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Air Force Institute of Technology

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Articles 91 - 120 of 372

Full-Text Articles in Signal Processing

Satellite Communications In The V And W Band: Natural And Artificial Scintillation Effects, David A. Smith Mar 2017

Satellite Communications In The V And W Band: Natural And Artificial Scintillation Effects, David A. Smith

Theses and Dissertations

In a natural atmospheric environment the troposphere will be the primary source of loss with the ionosphere loss being negligible. If the ionosphere was disturbed from a high altitude nuclear explosion (HANE) more than three times the amount of electrons would be present in the ionosphere and could represent a source of significant loss. In order to determine the amount of electrons distributed from a HANE, GSCENARIO, developed by Defense Threat Reduction Agency was used. The two sources of loss that were examined was signal absorption and amplitude scintillation. Signal loss was determined using GSCENARIO and amplitude scintillation loss was …

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Sound Based Positioning, David L. Weathers Mar 2017

Sound Based Positioning, David L. Weathers

Theses and Dissertations

With a growing interest in non-GPS positioning, navigation, and timing (PNT), sound based positioning provides a precise way to locate both sound sources and microphones through audible signals of opportunity (SoOPs). Exploiting SoOPs allows for passive location estimation. But, attributing each signal to a specific source location when signals are simultaneously emitting proves problematic. Using an array of microphones, unique SoOPs are identified and located through steered response beamforming. Sound source signals are then isolated through time-frequency masking to provide clear reference stations by which to estimate the location of a separate microphone through time difference of arrival measurements. Results …

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Physical Layer Defenses Against Primary User Emulation Attacks, Joan A. Betances Sep 2016

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.

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Comparison Of Methods For Radio Position Of Non-Emitting Dismounts, Collin J. Seanor Mar 2016

Comparison Of Methods For Radio Position Of Non-Emitting Dismounts, Collin J. Seanor

Theses and Dissertations

Radio Tomographic Imaging (RTI) is a form of Device Free Passive Localization (DFPL) that utilizes the Received Signal Strength (RSS) values from a collection of wireless transceivers to produce an image in order to localize a subject within a Wireless Sensor Network (WSN). Radio Mapping is another form of DFPL that can utilize the same RSS values from a WSN to localize a subject by comparing recent values to a set of calibration data. RTI and Radio Mapping have never been directly compared to one another as a means of localization within a WSN. The goal of this research is …

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Geosynchronous Binary Object Detection, Patrick B. Cunningham Mar 2016

Geosynchronous Binary Object Detection, Patrick B. Cunningham

Theses and Dissertations

This paper will compare competing methods for optically detecting binary objects. This is mostly intended for use in Space Situational Awareness (SSA), though has the potential to be used in other applications. The first method referred to as, “Single Object Detection” is a versatile algorithm which is currently used to detect extraterrestrial objects. However, it does not take into account interference by a nearby object. Therefore a second algorithm is investigated, referred to as “Binary Object Detection”, which does. The binary detection algorithm proved to have a comparable or superior Receiver Operating Characteristic (ROC) curve (based upon the area under …

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Hardware Development And Error Characterisation For The Afit Rail Sar System, Dayne A. Schmidt Mar 2016

Hardware Development And Error Characterisation For The Afit Rail Sar System, Dayne A. Schmidt

Theses and Dissertations

This research is focussed on updating the Air Force Institute of Technology (AFIT) Radar Instrumentation Lab (RAIL) Synthetic Aperture Radar (SAR) experimental system. Firstly, this research assesses current hardware limitations and updates the system configuration and methodology to enable collections from a receiver in motion. Secondly, orthogonal frequency-division multiplexing (OFDM) signals are used to form (SAR) images in multiple experimental and simulation configurations. This research analyses, characterises and attempts compensation of relevant SAR image error sources, such as Doppler shift or motion measurement errors (MMEs). Error characterisation is conducted using theoretical, simulated and experimental methods. Final experimental results are presented …

