Feasibility Studies for the Prediction of the Gravity Disturbance Vector in High Altitudes,

Abstract

The accuracy of the gravity disturbance vector in high altitude (30,000 - 200,000 feet), predicted from a surface-covering set of mean gravity anomalies, is estimated. Two methods are used and found to provide estimates which differ by less than 10%, the least-squares collocation and the integral solution. For the integral solution, the estimation of the representation error has been performed in the frequency domain. For the collocation solution an optimal algorithm has been developed which takes advantage of the regular data distribution and is up to 64 times faster than a non-optimized solution. Results indicate that the radial component of the gravity disturbance vector can be estimated with an accuracy of + or - 1 mgal at an altitude of about 50,000 ft on the basis of the available data sets; in order to achieve the same accuracy at 30,000 ft altitude, the data error, particularly that of 5 ft. x 5 ft. anomalies, has to be reduced by some 60%; the available data distributions are adequate. The prediction error drops quickly with increasing altitude. The situation is considerably different for the horizontal component: with the best available data distribution an accuracy of + or - 2.3 mgal at 30,000 ft altitude can be achieved; (this corresponds to + or - 0.5 sec in the direction of the gravity vector).

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1981
Accession Number
ADA102943

Entities

People

  • Hans Suenkel

Organizations

  • Ohio State University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Algorithms
  • Altitude
  • Computations
  • Data Sets
  • Eigenvalues
  • Elevation
  • Frequency
  • Frequency Domain
  • Gravity Anomalies
  • High Altitude
  • Integrals
  • Spherical Harmonics
  • Step Functions
  • United States
  • Universities

Readers

  • Approximation Theory.
  • Marine Hydrodynamics
  • Mathematics or Statistics