Optimum Filtering of Cyclostationary Processes Resulting from Scanning or Sampling of Communication and Control Signals.

Abstract

Random signal processes which have been subjected to some form of repetitive operation such as sampling, scanning or multiplexing will usually exhibit statistical properties which vary periodically with time. Specifically, a random process, x(t), for which the mean, E(x(t)), and the autocorrelation, E(x(t + tau) x (t)), are both periodic in t is termed a cyclostationary process. It is shown that many of the signal processes typically encountered in communication systems and control systems are cyclostationary, a fact often ignored in the analysis of such systems. Using the more accurate cyclostationary model for such processes, a more precise evaluation of system performance can be obtained and signal processors giving superior performance can be designed. In particular, general procedures are developed for finding the optimum periodically-time-varying filters for the continuous waveform estimation problem and the improvement in performance is demonstrated over the best time-invariant filter.

Document Details

Document Type
Technical Report
Publication Date
May 01, 1976
Accession Number
ADA026358

Entities

People

  • L. E. Franks

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Autocorrelation
  • Communication Systems
  • Communications Techniques
  • Control Systems
  • Data Science
  • Filters
  • Filtration
  • Information Science
  • Multiplexing
  • Sampling
  • Scanning
  • Test And Evaluation
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Statistical inference.