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Unequal A Priori Probability Multiple Hypothesis Testing In Space Domain Awareness With The Space Surveillance Telescope, Tyler J. Hardy, Stephen C. Cain, Travis F. Blake Jan 2016

Unequal A Priori Probability Multiple Hypothesis Testing In Space Domain Awareness With The Space Surveillance Telescope, Tyler J. Hardy, Stephen C. Cain, Travis F. Blake

Faculty Publications

This paper investigates the ability to improve Space Domain Awareness (SDA) by increasing the number of detectable Resident Space Objects (RSOs) from space surveillance sensors. With matched filter based techniques, the expected impulse response, or Point Spread Function (PSF), is compared against the received data. In the situation where the images are spatially undersampled, the modeled PSF may not match the received data if the RSO does not fall in the center of the pixel. This aliasing can be accounted for with a Multiple Hypothesis Test (MHT). Previously, proposed MHTs have implemented a test with an equal a priori prior …

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Global Navigation Satellite System Signal Decomposition And Parameterization Algorithm, Marshall E. Haker, John F. Raquet May 2015

Global Navigation Satellite System Signal Decomposition And Parameterization Algorithm, Marshall E. Haker, John F. Raquet

AFIT Patents

A method and apparatus is provided for intra-PIT signal decomposition of a signal received with RF front end hardware. The method begins by aligning a signal received by RF front end hardware into integer multiples of a duration of a pseudorandom noise code sequence. A search grid is computed based on an integer multiple of the aligned signal. A plurality of initial ray parameters associated with the computed search grid is coarsely estimated. Using the coarsely estimated plurality of initial ray parameters, a fine estimation of the plurality of initial ray parameters is initiated utilizing stochastic search and optimization techniques. …

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Estimating Single And Multiple Target Locations Using K-Means Clustering With Radio Tomographic Imaging In Wireless Sensor Networks, Jeffrey K. Nishida Mar 2015

Estimating Single And Multiple Target Locations Using K-Means Clustering With Radio Tomographic Imaging In Wireless Sensor Networks, Jeffrey K. Nishida

Theses and Dissertations

Geolocation involves using data from a sensor network to assess and estimate the location of a moving or stationary target. Received Signal Strength (RSS), Angle of Arrival (AoA), and/or Time Difference of Arrival (TDoA) measurements can be used to estimate target location in sensor networks. Radio Tomographic Imaging (RTI) is an emerging Device-Free Localization (DFL) concept that utilizes the RSS values of a Wireless Sensor Network (WSN) to geolocate stationary or moving target(s). The WSN is set up around the Area of Interest (AoI) and the target of interest, which can be a person or object. The target inside the …

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A Novel Analysis Of Performance Classification And Workload Prediction Using Electroencephalography (Eeg) Frequency Data, Donovan L. Ricks Mar 2015

A Novel Analysis Of Performance Classification And Workload Prediction Using Electroencephalography (Eeg) Frequency Data, Donovan L. Ricks

Theses and Dissertations

Across the DOD each task an operator is presented with has some level of difficulty associated with it. This level of difficulty over the course of the task is also known as workload, where the operator is faced with varying levels of workload as he or she attempts to complete the task. The focus of the research presented in this thesis is to determine if those changes in workload can be predicted and to determine if individuals can be classified based on performance in order to prevent an increase in workload that would cause a decline in performance in a …

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Timing Mark Detection On Nuclear Detonation Video, Daniel T. Schmitt, Gilbert L. Peterson Oct 2014

Timing Mark Detection On Nuclear Detonation Video, Daniel T. Schmitt, Gilbert L. Peterson

Faculty Publications

During the 1950s and 1960s the United States conducted and filmed over 200 atmospheric nuclear tests establishing the foundations of atmospheric nuclear detonation behavior. Each explosion was documented with about 20 videos from three or four points of view. Synthesizing the videos into a 3D video will improve yield estimates and reduce error factors. The videos were captured at a nominal 2500 frames per second, but range from 2300-3100 frames per second during operation. In order to combine them into one 3D video, individual video frames need to be correlated in time with each other. When the videos were captured …

