TWO-DIMENSIONAL POINT RESOLUTION,

Abstract

A hypothesis test has been designed for a situation which arises when multiple sensors observe the positions and only the positions of vessels in a specified region of the ocean. Given that two sensors each observe the position of a vessel, the problem is to determine whether the sensors observed the position of the same vessel or the positions of different vessels. Assuming the observations occur at the same time and the observation errors are normally distributed with known covariance matrices, it is a simple matter to design a test to test the null hypothesis that the observations refer to the same vessel against the alternative hypothesis that the observations refer to different vessels. This test is designed to have a fixed but arbitrary probability of the type 1 error (concluding that the observations refer to different vessels when they actually do not). Remaining is the question of the probability of the type 2 error (concluding that the observations refer to the same vessel when they actually do not). Without a complete statistical description of the processes, one cannot answer this question exactly. The authors have only assumed that the number of vessels in any subregion is a Poisson random variable having for the parameter the product of a constant and the area of the subregion, the constant being the expected number of vessels per unit area. Under this condition the least upper bound for the probability of the type 2 error is expressed as an explicit function of the error covariance matrices, the probability of the type 1 error, and the expected number of vessels per unit area. (Author)

Document Details

Document Type
Technical Report
Publication Date
Sep 11, 1970
Accession Number
AD0712508

Entities

People

  • J. H. Kullback
  • M. E. B. Owens

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Covariance
  • Data Science
  • Information Science
  • Mathematics
  • Observation
  • Probability
  • Probability Distributions
  • Random Variables
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.
  • Mechanical Engineering/Mechanics of Materials.