Prediction of Passive Sonar Detection Performance in Environments with Acoustical Fluctuations.

Abstract

Statistical methods of systems analysis are employed to predict the performance of a passive sonar receiver operating in environments with fluctuating signals and noise. The receiver analog employed is a multichannel processor that produces for each channel a decision threshold that is determined by the outputs of other channels. The receiver inputs are compound random processes exhibiting characteristics observed in experimental studies of ambient noise. The parameters of these processes including their relaxation times can be selected to suit a particular set of environmental conditions. The principal objective is to achieve realistic predictions of the probability of detection by single observations. Performance is found to depend on the autocovariance functions of the power envelopes of the fluctuating inputs as well as on their first order probability densities. Transition curves, giving probability of detection as a function of average excess signal-to-noise level, are developed for several cases of fluctuation parameters. Use of these curves for determining the single-look probability of detection merely requires evaluation of the sonar equation to determine the average excess signal-to-noise level for particular sonar operating environments. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1978
Accession Number
ADA062487

Entities

People

  • Magnus Moll

Organizations

  • BBN Technologies

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Ambient Noise
  • Analyzers
  • Bandwidth
  • Data Science
  • Detection
  • Detectors
  • Distribution Functions
  • Equations
  • Frequency Bands
  • Information Science
  • Passive Sonar
  • Probability Distributions
  • Random Variables
  • Relaxation Time
  • Stationary Processes
  • Stochastic Processes
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Acoustics.
  • Approximation Theory.
  • Radar Systems Engineering.