Title :
Performance of radar target recognition schemes using neural networks-a comparative study
Author :
Nandagopal, D. ; Martin, N.M. ; Johnson, R.P. ; Lozo, P. ; Palaniswami, M.
Author_Institution :
Guided Weapons Div., Defence Sci. & Technol. Organ., Salisbury, SA, Australia
Abstract :
Doppler signatures of experimental radar targets have been obtained and processed using conventional signal processing techniques to extract characteristic features. Radar target recognition using adaptive resonance theory, learning vector quantiser, feedforward, and probabilistic neural networks has been attempted. The performance characteristics of the above neural architectures in classifying the experimental radar targets are discussed and the results of a comparative study presented
Keywords :
ART neural nets; Doppler radar; feature extraction; feedforward neural nets; multilayer perceptrons; pattern classification; radar computing; radar signal processing; radar target recognition; self-organising feature maps; vector quantisation; Doppler signatures; adaptive resonance theory; comparative study; feedforward neural networks; learning vector quantiser; neural network; probabilistic neural networks; radar target recognition schemes; Artificial neural networks; Doppler radar; Neural networks; Neurons; Radar scattering; Radar signal processing; Radar tracking; Resonance; Target recognition; Target tracking;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389574
