Processing of the Manual Morse Signal Using Optimal Linear Filtering, Smoothing and Decoding

Abstract

This thesis investigates the problem of automatic transcription of the morse signal, and describes and documents several approaches to filtering, processing, and decoding it for transcription. The baseband signal is first modeled as a modified random telegraph wave. A discrete Kalman filter and a linear smoother are then used to process the demodulated signal in order to gain a measure of the effectiveness and applicability of this model. It is shown experimentally that this model and processing yield a significant reduction in the transcription error rate. Next, a Viterbi decoder algorithm based on a simple Markov model of the code is programmed and tested. Finally, the baseband signal model is incorporated in a more general model for pre-detection Kalman filtering. It is shown that this filter permits acceptable recovery of morse signals whose average signal-to-noise ratio is as low as -14 dB in a 2 kHz bandwidth.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1975
Accession Number
ADA019493

Entities

People

  • Edison L. Bell

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Bandpass Filters
  • Bandwidth
  • Computer Programming
  • Computer Programs
  • Computers
  • Decoding
  • Detection
  • Estimators
  • Filters
  • Filtration
  • Kalman Filters
  • Linear Filtering
  • Markov Models
  • Mathematical Filters
  • Morse Code
  • Notation

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Programming and Software Development.
  • Radio communications and signal processing.

Technology Areas

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