A Unifying Approach to Linear and Nonlinear Array Processing: A Tutorial.

Abstract

The concept of linear filtering is the focus of a unifying approach to linear and nonlinear array processing methods. A number of well-known methods (conventional, optimal, maximum likelihood) are typically discussed within the context of linear filtering, while others (maximum entropy, linear predictor, generalized eigenvector) are not usually presented in this way. Through rederivation of these methods in terms of constrained filtering, we are able to relate performance of the methods to imposed (or neglected) constraints. Each filter discussed is linearly constrained in the look direction and then optimized using quadratic forms based on noise and sidelobe structure. Each filter is more complicated than the ones preceding it, as we consider additional aims and impose additional constraints. Stability of the methods to mismatches is considered, and techniques for improving stability are presented. Appendixes on Fourier transform approximation, array gain and detection, and complex Gaussian random variables are included. Keywords: Noise suppression; Robustness; Data adaptive filtering. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 30, 1985
Accession Number
ADA164777

Entities

People

  • Charles L. Byrne

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Ambient Noise
  • Computational Science
  • Data Science
  • Detection
  • Detectors
  • Eigenvalues
  • Estimators
  • Frequency
  • Linear Filtering
  • Optimal Estimators
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Fields of Study

  • Engineering

Readers

  • Calculus or Mathematical Analysis
  • Phased Array Antenna Design.
  • Statistical inference.