DocumentCode
956971
Title
Low-angle radar tracking using radial basis function neural network
Author
Wong, T. ; Lo, T. ; Leung, H. ; Litva, J. ; Bosse, E.
Author_Institution
Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada
Volume
140
Issue
5
fYear
1993
fDate
10/1/1993 12:00:00 AM
Firstpage
323
Lastpage
328
Abstract
The authors apply the radial basis function (RBF) neural network to low-angle radar tracking. Computer simulations show that the RBF network is capable of tracking both stationary and moving targets with high accuracy. Also, the tracking performance of the RBF network is evaluated under different signal-to-noise ratio situations. Real-life data are used to test the RBF network. The results demonstrate the robustness and effectiveness of the network in terms of its independence of array errors and of the nature of the noise background
Keywords
array signal processing; feedforward neural nets; radar theory; tracking; computer simulations; low-angle radar tracking; oving targets; radial basis function neural network; robustness; signal processing; signal-to-noise ratio; stationary targets;
fLanguage
English
Journal_Title
Radar and Signal Processing, IEE Proceedings F
Publisher
iet
ISSN
0956-375X
Type
jour
Filename
238228
Link To Document