Multiple signal classification (MUSIC 2D) technique and self-organizing neural network applied in target radiolocation recognition

  • Authors:

  • Ioan-Gheorghe Ratiu;Adnan Khashman;Claudia-Georgeta Carstea;Nicoleta David;Lucian Patrascu

  • Affiliations:

  • Department of Mathematics, Informatics and Socio-Human Sciences, "George Baritiu" University, Brasov, Romania;Intelligent Systems Research Group, Near East University, Nicosia, Cyprus;Department of Mathematics, Informatics and Socio-Human Sciences, "George Baritiu" University, Brasov, Romania;Department of Mathematics, Informatics and Socio-Human Sciences, "George Baritiu" University, Brasov, Romania;Department of Economics Sciences, "George Baritiu" University, Brasov, Romania

  • Venue:
  • CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

The key problem in any decision-making system is to gather as much information as possible about the object or the phenomenon 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 supperresolution 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.