The objective of this dissertation is to explore the applications for Artificial Neural Networks (ANNs) in the field of Navigation. The state of the art for ANNs has improved significantly so now they can rival and even surpass humans in problems once thought impossible. We present different methods to augment, combine, or replace existing Navigation filters with ANN. The main focus of these methods is to use as much existing knowledge as possible then use ANNs to extend the current knowledge base. Next, improvements are made for a class of Artificial Neural Network (ANN)s which provide covariance called Mixture Density …

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 …

Optimal Control Methods For Missile Evasion, Ryan W. Carr

Theses and Dissertations

Optimal control theory is applied to the study of missile evasion, particularly in the case of a single pursuing missile versus a single evading aircraft. It is proposed to divide the evasion problem into two phases, where the primary considerations are energy and maneuverability, respectively. Traditional evasion tactics are well documented for use in the maneuverability phase. To represent the first phase dominated by energy management, the optimal control problem may be posed in two ways, as a fixed final time problem with the objective of maximizing the final distance between the evader and pursuer, and as a free final …

Combined Stereo Vision And Inertial Navigation For Automated Aerial Refueling, Daniel T. Johnson

Theses and Dissertations

This paper describes the design of an EKF to obtain the precise relative position of two aircraft in a refueling maneuver while operating in GPS denied environments. The EKF uses the INS already present in both aircraft as well as the stereo camera system organic to new tanker systems. The aircraft trajectories are generated according to authentic refueling profiles with flight dynamics software and executed in a 3D virtual environment to enable deterministic simulation of the stereo camera system and to demonstrate the effectiveness of the combined system in a refueling scenario. Results show the system can achieve sufficient accuracy …

Small Fixed-Wing Aerial Positioning Using Inter-Vehicle Ranging Combined With Visual Odometry, Benjamin M. Fain

Theses and Dissertations

There has been increasing interest in developing the ability for small unmanned aerial systems (SUAS) to be able to operate in environments where GPS is not available. This research considers the case of a larger aircraft loitering above a smaller GPS-denied SUAS. This larger aircraft is assumed to have greater resources which can overcome the GPS jamming and provide range information to the SUAS flying a mission below. This research demonstrates that using a ranging update combined with an aircraft motion model and visual odometry can greatly improve the accuracy of a SUASs estimated position in a GPS-denied environment.

Optimal Control Of An Uninhabited Loyal Wingman, Clay J. Humphreys

Theses and Dissertations

As researchers strive to achieve autonomy in systems, many believe the goal is not that machines should attain full autonomy, but rather to obtain the right level of autonomy for an appropriate man-machine interaction. A common phrase for this interaction is manned-unmanned teaming (MUM-T), a subset of which, for unmanned aerial vehicles, is the concept of the loyal wingman. This work demonstrates the use of optimal control and stochastic estimation techniques as an autonomous near real-time dynamic route planner for the DoD concept of the loyal wingman. First, the optimal control problem is formulated for a static threat environment and …

Improving Real-World Performance Of Vision Aided Navigation In A Flight Environment, Donald T. Venable

Theses and Dissertations

The motivation of this research is to fuse information from an airborne imaging sensor with information extracted from satellite imagery in order to provide accurate position when GPS is unavailable for an extended duration. A corpus of existing geo-referenced satellite imagery is used to create a key point database. A novel algorithm for recovering coarse pose using by comparing key points extracted from the airborne imagery to the reference database is developed. This coarse position is used to bootstrap a local-area geo-registration algorithm, which provides GPS-level position estimates. This research derives optimizations for existing local-area methods for operation in flight …

Visual-Ins Using A Human Operator And Converted Measurements, Turner J. Montgomery

Theses and Dissertations

A method human operated INS aiding is explored in which the pilot identifies and tracks a ground feature of unknown position over a short measurement epoch using an E/O sensor. One then refers to Visual-INS. In contrast to current research trends, a human operator is entrusted with visually tracking the ground feature. In addition, a less conventional measurement linearization technique is applied to generate “converted” measurements. A linear regression algorithm is then applied to the converted measurements providing an estimate of the INS horizontal velocity error and accelerometer biases. At the completion of the measurement epoch, the INS is corrected …

Real-Time Implementation Of Vision-Aided Monocular Navigation For Small Fixed-Wing Unmanned Aerial Systems, Timothy I. Machin

Theses and Dissertations

The goal of this project was to develop and implement algorithms to demonstrate real-time positioning of a UAV using a monocular camera combined with previously collected orthorectified imagery. Unlike previous tests, this project did not utilize a full inertial navigation system (INS) for attitude, but instead had to rely on the attitude obtained by inexpensive commercial off-the-shelf (COTS) autopilots. The system consisted of primarily COTS components and open-source software, and was own over Camp Atterbury, IN for a sequence of flight tests in Fall 2015. The system obtained valid solutions over much of the flight path, identifying features in the …

Theoretical Limits Of Lunar Vision Aided Navigation With Inertial Navigation System, David W. Jones

Theses and Dissertations

The precision navigation capabilities of the Global Positioning System (GPS) are used extensively within US military operations. However, GPS is highly vulnerable to intentional and unintentional external interference. Therefore, a need exists to develop a non-GPS precision navigation method to operate in GPS degraded environments. This research effort presents the theoretical limits of a precision navigation method based on an inertial navigation system (INS) aided by angle measurements with respect to lunar surface features observed by a fixed camera. To accomplish this task, an extended Kalman filter (EKF) was implemented to estimate INS drift errors and bring in simulated lunar …

Precision Relative Positioning For Automated Aerial Refueling From A Stereo Imaging System, Kyle P. Werner

Theses and Dissertations

The United States Air Force relies upon aerial refueling to fulfill its missions. Unmanned aerial systems (UAS) and remotely piloted aircraft (RPA) do not currently have access to this capability due to the lack of an on-board pilot to safely maintain a refueling position. This research examines stereo vision for precision relative navigation in order to accomplish the Automated Aerial Refueling (AAR) task. Previous work toward an AAR solution has involved the use of Differential Global Positioning (DGPS), Light Detection and Ranging (LiDAR), and monocular vision. This research aims to leverage organic systems in future aircraft to compliment these solutions. …

On The Integration Of Medium Wave Infrared Cameras For Vision-Based Navigation, Justin S. Tharp

Theses and Dissertations

The ubiquitous nature of GPS has fostered its widespread integration of navigation into a variety of applications, both civilian and military. One alternative to ensure continued flight operations in GPS-denied environments is vision-aided navigation, an approach that combines visual cues from a camera with an inertial measurement unit (IMU) to estimate the navigation states of a moving body. The majority of vision-based navigation research has been conducted in the electro-optical (EO) spectrum, which experiences limited operation in certain environments. The aim of this work is to explore how such approaches extend to infrared imaging sensors. In particular, it examines the …