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Articles 361 - 390 of 454
Full-Text Articles in Signal Processing
A Dispersive Scattering Center, Parametric Model For 1-D Atr, Dane F. Fuller
A Dispersive Scattering Center, Parametric Model For 1-D Atr, Dane F. Fuller
Theses and Dissertations
The dispersive scattering center (DSC) model characterizes high-frequency backscatter from radar targets as a finite sum of localized scattering geometries distributed in range, these geometries, along with their relative locations, can be conveniently used as features in a one-dimensional automatic target recognition (ATR) algorithm. The DSC model's type and range parameters correspond to geometry and distance features according to the geometric theory of diffraction (GTD). Since these parameters are estimated in the phase history domain of the radar signal, the range parameter does provide superresolution in the time domain. To demonstrate the viability of feature extraction based on the DSC …
The Rational Resolution Analysis: A Generalization Of Multi-Resolution Analyses With Application To To The Specific Emitter Identification Problem, Bruce P. Anderson
The Rational Resolution Analysis: A Generalization Of Multi-Resolution Analyses With Application To To The Specific Emitter Identification Problem, Bruce P. Anderson
Theses and Dissertations
The rational resolution analysis RRA is introduced and developed as a generalization of the integer, dilation multiresolution analyses MRA developed by Mallat and Meyer. Rational dilation factors are achieved by relaxing the condition on MRAs that successive approximation spaces be embedded. Conditions for perfect reconstruction are discussed and it is shown that perfect reconstruction is possible with specific constraints on the scaling function the scaling filter must have its roots on the unit circle. Furthermore, the required arrangement of the roots indicate the scaling function must be derived from a B-spline of some degree. It is proven the only compactly …
Visualization And Animation Of A Missile/Target Encounter, Jeffrey T. Bush
Visualization And Animation Of A Missile/Target Encounter, Jeffrey T. Bush
Theses and Dissertations
Existing missile/target encounter modeling and simulation systems focus on improving probability of kill models. Little research has been done to visualize these encounters. These systems can be made more useful to the engineers by incorporating current computer graphics technology for visualizing and animating the encounter. Our research has been to develop a graphical simulation package for visualizing both endgame and full fly-out encounters. Endgame visualization includes showing the interaction of a missile, its fuze cone proximity sensors, and its target during the final fraction of a second of the missile/target encounter. Additionally, this system displays dynamic effects such as the …
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 …
Parameter Estimation For Real Filtered Sinusoids, Daniel R. Zahirniak
Parameter Estimation For Real Filtered Sinusoids, Daniel R. Zahirniak
Theses and Dissertations
This research develops theoretical methods for parameter estimation of filtered, pulsed sinusoids in noise and demonstrates their effectiveness for Electronic Warfare EW applications. Within the context of stochastic modeling, a new linear model, parameterized by a set of Linear Prediction LP coefficients, is derived for estimating the frequencies of filtered sinusoids. This model is an improvement over previous modeling techniques since the effects of the filter and the coefficients upon the noise statistics are properly accounted for during model development. From this linear model, a relationship between LP coefficient estimation and Maximum Likelihood ML frequency estimation is derived and several …
Optimization Considerations For Adaptive Optics Digital Imagery Systems, Robert T. Brigantic
Optimization Considerations For Adaptive Optics Digital Imagery Systems, Robert T. Brigantic
Theses and Dissertations
This dissertation had three objectives. The first objective was to develop image quality metrics that characterize Adaptive Optics System (AOS) performance. The second objective was to delineate control settings that maximize AOS performance. The third objective was to identify and characterize trade-offs between fully and partially compensated adaptive. For the first objective, three candidate image quality metrics were considered: the Strehl ratio, a novel metric that modifies the Strehl ratio by integrating the modulus of the average system optical transfer function to a 'noise-effective-cutoff' frequency at which some specified image spectrum signal-to-noise-ratio level is attained, and the noise-effective-cutoff frequency. It …
