Evolutionary optimization for tuning nonlinear airborne sightline controllers using an image-based quality metric

Anderson, D. (2010) Evolutionary optimization for tuning nonlinear airborne sightline controllers using an image-based quality metric. In: SPIE Defence, Security & Sensing Conference, Orlando, USA, 5-9 Apr 2010, p. 769618. (doi:10.1117/12.849524)

Full text not currently available from Enlighten.

Publisher's URL: http://dx.doi.org/10.1117/12.849524

Abstract

For long-range imaging or low signal-to-noise ratio environments sightline jitter is a primary source of image degradation. The conventional pointing & stabilization figure of merit is therefore the jitter RMS, with bearing friction often the largest contributor overall. Recent work has shown that pixel smear during camera integration can be reduced if adaptive friction compensation 'shapes' the jitter frequency content in addition to reducing the RMS value. This paper extends this work by automating the tuning process for the sightline control parameters by using a genetic algorithm. The GA fitness metric is the integral of the modulation transfer function due to any residual sightline jitter. It is shown that this fitness function is significantly better than the current root-mean-square figure of merit typically employed in stabilization loop design.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Anderson, Dr David
Authors: Anderson, D.
College/School:College of Science and Engineering > School of Engineering > Aerospace Sciences

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
464201Nonlinear high performance real time control.David AndersonEngineering & Physical Sciences Research Council (EPSRC)EP/F031734/1Aerospace Sciences