Non-zero mean Gaussian process prior wind field models


This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.

Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Uncontrolled Keywords: polynomial-exponential covariance function,Gaussian process,local wind vector,multi-variate
ISBN: NCRG/98/020
PURE Output Type: Technical report
Published Date: 1998
Authors: Cornford, Dan (ORCID Profile 0000-0001-8787-6758)


Export / Share Citation


Additional statistics for this record