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Articles 1 - 30 of 42
Full-Text Articles in Engineering
Determination Of Fire Control Policies Via Approximate Dynamic Programming, Michael T. Davis
Determination Of Fire Control Policies Via Approximate Dynamic Programming, Michael T. Davis
Theses and Dissertations
Given the ubiquitous nature of both offensive and defensive missile systems, the catastrophe-causing potential they represent, and the limited resources available to countries for missile defense, optimizing the defensive response to a missile attack is a necessary endeavor. For a single salvo of offensive missiles launched at a set of targets, a missile defense system protecting those targets must decide how many interceptors to fire at each incoming missile. Since such missile engagements often involve the firing of more than one attack salvo, we develop a Markov decision process (MDP) model to examine the optimal fire control policy for the …
Bayesian Methods And Confidence Intervals For Automatic Target Recognition Of Sar Canonical Shapes, Richard W. Rademacher
Bayesian Methods And Confidence Intervals For Automatic Target Recognition Of Sar Canonical Shapes, Richard W. Rademacher
Theses and Dissertations
This research develops a new Bayesian technique for the detection of scattering primitives in synthetic aperture radar (SAR) phase history data received from a sensor platform. The primary goal of this research is the estimation of size, position, and orientation parameters defined by the “canonical” shape primitives of Jackson. Previous Bayesian methods for this problem have focused on the traditional maximum a posteriori (MAP) estimate based on the posterior density. A new concept, the probability mass interval, is developed. In this technique the posterior density is partitioned into intervals, which are then integrated to form a probability mass over that …
Spectral Detection Of Human Skin In Vis-Swir Hyperspectral Imagery Without Radiometric Calibration, Andrew P. Beisley
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 …
Hyperspectral-Based Adaptive Matched Filter Detector Error As A Function Of Atmospheric Profile Estimation, Allan W. Yarbrough
Hyperspectral-Based Adaptive Matched Filter Detector Error As A Function Of Atmospheric Profile Estimation, Allan W. Yarbrough
Theses and Dissertations
Hyperspectral imagery is collected as radiance data. This data is a function of multiple variables: the radiation profile of the light source, the reflectance of the target, and the absorption and scattering profile of the medium through which the radiation travels as it reflects off the target and reaches the imager. Accurate target detection requires that the collected image matches as closely as possible the known "true" target in the classification database. Therefore, the effect of the radiation source and the atmosphere must be removed before detection is attempted. While the spectrum of solar light is relatively stable, the effect …
Contextual Detection Of Anomalies In Hyperspectral Images, Adam J. Messer
Contextual Detection Of Anomalies In Hyperspectral Images, Adam J. Messer
Theses and Dissertations
The majority of anomaly detectors in Hyperspectral Imaging use only the statistical aspects of the spectral readings in the image. These detectors fail to use the spatial context that is contained in the images. The use of this information can yield detectors that out perform their spatially myopic counterparts. To demonstrate this, we will use an independent component analysis based detector, autonomous global anomaly detector (AutoGAD), developed at AFIT augmented to account for the spatial context of the detected anomalies. Through the use of segmentation algorithms, the anomalies identified are formed into regions. The size and shape of these regions …
The Effect Of Synthetic Aperture Radar Image Resolution On Target Discrimination, John E. Mcgowan
The Effect Of Synthetic Aperture Radar Image Resolution On Target Discrimination, John E. Mcgowan
Theses and Dissertations
This research details the effect of spatial resolution on target discrimination in Synthetic Aperture Radar (SAR) images. Multiple SAR image chips containing targets and non-targets are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial resolution. Spatial resolution is reduced by lowering the pixel count or synthesizing a degraded image by filtering and reducing the pixel count. A two-parameter Constant False Alarm Rate (CFAR) detector is tested, and three feature sets, size, contrast, and texture, are used to train a linear classifier and to estimate probability density functions for the two classes. The results are scored …
Monocular Passive Ranging By An Optical System With Band Pass Filtering, Joel R. Anderson
Monocular Passive Ranging By An Optical System With Band Pass Filtering, Joel R. Anderson
Theses and Dissertations
