Ocean Vessel Trajectory estimation and prediction based on Extended Kalman Filter

2010

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.

Autores da comunidade :

• 

  L

  Lokukaluge Prasad Channa Perera

  ist33250

• 

  C

  Carlos Guedes Soares

  ist11869

  Afiliações e fontes

  IST > CENTEC

  Centro de Engenharia e Tecnologia Naval e Oceânica

  De: cienciavitae

  ID: 1086454

VoR - Versão publicada

Proceedings of the Second International Conference on Adaptive and Self-adaptive Systems and Applications (ADAPTIVE 2010)

Lisbon, Portugal

21 de novembro de 2010

26 de novembro de 2010

14

20

other-engineering-and-technologies - Outras Ciências da Engenharia e Tecnologias

Palavras-chave

• Trajectory estimation
• Trajectory prediction
• Target tracking
• Extended Kalman Filter
• Curvilinear motion model

eng - Inglês