An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

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Resumé

Satellite tracking is a challenging task for marine applications due to the disturbance from ocean waves. An Attitude Heading and Reference System (AHRS) for measuring ship attitude, based on Microelectromechanical Systems (MEMS) sensors, is a key part for satellite tracking. In this paper, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves in high sea states. The attitude estimator algorithm is implemented in designed AHRS hardware, whose performance is validated through hardware experiment.
OriginalsprogEngelsk
TitelProceedings of OCEANS 2016 - Shanghai
Antal sider5
ForlagIEEE Press
Publikationsdatoapr. 2016
ISBN (Trykt)978-1-4673-9724-7
DOI
StatusUdgivet - apr. 2016
BegivenhedOCEANS 16: Marine Technology Society and the IEEE Oceanic Engineering Society - Monterey, CA, USA
Varighed: 19 sep. 201623 sep. 2016
http://www.oceans16mtsieeemonterey.org/

Konference

KonferenceOCEANS 16
LandUSA
ByMonterey, CA
Periode19/09/201623/09/2016
Internetadresse

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Kalman filters
Antennas
Marine applications
Hardware
Water waves
Extended Kalman filters
Covariance matrix
Accelerometers
MEMS
Ships
Sensors
Experiments

Citer dette

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title = "An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna",
abstract = "Satellite tracking is a challenging task for marine applications due to the disturbance from ocean waves. An Attitude Heading and Reference System (AHRS) for measuring ship attitude, based on Microelectromechanical Systems (MEMS) sensors, is a key part for satellite tracking. In this paper, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves in high sea states. The attitude estimator algorithm is implemented in designed AHRS hardware, whose performance is validated through hardware experiment.",
author = "Yunlong Wang and Mohsen Soltani and Hussain, {Dil muhammed Akbar}",
year = "2016",
month = "4",
doi = "10.1109/OCEANSAP.2016.7485526",
language = "English",
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publisher = "IEEE Press",

}

An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna. / Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar.

Proceedings of OCEANS 2016 - Shanghai. IEEE Press, 2016.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

AU - Wang, Yunlong

AU - Soltani, Mohsen

AU - Hussain, Dil muhammed Akbar

PY - 2016/4

Y1 - 2016/4

N2 - Satellite tracking is a challenging task for marine applications due to the disturbance from ocean waves. An Attitude Heading and Reference System (AHRS) for measuring ship attitude, based on Microelectromechanical Systems (MEMS) sensors, is a key part for satellite tracking. In this paper, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves in high sea states. The attitude estimator algorithm is implemented in designed AHRS hardware, whose performance is validated through hardware experiment.

AB - Satellite tracking is a challenging task for marine applications due to the disturbance from ocean waves. An Attitude Heading and Reference System (AHRS) for measuring ship attitude, based on Microelectromechanical Systems (MEMS) sensors, is a key part for satellite tracking. In this paper, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves in high sea states. The attitude estimator algorithm is implemented in designed AHRS hardware, whose performance is validated through hardware experiment.

U2 - 10.1109/OCEANSAP.2016.7485526

DO - 10.1109/OCEANSAP.2016.7485526

M3 - Article in proceeding

SN - 978-1-4673-9724-7

BT - Proceedings of OCEANS 2016 - Shanghai

PB - IEEE Press

ER -