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Articles 31 - 51 of 51
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Analysis Of Cooperative Behavior For Autonomous Wide Area Search Munitions, Orhan Gozaydin
Analysis Of Cooperative Behavior For Autonomous Wide Area Search Munitions, Orhan Gozaydin
Theses and Dissertations
This research investigates the effectiveness of autonomous wide area search munitions using cooperative and non-cooperative behavior algorithms under various scenarios. The scenarios involve multiple autonomous munitions searching for an unknown number of targets with different priorities at unknown locations. For the cooperative cases, communications are allowed between the munitions to help locate, identify, and decide to pursue an attack on a target or to continue searching the rest of the battlefield. For non cooperative cases, munitions independently search, detect, identify and decide to attack an identified target or continue to search. Performance of the cooperative munitions depends on numerous parameters …
Inquisitive Pattern Recognition, Amy L. Magnus
Inquisitive Pattern Recognition, Amy L. Magnus
Theses and Dissertations
The Department of Defense and the Department of the Air Force have funded automatic target recognition for several decades with varied success. The foundation of automatic target recognition is based upon pattern recognition. In this work, we present new pattern recognition concepts specifically in the area of classification and propose new techniques that will allow one to determine when a classifier is being arrogant. Clearly arrogance in classification is an undesirable attribute. A human is being arrogant when their expressed conviction in a decision overstates their actual experience in making similar decisions. Likewise given an input feature vector, we say …
Orbit Determination For A Microsatellite Rendezvous With A Non-Cooperative Target, Brian L. Foster
Orbit Determination For A Microsatellite Rendezvous With A Non-Cooperative Target, Brian L. Foster
Theses and Dissertations
This study investigated the minimum requirements to establish a satellite tracking system architecture for a hostile "parasitic microsatellite" to rendezvous with a larger, non-cooperative target satellite. Four types of tracking systems and their capabilities were reviewed with emphasis on "low-technology" level and/or mobile systems which could be used by technologically unsophisticated state or non-state adversaries. With the tracking system architecture selected, simulated tracking data was processed with a non- linear least squares orbit determination filter to determine and/or update the target satellite's state vector.
Automatic Target Recognition Classification System Evaluation Methodology, Christopher Brian Bassham
Automatic Target Recognition Classification System Evaluation Methodology, Christopher Brian Bassham
Theses and Dissertations
This dissertation research makes contributions towards the evaluation of developing Automatic Target Recognition (ATR) technologies through the application of decision analysis (DA) techniques. ATR technology development decisions should rely not only on the measures of performance (MOPs) associated with a given ATR classification system (CS), but also on the expected measures of effectiveness (MOEs). The purpose of this research is to improve the decision-makers in the ATR Technology development. A decision analysis framework that allows decision-makers in the ATR community to synthesize the performance measures, costs, and characteristics of each ATR system with the preferences and values of both the …
High Energy Laser Pointing Through Extended Turbulence, Jason A. Tellez
High Energy Laser Pointing Through Extended Turbulence, Jason A. Tellez
Theses and Dissertations
The airborne laser (ABL) uses adaptive optics to compensate the atmospheric turbulence between the ABL and the target. The primary purpose of this compensation is to increase the energy density of the energy laser at the target. However, the specifics of the engagement scenario require the tracking point of reference and the adaptive optics point of reference to be located at different points on the target. This research considers the effects of tracking a target in one direction while compensating for atmospheric turbulence in a different directions. The target references used are a point source and a rectangle, while a …
Airborne Radar Interference Suppression Using Adaptive Three-Dimensional Techniques, Todd B. Hale
Airborne Radar Interference Suppression Using Adaptive Three-Dimensional Techniques, Todd B. Hale
Theses and Dissertations
