Effective Statistical Tests for Detection Models

Abstract

A Detection Model is an entity which calculates an instantaneous probability of detection of a target by a hunter, from the values of variables which describe the environment and the actions of both hunter and target, including past history, if appropriate. Given such a model, and a succession of non-identical trials which terminate at detection or after a given period of time (whichever occurs first), it is desired to test the adequacy of the model. An approach to this problem is presented, based upon recognizing the set of trials as a non-homogeneous Poisson process. Ways to improve the power of such tests by rearranging various segments of the trials are presented and discussed, including proper implementation of the tests using a digital computer. Extensions to the problem of improving the model and/or devising a new model are briefly discussed.

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Document Details

Document Type
Technical Report
Publication Date
Feb 17, 1972
Accession Number
AD0740776

Entities

People

  • James A. Lechner

Organizations

  • George Washington University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Clocks
  • Computers
  • Detection
  • Digital Computers
  • Discontinuities
  • Engineering
  • Environment
  • Equations
  • Goodness Of Fit Tests
  • Probability
  • Random Variables
  • Security
  • Statistical Tests
  • Statistics
  • Stochastic Processes
  • Test Methods

Fields of Study

  • Mathematics

Readers

  • Sensor Fusion and Tracking Systems.
  • Statistical inference.
  • Systems Analysis and Design