A Support Vector Machine MUSIC Algorithm Articles uri icon

authors

  • El Gonnouni, A.
  • MARTINEZ RAMON, MANUEL
  • ROJO ALVAREZ, JOSE LUIS
  • CAMPS-VALLS, GUSTAVO
  • FIGUEIRAS VIDAL, ANIBAL RAMON
  • Christodoulou, C.G.

publication date

  • October 2012

start page

  • 4901

end page

  • 4910

issue

  • 10

volume

  • 60

International Standard Serial Number (ISSN)

  • 0018-926X

Electronic International Standard Serial Number (EISSN)

  • 1558-2221

abstract

  • This paper introduces a new Support Vector Machine (SVM) formulation for the direction of arrival (DOA) estimation problem. We establish a theoretical relationship between the Minimum Variance Distortionless Response (MVDR) and the MUltiple SIgnal Characterization (MUSIC) methods. This leads naturally to the derivation of an SVM-MUSIC algorithm, which combines the benefits of subspace methods with those of SVM. Spatially smoothed versions and a recursive form of the algorithms exhibit good performance against coherent signals. We test the method's performance in scenarios with noncoherent and coherent signals, and in small-sample size-situations obtaining an improved performance in comparison with existing standard approaches.