Kernel density estimation on the Siegel space applied to radar processing - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year :

Kernel density estimation on the Siegel space applied to radar processing

Abstract

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.
Fichier principal
Vignette du fichier
kernelSiegel.pdf (1.65 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01344910 , version 1 (12-07-2016)
hal-01344910 , version 2 (13-07-2016)

Identifiers

  • HAL Id : hal-01344910 , version 2

Cite

Emmanuel Chevallier, Frédéric Barbaresco, Jesus Angulo. Kernel density estimation on the Siegel space applied to radar processing. 2016. ⟨hal-01344910v2⟩
4696 View
132 Download

Share

Gmail Facebook Twitter LinkedIn More