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Articles 61 - 90 of 95
Full-Text Articles in Theory and Algorithms
Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson
Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson
Theses and Dissertations
Decision level fusion (DLF) algorithms combine outputs of multiple single sensors to make one confident declaration of a target. This research compares performance results of a DLF algorithm using measured data and a proven ATR system with results from simulated data and a modeled ATR system. This comparison indicates that DLF offers significant performance improvements over single sensor looks. However, results based on simulated data and a modeled ATR are slightly optimistic and overestimate results from measured data and a proven ATR system by nearly 10% over all targets tested.
An Evolutionary Algorithm To Generate Hyper-Ellipsoid Detectors For Negative Selection, Joseph M. Shapiro, Gary B. Lamont, Gilbert L. Peterson
An Evolutionary Algorithm To Generate Hyper-Ellipsoid Detectors For Negative Selection, Joseph M. Shapiro, Gary B. Lamont, Gilbert L. Peterson
Faculty Publications
This paper introduces hyper-ellipsoids as an improvement to hyper-spheres as intrusion detectors in a negative selection problem within an artificial immune system. Since hyper-spheres are a specialization of hyper-ellipsoids, hyper-ellipsoids retain the benefits of hyper-spheres. However, hyper-ellipsoids are much more flexible, mostly in that they can be stretched and reoriented. The viability of using hyper-ellipsoids is established using several pedagogical problems. We conjecture that fewer hyper-ellipsoids than hyper-spheres are needed to achieve similar coverage of nonself space in a negative selection problem. Experimentation validates this conjecture. In pedagogical benchmark problems, the number of hyper-ellipsoids to achieve good results is significantly …
Modeling Information Quality Expectation In Unmanned Aerial Vehicle Swarm Sensor Databases, Patrick D. Baldwin
Modeling Information Quality Expectation In Unmanned Aerial Vehicle Swarm Sensor Databases, Patrick D. Baldwin
Theses and Dissertations
Swarming Unmanned Aerial Vehicles (UAVs) are the future of Intelligence, Surveillance and Reconnaissance (ISR). Swarms of hundreds of these vehicles, each equipped with multiple sensors, will one day fill the skies over hostile areas. As the sensors collect hundreds of gigabytes of data, telemetry data links will be unable to transmit the complete data picture to the ground in real time. The collected data will be stored on board the UAVs and selectively downloaded through queries issued from analysts on the ground. Analysts expect to find relevant sensor data within the collection of acquired sensor data. This expectation is not …
An Evolutionary Algorithm To Generate Ellipsoid Detectors For Negative Selection, Joseph M. Shapiro
An Evolutionary Algorithm To Generate Ellipsoid Detectors For Negative Selection, Joseph M. Shapiro
Theses and Dissertations
Negative selection is a process from the biological immune system that can be applied to two-class (self and nonself) classification problems. Negative selection uses only one class (self) for training, which results in detectors for the other class (nonself). This paradigm is especially useful for problems in which only one class is available for training, such as network intrusion detection. Previous work has investigated hyper-rectangles and hyper-spheres as geometric detectors. This work proposes ellipsoids as geometric detectors. First, the author establishes a mathematical model for ellipsoids. He develops an algorithm to generate ellipsoids by training on only one class of …
A Genetic Algorithm For Uav Routing Integrated With A Parallel Swarm Simulation, Matthew A. Russell
A Genetic Algorithm For Uav Routing Integrated With A Parallel Swarm Simulation, Matthew A. Russell
Theses and Dissertations
This research investigation addresses the problem of routing and simulating swarms of UAVs. Sorties are modeled as instantiations of the NP-Complete Vehicle Routing Problem, and this work uses genetic algorithms (GAs) to provide a fast and robust algorithm for a priori and dynamic routing applications. Swarms of UAVs are modeled based on extensions of Reynolds' swarm research and are simulated on a Beowulf cluster as a parallel computing application using the Synchronous Environment for Emulation and Discrete Event Simulation (SPEEDES). In a test suite, standard measures such as benchmark problems, best published results, and parallel metrics are used as performance …
A Three Dimensional Helmet Mounted Primary Flight Reference For Paratroopers, Jason I. Thompson
A Three Dimensional Helmet Mounted Primary Flight Reference For Paratroopers, Jason I. Thompson
Theses and Dissertations
This thesis seeks to develop a Heads Up Display (HUD) presented on a Helmet Mounted Display (HMD), which presents a three-dimensional, graphical, predictive navigational reference to a paratrooper during a High Altitude, High Opening (HAHO) parachute jump. A Path Generating Algorithm (PGA) takes as input the Landing Zone's (LZ) location, the wind profile, and the paratrooper's parachute's performance characteristics, and returns a set of waypoints for the paratrooper to follow. The PGA attempts to maximize the distance that the paratrooper travels. The PGA's output is used to build a path to the LZ from a Release Point (RP). During the …
Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham
Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham
Theses and Dissertations