Diffraction Analysis And Tactical Applications Of Signal Propagation Over Rough Terrain, You-Cheol Jang
Diffraction Analysis And Tactical Applications Of Signal Propagation Over Rough Terrain, You-Cheol Jang
Theses and Dissertations
The free space propagation model is inadequate to predict the mean path-loss in ground wireless communication. Also, many existing propagation channel models do not adequately predict path-loss in rough terrain because most of them were based on measurements in urban areas. Hence, a channel model that estimates mean path-loss over many different kinds of terrain conditions is desired. In this thesis, two new propagation channel models, Real Terrain Diffraction Model (RTDMOD) and Universal Terrain Channel Model (UTCMOD), were developed. Other geometric theory of diffraction (GTD) methods (Epstein-Peterson (EP) and Deygout (DG)) agree within 5 % from 3 MHz to 3GHz …
Space Object Identification Using Feature Space Trajectory Neural Networks, Neal W. Bruegger
Space Object Identification Using Feature Space Trajectory Neural Networks, Neal W. Bruegger
Theses and Dissertations
The Feature Space Trajectory Neural Network (FSTNN) is a simple yet powerful pattern recognition tool developed by Neiberg and Casasent for use in an Automatic Target Recognition System. Since the FSTNN was developed, it has been used on various problems including speaker identification and space object identification. However, in these types of problems, the test set represents time series data rather than an independent set of points. Since the distance metric of the standard FSTNN treats each test point independently without regard to its position in the sequence, the FSTNN can yield less than optimal results in these problems. Two …
Analysis Of Multimode Low-Probability-Of-Intercept (Lpi) Communications With Atmospheric Effects, Ala Ghordlo
Analysis Of Multimode Low-Probability-Of-Intercept (Lpi) Communications With Atmospheric Effects, Ala Ghordlo
Theses and Dissertations
This research expanded Low Probability of Intercept (LPI) communications analysis in two areas. First, multimode communication was included to account for ground to ground and air to ground links in addition to the standard air to air links traditionally used in LPI analysis. The propagation equations for the three modes of interest were derived and included in LPI analytic models in the form of a mode quality factor to account for multimode LPI scenarios. This new quality factor was used in studying several communication and interception link combinations. Variations due to differences between the communication and interception modes were presented …
Optimization Of A Gps-Based Navigation Reference System, Jason B. Mckay
Optimization Of A Gps-Based Navigation Reference System, Jason B. Mckay
Theses and Dissertations
The development of increasingly accurate new aircraft navigation systems has caused the Air Force to develop a new Navigation Reference System to test them, called the Submeter Accuracy Reference System (SARS). The SARS is an inverted GPS system which consists of an array of GPS receivers on the ground and an airborne pseudolite mounted on the test aircraft. The SARS will provide a proof position estimate that is used to check the navigation system under test. Unfortunately, ground based inverted GPS systems tend to suffer from high geometric sensitivity to measurement errors. This research tackles the problem of optimizing the …
Interference Suppression For Spread Spectrum Signals Using Adaptive Beamforming And Adaptive Temporal Filter, Wonjin Park
Interference Suppression For Spread Spectrum Signals Using Adaptive Beamforming And Adaptive Temporal Filter, Wonjin Park
Theses and Dissertations
Interference and jamming signals are a serious concern in an operational military communication environment. This thesis examines the utility and performance of combining adaptive temporal filtering with adaptive spatial filtering (i.e. adaptive beamforming) to improve the signal-to-jammer ratio (SJR) in the presence of narrowband and wideband interference. Adaptive temporal filters are used for narrowband interference suppression while adaptive beamforming is used to suppress wideband interference signals. A procedure is presented for the design and implementation of a linear constraints minimum variance generalized sidelobe canceler (LCMV-GSC) beamformer. The adaptive beamformer processes the desired signal with unity gain while simultaneously and adaptively …
Performance Analysis Of A Hartman Wavefront Sensor Used For Sensing Atmospheric Turbulence Statistics, Toby D. Reeves
Performance Analysis Of A Hartman Wavefront Sensor Used For Sensing Atmospheric Turbulence Statistics, Toby D. Reeves
Theses and Dissertations