An instrument for monocular passive ranging based on atmospheric oxygen absorption near 762 nm has been designed, built and deployed to track emissive targets, including the plumes from jet engines or rockets. An intensified CCD array is coupled to variable band pass liquid crystal display filter and 3.5 – 8.8 degree field of view optics to observe the target. By recording sequential images at 7 Hz in three 6 nm width bands, the transmittance of the R-branch of the O2 (X-b) (0,0) band is determined. A metric curve for determining range from transmittance is developed using the HITRAN spectral …
Pulse Shape Correlation For Laser Detection And Ranging (Ladar), Brian T. Deas
Pulse Shape Correlation For Laser Detection And Ranging (Ladar), Brian T. Deas
Theses and Dissertations
Radar systems provide an important remote sensing capability, and are crucial to the layered sensing vision; a concept of operation that aims to apply the right number of the right types of sensors, in the right places, at the right times for superior battle space situational awareness. The layered sensing vision poses a range of technical challenges, including radar, that are yet to be addressed. To address the radar-specific design challenges, the research community responded with waveform diversity; a relatively new field of study which aims reduce the cost of remote sensing while improving performance. Early work suggests that the …
Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James
Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James
Theses and Dissertations
The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …
Using Shadows To Detect Targets In Synthetic Aperture Radar Imagery, Brian P. Donnell
Using Shadows To Detect Targets In Synthetic Aperture Radar Imagery, Brian P. Donnell
Theses and Dissertations
Synthetic Aperture Radar (SAR) can generate high resolution imagery of re- mote scenes by combining the phase information of multiple radar pulses along a given path. SAR based Intelligence, Surveillance, and Reconnaissance (ISR) has the advantage over optical ISR that it can provide usable imagery in adverse weather or nighttime conditions. Certain radar frequencies can even result in foliage or limited soil penetration, enabling imagery to be created of objects of interest that would otherwise be hidden from optical surveillance systems. This thesis demonstrates the capability of locating stationary targets of interest based on the locations of their shadows and …
Waypoint Generation Based On Sensor Aimpoint, Shannon M. Farrell
Waypoint Generation Based On Sensor Aimpoint, Shannon M. Farrell
Theses and Dissertations
Secretary of Defense Robert M. Gates has emphasized a need for a greater number of intelligence, surveillance, and reconnaissance (ISR) assets to support combatant commanders and military operations globally. Unmanned systems, especially MAVs, used as ISR platforms provide the ability to maintain covertness during missions and help reduce the risk to human life. This research develops waypoint generation algorithms required to keep a point of interest (POI) in the field of view (FOV) of a fixed sensor on a micro air vehicle (MAV) in the presence of a constant wind.
Fixed sensors, while cheaper and less prone to mechanical failure …
Using Multiple Robust Parameter Design Techniques To Improve Hyperspectral Anomaly Detection Algorithm Performance, Matthew T. Davis
Using Multiple Robust Parameter Design Techniques To Improve Hyperspectral Anomaly Detection Algorithm Performance, Matthew T. Davis
Theses and Dissertations
Detecting and identifying objects of interest is the goal of all remote sensing. New advances, specifically in hyperspectral imaging technology have provided the analyst with immense amounts of data requiring evaluation. Several filtering techniques or anomaly detection algorithms have been proposed. However, most new algorithms are insufficiently verified to be robust to the broad range of hyperspectral data being made available. One such algorithm, AutoGAD, is tested here via two separate robust parameter design techniques to determine optimal parameters for consistent performance on a range of data with large attribute variances. Additionally, the results of the two techniques are compared …
Combat Identification Using Multiple Tuav Swarm, Younin Kang
Combat Identification Using Multiple Tuav Swarm, Younin Kang
Theses and Dissertations
In modern warfare, Tactical Unmanned Aerial Vehicles (TUAVs) are rapidly taking on a leading role in traditional and non-traditional ISR, to include Automatic Target Recognition (ATR). However, additional advancements in processors and sensors on TUAVs are still needed before they can be widely employed as a primary source for positive identification in the Combat Identification (CID) process. Cost is a driving factor for operating an ATR system using multiple TUAVs. The cost of high quality sensors appropriate for a single TUAV can be significantly higher than less sophisticated sensors suitable for deployment on a group, or swarm, of coordinated TUAVs. …
