ANALYTICAL INVESTIGATIONS OF DIGITAL INFORMATION PROCESSING SYSTEMS. VOLUME I.

Abstract

The aim of this project is to provide basic knowledge concerning the methods which may be used by a man-computer system to detect the presence of a target using data from a passive sonar receiver. This research consists of analytical studies to evaluate important system parameters and experimental investigations to measure operator performance under various operating conditions. The first two reports evaluate the loss in detection capability if clipped data rather than continuous data is used for detection. Under the alerted operator assumption it is shown that, on the average, fewer signal samples are required to achieve a given detection capability using sequential detection techniques instead of fixed sample size detection techniques. The next two reports describe methods of improving detection probability through pre-processing of the clipped signal before it is presented to the operator in the form of a binary bearing-time display. The last two reports investigate methods to analyze the statistical properties of correlated random digital sequences. It is shown that the complete distributions of a large class of random digital sequences can be described as either multinomial processes, Markov processes, or linearly dependent processes. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1966
Accession Number
AD0803277

Entities

People

  • Herbert M. Kaufman
  • James R. Walter
  • Robert M. Glorioso
  • Robert M. Levy
  • Taylor L. Booth

Organizations

  • General Dynamics Electric Boat

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computer Programs
  • Detection
  • Digital Information
  • Information Processing
  • Information Systems
  • Markov Processes
  • Passive Sonar
  • Probability
  • Sequences
  • Sonar
  • Sonar Receivers

Fields of Study

  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Statistical inference.
  • Systems Analysis and Design