The structure from motion process creates three-dimensional models from a sequence of images. Until recently, most research in this field has been restricted to land-based imagery. This research examines the current methods of land-based structure from motion and evaluates their performance for aerial imagery. Current structure from motion algorithms search the initial image for features to track though the subsequent images. These features are used to create point correspondences between the two images. The correspondences are used to estimate the motion of the camera and then the three-dimensional structure of the scene. This research tests current algorithms using synthetic data …
Robot Mapping With Real-Time Incremental Localization Using Expectation Maximization, Kevin L. Owens
Robot Mapping With Real-Time Incremental Localization Using Expectation Maximization, Kevin L. Owens
Theses and Dissertations
This research effort explores and develops a real-time sonar-based robot mapping and localization algorithm that provides pose correction within the context of a single room, to be combined with pre-existing global localization techniques, and thus produce a single, well-formed map of an unknown environment. Our algorithm implements an expectation maximization algorithm that is based on the notion of the alpha-beta functions of a Hidden Markov Model. It performs a forward alpha calculation as an integral component of the occupancy grid mapping procedure using local maps in place of a single global map, and a backward beta calculation that considers the …
Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver
Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver
Theses and Dissertations
A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stochastic objective functions and a mixture of design variable types. The generalized pattern search (GPS) class of algorithms is extended to a new problem setting in which objective function evaluations require sampling from a model of a stochastic system. The approach combines GPS with ranking and selection (R&S) statistical procedures to select new iterates. The derivative-free algorithms require only black-box simulation responses and are applicable over domains with mixed variables (continuous, discrete numeric, and discrete categorical) to include bound and linear constraints on …
Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, And Developing, Jesse B. Zydallis
Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, And Developing, Jesse B. Zydallis
Theses and Dissertations
This dissertation research emphasizes explicit Building Block (BB) based MO EAs performance and detailed symbolic representation. An explicit BB-based MOEA for solving constrained and real-world MOPs is developed the Multiobjective Messy Genetic Algorithm II (MOMGA-II) which is designed to validate symbolic BB concepts. The MOMGA-II demonstrates that explicit BB-based MOEAs provide insight into solving difficult MOPs that is generally not realized through the use of implicit BB-based MOEA approaches. This insight is necessary to increase the effectiveness of all MOEA approaches. In order to increase MOEA computational efficiency parallelization of MOEAs is addressed. Communications between processors in a parallel MOEA …
Active Processor Scheduling Using Evolution Algorithms, David J. Caswell
Active Processor Scheduling Using Evolution Algorithms, David J. Caswell
Theses and Dissertations
The allocation of processes to processors has long been of interest to engineers. The processor allocation problem considered here assigns multiple applications onto a computing system. With this algorithm researchers could more efficiently examine real-time sensor data like that used by United States Air Force digital signal processing efforts or real-time aerosol hazard detection as examined by the Department of Homeland Security. Different choices for the design of a load balancing algorithm are examined in both the problem and algorithm domains. Evolutionary algorithms are used to find near-optimal solutions. These algorithms incorporate multiobjective coevolutionary and parallel principles to create an …
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Theses and Dissertations
The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …
Traveling Salesman Problem For Surveillance Mission Using Particle Swarm Optimization, Barry R. Secrest
Traveling Salesman Problem For Surveillance Mission Using Particle Swarm Optimization, Barry R. Secrest
Theses and Dissertations
The surveillance mission requires aircraft to fly from a starting point through defended terrain to targets and return to a safe destination (usually the starting point). The process of selecting such a flight path is known as the Mission Route Planning (MRP) Problem and is a three-dimensional, multi-criteria (fuel expenditure, time required, risk taken, priority targeting, goals met, etc.) path search. Planning aircraft routes involves an elaborate search through numerous possibilities, which can severely task the resources of the system being used to compute the routes. Operational systems can take up to a day to arrive at a solution due …
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
Theses and Dissertations
Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This thesis evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentors. This objective comparison uses a multi-metric a approach with a set of …
Global Positioning System (Gps) Error Source Prediction, Marcus G. Ferguson
Global Positioning System (Gps) Error Source Prediction, Marcus G. Ferguson
