Hostname: page-component-7b7567c8c-fvjsw Total loading time: 0 Render date: 2026-11-14T10:03:21.898Z Has data issue: false hasContentIssue false
  • English
  • Français

Wavelet analysis of pilot workload in helicopter low-level flying tasks

Published online by Cambridge University Press:  04 July 2016

J. G. Jones,
G. D. Padfield and
M. T. Charlton
J. G. Jones
Affiliation:
Flight Dynamics and Simulation DepartmentDefence Evaluation and Research AgencyBedford, UK
G. D. Padfield
Affiliation:
Flight Dynamics and Simulation DepartmentDefence Evaluation and Research AgencyBedford, UK
M. T. Charlton
Affiliation:
Flight Dynamics and Simulation DepartmentDefence Evaluation and Research AgencyBedford, UK
Get accessRights & Permissions [Opens in a new window]

Abstract

As part of a programme of research to improve mission effectiveness by studying pilot workload and task performance in mission-oriented flight tasks, a methodology has been developed in which wavelet analysis is used to extract information from records of vehicle response and of pilot control activity. By decomposing the records into discrete wavelets, components of vehicle agility and pilot workload are derived in the form of wavelet-based ‘quickness’ parameters for vehicle agility and so-called ‘attack’ parameters for pilot workload. It is shown how individual wavelet components in the records of pilot control activity, referred to as ‘worklets', can be associated with the sub-tasks of ‘guidance’ and ‘stabilisation'. It is demonstrated how these concepts can be applied to quantify changes in pilot control activity associated with increasing task difficulty or changes in aircraft handling qualities. Two examples are presented, one from a flight trial in which the task difficulty was increased by changes in a prescribed ground track and the other from a simulation trial in which an increased time delay was introduced into the response of the flight control system.

Information

Type
Research Article
Information
The Aeronautical Journal , Volume 103 , Issue 1019 , January 1999, pp. 55 - 63
Copyright
Copyright © Royal Aeronautical Society 1999 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

1. Padfield, G.D., Charlton, M.T., Jones, J.P., Howell, S.E. and Bradley, R. Where does the workload go when pilots attack manoeuvres? An analysis of results from flying qualities theory and experiment, Twentieth European Rotorcraft Forum, Amsterdam, 4-7 October 1994.Google Scholar
2. Grossman, A. and Morlet, G. Decomposition of functions into wavelets of constant shape, and related transforms. In: Mathematics and Physics: Lectures on Recent Results, 1, Streit, L. (Ed), Singapore: World Scientific, 1985.Google Scholar
3. Kronland-Martinet, R., Morlet, J. and Grossman, A. Analysis of sound patterns through wavelet transforms, Int J Pattern Recognition and Artificial Intelligence, 1987, 1, (2), pp 273–302.Google Scholar
4. Watson, G.H. and Jones, J.G. Positive wavelet representation of fractal signals and images. In: Applications of Fractals and Chaos, 1993, Crilly, A.J., Earnshaw, R.A. and Jones, H. (Eds), pp 117–135, Springer-Verlag.Google Scholar
5. Jones, J.G. and Watson, G.H. Multiresolution analysis using adaptive wavelets, In: Wavelet Applications, Szu, H.H. (Ed), SPIE Proceedings, 1994, 2242, pp 119–129.Google Scholar
6. Bradley, R. and Thomson, D.G. The development and potential of inverse simulation for the quantitative assessment of helicopter handling qualities. Twentieth European Rotorcraft Forum, Amsterdam, 4-7 October 1994.Google Scholar
7. Padfield, G.D. Helicopter Flight Dynamics, BlackwellScience, Oxford, 1996.Google Scholar
8. Charlton, M.T. A report on the preparation for, conduct of and results from the EUROACTO helicopter simulation trial, DRA Working Paper FSB(92) 012, ACT-DRA-WT1-003WP, March 1992.Google Scholar