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Signal Processing

Air Force Institute of Technology

1998

Articles 1 - 9 of 9

Full-Text Articles in Engineering

Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson Sep 1998

Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson

Theses and Dissertations

Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …

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Global Positioning System (Gps) Receiver Design For Multipaths Mitigation, El-Sayed Abdel-Salam Gadallah Aug 1998

Global Positioning System (Gps) Receiver Design For Multipaths Mitigation, El-Sayed Abdel-Salam Gadallah

Theses and Dissertations

Multipath effects are a source of error degrading the accuracy of DGPS signal processing. The statistical models of multipath are determined by user location and, in addition are time varying. There is no unified statistical model for the multipath signal. Therefore the solution of the multipath problem using statistical models is difficult. This research introduces a new estimator that can detect the presence of multipath, can determine the unknown number of multipath components and can estimate multipath parameters in the GPS receiver (time delay and attenuation coefficients). Furthermore the multipath signal parameters are estimated at any instant of observation. The …

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Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki Jun 1998

Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki

Theses and Dissertations

Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L2(R) and the Hardy spaces Hp(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …

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Effects Of Clutter Height Distribution On Adaptive Clutter Erasure Performance, Kelce Steven Wilson Jun 1998

Effects Of Clutter Height Distribution On Adaptive Clutter Erasure Performance, Kelce Steven Wilson

Theses and Dissertations

A new real beam interferometric processing technique, called Adaptive Clutter Erasure (ACE), is investigated for applicability to ground clutter suppression in airborne radar systems. By analysis and simulation, the viability of the ACE concept as a next generation clutter suppression technique is demonstrated to achieve performance enhancements commensurate with currently implemented techniques. Research results indicate the ACE concept provides a reliably consistent 10dB Signal-to-Clutter Ratio (SCR) advantage over the APG-63, an operational radar system used for baseline comparison. ACE system concept development and performance predictions are conducted in conformity with the physical and operational design parameters of the APG-63, namely …

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Trigonometric Transforms For Image Reconstruction, Thomas M. Foltz Jun 1998

Trigonometric Transforms For Image Reconstruction, Thomas M. Foltz

Theses and Dissertations

This dissertation demonstrates how the symmetric convolution-multiplication property of discrete trigonometric transforms can be applied to traditional problems in image reconstruction with slightly better performance than Fourier techniques and increased savings in computational complexity for symmetric point spread functions. The fact that the discrete Fourier transform a circulant matrix provides an alternate way to derive the symmetric convolution-multiplication property for discrete trigonometric transforms. Derived in this manner, the symmetric convolution-multiplication property extends easily to multiple dimensions and generalizes to multidimensional asymmetric sequences. The symmetric convolution-multiplication property allows for linear filtering of degraded images via point-by-point multiplication in the transform domain …

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Channel-Mismatch Compensation In Speaker Identification Feature Selection And Adaptation With Artificial Neural Networks, Edmund A. Fitzgerald Mar 1998

Channel-Mismatch Compensation In Speaker Identification Feature Selection And Adaptation With Artificial Neural Networks, Edmund A. Fitzgerald

Theses and Dissertations

We develop and present results of an artificial neural network (ANN) based compensation technique for mismatched classifier training and testing conditions in speaker identification (SID). One ANN per feature per speaker is trained to perform a mapping of that feature from a corrupted condition to an undistorted condition. Therefore, a classifier trained under one condition may be used to classify data collected under a different condition. Speech utterances from 168 speakers, collected in a studio, and also re-recorded after transmission over telephone networks, are used for developing and testing the method. Peak formant resonant frequencies, their bandwidths, and pitch are …

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Linear Reconstruction Of Non-Stationary Image Ensembles Incorporating Blur And Noise Models, Stephen D. Ford Mar 1998

Linear Reconstruction Of Non-Stationary Image Ensembles Incorporating Blur And Noise Models, Stephen D. Ford

Theses and Dissertations

Two new linear reconstruction techniques are developed to improve the resolution of images collected by ground-based telescopes imaging through atmospheric turbulence. The classical approach involves the application of constrained least squares (CLS) to the deconvolution from wavefront sensing (DWFS) technique. The new algorithm incorporates blur and noise models to select the appropriate regularization constant automatically. In all cases examined, the Newton-Raphson minimization converged to a solution in less than 10 iterations. The non-iterative Bayesian approach involves the development of a new vector Wiener filter which is optimal with respect to mean square error (MSE) for a non-stationary object class degraded …

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Performance Of Imaging Laser Radar In Rain And Fog, Kathleen M. Campbell Mar 1998

Performance Of Imaging Laser Radar In Rain And Fog, Kathleen M. Campbell

Theses and Dissertations

The Air Force is currently developing imaging laser radar systems (ladar) for use on precision guided munitions and other imaging systems. Scientists at Eglin Air Force Base, in conjunction with Wright Laboratories, are testing a 1.06-um wavelength ladar system and need to understand the weather effects on the ladar images. As the laser beam propagates through the atmosphere, fog droplets and raindrops can cause image degradation, and these image degradations are manifested as either dropouts or false returns. An analysis of the dropouts and false returns helped to quantify the performance of the system in adverse weather conditions. Statistical analysis …

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Real Time Detection Of Anomalous Satellite Behavior Has Ground Based Telescope Images, Geoffrey S. Maron Mar 1998

Real Time Detection Of Anomalous Satellite Behavior Has Ground Based Telescope Images, Geoffrey S. Maron

Theses and Dissertations

Air Force analysts are faced with the task of monitoring satellites with ground based telescopes. Images are collected and analyzed in a time consuming and subjective effort to detect any behavior that is anomalous. This research maximizes use of a priori information to create an automated, real time satellite behavior classification tool. Using modeling software and knowledge of a satellite's orbit, reference imagery is created for each measured image in a satellite pass. Features are extracted from the measured and reference image pairs that provide good overall Gaussian classification accuracy (85%), reduce the dimensionality of the problem (from 32,768 down …

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