Theses and Dissertations
With the initiation of the navigation accuracy prediction algorithm used to estimate the amount of GPS solution (location and time) error for receivers, the capability to accurately predict solution errors due to the major GPS error sources is growing. Although some sources of error within the GPS solution have been previously analyzed, modeled, and/or accounted for within various modeling efforts, a formal evaluation of the seven major error sources that distort GPS activity has not been officially conducted up until this point. This research offers a logical assessment of all the major GPS error sources and their definitive impact on …
Stochastic Modeling-Based Dgps Estimation Algorithm, James T. Broaddus
Stochastic Modeling-Based Dgps Estimation Algorithm, James T. Broaddus
Theses and Dissertations
A Kinematic Differential Global Positioning System (KDGPS) algorithm is developed. A number of mobile receivers is considered, one of which will be designated the reference station' which will have known position and velocity information at the beginning of the time interval examined. Satellite clock biases are used to model Selective Availability. The measurement situation on hand is properly modeled and a centralized estimation algorithm processing several epochs of data. The effect of uncertainty in the reference receiver's position and the level of receiver noise is examined. Monte Carlo simulations are performed to examine the ability of the algorithm to correctly …
An Efficient Gps Position Determination Algorithm, Carlos R. Colon
An Efficient Gps Position Determination Algorithm, Carlos R. Colon
Theses and Dissertations
The use of detect, or closed-form solutions of the trilateration equations used to obtain the position fix in GPS receivers is investigated. The paper is concerned with the development of an efficient new position determination algorithm that uses the closed-form solution of the trilateration equations and works in the presence of pseudorange measurement noise and for an arbitrary number of satellites. in addition, an initial position guess is not required and good estimation performance is achieved even under high GDOP conditions. A two step GPS position determination algorithm which 1) entails the solution of a linear regression problem and, 2) …
Computation Of Scattering From Bodies Of Revolution Using An Entire-Domain Basis Implementation Of The Moment Method, Arthur P. Ford Iv
Computation Of Scattering From Bodies Of Revolution Using An Entire-Domain Basis Implementation Of The Moment Method, Arthur P. Ford Iv
Theses and Dissertations
Research into improved calibration targets for measurement of radar cross-section has created a need for the ability to accurately compute the scattering from perfectly conducting bodies of revolution. Common computational techniques use Moment Method codes that employ subdomain basis functions to expand the unknown current density. This approach has its shortcomings. Large numbers of basis functions are required, and increasing the number of basis functions to improve accuracy after an initial computation requires re-computation of previous results and lost processing time. This research involves using basis functions that have as their domain the entire length of the surface. Entire-domain basis …
Gps Signal Offset Detection And Noise Strength Estimation In A Parallel Kalman Filter Algorithm, Barry J. Vanek
Gps Signal Offset Detection And Noise Strength Estimation In A Parallel Kalman Filter Algorithm, Barry J. Vanek
Theses and Dissertations
Measurements from Global Positioning System (GPS) satellites are subject to corruption by signal interference and induced offsets. This thesis presents two independent algorithms to ensure the navigation system remains uncorrupted by these possible GPS failures. The first is a parameter estimation algorithm that estimates the measurement noise variance of each satellite. A redundant measurement differencing (RMD) technique provides direct observability of the differenced white measurement noise samples. The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter structure, which then adapts to changes in the real-world measurement noise strength. The parallel Kalman …
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Theses and Dissertations
Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L2(R) and the Hardy spaces Hp(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …
New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez
New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez
Theses and Dissertations
The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard Multiple Model Adaptive Estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. A new moving-bank MMAE algorithm is developed based on exploitation of the density data available from the MMAE. The methods used to exploit this information include various measures of the density data and a decision-making logic used to move, expand, and contract the MMAE bank of filters. Parameter discretization within …
Breast Cancer Mass Detection Using Difference Of Gaussians And Pulse Coupled Neural Networks, Donald A. Cournoyer
Breast Cancer Mass Detection Using Difference Of Gaussians And Pulse Coupled Neural Networks, Donald A. Cournoyer
Theses and Dissertations
CAD, serving as a second reader, has been shown to improve the success of radiologists at detecting breast cancer. This thesis will develop a new algorithm to identify masses in mammograms. The system developed for this thesis will be capable of assisting a radiologist in making decisions.
