STUDY OF AIRCRAFT SEPARATION CRITERIA.

Abstract

The purposes of this study are (1) identification of the significant factors that influence en route separation minima for aircraft in flight and (2) development of a mathematical model that functionally relates these factors. Both radar and non-radar modes of ATC are considered; only the domestic ATC and the domestic navigational environment are included; variable aircraft spacings are not explicitly analyzed and are considered only to the extent that they influence the fixed standards; and the computation of specific spacing criteria is undertaken only for illustrative purposes. The result of this effort is that the smallest and least detailed set of factors characterizing the problem at hand have been identified, and these have been related to each other by a general model utilizing the mathematics of probability theory. These factors are the distance, time, and speed relationships of the aircraft involved, and, most importantly, the probability theory. These factors are the distance, time, and speed relationships of the aircraft involved, and, most importantly, the probability density functions which describe the accuracy to which these variables are known to the data processing, decision-making, and control elements of the system. The model is believed to be completely exhaustive in that any source of error in the entire ATC system should be identifiable as a component of one of the three basic errors. (Author)

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1964
Accession Number
AD0700304

Entities

People

  • Joseph W. Little
  • Lyle D. Filkins

Organizations

  • University of Michigan

Tags

DTIC Thesaurus Topics

  • Aircrafts
  • Computations
  • Data Processing
  • Domestic
  • Errors
  • Mathematical Models
  • Mathematics
  • Models
  • Probability
  • Probability Density Functions

Readers

  • Aerospace Test and Evaluation
  • Computational Modeling and Simulation
  • Geodesy

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space