Spectral Estimation of Continuous Time Processes Using Poisson Distributed Time Samples

Abstract

Report compares two discrete time spectral estimation techniques for estimating the spectral density function of a continuous time process - periodic spectral estimation and Poisson spectral estimation. It shows the Poisson to excel when the spectral density is not bandlimited; when the shape of the spectral density is not known a priori; and when the sampling rate is constrained to be below that of Nyquist. The Poisson theory applies to other areas of signal processing. The Poisson technique could be used in applications such as cross spectral estimation, estimation of the coherence function, and antenna array beamforming.

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Document Details

Document Type
Technical Report
Publication Date
Apr 07, 1978
Accession Number
ADA054903

Entities

People

  • C. Mirabile
  • D. Klamer

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Classification
  • Computer Programming
  • Cross Correlation
  • Data Science
  • Demographic Cohorts
  • Estimators
  • Frequency
  • Gaussian Processes
  • Information Processing
  • Information Science
  • Markov Processes
  • Random Variables
  • Sampling
  • Signal Processing
  • Simulations
  • Statistical Algorithms
  • Stochastic Processes

Fields of Study

  • Engineering

Readers

  • Calculus or Mathematical Analysis
  • Life Cycle Cost Analysis
  • Speech Processing/Speech Recognition.