Mapping electron density in the ionosphere: a principal component MCMC algorithm

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The outer layers of the Earth's atmosphere are known as the ionosphere, a plasma of free electrons and positively charged atomic ions. The electron density of the ionosphere varies considerably with time of day, season, geographical location and the sun's activity. Maps of electron density are required because local changes in this density can produce inaccuracies in the Navy Navigation Satellite System (NNSS) and Global Positioning System (GPS). Satellite to ground based receiver measurements produce tomographic information about the density in the form of path integrated snapshots of the total electron content which must be inverted to generate electron density maps. A Bayesian approach is proposed for solving the inversion problem using spatial priors in a parsimonious model for the variation of electron density with height. The Bayesian approach to modelling and inference provides estimates of electron density along with a measure of uncertainty for these estimates, leading to credible intervals for all quantities of interest. The standard parameterisation does not lend itself well to standard Metropolis-Hastings algorithms. A much more efficient form of Markov chain Monte Carlo sampler is developed using a transformation of variables based on a principal components analysis of initial output.
Original languageEnglish
Pages (from-to)338-352
Number of pages15
JournalComputational Statistics & Data Analysis
Volume55
Issue number1
Early online date8 May 2010
DOIs
Publication statusPublished - 1 Jan 2011

Fingerprint

MCMC Algorithm
Ionosphere
Principal Components
Carrier concentration
Electron
Satellites
Bayesian Approach
Earth atmosphere
Electrons
Parameterization
Credible Interval
Sun
Principal component analysis
Markov processes
Metropolis-Hastings Algorithm
Global positioning system
Global Positioning System
Navigation
Snapshot
Markov Chain Monte Carlo

Keywords

  • tomography
  • inversion
  • Bayesian modelling
  • principal components
  • Markov chain Monte Carlo
  • ionospheric mapping

Cite this

Mapping electron density in the ionosphere: a principal component MCMC algorithm. / Khorsheed, E; Hurn, Merrilee; Jennison, Christopher.

In: Computational Statistics & Data Analysis, Vol. 55, No. 1, 01.01.2011, p. 338-352.

Research output: Contribution to journalArticle

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