Time-Domain Wiener Adaptive Beamforming with Distributed Signal Models

Abstract

This report is a mathematical study of time-domain Wiener adaptive multichannel filtering using distributed signal models. It presents derivations for two Wiener adaptive algorithms and describes the basic technique for implementing a Wiener adaptive processor with directionally distributed signal models. In order to obtain the signal-model crosscorrelation functions needed in the Wiener adaptive algorithms, the probability density function p(tau) for the time delay between a reference sensor and the individual channels must be specified. Analytic derivations of this function are presented for inverse velocity space models, distributed ring models, and velocity-azimuth space models. These derivations are of interest in their own right: they are useful in specifying two-channel crosscorrelation functions for various directional energy distributions.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 16, 1975
Accession Number
ADA015052

Entities

People

  • Thomas E. Barnard

Organizations

  • Texas Instruments

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Adaptive Filters
  • Air Force
  • Algorithms
  • Data Science
  • Distribution Functions
  • Frequency
  • Information Science
  • Intervals
  • Normal Distribution
  • Power Spectra
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Quadrants
  • Sampling
  • Time Domain
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Phased Array Antenna Design.
  • Radar Systems Engineering.
  • Statistical inference.

Technology Areas

  • Directed Energy
  • Space