Multi-Sensor Data Fusion for Obstacle Tracking using Neuro-Fuzzy Estimation Algorithms
Doyle, R. and Harris, C.J. (1994) Multi-Sensor Data Fusion for Obstacle Tracking using Neuro-Fuzzy Estimation Algorithms. Optical Engineering in Aerospace Sensing: Sensor Fusion and Aerospace Applications II
Download
Full text not available from this repository.
Description/Abstract
The problem addressed in this paper is that of estimating the tracks of dynamic obstacles in the environment of a helicopter operating in hazardous conditions. Fuzzy logic and neural networks have shown their strength in recent years in the solutions to non-linear problems. The aim of this paper is to present neuro-fuzzy data fusion algorithms which can be used to fuse information provided by multiple spatially separate sensors engaged in the tracking of obstacles whose dynamics are a priori unknown.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | Organisation: SPIE Address: Orlando, FL |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 250262 |
| Date Deposited: | 04 May 1999 |
| Last Modified: | 02 Mar 2012 11:56 |
| Contributors: | Doyle, R. (Author) Harris, C.J. (Author) |
| Date: | 1994 |
| Additional Information: | Organisation: SPIE Address: Orlando, FL |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/250262 |
Actions (login required)
 |
View Item |
