Research on Large Adaptive Arrays.

Abstract

Most adaptive filters are designed to achieve minimization of estimation error. Other design goals could include satisfaction of constraints as well as minimization of mean square error. The paper proposes a particular set of performance criteria, involving 'soft constraints'. A 'soft-constraint LMS algorithm' is derived from a performance function which is the sum of mean square error and weighted squared constraint violation errors. The soft constraint algorithm is applied to adaptive antenna arrays as an example, which includes a demonstration of the effects of varying the softness of the constraints. Also, convergence properties of the algorithm are presented. A relation between the output power of a signal from a converged soft constraint LMS adaptive filter and the signal's input power is derived, which demonstrates some unexpected behavior. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1979
Accession Number
ADA081388

Entities

People

  • B. Widrow
  • H. Mesiwala
  • K. Duvall
  • R. Chestek

Organizations

  • Syracuse University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Adaptive Filters
  • Algorithms
  • Angle Of Arrival
  • Antenna Arrays
  • Antennas
  • Arrays
  • Convergence
  • Cross Correlation
  • Data Science
  • Eigenvalues
  • Filters
  • Frequency
  • Information Science
  • Random Variables
  • Stationary Processes
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research
  • Phased Array Antenna Design.