This research advances adaptive interference suppression techniques for airborne radar, addressing the problem of target detection within severe interference environments characterized by high ground clutter levels, levels, noise jammer infiltration, and strong discrete interferers. Two-dimensional (2D) Space-Time Adaptive Processing (STAP) concepts are extended into three-dimensions (3D) by casting each major 2D STAP research area into a 3D framework. The work first develops an appropriate 3D data model with provisions for range ambiguous clutter returns. Adaptive 3D development begins with two factored approaches, 3D Factored Time-Space (3D-FTS) and Elevation-Joint Domain Localized (Elev-JDL). The 3D adaptive development continues with optimal techniques, i.e., …
An Examination Of Latency And Degradation Issues In Unmanned Combat Aerial Vehicle Environments, Shane A. Dougherty
An Examination Of Latency And Degradation Issues In Unmanned Combat Aerial Vehicle Environments, Shane A. Dougherty
Theses and Dissertations
Since the multidimensional knapsack problems are NP-hard problems, the exact solutions of knapsack problems often need excessive computing time and storage space. Thus, heuristic approaches are more practical for multidimensional knapsack problems as problems get large. This thesis presents the results of an empirical study of the performance of heuristic solution procedures based on the coefficients correlation structures and constraint slackness settings. In this thesis, the three representative greedy heuristics, Toyoda, Senju and Toyoda, and Loulou and Michaelides methods, are studied. The purpose of this thesis is to explore which heuristic of the three representative greedy heuristics perform best under …
A Traffic Pattern-Based Comparison Of Bulk Image Request Response Times For A Virtual Distributed Laboratory, David B. Hooten
A Traffic Pattern-Based Comparison Of Bulk Image Request Response Times For A Virtual Distributed Laboratory, David B. Hooten
Theses and Dissertations
Various agencies throughout the Department of Defense possess intelligence imagery and electrooptical signature data required by researchers in the field of automatic target recognition (ATR). The Air Force Research Laboratory, Sensors Directorate, as been tasked with creating a virtual distributed laboratory (VDL) which will make this data available to ATR researchers via high speed networks such as the defense research and engineering network (DREN). For this research, a model for simulating potential operational network configurations and collaboration scenarios was developed and implemented using OPNET. The results of the simulations were analyzed using statistical methods to determine the impact on performance …
Air Vehicle Optimal Trajectories For Radar Exposure Minimization, Michael C. Novy
Air Vehicle Optimal Trajectories For Radar Exposure Minimization, Michael C. Novy
Theses and Dissertations
This study addresses the problem of analyzing the single vehicle path planning problem for radar exposure minimization. The calculus of Variations and optimal control are applied to formulate the cost function and numerical algorithms are used to solve for the optimal paths. Cost sensitivity to path length is analyzed for flight against one radar; a second radar is then included in the formulation and the optimal path for flight between the radars is found for cases of equal and unequal radar power. The costs of the optimal path, direct path, and Voronoi diagram-generated paths are compared. Results indicate low sensitivity …
Embedding A Reactive Tabu Search Heuristic In Unmanned Aerial Vehicle Simulations, Joel L. Ryan
Embedding A Reactive Tabu Search Heuristic In Unmanned Aerial Vehicle Simulations, Joel L. Ryan
Theses and Dissertations
We apply a Reactive Tabu Search (RTS) heuristic within a discrete event simulation to solve routing problems for Unmanned Aerial Vehicles (UAVs). Our formulation represents this problem as a multiple Traveling Salesman Problem with time windows (mTSPTW), with the objective of attaining a specified level of target coverage using a minimum number of vehicles. Incorporating weather and probability of UAV survival at each target as random inputs, the RTS heuristic in the simulation searches for the best solution in each realization of the problem scenario in order to identify those routes that are robust to variations in weather, threat, or …
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target In Identification Synthetic Aperture Radar Images, Matthew P. Pepin
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target In Identification Synthetic Aperture Radar Images, Matthew P. Pepin
Theses and Dissertations
