Kernel density estimation on the Siegel space applied to radar processing

Emmanuel Chevallier (1) , Frédéric Barbaresco (2) , Jesus Angulo (3)

1 Weizmann Institute of Science [Rehovot, Israël]
2 Thales Air Systems
3 CMM - Centre de Morphologie Mathématique

Main techniques of probability density estimation on Riemannian manifolds are reviewed in the case of the Siegel space. For computational reasons we chose to focus on the kernel density estimation. The main result of the paper is the expression of Pelletier's kernel density estimator. The method is applied to density estimation of reflection coefficients from radar observations.

Keywords: Kernel density estimation; Siegel space; Symmetric space; Radar signals

Domains: Signal and Image Processing; Statistics [stat]

Emmanuel Chevallier, Frédéric Barbaresco, Jesus Angulo. Kernel density estimation on the Siegel space applied to radar processing. 2016. ⟨hal-01344910v2⟩