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Machine Learning Nuclear Detonation Features, Daniel T. Schmitt, Gilbert L. Peterson Oct 2014

Machine Learning Nuclear Detonation Features, Daniel T. Schmitt, Gilbert L. Peterson

Faculty Publications

Nuclear explosion yield estimation equations based on a 3D model of the explosion volume will have a lower uncertainty than radius based estimation. To accurately collect data for a volume model of atmospheric explosions requires building a 3D representation from 2D images. The majority of 3D reconstruction algorithms use the SIFT (scale-invariant feature transform) feature detection algorithm which works best on feature-rich objects with continuous angular collections. These assumptions are different from the archive of nuclear explosions that have only 3 points of view. This paper reduces 300 dimensions derived from an image based on Fourier analysis and five edge …

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Gps Multipath Reduction With Correlator Beamforming, Jason M. Barhorst Mar 2014

Gps Multipath Reduction With Correlator Beamforming, Jason M. Barhorst

Theses and Dissertations

This research effort investigates the feasibility of beamforming using a single Global Positioning System (GPS) front end. Traditional methods of beamforming use multiple front ends, typically one per antenna element. By enabling a receiver to sample a switched antenna array, the hardware cost of implementing a GPS antenna array can be significantly reduced. Similar techniques of reducing the number of receivers have been used by Locata Corporation in the design of their non-GPS positioning systems. However, Locata Corporation's local transmitters provide a signal strength much higher than GPS's signal strength. For this reason, the inclusion of low-noise amplifiers into the …

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An Experimental Evaluation Of Image Quality For Various Scenarios In A Chromotomographic System With A Spinning Prism, Kyle J. Dufaud Mar 2014

An Experimental Evaluation Of Image Quality For Various Scenarios In A Chromotomographic System With A Spinning Prism, Kyle J. Dufaud

Theses and Dissertations

A lab and eld based hyperspectral chromotomographic imager has been developed at the Air Force Institute of Technology. It is a prototype used to study the requirements for a space-based system. The imager uses a high speed visible band camera behind a direct-vision prism to image both spatial dimensions and the spectral dimension at the same time. Capturing all 3 simultaneously allows for the hyperspectral imaging of transient events. The prism multiplexes the spectral and spatial information, so tomographic reconstruction algorithms must be used to separate hyperspectral channels. Experiments were conducted to compare reconstructed image quality as a function of …

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Metrics For Emitter Selection For Multistatic Synthetic Aperture Radar, Sean R. Stevens Sep 2013

Metrics For Emitter Selection For Multistatic Synthetic Aperture Radar, Sean R. Stevens

Theses and Dissertations

A bistatic implementation of synthetic aperture radar (SAR) to form images of the ground from an aircraft makes use of separate emitters and receivers. When not using cooperative emitters, ground based communications systems can provide illumination. One way to improve performance of these waveforms, which are not designed for SAR, is a multistatic implementation, formed from multiple bistatic systems. This leads to the problem of selecting a subset from a potentially large set of emitters to use for image formation. A framework for this selection between sets of emitters is proposed using multiple objective optimization. This approach requires use of …

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Development Of A Model And Localization Algorithm For Received Signal Strength-Based Geolocation, Amanda S. King Jun 2013

Development Of A Model And Localization Algorithm For Received Signal Strength-Based Geolocation, Amanda S. King

Theses and Dissertations

Location-Based Services (LBS), also called geolocation, have become increasingly popular in the past decades. They have several uses ranging from assisting emergency personnel, military reconnaissance and applications in social media. In geolocation a group of sensors estimate the location of transmitters using position and Radio Frequency (RF) information. A review of the literature revealed that a majority of the Received Signal Strength (RSS) techniques used made erroneous assumptions about the distribution or ignored effects of multiple transmitters, noise and multiple antennas. Further, the corresponding algorithms are often mathematically complex and computationally expensive. To address the issues this dissertation focused on …

