Improvement of Resolution and Reduction of Computation in 2D Spectral Estimation Using Decimation,

Abstract

This paper is concerned with spectral estimation of a finite number of two dimensional siunsoids embedded in white noise. Closed form expressions are derived for estimates using the autoregressive (AR) prediction error filter approach, as well as using periodogram with Bartlett window, and the maximum likelihood (ML) method. These expressions are useful in the study of resolving closely spaced sinusoidal signals. Over a narrow frequency band, direct decimation can be applied to improve resolution and/or to reduce computation. Simulation results demonstrate that decimation by (D1, D2) with a support size (N1, N2) yields approximately the same resolution as a support size (D1 N1, D2 N2) used with the undecimated signal. The use of decimation also reduces significantly computation.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1984
Accession Number
ADA171692

Entities

People

  • Bede Liu
  • Lihe Zou

Organizations

  • Princeton University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Autocorrelation
  • Bandpass Filters
  • Computations
  • Computer Science
  • Electrical Engineering
  • Engineering
  • Filters
  • Frequency
  • Frequency Bands
  • Noise
  • Signal Processing
  • Simulations
  • Spectra
  • Two Dimensional
  • White Noise

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Image Processing and Computer Vision.
  • Statistical inference.

Technology Areas

  • Space