Atmospheric turbulence parameters, such as Fried's coherence diameter, the outer scale of turbulence, and the turbulence power law, are related to the wavefront slope structure function (SSF). The SSF is defined as the second moment of the wavefront slope difference as a function of both time and position. Knowledge of the SSF allows turbulence parameters to be estimated. Hartmann wavefront sensor (H-WFS) slope measurements composed of both signal and noise, allow the SSF to be estimated by computing a mean square difference of H-WFS slope measurements. The quality of the SSF estimate is quantified by the signal-to-noise ratio (SNR) of …
Mmae Detection Of Interference/Jamming And Spoofing In A Dpgs-Aided Inertial System, Nathan A. White
Mmae Detection Of Interference/Jamming And Spoofing In A Dpgs-Aided Inertial System, Nathan A. White
Theses and Dissertations
Previous research at AFIT has resulted in the development of a DGPS-aided INS-based precision landing system (PLS) capable of meeting the FAA precision requirements for instrument landings. The susceptibility of DGPS transmissions to interference/jamming and spoofing must be addressed before DGPS may be used in such a safety-of-flight critical role. This thesis applies multiple model adaptive estimation (MMAE) techniques to the problem of detecting and identifying interference/jamming and spoofing failures in the DGPS signal. Such an MMAE is composed of a bank of parallel filters, each hypothesizing a different failure status, along with an evaluation of the current probability of …
Countering The Effects Of Measurement Noise During The Identification Of Dynamical Systems, Odell R. Reynolds
Countering The Effects Of Measurement Noise During The Identification Of Dynamical Systems, Odell R. Reynolds
Theses and Dissertations
Sensor noise is an unavoidable fact of life when it comes to measurements on physical systems, as is the case in feedback control. Therefore, it must be properly addressed during dynamic system identification. In this work, a novel approach is developed toward the treatment of measurement noise in dynamical systems. This approach hinges on proper stochastic modeling, and it can be adapted easily to many different scenarios, where it yields consistently good parameter estimates. The Generalized Minimum Variance algorithm developed and used in this work is based on the theory behind the minimum variance identification process, and the estimate produced …
Perceptual Fidelity For Digital Color Imagery, Curtis E. Martin
Perceptual Fidelity For Digital Color Imagery, Curtis E. Martin
Theses and Dissertations
The problem of measuring the fidelity of digital color images in a manner that corresponds to human perceptual assessments is addressed. Experiments are performed to validate human visual system (HVS) models, which provide access to a 'perceptual space' in which visual distortions may be measured, and then a model is proposed for assessing the perceptual fidelity of digital color image. Color Mach bands are produced in the first experiment, demonstrating that, as in the brightness channel, low spatial frequency attenuation occurs in the chromatic channels of the HVS. In the second experiment, a correlation between the chromatic channels of the …
Evaluation Of Design Tools For Rapid Prototyping Of Parallel Signal Processing Algorithms, James C. Savage
Evaluation Of Design Tools For Rapid Prototyping Of Parallel Signal Processing Algorithms, James C. Savage
Theses and Dissertations
Digital signal processing (DSP) has become a popular method for handling not only signal processing, but communications, and control system applications. A DSP application of interest to the Air Force is high speed avionics processing. The real time computing requirements of avionics processing exceed the capabilities of current single chip DSP processors, and parallelization of multiple DSP processors is a solution to handle such requirements. Designing and implementing a parallel DSP algorithm has been a lengthy process often requiring different design tools and extensive programming experience. Through the use of integrated software development tools, rapid prototyping becomes possible by simulating …
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 …
Parameter Estimation For Superimposed Weighted Exponentials, Edwards A. Ingham
Parameter Estimation For Superimposed Weighted Exponentials, Edwards A. Ingham
Theses and Dissertations
The approach of modeling measured signals as superimposed exponentials in white Gaussian noise is popular and effective. However, estimating the parameters of the assumed model is challenging, especially when the data record length is short, the signal strength is low, or the parameters are closely spaced. In this dissertation, we first review the most effective parameter estimation scheme for the superimposed exponential model: maximum likelihood. We then provide a historical review of the linear prediction approach to parameter estimation for the same model. After identifying the improvements made to linear prediction and demonstrating their weaknesses, we introduce a completely tractable …
