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Engineering

Theses and Dissertations

Target acquisition

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Full-Text Articles in Physical Sciences and Mathematics

Hyperspectral-Based Adaptive Matched Filter Detector Error As A Function Of Atmospheric Profile Estimation, Allan W. Yarbrough Sep 2011

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 …


Monocular Passive Ranging By An Optical System With Band Pass Filtering, Joel R. Anderson Mar 2010

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 …


Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James Mar 2009

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 …


Waypoint Generation Based On Sensor Aimpoint, Shannon M. Farrell Mar 2009

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 …


Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson Mar 2006

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.


Consistency Results For The Roc Curves Of Fused Classifiers, Kristopher S. Bjerkaas Dec 2004

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 …


An Investigation Of The Effects Of Correlation, Autocorrelation, And Sample Size In Classifier Fusion, Nathan J. Leap Mar 2004

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 Mar 2003

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 …


Non-Imaging Infrared Spectral Target Detection, Matthew R. Whiteley Sep 1995

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 …


Multispectral Detection Of Ground Targets In Highly Correlated Backgrounds, Jason E. Thomas Dec 1994

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 …