Search
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.
Citations
-
5
CrossRef
-
0
Web of Science
-
8
Scopus
Authors (3)
Cite as
Full text
full text is not available in portal
Keywords
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
seen 121 times