Application of Robust Statistical Methods to Data Reduction.

Abstract

Robust Statistics provides a fresh approach to the difficult problem of editing in data reduction. Of prime concern are grossly erroneous measurements which, when undetected, completely destroy automated data reduction procedures causing costly reruns and time delays with human detection of the erroneous measurements. The application of robust statistical methods has been highly successful in dealing with this problem. An introduction to the robust M-estimates and their numerical computation is given. The application of M-estimates to data preprocessing, instrument calibration, N-station cinetheodolites, N-station radar solution, and filtering are described in detail. Numerical examples of these applications using real measurements are given. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1978
Accession Number
ADA052543

Entities

People

  • Robert H. Turner
  • William S. Agee

Tags

Communities of Interest

  • Air Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Calibration
  • Computations
  • Covariance
  • Data Reduction
  • Data Science
  • Detection
  • Equations
  • Filters
  • Filtration
  • Information Processing
  • Information Science
  • Measurement
  • Measuring Instruments
  • New Mexico
  • Phototheodolites
  • Preprocessing
  • Statistics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Approximation Theory.