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

Yunlong Wang; Mohsen Soltani; Dil muhammed Akbar Hussain

doi:10.1109/OCEANSAP.2016.7485526

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

Yunlong Wang, Mohsen Soltani, Dil muhammed Akbar Hussain

AAU Energy

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceedings of OCEANS 2016 - Shanghai
Number of pages	5
Publisher	IEEE Press
Publication date	Apr 2016
ISBN (Print)	978-1-4673-9724-7
DOIs	https://doi.org/10.1109/OCEANSAP.2016.7485526
Publication status	Published - Apr 2016
Event	OCEANS 16: Marine Technology Society and the IEEE Oceanic Engineering Society - Monterey, CA, United States Duration: 19 Sept 2016 → 23 Sept 2016 http://www.oceans16mtsieeemonterey.org/

Conference

Conference	OCEANS 16
Country/Territory	United States
City	Monterey, CA
Period	19/09/2016 → 23/09/2016
Internet address	http://www.oceans16mtsieeemonterey.org/

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10.1109/OCEANSAP.2016.7485526

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Star2Com: Stabilization and control of Satellite-tracking antennas for marine Communication (Star2 Com)
N. Soltani, M., Pedersen, J. K., Yang, Z., Nielsen, P. & Christensen, J.
HTF
01/04/2014 → 31/10/2017
Project: Research

Cite this

@inproceedings{6430d60246374240bb22c91bfd9b8488,

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 = apr,

doi = "10.1109/OCEANSAP.2016.7485526",

language = "English",

isbn = "978-1-4673-9724-7",

booktitle = "Proceedings of OCEANS 2016 - Shanghai",

publisher = "IEEE Press",

note = "OCEANS 16 : Marine Technology Society and the IEEE Oceanic Engineering Society ; Conference date: 19-09-2016 Through 23-09-2016",

url = "http://www.oceans16mtsieeemonterey.org/",

}

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

T2 - OCEANS 16

Y2 - 19 September 2016 through 23 September 2016

ER -

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

Abstract

Conference

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Projects

Star2Com: Stabilization and control of Satellite-tracking antennas for marine Communication (Star2 Com)

Cite this