This dissertation develops techniques for estimating exponential signals in unknown colored noise. The Maximum Likelihood ML estimators of the exponential parameters are developed. Techniques are developed for one and two dimensional exponentials, for both the deterministic and stochastic ML model. The techniques are applied to Synthetic Aperture Radar SAR data whose point scatterers are modeled as damped exponentials. These estimated scatterer locations exponentials frequencies are potential features for model-based target recognition. The estimators developed in this dissertation may be applied with any parametrically modeled noise having a zero mean and a consistent estimator of the noise covariance matrix. ML techniques …
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target Identification In Synthetic Aperture Radar Images, Matthew P. Pepin
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target Identification In Synthetic Aperture Radar Images, Matthew P. Pepin
Theses and Dissertations
This dissertation develops techniques for estimating exponential signals in unknown colored noise. The Maximum Likelihood (ML) estimators of the exponential parameters are developed. Techniques are developed for one and two dimensional exponentials, for both the deterministic and stochastic ML model. The techniques are applied to Synthetic Aperture Radar (SAR) data whose point scatterers are modeled as damped exponentials. These estimated scatterer locations (exponentials frequencies) are potential features for model-based target recognition. The estimators developed in this dissertation may be applied with any parametrically modeled noise having a zero mean and a consistent estimator of the noise covariance matrix. ML techniques …
Non-Imaging Infrared Spectral Target Detection, Matthew R. Whiteley
Non-Imaging Infrared Spectral Target Detection, Matthew R. Whiteley
Theses and Dissertations
Automatic detection of time-critical mobile targets using spectral-only infrared radiance data is explored. A quantification of the probability of detection, false alarm rate, and total error rate associated with this detection process is provided. A set of classification features is developed for the spectral data, and these features are utilized in a Bayesian classifier singly and in combination to provide target detection. The results of this processing are presented and sensitivity of the class separability to target set, target configuration, diurnal variations, mean contrast, and ambient temperature estimation errors is explored. This work introduces the concept of atmospheric normalization of …
An Improved Solution Methodology For The Arsenal Exchange Model (Aem), Jeffery D. Weir
An Improved Solution Methodology For The Arsenal Exchange Model (Aem), Jeffery D. Weir
Theses and Dissertations
The purpose of this research was to design a solution methodology for the Arsenal Exchange Model (AEM) that is faster and contains less precision error than the current one. The current solution methodology modifies some of the original constraints and uses a computationally slow matrix inverter. The improved methodology uses a revised simplex algorithm to first solve a subproblem having only the weapon constraints generated by the AEM. Given this optimal allocation, hedge constraints and target constraints that are violated by the current solution are added to the original subproblem. A dual simplex algorithm is used to find the optimal …
Perceptual Based Image Fusion With Applications To Hyperspectral Image Data, Terry A. Wilson
Perceptual Based Image Fusion With Applications To Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Development of new imaging sensors has created a need for image processing techniques that can fuse images from different sensors or multiple images produced by the same sensor. The methods presented here focus on combining image data from the Airborne Visual and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor into a single or smaller subset of images while maintaining the visual information necessary for human analysis. Three hierarchical multi-resolution image fusion techniques are implemented and tested using the AVIRIS image data and test images that contain various levels of correlated or uncorrelated noise. Two of the algorithms are published fusion methods …
Classification Of Ultra High Range Resolution Radar Using Decision Boundary Analysis, Christopher L. Eisenbies
Classification Of Ultra High Range Resolution Radar Using Decision Boundary Analysis, Christopher L. Eisenbies
Theses and Dissertations
This thesis examines the discrimination of targets with Ultra High Range Resolution (UHRR) radar data. Using these measured signals from frontal aspect angles of four aircraft classes, the baseline performance of the Adaptive Gaussian Classifier (AGC) is tested with respect to aligning exemplars to templates. Alignment plays a crucial role in the AGC's classification performance which can degrade by 11% for a target class. The AGC is compared to non-parametric classifiers, but no statistically significant degradation of performance is found. Data separability is analyzed by hounding the Bayes error. The data is well separated in a statistical sense. A feature …
