Technical Specifications for Spread Function Model.

Abstract

In order to design and accurately estimate the performance of a candidate passive sonar system the systems engineer needs considerably more information than the standard terms in the passive sonar equation. The sonar equation typically deals with the mean values of the total signal and noise fields. All departures from these means are considered only in the time domain as fluctuations in signal excess which lead to the probabilistic description of the detection process in terms of ROC curves, etc. As a first refinement of this approach, still in the mean value sense however, a higher resolution description of these fields is sought. In order to estimate array signal gain, processor gain, and detection and localization performance additional information beyond these means is required on the spreads of these values. This paper addresses the technical specifications for a set of models to support these requirements. For this treatment only second moments (distributions for angles, decorrelation times, frequency spreads) will be considered. While higher-order moments are desirable, their general treatment is beyond the scope of the present effort. In some special cases, such as the distribution of intensity (a collapsed fourth-order moment), estimates may be possible and are considered.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA137292

Tags

Communities of Interest

  • Air Platforms
  • Engineered Resilient Systems
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Boltzmann Equation
  • Databases
  • Diffraction
  • Doppler Effect
  • Frequency
  • Geometry
  • Internal Waves
  • Passive Sonar
  • Plane Waves
  • Refraction
  • Scattering
  • Shallow Water
  • Sonar
  • Statistics
  • Surface Waves
  • Two Dimensional
  • Waves

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Phased Array Antenna Design.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms