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 :
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