Mathematical Models and Monte-Carlo Algorithms for Improved Detection of Targets in the Commercial Maritime Domain



Vladimirov, Lyudmil ORCID: 0000-0003-3521-7085
(2021) Mathematical Models and Monte-Carlo Algorithms for Improved Detection of Targets in the Commercial Maritime Domain. Doctor of Philosophy thesis, University of Liverpool.

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Abstract

Commercial Vessel Traffic Monitoring Services (VTMSs) are widely used by port authorities and the military to improve the safety and efficiency of navigation, as well as to ensure the security of ports and marine life as a whole. Technology based on the Kalman Filtering framework is in widespread use in modern operational VTMS systems. At a research level, there has also been a significant interest in Particle Filters, which are widely researched but far less widely applied to deliver an operational advantage. The Monte-Carlo nature of Particle Filters places them as the ideal candidate for solving the highly non-linear, non-Gaussian problems encountered by modern VTMS systems. However, somewhat counter-intuitively, while Particle Filters are best suited to exploit such non-linear, non-Gaussian problems, they are most frequently used within a context that is mostly linear and Gaussian. The engineering challenge tackled by the PhD project reported in this thesis was to study and experiment with models that are well placed to capitalise on the abilities of Particle Filters and to develop solutions that make use of such models to deliver a direct operational advantage in real applications within the commercial maritime domain.

Item Type: Thesis (Doctor of Philosophy)
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 21 Jun 2021 14:34
Last Modified: 18 Jan 2023 22:53
DOI: 10.17638/03118824
Supervisors:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3118824