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Articles 1 - 14 of 14
Full-Text Articles in Signal Processing
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …