Adaptive Enhancement of Multiple Sinusoids in Uncorrelated Noise.

Abstract

The steady-state behavior of the adaptive line enhancer (ALE), a new implementation of adaptive filtering that has application in detecting and tracking narrowband signals in broadband noise, is analysed for a stationary input consisting of multiple sinusoids in white noise. It is shown that the steady-state performance of an L-weight ALE for this case can be modeled by the L X L Wiener-Hopf matrix equation and that this matrix equation can be transformed into a set of 2N coupled linear equations, where N is the number of sinusoids. It is also shown that the expected values of the ALE weights in steady state can be written as a sum of sinusoids and that the amplitude of each sinusoid is coupled to that of all other sinusoids by coefficients that approach zero as the number of ALE weights becomes large. The analytical results are compared to experimental results obtained with a hardware implementation of the ALE of variable length (up to 256 weights) and show good agreement. Theoretical expressions for linear predictive spectral estimates are also derived for multiple sinusoids in white noise. Comparisons are made between the magnitude of the discrete Fourier transform of the ALE weights and the linear predictive spectral estimate for two sinusoids in white noise. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1977
Accession Number
ADA053461

Entities

People

  • D. M. Chabries
  • E. H. Satorius
  • H. T. Wexler
  • J. R. Zeidler

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Adaptive Filters
  • Algorithms
  • Bandpass Filters
  • Electrical Engineering
  • Engineering
  • Equations
  • Filters
  • Filtration
  • Frequency
  • Frequency Response
  • Power Spectra
  • Signal Processing
  • Spectra
  • Steady State
  • Systems Science
  • Transfer Functions
  • White Noise

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Phased Array Antenna Design.