Title :
Target identification using neural nets and C4.5
Author_Institution :
Inf. Technol. Div., Defence Sci. & Technol. Organ., Salisbury, SA, Australia
fDate :
29 Nov-2 Dec 1994
Abstract :
This paper addresses the application of linear prediction with the backpropagation neural network (BPNN) and C4.5 for distinguishing jet and propeller driven aircraft using Doppler spectra derived from a continuous-wave (CW) coherent (X band) radar. To verify the BPNN´s and C4.5´s classification of the data random noise was added to the Doppler data and results from both techniques compared
Keywords :
CW radar; Doppler radar; aircraft; backpropagation; learning (artificial intelligence); military computing; neural nets; radar computing; random noise; C4.5; Doppler spectra; backpropagation neural network; continuous-wave coherent radar; data classification; jet aircraft; linear prediction; neural nets; propeller driven aircraft; random noise; target identification; Airborne radar; Aircraft; Backpropagation; Blades; Doppler radar; Neural networks; Propellers; Radar applications; Radar signal processing; Signal to noise ratio;
Conference_Titel :
Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-7803-2404-8
DOI :
10.1109/ANZIIS.1994.396941
