Poisson Spectral Estimation using Hardlimited Samples.

Abstract

In this report, the problem of reconstructing the spectral density of a Gaussian signal process from hardlimited observations taken at Poisson sampling instants was considered. The estimate was shown to be asymptotically unbiased as the number of observation points approached infinity. In addition, the covariance of the estimate was also asymptotically bounded as the number of observations tended to infinity. The focus of future work will be to obtain tighter bounds on the covariance of the estimate and to show that these bounds tend to zero as the number of observations tends to infinity. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 15, 1978
Accession Number
ADA066376

Entities

People

  • D. M. Klamer

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Convergence
  • Covariance
  • Data Science
  • Distribution Functions
  • Estimators
  • Exponential Functions
  • Gaussian Processes
  • Inequalities
  • Numbers
  • Observation
  • Random Variables
  • Sampling
  • Signal Processing
  • Stationary Processes
  • Statistical Sampling
  • Stochastic Processes
  • Undersea Surveillance

Fields of Study

  • Mathematics

Readers

  • Life Cycle Cost Analysis
  • Mathematical Modeling and Probability Theory.