Optimal Space-Time Interpolation of Gappy Frontal Position Data,

Abstract

The primary goal of this study is to develop an improved algorithm for space-time interpolation of gappy frontal data sets. The major improvements are the inclusions of (1) two-dimensional phase speed, (2) a more autonomous algorithm, (3) a better feature matching algorithm, and (4) the inclusion of a temporal smoothness constraint. The space-time interpolator is formulated in framework of probabilities (Bayesian) estimation. This report first reviews such an estimation theoretic framework and, in particular, a Kalman filter-based interpolation algorithm. Then, feature detection and matching algorithms are discussed, followed by presentation and discussion of some preliminary results

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1993
Accession Number
ADP008739

Entities

People

  • Arthur J. Mariano
  • Toshio M. Chin

Organizations

  • Rosenstiel School of Marine, Atmospheric, and Earth Science

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Data Sets
  • Detection
  • Filters
  • Inclusions
  • Interpolation
  • Kalman Filters
  • Mathematics
  • Oceanography
  • Physical Oceanography
  • Probability
  • Two Dimensional
  • Workshops

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.
  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space