A Wide Area Bipolar Cascade Resonant Cavity Light Emitting Diode For A Hybrid Range-Intensity, Reginald J. Turner
A Wide Area Bipolar Cascade Resonant Cavity Light Emitting Diode For A Hybrid Range-Intensity, Reginald J. Turner
Theses and Dissertations
This dissertation focused on the development of an illuminator for the HRIS. This illuminator enables faster image rendering and reduces the potential of errors in return signal data, that could be generated from extremely rough terrain. Four major achievements resulted from this work, which advance the field of 3-D image acquisition. The first is that the TJ is an effective current spreading layer for LEDs with mesa width up to 140 micrometers and current densities of approximately 1 x 106 Amp/square centimeter. The TJ allows fabrication of an efficient illuminator, with required geometry for the HRIS to operate as …
Hyperspectral Imagery Target Detection Using Improved Anomaly Detection And Signature Matching Methods, Timothy E. Smetek
Hyperspectral Imagery Target Detection Using Improved Anomaly Detection And Signature Matching Methods, Timothy E. Smetek
Theses and Dissertations
This research extends the field of hyperspectral target detection by developing autonomous anomaly detection and signature matching methodologies that reduce false alarms relative to existing benchmark detectors, and are practical for use in an operational environment. The proposed anomaly detection methodology adapts multivariate outlier detection algorithms for use with hyperspectral datasets containing tens of thousands of non-homogeneous, high-dimensional spectral signatures. In so doing, the limitations of existing, non-robust, anomaly detectors are identified, an autonomous clustering methodology is developed to divide an image into homogeneous background materials, and competing multivariate outlier detection methods are evaluated for their ability to uncover hyperspectral …
Point Spread Function Characterization Of A Radially Displaced Scatterer Using Circular Synthetic Aperture Radar, Uttam K. Majumder
Point Spread Function Characterization Of A Radially Displaced Scatterer Using Circular Synthetic Aperture Radar, Uttam K. Majumder
Theses and Dissertations
This research effort investigated characterizing the point spread function (PSF) behavior of radially displaced point scatterers using circular synthetic aperture radar (CSAR). Thus far, research has been conducted to understand PSF of a scatterer located at the imaging scene center. An analytic closed-form solution has been derived assuming the scatterer is located at the origin of the CSAR imaging geometry. However, it is difficult to derive an analytic PSF solution for a scatterer that is radially displaced from the imaging scene center. Using the back projection image formation algorithm, PSF responses are generated at various point target locations. Consistent with …
Laser Covariance Vibrometry For Unsymmetrical Mode Detection, Michael C. Kobold
Laser Covariance Vibrometry For Unsymmetrical Mode Detection, Michael C. Kobold
Theses and Dissertations
Simulated cross - spectral covariance (CSC) from optical return from simulated surface vibration indicates CW phase modulation may be an appropriate phenomenology for adequate classification of vehicles by structural mode. The nonlinear structural to optical relationship is close to unity, avoiding nulls and high values; optical return contains sufficient spectral ID information necessary for data clustering. The FE model has contact between the homogeneous rolled armor and vehicle hull, a simple multi - layer skin model typical of most vehicles. Most of the high frequency energy moved to lower frequencies. This nonlinearity segments contact vibration modes into two classes: symmetrical …
A Minimum Effort Control Approach To Guided Munition Path Planning, Jeffrey M. Borkowski
A Minimum Effort Control Approach To Guided Munition Path Planning, Jeffrey M. Borkowski
Theses and Dissertations
An advance in the development of smart munitions entails autonomously modifying target selection during flight to maximize the value of the target being destroyed. Target identification and classification provides a basis for target value, which is used in conjunction with multi-target tracks to determine an optimal aim point for the munition. A unique guidance law can be constructed that exploits attribute and kinematic data from an onboard video sensor. This thesis develops an innovative path planning algorithm that provides an obstacle avoidance function while navigating the munition toward the highest value target. The foundation of this path planning method is …
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.