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Improving Multiple Surface Range Estimation Of A 3-Dimensional Flash Ladar In The Presence Of Atmospheric Turbulence, Brian J. Neff Jun 2013

Improving Multiple Surface Range Estimation Of A 3-Dimensional Flash Ladar In The Presence Of Atmospheric Turbulence, Brian J. Neff

Theses and Dissertations

Laser Radar sensors can be designed to provide two-dimensional and three-dimensional (3-D) images of a scene from a single laser pulse. Currently, there are various data recording and presentation techniques being developed for 3-D sensors. While the technology is still being proven, many applications are being explored and suggested. As technological advancements are coupled with enhanced signal processing algorithms, it is possible that this technology will present exciting new military capabilities for sensor users. The goal of this work is to develop an algorithm to enhance the utility of 3-D Laser Radar sensors through accurate ranging to multiple surfaces per …

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Automatic Modulation Classification Of Common Communication And Pulse Compression Radar Waveforms Using Cyclic Features, John A . Hadjis Mar 2013

Automatic Modulation Classification Of Common Communication And Pulse Compression Radar Waveforms Using Cyclic Features, John A . Hadjis

Theses and Dissertations

This research develops a feature-based MAP classification system and applies it to classify several common pulse compression radar and communication modulations. All signal parameters are treated as unknown to the classifier system except SNR and the signal carrier frequency. The features are derived from estimated duty cycle, cyclic spectral correlation, and cyclic cumulants. The modulations considered in this research are BPSK, QPSK, 16-QAM, 64-QAM, 8-PSK, and 16-PSK communication modulations, as well as Barker coded, Barker coded, Barker coded, Frank coded, Px49 coded, and LFM pulse compression modulations. Simulations show that average correct signal modulation type classification %C 90% is achieved …

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The Miniaturization Of The Afit Random Noise Radar, Aaron T. Myers Mar 2013

The Miniaturization Of The Afit Random Noise Radar, Aaron T. Myers

Theses and Dissertations

Advances in technology and signal processing techniques have opened the door to using an UWB random noise waveform for radar imaging. This unique, low probability of intercept waveform has piqued the interest of the U.S. DoD as well as law enforcement and intelligence agencies alike. While AFIT's noise radar has made significant progress, the current architecture needs to be redesigned to meet the space constraints and power limitations of an aerial platform. This research effort is AFIT's first attempt at RNR miniaturization and centers on two primary objectives: 1) identifying a signal processor that is compact, energy efficient, and capable …

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Detection Optimization Of The Progressive Multi-Channel Correlation Algorithm Used In Infrasound Nuclear Treaty Monitoring, Anthony M. Runco Mar 2013

Detection Optimization Of The Progressive Multi-Channel Correlation Algorithm Used In Infrasound Nuclear Treaty Monitoring, Anthony M. Runco

Theses and Dissertations

This thesis develops methods to determine optimum detection thresholds for the Progressive Multi-Channel Correlation (PMCC) algorithm used by the International Data Centre (IDC) to perform infrasound station-level nuclear-event detection. Receiver Operating Characteristic (ROC) curve analysis is used with real ground truth data to determine the trade-off between the probability of detection (P sub D) and the false alarm rate (FAR) at various consistency detection thresholds. Further, statistical detection theory via maximum a posteriori and Bayes cost approaches is used to determine station-level optimum family size thresholds of grouped detection pixels with similar signal attributes (i.e. trace velocity, azimuth, time of …

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A Nonparametric Approach To Segmentation Of Ladar Images, Eric A. Buschelman Dec 2012

A Nonparametric Approach To Segmentation Of Ladar Images, Eric A. Buschelman

Theses and Dissertations

The advent of advanced laser radar (ladar) systems that record full-waveform signal data has inspired numerous inquisitions which aspire to extract additional, previously unavailable, information about the illuminated scene from the collected data. The quality of the information, however, is often related to the limitations of the ladar camera used to collect the data. This research project uses full-waveform analysis of ladar signals, and basic principles of optics, to propose a new formulation for an accepted signal model. A new waveform model taking into account backscatter reflectance is the key to overcoming specific deficiencies of the ladar camera at hand, …

