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Ocean Vessel Trajectory Estimation and Prediction Based on Extended Kalman Filter

Authors:
Lokukaluge P. Perera
Carlos Guedes Soares

Keywords: Trajectory estimation; Trajectory prediction; Target tracking; Extended Kalman Filter; Curvilinear motion model.

Abstract:
The accurate estimation and prediction of the trajectories of maneuvering vessels in ocean navigation are important tools to improve maritime safety and security. Therefore, many conventional ocean navigation systems and Vessel Traffic Management & Reporting Services are equipped with Radar facilities for this purpose. However, the accuracy of the predictions of maneuvering trajectories of vessels depends mainly on the goodness of estimation of vessel position, velocity and acceleration. Hence, this study presents a maneuvering ocean vessel model based on a curvilinear motion model with the measurements based on a linear position model for the same purpose. Furthermore, the system states and measurements models associated with a white Gaussian noise are also assumed. The Extended Kalman Filter is proposed as an adaptive filter algorithm for the estimation of position, velocity and acceleration that are used for prediction of maneuvering ocean vessel trajectory. Finally, the proposed models are implemented and successful computational results are obtained with respect to prediction of maneuvering trajectories of vessels in ocean navigation in this study.

Pages: 14 to 20

Copyright: Copyright (c) IARIA, 2010

Publication date: November 21, 2010

Published in: conference

ISSN: 2308-4146

ISBN: 978-1-61208-109-0

Location: Lisbon, Portugal

Dates: from November 21, 2010 to November 26, 2010