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Full-Text Articles in Signal Processing
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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., …
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 …
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 …
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 …
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 …
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 …