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Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system

Abstract

Depending on standards and class, dynamically positioned ships make use of different numbers of redundant sensors to determine current ship position. The paper presents a multi-sensor data fusion algorithm for the dynamic positioning system which allows it to record the proper signal from a number of sensors (GPS receivers). In the research, the Particle Kalman Filter with data fusion was used to estimate the position of the vessel. The presented algorithms generate a virtual measurement using three measurements from independent sensors. The performance of the Particle Kalman Filter algorithm was evaluated in simulation tests for two specific cases: in regular operation and when the signal of one sensor disappears.

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Details

Category:
Conference activity
Type:
materiały konferencyjne indeksowane w Web of Science
Title of issue:
Methods and Models in Automation and Robotics (MMAR), 2017 22nd International Conference on strony 1 - 4
Language:
English
Publication year:
2017
Bibliographic description:
Jaroś K., Witkowska A., Śmierzchalski R..: Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system, W: Methods and Models in Automation and Robotics (MMAR), 2017 22nd International Conference on, 2017, ,.
DOI:
Digital Object Identifier (open in new tab) 10.1109/mmar.2017.8046804
Verified by:
Gdańsk University of Technology

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