Investigation Of Radio Wave Propagation In The Martian Ionosphere Utilizing Hf Sounding Techniques, Robert J. Yowell
Investigation Of Radio Wave Propagation In The Martian Ionosphere Utilizing Hf Sounding Techniques, Robert J. Yowell
Theses and Dissertations
This thesis presents a preliminary design of an ionospheric sounder to be carried aboard one or more of NASA's Mars Surveyor landers. Past Russian and American probes have indicated the existence of an ionosphere, but none of these missions remotely sensed this atmospheric layer from the surface. The rationale for utilizing a surface-based Martian ionospheric sounder is discussed. Based on NASA's choice of launch vehicle and power source, a low-weight, low-powered Chirp sounder using a horizontally-polarized dipole antenna is recommended for the sounder experiment. The sounder experiment should be conducted for at least one Martian year, in order to investigate …
An Investigation Of Preliminary Feature Screening Using Signal-To-Noise Ratios, David B. Sumrell
An Investigation Of Preliminary Feature Screening Using Signal-To-Noise Ratios, David B. Sumrell
Theses and Dissertations
A new saliency metric and a new saliency screening method are developed. This new metric, the SN saliency metric, is based upon signal-to-noise ratios, where the signal is provided by a sum of squared weights associated with a given feature, and the noise is based upon a sum of squared weights associated with a reference noise feature which is injected into the data. The resultant metric allows for a direct comparison of the feature of interest with a reference noise feature which is known to be nonsalient. The SN saliency screening method, which uses the SN saliency metric, offers the …
Text-Independent, Open-Set Speaker Recognition, Stephen V. Pellissier
Text-Independent, Open-Set Speaker Recognition, Stephen V. Pellissier
Theses and Dissertations
Speaker recognition, like other biometric personal identification techniques, depends upon a person's intrinsic characteristics. A realistically viable system must be capable of dealing with the open-set task. This effort attacks the open-set task, identifying the best features to use, and proposes the use of a fuzzy classifier followed by hypothesis testing as a model for text-independent, open-set speaker recognition. Using the TIMIT corpus and Rome Laboratory's GREENFLAG tactical communications corpus, this thesis demonstrates that the proposed system succeeded in open-set speaker recognition. Considering the fact that extremely short utterances were used to train the system (compared to other closed-set speaker …
Generalized Hidden Filter Markov Models Applied To Speaker Recognition, John M. Colombi
Generalized Hidden Filter Markov Models Applied To Speaker Recognition, John M. Colombi
Theses and Dissertations
Classification of time series has wide Air Force, DoD and commercial interest, from automatic target recognition systems on munitions to recognition of speakers in diverse environments. The ability to effectively model the temporal information contained in a sequence is of paramount importance. Toward this goal, this research develops theoretical extensions to a class of stochastic models and demonstrates their effectiveness on the problem of text-independent (language constrained) speaker recognition. Specifically within the hidden Markov model architecture, additional constraints are implemented which better incorporate observation correlations and context, where standard approaches fail. Two methods of modeling correlations are developed, and their …
Adaptive And Fixed Wavelet Features For Narrowband Signal Classification, Anthony J. Pohl
Adaptive And Fixed Wavelet Features For Narrowband Signal Classification, Anthony J. Pohl
Theses and Dissertations
The application of the multiresolution analysis developed by Mallat to signal classification by Pati and Krishnaprasad and Szu, et al, is further explored in this thesis. Several different wavelet based feature extraction and classification systems are developed and implemented. Methods which rely on the traditional dyadic wavelet decomposition and on the adaptive wavelet representation are presented. Each of the classification systems is implemented for a labeled data set of narrowband signals. Finally, classification results on the full data set and on low frequency Fourier coefficients are provided as baseline comparisons for our work.
