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1- PHD student of Marine Engineering, Sharif University of Technology
2- Professor, Center of Excellence in Hydrodynamics & Dynamics of Marine Vehicle, Sharif University of Technology
2- Professor, Center of Excellence in Hydrodynamics & Dynamics of Marine Vehicle, Sharif University of Technology
Abstract: (259 Views)
| The accurate estimation and prediction of the trajectories of maneuvering vessels in navigation are important tools to improve maritime safety and security. Therefore, many conventional 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. In this article, the information related to two navigation devices named GPS and INS is collected and by giving the data obtained from the system identification and using the equations of the developed Kalman filter algorithm, the path and position of the two zigzag and bypass maneuvers are estimated. to be and finally, after estimating the maneuvering path, the movement of the float is validated with the experimental movement recorded by the navigation devices Among the innovations that can be mentioned in this article is the integration of the control system design based on the dynamic model for a high-speed boat. Because the work on the high-speed float using the system identification method is very limited. The reason for using the developed Kalman filter method is that this method is able to estimate several unknowns in a nonlinear system by only having measured inputs from model testing. |
Keywords: Dynamic model, Extended Kalman filter, Maneuver, System identification, Estimate the situation
Type of Study: Research Paper |
Subject:
Ship Hydrodynamic
Received: 2024/06/9 | Accepted: 2025/02/27
Received: 2024/06/9 | Accepted: 2025/02/27
References
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International Journal of Maritime Technology is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License.