Paper
4 April 1997 Fuzzy radial basis function neural network for radar target recognition
Author Affiliations +
Abstract
The radial basis function network (RBFN) is analyzed and the fuzzy radial basis function network (FRBFN) which is more suitable for the radar target recognition is proposed in this paper. Here both of the two networks are used as classifiers. This FRBFN utilize fuzzy clustering method to determine the structure of the net. The generalization property of the two networks are discussed. It is shown from the theoretical analysis and experiment that the FRBFN has better generalization property. The Doppler echoes of the targets gotten from a current surveillance radar are used in the experiment. The experimental results shows that the classification rate of the FRBFN is higher than that of the RBFN. The network proposed in this paper is promising in the application of radar target recognition.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yunhong Wang, Guo-Sui Liu, Guangmin Sun, and Yiding Wang "Fuzzy radial basis function neural network for radar target recognition", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); https://doi.org/10.1117/12.271529
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Cited by 1 scholarly publication.
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KEYWORDS
Radar

Target recognition

Neural networks

Doppler effect

Network security

Surveillance

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