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Modeling The Effects Of The Local Environment On A Received Gnss Signal, Marshall E. Haker Dec 2012

Modeling The Effects Of The Local Environment On A Received Gnss Signal, Marshall E. Haker

Theses and Dissertations

There is an ongoing need in the GNSS community for the development of high-fidelity simulators which generate data that replicates what can truly be expected from a challenging environment such as an urban canyon or an indoor environment. The algorithm developed for use in the research in this dissertation, the Signal Decomposition and Parameterization Algorithm (SDPA), is presented in order to respond to this need. This algorithm is designed to decompose a signal received using a GNSS recording and playback system and output parameters that can be used to reconstruct the effects on the signal of the environment local to …

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Resolution Study Of A Hyperspectral Sensor Using Computed Tomography In The Process Of Noise, Samuel V. Mantravadi Sep 2012

Resolution Study Of A Hyperspectral Sensor Using Computed Tomography In The Process Of Noise, Samuel V. Mantravadi

Theses and Dissertations

Recently, a new type of hyperspectral imaging sensor has been proposed which simultaneously records both spectral data and multiple spatial dimensions. Unlike dispersive imaging spectrometers, chromo-tomographic hyperspectral imaging sensors (CTHIS) record two spatial dimensions as well as a spectral dimension using computed tomography (CT) techniques with only a finite number of spatially-spectrally diverse images. To date, the factors affecting resolution of these sensors have not been examined. This research examines factors affecting resolution, specifically the number of the focus planes needed to resolve a particular object calculated from a theoretical lower bound, determine a method of reconstructing a hyperspectral object …

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Towards The Mitigation Of Correlation Effects In The Analysis Of Hyperspectral Imagery With Extension To Robust Parameter Design, Jason P. Williams Sep 2012

Towards The Mitigation Of Correlation Effects In The Analysis Of Hyperspectral Imagery With Extension To Robust Parameter Design, Jason P. Williams

Theses and Dissertations

Standard anomaly detectors and classifiers assume data to be uncorrelated and homogeneous, which is not inherent in Hyperspectral Imagery (HSI). To address the detection difficulty, a new method termed Iterative Linear RX (ILRX) uses a line of pixels which shows an advantage over RX, in that it mitigates some of the effects of correlation due to spatial proximity; while the iterative adaptation from Iterative Linear RX (IRX) simultaneously eliminates outliers. In this research, the application of classification algorithms using anomaly detectors to remove potential anomalies from mean vector and covariance matrix estimates and addressing non-homogeneity through cluster analysis, both of …

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Multi-Observation Continuous Density Hidden Markov Models For Anomaly Detection In Full Motion Video, Matthew P. Ross Jun 2012

Multi-Observation Continuous Density Hidden Markov Models For Anomaly Detection In Full Motion Video, Matthew P. Ross

Theses and Dissertations

An increase in sensors on the battlefield produces an abundance of collected data that overwhelms the processing capability of the DoD. Automated Visual Surveillance (AVS) seeks to use machines to better exploit increased sensor data, such as by highlighting anomalies. In this thesis, we apply AVS to overhead Full Motion Video (FMV). We seek to automate the classification of soldiers in a simulated combat scenario into their agent types. To this end, we use Multi-Dimensional Continuous Density Hidden Markov Models (MOCDHMMs), a form of HMM which models a training dataset more precisely than simple HMMs. MOCDHMMs are theoretically developed but …

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Implementation Of Branch-Point-Tolerant Wavefront Reconstructor For Strong Turbulence Compensation, Michael J. Steinbock Jun 2012

Implementation Of Branch-Point-Tolerant Wavefront Reconstructor For Strong Turbulence Compensation, Michael J. Steinbock

