AUTOMATIC RADAR TARGET RECOGNITION USING SUPERRESOLUTION MUSIC 2D IMAGES AND SELF-ORGANIZING NEURAL NETWORK (FriAmOR8)
Author(s) :
Emanuel Radoi (ENSIETA, France)
Andre Quinquis (ENSIETA, France)
Felix Totir (ENSIETA, France)
Fabrice Pellen (ENSIETA, France)
Abstract : The key problem in any decision-making system is to gather as much information as possible about the object or the phe-nomenon under study. In the case of the radar targets the frequency and angular information is integrated to form a radar image, which has high information content. A supper-resolution technique (MUSIC 2D) is used in the paper in order to reconstruct the target image. A supervised self-organizing neural network was developed to classify the images obtained in this way for ten different radar targets in an anechoic chamber.

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