Adaptive Nulling and Spatial Spectral Estimation Using an Iterated Principal Components Decomposition,

Abstract

An iterative algorithm is described for computing a reduced rank principal component least squares estimate of the adaptive weight vector to be used for spatially nulling interference received in the sidelobes of the formed beams of an array of antenna elements. Based on a power/deflation method for extracting estimates of the dominant eigenstructure components, the algorithm is used to approximate the subspace spanned by the sample covariance eigenvectors associated with the directions of arrival of spatially coherent interference. Side information is also produced that can aid the discrimination between interference and noise subspaces. Performance is illustrated by the results of processing actual signals recorded from the individual elements of a linear antenna array operating in the HF band.

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1992
Accession Number
ADP007429

Entities

People

  • Dean O. Carhoun

Organizations

  • MITRE Corporation

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Antenna Arrays
  • Antenna Radiation Patterns
  • Antennas
  • Arrays
  • Covariance
  • Data Science
  • Decomposition
  • Discrimination
  • Eigenvectors
  • Information Processing
  • Information Science
  • Mathematics
  • Sidelobes

Fields of Study

  • Engineering

Readers

  • Neural Network Machine Learning.
  • Radio communications and signal processing.
  • Statistical inference.