Nonparametric Estimation of the Cyclic Cross-Spectrum

Abstract

Cyclostationary processes are an important class of nonstationary processes. In this report we consider nonparametric estimation of the cyclic cross-spectrum. A periodogram-based estimator is studied and its asymptotic behavior characterized. This extends the recent univariate work of Dandawate and Giannakis to the multivariate case. The results are useful for a variety of multi-sensor cyclostationary signal processing scenarios, such as bearing estimation. Cyclostationary, Cyclic spectrum, Cyclic periodogram

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1994
Accession Number
ADA285756

Entities

People

  • Brian M. Sadler

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Covariance
  • Data Science
  • Detectors
  • Equations
  • Estimators
  • Fourier Series
  • Information Processing
  • Information Science
  • Power Spectra
  • Signal Processing
  • Spectra
  • Stationary
  • Stationary Processes
  • Statistical Algorithms
  • Statistics
  • Time Dependence

Fields of Study

  • Engineering

Readers

  • Radio communications and signal processing.
  • Statistical inference.