Assaf, Mansour and Petriu, E.M. and Groza, V.Z. (2018) Ship track estimation using GPS data and Kalman Filter. [Conference Proceedings]
Full text not available from this repository. (Request a copy)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 |
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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 00:57 |
Last Modified: | 30 Aug 2018 00:57 |
URI: | https://repository.usp.ac.fj/id/eprint/10929 |
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