Monotonous trend estimation of deck displacement for automatic landing of rotorcraft UAVs

Yang, Xilin, Garratt, Matt, & Pota, Hemanshu (2011) Monotonous trend estimation of deck displacement for automatic landing of rotorcraft UAVs. Journal of Intelligent & Robotic Systems, 61(1), pp. 267-285.

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This paper presents a novel and practical procedure for estimating the mean deck height to assist in automatic landing operations of a Rotorcraft Unmanned Aerial Vehicle (RUAV) in harsh sea environments. A modified Prony Analysis (PA) procedure is outlined to deal with real-time observations of deck displacement, which involves developing an appropriate dynamic model to approach real deck motion with parameters identified through implementing the Forgetting Factor Recursive Least Square (FFRLS) method. The model order is specified using a proper order-selection criterion based on minimizing the summation of accumulated estimation errors. In addition, a feasible threshold criterion is proposed to separate the dominant components of deck displacement, which results in an accurate instantaneous estimation of the mean deck position. Simulation results demonstrate that the proposed recursive procedure exhibits satisfactory estimation performance when applied to real-time deck displacement measurements, making it well suited for integration into ship-RUAV approach and landing guidance systems.

Impact and interest:

2 citations in Scopus
2 citations in Web of Science®
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ID Code: 63435
Item Type: Journal Article
Refereed: Yes
Additional Information: The final publication is available at
Keywords: Prony analysis, Automatic landing, Unmanned aerial system
DOI: 10.1007/s10846-010-9474-z
ISSN: 1573-0409
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MARITIME ENGINEERING (091100) > Ship and Platform Hydrodynamics (091104)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: UNSW at Canberra
Deposited On: 16 Oct 2013 06:04
Last Modified: 30 Oct 2013 16:28

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