Processing Of Wide-Angle Synthetic Aperture Radar Signals For Detection Of Obscured Ground Targets, Richard J. Sumner
Processing Of Wide-Angle Synthetic Aperture Radar Signals For Detection Of Obscured Ground Targets, Richard J. Sumner
Theses and Dissertations
This thesis investigates advanced processing techniques for the detection of radar targets in the presence of clutter. It is assumed that the radar data available consist of multi-aspect angle, fully polarimetric Synthetic Aperture Radar (SAR) images. Various techniques are introduced and tested on available SAR data. These techniques attempt to exploit the multi-aspect angles in order to extract target characteristics not available in any single image. SAR images are manipulated in such a way to decrease the probability of false alarms in the target detection process. Target detection performance of the techniques is presented and compared. The techniques are shown …
Multispectral Detection Of Ground Targets In Highly Correlated Backgrounds, Jason E. Thomas
Multispectral Detection Of Ground Targets In Highly Correlated Backgrounds, Jason E. Thomas
Theses and Dissertations
Multispectral detection methods attempt to discriminate targets in a dominant clutter background using multiple images of the same real-world scene taken in different narrow spectral bands in the infrared. Detection is possible due to the empirically observed phenomenon that the radiance of man-made objects, such as a tank or truck, often lies off the main spectral correlation axis of that of natural backgrounds. Radiometric measurements of several vehicles and a tree canopy background taken over three days in June. 1994 were used to examine the factors affecting multispectral detection. Results clearly showed that the processes which provide for higher spectral …
Processing Of Wide-Angle Synthetic Aperture Radar Signals For Target Detection, Kurt W. Knurr
Processing Of Wide-Angle Synthetic Aperture Radar Signals For Target Detection, Kurt W. Knurr
Theses and Dissertations
This study investigated methods of targets detection using Wide-Angle Synthetic Aperture Radar (WASAR). WASAR uses multiple aspect angle Synthetic Aperture Radar (SAR) images of the same scene. The SAR images were generated using a pre-release software package from package from Loral Corporation. The software was able to generate 512 by 512 pixel SAR images that contained various vegetation return which for our purposes we classified as clutter. Within this clutter, targets (M35 trucks) could be placed at random location and orientations. The software also had the capability of generating fully- polarimetic WASAR images with multiple depression angles. This data was …
Three Dimensional Object Recognition Using A Complex Autoregressive Model, David E. Chelen
Three Dimensional Object Recognition Using A Complex Autoregressive Model, David E. Chelen
Theses and Dissertations
Based on an autoregressive model, Complex Partial Correlation CPARCOR features are known to provide exceptional Position, Scale, and Rotation Invariant PSRI properties for planar 2-Dimensional 2-D object recognition. Although autogressive models have been successfully applied to numerous spatio-temporal recognition tasks, the effects of out-of-plane image rotations were never considered. This study investigates application of the CPAR-COR model to a five class problem of nonplanar 2-D views of 3-D objects. Recognition based on CPAR-COR features is evaluated using a Template Matching algorithm, two K-Nearest-Neighbor KNN classifiers, and a Hidden Markov Model HMM. Direct comparisons to recognition based on Fourier features are …
Application Of Sequence Comparison Methods To Multisensor Data Fusion And Target Recognition, Edmund W. Libby
Application Of Sequence Comparison Methods To Multisensor Data Fusion And Target Recognition, Edmund W. Libby
Theses and Dissertations
This research addresses methods for exploiting the joint likelihood of observed kinematic and nonkinematic (sensor signature) physical events to improve dynamic object and target recognition. A principal direction is the application of dynamic programming sequence comparison techniques to condition matching of object signatures to known models according to observed kinematics. A second direction is the application of kinematic/aspect-angle Kalman filter trackers to condition kinematic tracking according to observed signatures. These conditioning processes dramatically reduce ambiguity in object recognition, and can be used together or separately to allow computation of a posterior probabilities of object class membership using Bayesian methods. Proposals …