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Articles 1 - 17 of 17
Full-Text Articles in Signal Processing
Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung
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 …
Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli
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 …
Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky
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.
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
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 …
One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data For Spatially Separable Objects, Marc R. Brown
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.
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 …
Mismatched Filter Effects On Synthetic Aperture Radar Image Quality Metrics, Jerrod M. Kempf
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 …
Wideband Metasurface Antenna, Thomas A. Lepley
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 …
Extracting Range Data From Images Using Focus Error, Erik M. Madden
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 …
A Comparative Evaluation Of The Detection And Tracking Capability Between Novel Event-Based And Conventional Frame-Based Sensors, James P. Boettiger
A Comparative Evaluation Of The Detection And Tracking Capability Between Novel Event-Based And Conventional Frame-Based Sensors, James P. Boettiger
Theses and Dissertations
Traditional frame-based technology continues to suffer from motion blur, low dynamic range, speed limitations and high data storage requirements. Event-based sensors offer a potential solution to these challenges. This research centers around a comparative assessment of frame and event-based object detection and tracking. A basic frame-based algorithm is used to compare against two different event-based algorithms. First event-based pseudo-frames were parsed through standard frame-based algorithms and secondly, target tracks were constructed directly from filtered events. The findings show there is significant value in pursuing the technology further.
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. …
Simulation Of Sporadic-E Parameters Using Phase Screen Method, Daniel W. Stambovsky
Simulation Of Sporadic-E Parameters Using Phase Screen Method, Daniel W. Stambovsky
Theses and Dissertations
A phase screen simulation experiment is designed and implemented to model radio occultation through sporadic-E ionospheric disturbances between a GPS transmitter operating at the L1 frequency and a second receiving satellite in low earth orbit (LEO). Simulations were made to test the linear relationship between plasma intensity and scintillation S4 index both posited (Arras and Wickert, 2018) and contended (Gooch et al., 2020) in previous literature. Results brought into question both the linear relationship and the use of S4 as a whole and an alternate metric was sought.
Verifying And Improving A Flight Reference System's Performance, Loren E. Myers
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.
Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler
Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler
Theses and Dissertations
Narcotics smuggling across the Caribbean Sea is a growing concern for the United States Coast Guard. One vector for this illicit trafficking is via small aircraft. This thesis proposes a multi-static radar architecture using the Global Positioning System (GPS) constellation as a transmission source to detect these aircraft as they transit a detection fence. The system developed in this thesis relies on the forward-scatter phenomenon in which a radar shadow is cast by a target as it crosses in front of a transmitter, creating a measurable difference in the signal amplitude at the receiver. This thesis first develops a mathematical …
Wireless Sensor Network Optimization For Radio Tomographic Imaging, Grant T. Nafziger
Wireless Sensor Network Optimization For Radio Tomographic Imaging, Grant T. Nafziger
Theses and Dissertations
Radio tomographic imaging (RTI) is a form of device-free, passive localization (DFPL) that uses a wireless sensor network (WSN) typically made up of affordable, low-power transceivers. The intent for RTI is to have the ability to monitor a given area, localizing and tracking obstructions within. The specific advantages rendered by RTI include the ability to provide imaging, localization, and tracking where other well developed methods like optical surveillance fall short. RTI can function through optical obstructions such as smoke and even physical obstructions like walls. This provides a tool that is particularly valuable for tactical operations like emergency response and …
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 …
Object Identification In Radar Imaging Via The Reciprocity Gap Method, Matthew Charnley, Aihua W. Wood
Object Identification In Radar Imaging Via The Reciprocity Gap Method, Matthew Charnley, Aihua W. Wood
Faculty Publications
In this paper, we present an experimental method for locating and identifying objects in radar imaging, specifically problems that could arise in physical situations. The data for the forward problem are generated using a discretization of the Lippmann‐Schwinger equation, and the inverse problem of object location is solved using the reciprocity gap approach to the linear sampling method. The main new development in this paper is an exploration of determining the permittivity of the object from the back‐scattered data, utilizing another discretization of the Lippmann‐Schwinger equation.
Abstract © AGU.