The University of Southampton
University of Southampton Institutional Repository

Multi-Sensor Data Fusion for Helicopter Guidance using Neuro-Fuzzy Estimation Algorithms

Doyle, R.S. and Harris, C.J. (1996) Multi-Sensor Data Fusion for Helicopter Guidance using Neuro-Fuzzy Estimation Algorithms The Royal Aeronautical Society Journal, 241--251.

Record type: Article

Abstract

The purpose of this paper is to describe an approach that performs data fusion on the output of multiple spatially separate sensors engaged in the real time tracking of obstacles in a helicopter's environment. The generated information can be used either as a flight director aid or as feedback required by an automatic collision avoidance system. Obstacle track estimation has been commonly carried out using the Kalman Filter (KF) for linear estimation, or the Extended Kalman Filter (EKF) for use on non-linear problems. However certain assumptions made in the derivation of the EKF algorithms render it sub-optimal for aerial obstacle track estimation. Additionally the EKF has problems with initialisation and divergence (stability) for many non-linear processes. Research at the University of Southampton has highlighted a link between fuzzy networks and associative memory neural networks. This link is important as it allows new learning rules to be developed for training fuzzy rules, and learning convergence to be proved. This paper will explore methods for the fusion of estimates using these neurofuzzy models, and also address some of the weakness of the Kalman filter approximation introduced by the assumptions made in its derivation.

Full text not available from this repository.

More information

Published date: June 1996
Additional Information: Awarded 1996 Simms prize for best paper in electrical and electronic systems
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250167
URI: http://eprints.soton.ac.uk/id/eprint/250167
PURE UUID: c6a119a9-6c10-4e33-b03c-1d6daaf63020

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:43

Export record

Contributors

Author: R.S. Doyle
Author: C.J. Harris

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×