• DocumentCode
    49253
  • Title

    Riemannian Medians and Means With Applications to Radar Signal Processing

  • Author

    Arnaudon, M. ; Barbaresco, F. ; Le Yang

  • Author_Institution
    Lab. de Mathemathiques et Applic., Univ. de Poitiers, Chasseneuil, France
  • Volume
    7
  • Issue
    4
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    595
  • Lastpage
    604
  • Abstract
    We develop a new geometric approach for high resolution Doppler processing based on the Riemannian geometry of Toeplitz covariance matrices and the notion of Riemannian p -means. This paper summarizes briefly our recent work in this direction. First of all, we introduce radar data and the problem of target detection. Then we show how to transform the original radar data into Toeplitz covariance matrices. After that, we give our results on the Riemannian geometry of Toeplitz covariance matrices. In order to compute p-means in practical cases, we propose deterministic and stochastic algorithms, of which the convergence results are given, as well as the rate of convergence and error estimates. Finally, we propose a new detector based on Riemannian median and show its advantage over the existing processing methods.
  • Keywords
    Doppler radar; Toeplitz matrices; covariance matrices; deterministic algorithms; radar detection; radar signal processing; stochastic processes; Radar signal processing; Riemannian geometry; Riemannian means; Riemannian medians; Toeplitz covariance matrices; deterministic algorithm; high resolution Doppler processing; signal detector; stochastic algorithm; target detection; Covariance matrices; Manifolds; Measurement; Radar detection; Signal processing algorithms; Vectors; Mean; Riemannian geometry; Toeplitz covariance matrix; median; radar target detection;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Signal Processing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1932-4553
  • Type

    jour

  • DOI
    10.1109/JSTSP.2013.2261798
  • Filename
    6514112