← Back to list of papers of the 2019 EuroGNC conference

CEAS EuroGNC 2019

Adaptive Prediction for Ship Motion in Rotorcraft Maritime Operations

Antoine Monneau Informatics and Sciences Laboratory (LIS) UMR CNRS 7020 of AMU, the Aix Marseille Univeristy and Airbus Helicopters, Marignane, France
Nacer K M'Sirdi Informatics and Sciences Laboratory (LIS) UMR CNRS 7020 of AMU, the Aix Marseille Univeristy
Sebastien Mavromatis Informatics and Sciences Laboratory (LIS) UMR CNRS 7020 of AMU, the Aix Marseille Univeristy
Guillaume Varra Airbus Helicopters, Marignane, France
Marc Salesse Airbus Helicopters, Marignane, France
Jean Sequeira Informatics and Sciences Laboratory (LIS) UMR CNRS 7020 of AMU, the Aix Marseille Univeristy
Abstract:
This paper focuses on motion prediction for a ship navigating through sea swell. Ship motion prediction may be useful for helicopter maritime operations, notably for search and rescue missions. An efficient prediction method based on adaptive notch filters (ANF) is proposed for non stationary perturbations. Classic methods of prediction are reviewed for comparison. An application using real ship motion data is considered in a performance evaluation. Finally, a comparative analysis based on prediction performance and real-time implementation constraints is presented.
Keywords: Aircraft trajectory planning; Parameter estimation; Robust and adaptive filtering
View PDFCEAS-GNC-2019-068


Antoine Monneau, Nacer K M'Sirdi, Sebastien Mavromatis, Guillaume Varra, Marc Salesse, Jean Sequeira: Adaptive Prediction for Ship Motion in Rotorcraft Maritime Operations. Proceedings of the 2019 CEAS EuroGNC conference. Milan, Italy. April 2019. CEAS-GNC-2019-068.
BibTeX entry:

@Incollection{CEAS-GNC-2019-068,
    authors = {Monneau, Antoine and M'Sirdi, Nacer K and Mavromatis, Sebastien and Varra, Guillaume and Salesse, Marc and Sequeira, Jean},
    title = {Adaptive Prediction for Ship Motion in Rotorcraft Maritime Operations},
    booktitle = {Proceedings of the 2019 {CEAS EuroGNC} conference},
    address = {Milan, Italy},
    month = apr,
    year = {2019},
    note = {CEAS-GNC-2019-068}
}