Reduced Dimension Adaptive Beamforming

Abstract

Adaptive methods of beamforming that yield high resolution beam outputs require a much greater numerical intensity than conventional Fourier techniques of beamforming. Reduction of the adaptive dimension of these data dependent beamformers can alleviate the numerical intensity problem with a negligible loss in performance. The adaptive dimension reduction may be accomplished by a matrix premultiplication of the array sensor data. The matrix premultiplication, known as matrix preprocessing, transforms the N dimension array data vector into an M dimensional space where M < N. The M dimensional data is then beamformed with a minimum variance distortionless response (MVDR) adaptive beamformer. Another method of reducing the adaptive dimension is by the approximation of the covariance or cross spectral density matrix (CSDM) by its dominant or strongest eigenvectors.

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Document Details

Document Type
Technical Report
Publication Date
Jul 31, 1990
Accession Number
ADA226461

Entities

People

  • Douglas A. Abraham

Organizations

  • Naval Underwater Systems Center

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Angle Of Arrival
  • Background Noise
  • Eigenvalues
  • Estimators
  • Frequency
  • Frequency Domain
  • Geometry
  • High Resolution
  • Phase Shift
  • Plane Waves
  • Signal Processing
  • Square Roots
  • Time Domain
  • Transfer Functions
  • Traveling Waves
  • Wave Propagation

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Linear Algebra
  • Phased Array Antenna Design.

Technology Areas

  • Space