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Real-Time Localization of a Magnetic Anomaly: A Study of the Effectiveness of a Genetic Algorithm for Implementation on an Autonomous Underwater Vehicle

The primary objective of this research is to investigate the viability of magnetic
anomaly localization with an autonomous underwater vehicle, using a genetic algorithm
(GA). The localization method, first proposed by Sheinker. et al. 2008, is optimized here
for the case of a moving platform. Extensive magnetic field modeling and algorithm
simulation has been conducted and yields promising results. Field testing of the method is
conducted with the use of the Ocean Floor Geophysics Self-Compensating Magnetometer
(SCM). Extensive out-of-water field testing is conducted to validate the ability to
measure a target signal in a uniform NED frame as well as to validate the effectiveness of
the GA. The outcome of the simulation closely matches the results of the conducted field
tests. Additionally, the SCM is fully integrated with FAU’s Remus 100 AUV and
preliminary in-water testing of the system has been conducted. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Identiferoai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_39783
ContributorsPhilippeaux, Harryel Arsene (author), Dhanak, Manhar R. (Thesis advisor), Florida Atlantic University (Degree grantor), College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
PublisherFlorida Atlantic University
Source SetsFlorida Atlantic University
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation, Text
Format105 p., application/pdf
RightsCopyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/

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