Theses and Dissertations

Branch points arise in optical transmissions due to strong atmospheric turbulence, long propagation paths, or a combination of both. Unfortunately, these conditions are very often present in desired operational scenarios for laser weapon systems, optical communication, and covert imaging, which suffer greatly when traditional adaptive optics systems either cannot sense branch points or implement non-optimal methods for sensing and correcting branch points. Previous research by Pellizzari presented a thorough analysis of various novel branch point tolerant reconstructors in the absence of noise. In this research a realistic model of the Air Force Institute of Technology's adaptive optics system is developed …

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Spectral Detection Of Human Skin In Vis-Swir Hyperspectral Imagery Without Radiometric Calibration, Andrew P. Beisley Mar 2012

Spectral Detection Of Human Skin In Vis-Swir Hyperspectral Imagery Without Radiometric Calibration, Andrew P. Beisley

Theses and Dissertations

Many spectral detection algorithms require precise ground truth measurements that are hand-selected in the image to apply radiometric calibration, converting image pixels into estimated reflectance vectors. That process is impractical for mobile, real-time hyperspectral target detection systems, which cannot empirically derive a pixel-to-reflectance relationship from objects in the image. Implementing automatic target recognition on high-speed snapshot hyperspectral cameras requires the ability to spectrally detect targets without performing radiometric calibration. This thesis demonstrates human skin detection on hyperspectral data collected at a high frame rate without using calibration panels, even as the illumination in the scene changes. Compared to an established …

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Binary Classification Of An Unknown Object Through Atmospheric Turbulence Using A Polarimetric Blind-Deconvolution Algorithm Augmented With Adaptive Degree Of Linear Polarization Priors, Mu J. Kim Mar 2012

Binary Classification Of An Unknown Object Through Atmospheric Turbulence Using A Polarimetric Blind-Deconvolution Algorithm Augmented With Adaptive Degree Of Linear Polarization Priors, Mu J. Kim

Theses and Dissertations

This research develops an enhanced material-classification algorithm to discriminate between metals and dielectrics using passive polarimetric imagery degraded by atmospheric turbulence. To improve the performance of the existing technique for near-normal collection geometries, the proposed algorithm adaptively updates the degree of linear polarization (DoLP) priors as more information becomes available about the scene. Three adaptive approaches are presented. The higher-order super-Gaussian method fits the distribution of DoLP estimates with a sum of two super-Gaussian functions to update the priors. The Gaussian method computes the classification threshold value, from which the priors are updated, by fitting the distribution of DoLP estimates …

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Ladar Range Image Interpolation Exploiting Pulse Width Expansion, Jeramy W. Motes Mar 2012

Ladar Range Image Interpolation Exploiting Pulse Width Expansion, Jeramy W. Motes

Theses and Dissertations

Laser Detection and Ranging (LADAR) systems produce both a range image and an intensity image by measuring the intensity of light reflected off a surface target. When the transmitted LADAR pulse strikes a sloped surface, the returned pulse is expanded temporally. This characteristic of the reflected laser pulse enables the possibility of estimating the gradient of a surface. This study estimates the gradient of the surface of an object from a modeled LADAR return pulse that includes accurate probabilistic noise models. The range and surface gradient estimations are incorporated into a novel interpolator that facilitates an effective three dimensional (3D) …

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Local Histograms For Per-Pixel Classification, Melody R. Massar Mar 2012

Local Histograms For Per-Pixel Classification, Melody R. Massar

Theses and Dissertations

We introduce a rigorous mathematical theory for the analysis of local histograms, and study how they interact with textures that can be modeled as occlusions of simpler components. We first show how local histograms can be computed as a system of convolutions and discuss some basic local histogram properties. We then introduce a probabilistic, occlusion-based model for textures and formally demonstrate that local histogram transforms are natural tools for analyzing the textures produced by our model. Next, we characterize all nonlinear transforms which satisfy the three key properties of local histograms and consider the appropriateness of local histogram features in …

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