A Comparison of Spread and Point-Source Multiple-Direction Estimation Techniques for High Latitude HF Direction Finding

Abstract

Previous simulation studies were conducted to determine the direction finding performance of four different antenna array geometries with and without antenna pattern errors, operating with the deterministic maximum likelihood (ML) algorithm. Here they are extended to a new DF algorithm, spread maximum likelihood (SML), which assumes distributions of signal directions, rather than single directions, to approximate the signal information seen by the array. The SML algorithm is thought to be more appropriate to the high latitude HF radio environment, where signals often arrive from a spread set of directions, due to multiple reflections or scattering from irregularities in the ionosphere and, at the same time, from a single great circle direction as a results of sporadic E propagation. Using a performance criterion of point source visibility in the presence of a stronger spread source, the simulation shows the SML technique to yield substantially better performance than ML, for all arrays and levels of error, and array apertures of four wavelengths or more. SML technique extended the useful range of array apertures upwards to 10 wavelengths in most cases. As was seen previously for the ML algorithm, the three pronged star configuration was found to be best of the array geometries tested.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1998
Accession Number
ADA349736

Entities

People

  • Robert. W. Jenkins

Organizations

  • Communications Research Centre Canada

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Antenna Arrays
  • Antennas
  • Arrays
  • Classification
  • Direction Finding
  • Electromagnetic Wave Propagation
  • Electron Density
  • Electrons
  • Environment
  • Frequency
  • High Latitudes
  • Polar Cap
  • Radio Waves
  • Scattering
  • Security
  • Simulations

Readers

  • Neural Network Machine Learning.
  • Phased Array Antenna Design.
  • Radio communications and signal processing.