A Study of PC-Based HF Ionospheric Propagation Predictions for Use in Naval Communications.

Abstract

High frequency (HF) ionospheric propagation predictions have been available on mainframe computers since the late 1960s. Since the advent of low cost, computationally powerful personnel computers, several propagation codes have been ported from mainframes to PC's. This study compares results from two versions of the IONCAP and PROPHET HF propagation prediction codes to a database of measured electric field strengths. IONCAP-PC 2.5 predictions were compared to IONCAP-VAX 85.04 predictions and to those from PROPHET 3.2 (PC-version). A database of measured signal strengths from the CCIR containing over 16,000 points or cases was used as a benchmark for comparing code results. For both IONCAP-PC 2.5 and PROPHET 3.2, field strength predictions were low in more than 50% of the cases examined. This was particularly true for PROPHET, which is considered to be a conservative model. PROPHET features quick solution, graphical outputs, and a user-friendly environment, in comparison to IONCAP. IONCAP-PC 2.5, which is an improved version of a previous mainframe IONCAP, produced slightly more accurate predictions than IONCAP 85.04, and substantially better results than those from PROPHET.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1990
Accession Number
ADA232466

Entities

People

  • Georgios H. Giakoumakis

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Communication Systems
  • Computer Programs
  • Computers
  • Databases
  • Electric Fields
  • Electromagnetic Wave Propagation
  • Electron Density
  • Environment
  • Frequency
  • Ionosphere
  • Ionospheric Propagation
  • Mainframe Computers
  • Radiation
  • Radio Waves
  • Sky Waves
  • Statistical Analysis
  • Wave Propagation

Readers

  • Computational Modeling and Simulation
  • Computer Science.
  • Information Retrieval