Estimators for Model-Based Passive Localization

Abstract

A comparative study is made of the performance of four different estimators as used in the matched-field technique of passive localization. The study is based on both real and synthesized data. In the synthesized data case, a comparison is made of the performance of the estimators for various signal-to- noise ratios. The four estimators studied are Bucker's Estimators, which can be thought of as a spatial matched filter, and three likelihood-type estimators. The results indicate that the matched-field type estimator has a slightly better signal-to-noise performance than the others, but rather poor sidelobe behaviour, whereas for the likelihood-type estimator the sidelobe behaviour is quite good. Keywords: Inverse problems; Matched-field processing; Model-based signal processing; Passive localization; Passive ranging; Hydrophones; Underwater acoustics; Mediterranean Sea.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1988
Accession Number
ADA199702

Entities

People

  • E. J. Sullivan
  • S. Bongi
  • W. Volkmann

Organizations

  • SACLANT ASW Research Centre

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustics
  • Amplitude
  • Arrays
  • Data Science
  • Defense Planning
  • Detection
  • Estimators
  • Governments
  • Hydrophones
  • Inverse Problems
  • Matched Filters
  • Nato
  • Shallow Water
  • Sidelobes
  • Signal Processing
  • Towed Arrays
  • Underwater Acoustics

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Phased Array Antenna Design.
  • Radar Systems Engineering.