Signal Processing Commons^™

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

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 …

Detection For A Statistically-Known, Time-Varying Dispersive Channel, David W. Matolak, S. G. Wilson

Faculty Publications

Detection for the statistically known channel (SKC) is aimed at obtaining good performance in situations where our statistical knowledge of a time-varying channel is good, and where other equalization/detection schemes are either too complex to implement, or their performance is limited due to the rapidity of channel fading, or where we are simply unable to perform channel estimation. By using a statistical characterization of the channel, we develop a new detector that performs maximum-likelihood sequence estimation (MLSE) (given the channel model) on blocks of N symbols. Both symbol-spaced and fractionally spaced samples are used, to obtain two different detectors, that …

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

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

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

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

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

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 …

Acuta 25th Annual Conference- Silver Anniversary- July 14-18, 1996- Chicago Hilton & Towers.

ACUTA: Other Publications

Registration & Hotel Information

Registration if postmarked by June 24, 1996.(Extended from June 14)

. Member Institution/Associate Member - $525. Corporate Affiliate - $525. Non-Member - $650

Registration if postmarked after June 24, 1996.

Member Institution/Associate Member - $57. Corporate Affiliate - $575 . Non-Member - $700

Hotel: Chicago Hilton & Towers

312-922-4400. Rates are $118 Single or Double. Be sure and mention the ACUTA rate! Cutoff date

for hotel is June 19,19961

Due to the popularity of this event and the Chicago destination, the hotel is full on some nights.

However, the ACUTA rate of $ll8 single/double per night …

Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan

Electrical & Computer Engineering Theses & Dissertations

Motivated by the fact that human speech perception is a bimodal process (auditory and visual), several researchers have designed and implemented automatic speech recognition (ASR) systems consisting of both audio and visual subsystems, and shown improved performance relative to traditional purely auditory systems. Several visual speech reading approaches have used deformable templates to model the shape of a speaker's lips. Deformable templates are models of image objects, which can be deformed by adjusting a set of parameters to match the object in some optimal way, as defined by a cost function. Using a single deformable lip model has disadvantages such …

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

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 …

Adaptive Integration Of Audio And Visual Information Using Discrete And Semi-Continuous Hidden Markov Models In Audiovisual Automatic Speech Recognition, Qin Su

Electrical & Computer Engineering Theses & Dissertations

An audiovisual semi-continuous hidden Markov model (HMM)-based Automatic Speech Recognition (ASR) system and an improved method of integrating audio and visual information in an audiovisual discrete HMM-based ASR system are investigated.

In the audiovisual discrete HMM, an adaptive integration formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A visual weighting parameter is determined automatically, which allows the relative contribution of audio and visual information to be adjusted adaptively. Using an adaptive weight, the accuracy increased by 13% compared to the same model with no adaptive weight.

The semi-continuous HMM is a class of models …

An Enhanced Signal Processing Strategy For Fetal Heart Rate Detection, Charles Brewton

Electrical & Computer Engineering Theses & Dissertations

The goal of the research was to improve the signal processing strategy for an acoustic fetal heart rate monitor. The theory, implementation, and testing of several possible signal processing strategies for fetal heart rate detection are presented. The enhanced signal processing strategy implemented is discussed and justified with off-line Matlab simulations and real-time experiments. A FIR matched filter was used as a preprocessor to increase the SNR of the acoustic fetal heart signal. The Teager energy operator and autocorrelation, used in the previous version of the monitor, were combined with a matched filter. Linear prediction and quadratic energy detection were …

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

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

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 …

Variable-Complexity Trellis Decoding Of Binary Convolutional Codes, David W. Matolak, S. G. Wilson

Faculty Publications

Considers trellis decoding of convolutional codes with selectable effort, as measured by decoder complexity. Decoding is described for single parent codes with a variety of complexities, with performance "near" that of the optimal fixed receiver complexity coding system. Effective free distance is examined. Criteria are proposed for ranking parent codes, and some codes found to be best according to the criteria are tabulated, Several codes with effective free distance better than the best code of comparable complexity were found. Asymptotic (high SNR) performance analysis and error propagation are discussed. Simulation results are also provided.

Simulink Implementation Of A Cdma Transmitter, Visalakshi Ramakonar

Theses : Honours

An implementation of a Code Division Multiple Access (CDMA) transmitter has been developed using SIMULINK and MATLAB. This transmitter uses a modified carrier in modulation. This modified carrier, which is frequency modulated, has been shown to reduce intersymbol interference (ISI) and multiple access interference (MAl). These two types of interference are caused by multipath propagation which results in delayed versions of the original signal. The benefits of this modified modulation technique are apparent when there are delays involved. The spreading sequences used are 7- bit Gold codes which allow a maximum of nine users. The initial trials of the transmitter …

A Self-Consistent Numerical Method For Simulation Of Quantum Transport In High Electron Mobility Transistor; Part 1: The Boltzmann-Poisson-Schrodinger Solver, Rahim Khoie

Electrical & Computer Engineering Faculty Research

A self-consistent Boltzmann-Poisson-Schrödinger solver for High Electron Mobility Transistor is presented. The quantization of electrons in the quantum well normal to the heterojunction is taken into account by solving the two higher moments of Boltzmann equation along with the Schrödinger and Poisson equations, self-consistently. The Boltzmann transport equation in the form of a current continuity equation and an energy balance equation are solved to obtain the transient and steady-state transport behavior. The numerical instability problems associated with the simulator are presented, and the criteria for smooth convergence of the solutions are discussed. The current-voltage characteristics, transconductance, gate capacitance, and unity-gain …

A Self-Consistent Numerical Method For Simulation Of Quantum Transport In High Electron Mobility Transistor; Part Ii: The Full Quantum Transport, Rahim Khoie

Electrical & Computer Engineering Faculty Research

In Part I of this paper we reported a self-consistent Boltzmann-Schrodinger-Poisson simulator for HEMT in which only electrons in the first subband were assumed to be quantized with their motion restricted to 2 dimensions. In that model, the electrons in the second and higher subbands were treated as bulk system behaving as a 3 dimensional electron gas. In Part II of this paper, we extend our simulator to a self-consistent full-quantum model in which the electrons in the second subband are also treated as quantized 2 dimensional gas. In this model, we consider the electrons in the lowest two subbands …

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

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

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

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

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

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

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

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 …