Analysis of Statistical Performance Measures

Abstract

When only a limited number of snapshots is available for estimating the spatial correlation matrix, a low-rank solution of the MVDR equations, obtained via a small number of iterations of Conjugate Gradients (CG), can yield a higher SINR than the full-rank MVDR beamformer. A primary issue addressed in this effort is whether the unity gain constraint in the look direction should be enforced a-priori via the use of a blocking matrix, constituting Steering Dependent Conjugate Gradients (SD-CG), or effected a-posteriori through simple scaling of the beamforming vector, constituting Steering Independent Conjugate Gradients (SI-CG). A major contribution was that the two methods yield exactly the same low-rank beamformer. This is an important result since the construction, and application to the data, of a blocking matrix for each "look" direction is computationally burdensome. A simplified expression for the power estimate obtained with the SI-CG beamformer was also developed. Extensive simulations were conducted to verify the efficacy of the theory. While it was known that the optimal number of steps of SI-CG varies with look direction, simulations presented here reveal that the optimal number of principal eigenvectors for the PCI beamformer varies substantially with look direction.

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Document Details

Document Type
Technical Report
Publication Date
May 12, 2004
Accession Number
ADA422819

Entities

People

  • Michael D. Zoltowski

Organizations

  • Purdue University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Construction
  • Detectors
  • Digital Communications
  • Digital Signal Processing
  • Eigenvectors
  • Electrical Engineering
  • Electronic Mail
  • Engineering
  • Equations
  • Filtration
  • Military Research
  • Signal Processing
  • Simulations
  • Steering
  • Universities

Fields of Study

  • Engineering

Readers

  • Linear Algebra
  • Phased Array Antenna Design.
  • Regression Analysis.