The Use of Linear Prediction for the Interpolation and Extrapolation of Missing Data and Data Gaps Prior to Spectral Analysis

Abstract

The spectral analysis of a series of equally spaced samples of a time-stationary process becomes difficult when samples are missing or sizable data gaps occur within the interval of interest. A linear prediction algorithm can be used to fill in the missing data with estimates that are spectrally consistent with the data that are observed. Simulated and practical radar examples demonstrate an improvement in resolution and a reduction of sidelobe interference levels. Computer programs are provided which accomplish the extrapolation and interpolation for complex data.

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Document Details

Document Type
Technical Report
Publication Date
Jun 18, 1979
Accession Number
ADA075515

Entities

People

  • Shu T. Lai
  • Stephen B. Bowling

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Computers
  • Data Processing
  • Data Sets
  • Digital Information
  • Fourier Transformation
  • Frequency
  • Interpolation
  • Intervals
  • Observation
  • Power Spectra
  • Procedures (Computers)
  • Radar Pulses
  • Sidelobes
  • Spectra

Readers

  • Phased Array Antenna Design.
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • Space