Fractional Integral Transforms and Radar Imaging in Euclidean Space
In filtering an noisy radar image, we can encounter the distortion overlapping with the desired information in the time–frequency. This is especially true when filtering noise in a radar or SAR image as such there is smearing in the image with the classical discrete Fourier Transform. That is there is chirps of much magnitudes overlapping with one another to where the radar image appears smeared. To compensate for this quandry, we propose a novel application of Discrete Fractional Fourier Transform in in Euclidean space that ascertains optimum angle of rotation in time-frequency domain to isolate the noise from rest of signal.
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- Date: 22 Sep 2023
- Time: 03:00 PM to 04:00 PM
- All times are (UTC-04:00) Eastern Time (US & Canada)
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timothy.wolfe@afit.edu
tswolfe@ieee.org
- Co-sponsored by Wright-Patt Multi-Intelligence Development Consortium (WPMDC), The DOD & DOE Communities
Speakers
Ernest Mitchell of AFRL
Fractional Integral Transforms and Radar Imaging in Euclidean Space
In filtering an noisy radar image, we can encounter the distortion overlapping with the desired information in the time–frequency. This is especially true when filtering noise in a radar or SAR image as such there is smearing in the image with the classical discrete Fourier Transform. That is there is chirps of much magnitudes overlapping with one another to where the radar image appears smeared. To compensate for this quandry, we propose a novel application of Discrete Fractional Fourier Transform in in Euclidean space that ascertains optimum angle of rotation in time-frequency domain to isolate the noise from rest of signal.
Biography:
Presently I work with customers at AFRL/RYMS in mathematical modeling of novel radar sensing and SAR imaging algorithms as the Associate Electronics Research Engineer. I am presently enrolled at Wright State University Graduate Track in Electrical Engineering: RF Systems. I have previous experiences in mathematical modeling at AFRCMC, including center point optimization for a new C-130 hangar in Marietta, GA, as well as RF modeling in optimizing sensor parameters in target acquisition and response. Among my skills acquired are: AGILE software development, Partial Differential Equations, solutions to Maxwell’s Equations, Factorial Analysis, filter design, and Real Analysis
Agenda
In filtering an noisy radar image, we can encounter the distortion overlapping with the desired information in the time–frequency. This is especially true when filtering noise in a radar or SAR image as such there is smearing in the image with the classical discrete Fourier Transform. That is there is chirps of much magnitudes overlapping with one another to where the radar image appears smeared. To compensate for this quandry, we propose a novel application of Discrete Fractional Fourier Transform in in Euclidean space that ascertains optimum angle of rotation in time-frequency domain to isolate the noise from rest of signal.
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