The Role Of Frame Selection And Bispectrum Phase Reconstruction For Speckle Imaging Through Atmospheric Turbulence, Elizabeth A. Harpold
The Role Of Frame Selection And Bispectrum Phase Reconstruction For Speckle Imaging Through Atmospheric Turbulence, Elizabeth A. Harpold
Theses and Dissertations
Frame selection using quality sharpness metrics have been shown in previous AFIT theses, to be effective in improving the final product of images obtained using adaptive optics. This thesis extends this idea to noncompensated speckle image data. Speckle image reconstruction is simulated with and without frame selection. Speckle images require the processing of hundreds of data frames. Frame selection is a method of reducing the amount of data required to reconstruct the image. A collection of short exposure image data frames of a single object are sorted based on sharpness metrics. Only the highest quality frames are retained and processed …
Narrowband Interference Suppression In Spread Spectrum Communication Systems, James A. Lascody
Narrowband Interference Suppression In Spread Spectrum Communication Systems, James A. Lascody
Theses and Dissertations
Of significant interest to the United States military is the ability of an enemy to deny or disrupt the operation of the Global Positioning System. To combat this threat the GPS JPO initiated the Tactical GPS AntiJam Technology project, which yielded a prototype Digital Excision Filter (DEF) to remove narrowband jammers. This research describes the work performed to get the DEF hardware operational and extends the previous research performed in this area. Comdisco's Signal Processing Worksystem was used to examine the effect of the DEF on the probability of bit error. This research uses peak to average correlation value, probability …
Effects Of Jamming And Excision Filtering Upon Error Rates And Detectability Of A Spread Spectrum Communication System, Christopher B. Madden
Effects Of Jamming And Excision Filtering Upon Error Rates And Detectability Of A Spread Spectrum Communication System, Christopher B. Madden
Theses and Dissertations
This thesis examines the effects of a digital excision filter (DEF) upon the error rates and detectability of a Direct Sequence Binary Phase Shift Keyed communication signal in the presence of both continuous wave (CW) and pulsed jammers. Simulations were performed using the Comdisco Signal Processing Worksystem. Detector models used were the wideband radiometer and two forms of the chip-rate detector. Twelve jamming scenarios were used to test the performance of the DEF in the presence of the CW and pulsed jammers. In addition, the effects of the CW jammer frequency, the pulsed jammer duty cycle, and the pulsed jammer …
Space Object Identification Using Spatio-Temporal Pattern Recognition, Gary W. Brandstrom
Space Object Identification Using Spatio-Temporal Pattern Recognition, Gary W. Brandstrom
Theses and Dissertations
This thesis is part of a research effort to automate the task of characterizing space objects or satellites based on a sequence of images. The goal is to detect space object anomalies. Two algorithms are considered - the feature space trajectory neural network (FST NN) and hidden Markov model (HMM) classifier. The FST NN was first presented by Leonard Neiberg and David P. Casasent in 1994 as a target identification tool. Kenneth H. Fielding and Dennis W. Ruck recently applied the hidden Markov model classifier to a 3D moving light display identification problem and a target recognition problem, using time …
Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk
Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk
Theses and Dissertations
A comparative study of texture measures for the classification of breast tissue is presented. The texture features investigated include Angular Second Moments, Power Spectrum Analysis and a novel feature, Laws Energy Ratios. The texture study was accomplished as part of the development of a Model Based Vision (MBV) system for the automatic detection of microcalcifications. An overview of the Microcalcification Detection System is presented, which applies image differencing techniques, feature selection methods, and neural networks for locating microcalcification clusters in mammograms. The Power Spectrum Analysis feature set had the best overall performance with an 83% Probability of Detection and an …
Three Dimensional Localization Of Lesions From Digitized Mammograms, Amy L. Magnus
Three Dimensional Localization Of Lesions From Digitized Mammograms, Amy L. Magnus
Theses and Dissertations
This thesis describes new algorithms to localize regions-of-interests (ROIs) three dimensionally from a pair of digitized mammograms. This work is intended to add a layer of sophistication to computer aided diagnosis by putting to use the fixed and measurable parameters of mammographic imaging. The fixed parameters are the source to film orientation and the podium-image distance. Measurable parameters are the rotation angle of the x-ray tube from the horizontal and the compression depth (the distance from compression paddle to contact podium distance) at the time of imaging. As an additional benefit, three dimensional localization algorithms alleviate the confusion radiologists may …
Three Dimensional Inverse Synthetic Aperture Radar Imaging, Jack D. Pullis
Three Dimensional Inverse Synthetic Aperture Radar Imaging, Jack D. Pullis
Theses and Dissertations
This research investigates the generation, display, and interpretation of three-dimensional (3-D) Synthetic Aperture Radar images. Three-dimensional assumes that the data collected consists of one temporal dimension and two orthogonal angular dimensions. From this data, a three dimensional reflectivity map, or 3-D image, of a target can be constructed. This thesis effort develops and applies a three-dimensional imaging algorithm on actual radar data measured on a one-third scale model of a C-29 aircraft. Two-dimensional slices of the three-dimensional image as well as three-dimensional isosurfaces are compared to the physical properties of the target. The results demonstrate the ability to produce three-dimensional …