Title :
Neural recognition of aerial target types using a high range resolution radar
Author_Institution :
Kharkiv Univ. of Air Forces, Ukraine
Abstract :
The combination of the least mean squares and back propagation training procedures for the ANN training is considered on the example task of recognition between 11 types of aerial objects using a high range resolution radar (HRR radar) allowing to obtain single range profiles (RP) or trains of RPs. Results of simulation are presented.
Keywords :
backpropagation; feedforward neural nets; least mean squares methods; object recognition; radar resolution; radar target recognition; ANN training; aerial object recognition; aerial target; back propagation network training; feed forward neural network; high range resolution radar; least mean square; neural recognition; single range profile; Aircraft; Artificial neural networks; Electronic mail; Feedforward neural networks; Feeds; Least mean squares methods; Missiles; Neural networks; Radar; Target recognition;
Conference_Titel :
Ultrawideband and Ultrashort Impulse Signals, 2004 Second International Workshop
Print_ISBN :
0-7803-8673-6
DOI :
10.1109/UWBUS.2004.1388056