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Theses and Dissertations
Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …
Weighted Mahalanobis Distance For Hyper-Ellipsoidal Clustering, Khaled S. Younis
Weighted Mahalanobis Distance For Hyper-Ellipsoidal Clustering, Khaled S. Younis
Theses and Dissertations
Cluster analysis is widely used in many applications, ranging from image and speech coding to pattern recognition. A new method that uses the weighted Mahalanobis distance (WMD) via the covariance matrix of the individual clusters as the basis for grouping is presented in this thesis. In this algorithm, the Mahalanobis distance is used as a measure of similarity between the samples in each cluster. This thesis discusses some difficulties associated with using the Mahalanobis distance in clustering. The proposed method provides solutions to these problems. The new algorithm is an approximation to the well-known expectation maximization (EM) procedure used to …
Inference Algorithm Performance And Selection Under Constrained Resources, Brett J. Borghetti
Inference Algorithm Performance And Selection Under Constrained Resources, Brett J. Borghetti
Theses and Dissertations
Knowing that reasoning over probabilistic networks is, in general, NP-hard, and that most reasoning environments have limited resources, we need to select algorithms that can solve a given problem as fast as possible. This thesis presents a method for predicting the relative performance of reasoning algorithms based on the domain characteristics of the target knowledge structure. Armed with this knowledge, the research shows how to choose the best algorithm to solve the problem. The effects of incompleteness of the knowledge base at the time of inference is explored, and requirements for reasoning over incompleteness are defined. Two algorithms for reasoning …
Refined Genetic Algorithms For Polypeptide Structure Prediction, Charles E. Kaiser Jr.
Refined Genetic Algorithms For Polypeptide Structure Prediction, Charles E. Kaiser Jr.
Theses and Dissertations
Accurate and reliable prediction of macromolecular structures has eluded researchers for nearly 40 years. Prediction via energy minimization assumes the native conformation has the globally minimal energy potential. An exhaustive search is impossible since for molecules of normal size, the size of the search space exceeds the size of the universe. Domain knowledge sources, such as the Brookhaven PDB can be mined for constraints to limit the search space. Genetic algorithms (GAs) are stochastic, population based, search algorithms of polynomial (P) time complexity that can produce semi-optimal solutions for problems of nondeterministic polynomial (NP) time complexity such as PSP. Three …
Analysis Of Linkage-Friendly Genetic Algorithms, Laurence D. Merkle
Analysis Of Linkage-Friendly Genetic Algorithms, Laurence D. Merkle
Theses and Dissertations
Evolutionary algorithms (EAs) are stochastic population-based algorithms inspired by the natural processes of selection, mutation, and recombination. EAs are often employed as optimum seeking techniques. A formal framework for EAs is proposed, in which evolutionary operators are viewed as mappings from parameter spaces to spaces of random functions. Formal definitions within this framework capture the distinguishing characteristics of the classes of recombination, mutation, and selection operators. EAs which use strictly invariant selection operators and order invariant representation schemes comprise the class of linkage-friendly genetic algorithms (lfGAs). Fast messy genetic algorithms (fmGAs) are lfGAs which use binary tournament selection (BTS) with …
An Analysis Of Bayesian Networks As Classifiers, Gregory C. Ahlquist
An Analysis Of Bayesian Networks As Classifiers, Gregory C. Ahlquist
Theses and Dissertations
An analysis of Bayesian networks as classifiers is presented. This analysis results in an algorithm and several tools related to Bayesian network classifiers. The tools calculate and display the decision regions for two level Bayesian network classifiers. They collectively provide an approach to analyze the effects of changing network parameters on the network's decision regions. The algorithm defines a Bayesian network classifier to solve traditional classification problems. The algorithm is data driven, meaning that the resulting Bayesian network classifier is uniquely tuned to the classification problem at hand. Also, the algorithm contains procedures for defining the topology of a Bayesian …
Effective Parallel Algorithm Animation, Paul W. Chase
Effective Parallel Algorithm Animation, Paul W. Chase
Theses and Dissertations
The AFIT Algorithm Animation Research Facility AAARF was developed by the Air Force Institute of Technology AFIT as a teaching aid for data structures and algorithm design. In particular, an extensive set of performance animations has been developed for the Intel iPSC Hypercube parallel processing system. This research focuses in part on developing animation support for discrete event simulation, mission routing, and evolutionary algorithms based on abstract representations of parallel algorithm behavior. The effort also builds extensions to the AAARF system and examines direction for further research. An innovative adaptable application-specific animation construction environment has been designed and implemented. The …