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Ship track estimation using GPS data and Kalman Filter

Assaf, Mansour and Petriu, E.M. and Groza, V.Z. (2018) Ship track estimation using GPS data and Kalman Filter. [Conference Proceedings]

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Abstract

Extended Kalman Filter (EKF) is a technique used in non-linear applications and dynamic systems identification (e.g. tracking marine vessels and ships) that require state and parameter estimation. This paper studies Kalman Filter (KF) based techniques for tracking ships using Global Positioning System (GPS) data. The present work proposes to exploit information from GPS sensors in order to track a ship in real-time. The absence and presence problem of a ship is handled by a applying KF theory to analyze GPS coordinates and compare current marine vessel routes to previously recorded ones. To study tracking performance, the system was implemented in C++ and simulation results demonstrate the feasibility and high accuracy of the proposed tracking method.

Item Type: Conference Proceedings
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Mansour Assaf
Date Deposited: 30 Aug 2018 12:57
Last Modified: 30 Aug 2018 12:57
URI: http://repository.usp.ac.fj/id/eprint/10929
UNSPECIFIED

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