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Radar cross section of an open-ended rectangular waveguide cavity: A massively parallel implementation applied to high-resolution radar cross section imaging
Title
Radar cross section of an open-ended rectangular waveguide cavity: A massively parallel implementation applied to high-resolution radar cross section imaging.
Creator
Vann, Laura Dominick., Florida Atlantic University, Helmken, Henry, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This thesis is concerned with adapting a sequential code that calculates the Radar Cross Section (RCS) of an open-ended rectangular waveguide cavity to a massively parallel computational platform. The primary motivation for doing this is to obtain wideband data over a large range of incident angles in order to generate a two-dimensional radar cross section image. Images generated from measured and computed data will be compared to evaluate program performance. The computer used in this...
Show moreThis thesis is concerned with adapting a sequential code that calculates the Radar Cross Section (RCS) of an open-ended rectangular waveguide cavity to a massively parallel computational platform. The primary motivation for doing this is to obtain wideband data over a large range of incident angles in order to generate a two-dimensional radar cross section image. Images generated from measured and computed data will be compared to evaluate program performance. The computer used in this implementation is a MasPar MP-1 single instruction, multiple data massively parallel computer consisting of 4,096 processors arranged in a two-dimensional mesh. The algorithm uses the mode matching method of analysis to match fields over the cavity aperture to obtain an expression for the scattered far field.
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Date Issued
1993
PURL
http://purl.flvc.org/fcla/dt/14984
Subject Headings
Radar cross sections, Algorithms--Data processing, Imaging systems
Format
Document (PDF)
maximum entropy bandwidth extrapolation technique using wavelet subspaces
Title
A maximum entropy bandwidth extrapolation technique using wavelet subspaces.
Creator
Vann, Laura Dominick., Florida Atlantic University, Helmken, Henry, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This dissertation is concerned with the development of a bandwidth extrapolation technique that performs maximum entropy estimations over wavelet subspaces. Bandwidth extrapolation techniques have been used in radar applications to improve range and cross range resolution of radar cross section (RCS) images. Comparisons are made of the performance of conventional maximum entropy estimation to maximum entropy estimation over wavelet subspaces. A least squares prediction error measure is used...
Show moreThis dissertation is concerned with the development of a bandwidth extrapolation technique that performs maximum entropy estimations over wavelet subspaces. Bandwidth extrapolation techniques have been used in radar applications to improve range and cross range resolution of radar cross section (RCS) images. Comparisons are made of the performance of conventional maximum entropy estimation to maximum entropy estimation over wavelet subspaces. A least squares prediction error measure is used to compare original measured RCS data to extrapolated data. Then a relative error is defined as the ratio of prediction error using conventional maximum entropy to prediction error using maximum entropy over wavelet subspaces. Application of the bandwidth extrapolation technique is to measured RCS data of two objects. The first object consists of two 3/8" diameter conducting spheres placed 4" apart. Measurements used are for vertical polarization and 0 degree aspect angle covering a frequency range of 8.0 to 12.3827 GHz. The second object is a 1.6 meter aluminum cone. Measurements used are for vertical polarization and 0 degree aspect angle (nose on) covering a frequency range of 4.64 to 18.00 GHz. Results are shown for extrapolate measured data plus the original data with Gaussian white noise added to noise ratios of 25 dB, 20 dB, 15 dB, and 10 dB.
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Date Issued
1997
PURL
http://purl.flvc.org/fcla/dt/12531
Subject Headings
Maximum entropy method, Wavelets (Mathematics), Radar cross sections
Format
Document (PDF)