Abstract
Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method.
Highlights
Methods to produce sharper delineated objects at depth using ground penetrating radar (GPR) is a continuing topic of study
We explore using a chirp excitation function-based radar to replace the multiple frequency scans used in the EM Gaussian mixture model (GMM) algorithm analysis, comparing the result with EM processed scans
Our EM developed method, the compositing of GPR scans [1,2,3,4,5], was preceded by Dougherty et al [20] who focused on a method to subtract the direct arrival pulse and combine each signal weighted with equal magnitudes
Summary
Methods to produce sharper delineated objects at depth using ground penetrating radar (GPR) is a continuing topic of study. Imaging results from ground-based scans and scans at various heights have benefited from the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm technique [1,2,3,4,5] of combining scans at differing frequencies over the same terrain. We explore using a chirp excitation function-based radar to replace the multiple frequency scans used in the EM GMM algorithm analysis, comparing the result with EM processed scans.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