Optimization Of Automatic Target Recognition With A Reject Option Using Fusion And Correlated Sensor Data, Trevor I. Laine
Optimization Of Automatic Target Recognition With A Reject Option Using Fusion And Correlated Sensor Data, Trevor I. Laine
Theses and Dissertations
This dissertation examines the optimization of automatic target recognition (ATR) systems when a rejection option is included. First, a comprehensive review of the literature inclusive of ATR assessment, fusion, correlated sensor data, and classifier rejection is presented. An optimization framework for the fusion of multiple sensors is then developed. This framework identifies preferred fusion rules and sensors along with rejection and receiver operating characteristic (ROC) curve thresholds without the use of explicit misclassification costs as required by a Bayes' loss function. This optimization framework is the first to integrate both "vertical" warfighter output label analysis and "horizontal" engineering confusion matrix …
An Investigation Of The Effects Of Correlation And Autocorrelation In Classifier Fusion With Non-Declarations, Frank M. Mindrup
An Investigation Of The Effects Of Correlation And Autocorrelation In Classifier Fusion With Non-Declarations, Frank M. Mindrup
Theses and Dissertations
Air Force doctrine requires reliable and accurate information when striking targets. Further, this doctrine states that fusion should be utilized whenever possible to ensure the best possible information is conveyed; there is no specific guidance as to how to fuse this information. This thesis extends the research found in Leap, Bauer, and Oxley (2004) to include a non-declared class. The Identification system operating characteristic (ISOC) was adapted to allow for non-declarations both at the individual sensor level as well as the fused output level. A probabilistic neural network (PNN) was also used as a fusion technique. A cost function was …
Consistency Results For The Roc Curves Of Fused Classifiers, Kristopher S. Bjerkaas
Consistency Results For The Roc Curves Of Fused Classifiers, Kristopher S. Bjerkaas
Theses and Dissertations
The U.S. Air Force is researching the fusion of multiple classifiers. Given a finite collection of classifiers to be fused, one seeks a new classifier with improved performance. An established performance quantifier is the Receiver Operating Characteristic (ROC) curve, which allows one to view the probability of detection versus the probability of false alarm in one graph. Previous research shows that one does not have to perform tests to determine the ROC curve of this new fused classifier. If the ROC curve for each individual classifier has been determined, then formulas for the ROC curve of the fused classifier exist …
Target Recognition Using Late-Time Returns From Ultra-Wideband, Short-Pulse Radar, Kenneth J. Pascoe
Target Recognition Using Late-Time Returns From Ultra-Wideband, Short-Pulse Radar, Kenneth J. Pascoe
Theses and Dissertations
The goal of this research is to develop algorithms that recognize targets by exploiting properties in the late-time resonance induced by ultra-wide band radar signals. A new variant of the Matrix Pencil Method algorithm is developed that identifies complex resonant frequencies present in the scattered signal. Kalman filters are developed to represent the dynamics of the signals scattered from several target types. The Multiple Model Adaptive Estimation algorithm uses the Kalman filters to recognize targets. The target recognition algorithm is shown to be successful in the presence of noise. The performance of the new algorithms is compared to that of …
Target Recognition Using Linear Classification Of High Range Resolution Radar Profiles, Ricardo A. Diaz
Target Recognition Using Linear Classification Of High Range Resolution Radar Profiles, Ricardo A. Diaz
Theses and Dissertations
High Range Resolution (HRR) radar profiles map three-dimensional target characteristics onto one-dimensional signals that represent reflected radar intensity along target extent. In this thesis, second through fourth statistical moments are extracted from HRR profiles and input to Fisher Linear Discriminant (FLD) classifiers. An iterative classification process is applied that gradually minimizes required a priori knowledge about the target data. It is found that the second through fourth statistical moments of HRR profiles are useful features in the FLD classification of dissimilar targets and they provide reasonable discrimination of similar targets. Greater than 69% correct classification for two-target scenarios and greater …
Characterization Of The Target-Mount Interaction In Radar Cross Section Measurement Calibrations, Donald W. Powers
Characterization Of The Target-Mount Interaction In Radar Cross Section Measurement Calibrations, Donald W. Powers
Theses and Dissertations
Radar Cross Section (RCS) measurements are quintessential in understanding target scattering phenomenon. The reduced RCS of modern weapons systems stresses the capability of current RCS measurement ranges. A limiting factor that has recently become more significant is the electromagnetic coupling between a test target and the mounting hardware used to support it and control its orientation during the RCS measurement. Equally important is the electromagnetic coupling between the RCS calibration artifact and its mount, which provides an opportunity to explore the coupling phenomena without delving into operationally sensitive areas. The primary research goal was to characterize the interaction between a …
An Investigation Of The Effects Of Correlation, Autocorrelation, And Sample Size In Classifier Fusion, Nathan J. Leap
An Investigation Of The Effects Of Correlation, Autocorrelation, And Sample Size In Classifier Fusion, Nathan J. Leap
Theses and Dissertations
This thesis extends the research found in Storm, Bauer, and Oxley, 2003. Data correlation effects and sample size effects on three classifier fusion techniques and one data fusion technique were investigated. Identification System Operating Characteristic Fusion (Haspert, 2000), the Receiver Operating Characteristic Within Fusion method (Oxley and Bauer, 2002), and a Probabilistic Neural Network were the three classifier fusion techniques; a Generalized Regression Neural Network was the data fusion technique. Correlation was injected into the data set both within a feature set (autocorrelation) and across feature sets for a variety of classification problems, and sample size was varied throughout. Total …
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.
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 …
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 …