Analysis of Wideband Beamformers Designed with Artificial Neural Networks

Abstract

The ability to determine the direction of an approaching wave is demonstrated by using an artificial neural network and a beamformer array. To demonstrate the ability of a neural network to learn a satisfactory solution to this problem, simulations were performed to test the system's sensitivity to several variables. These variables include amplitude range, noise level, frequency bandwidth, linear and nonlinear inputs, the number of sensor inputs, and the number of hidden units used in the network. Simulations are provided for both narrow band and wideband signals. An empirical test and a comparison between ANN beamformers and FFT beamformers are also used to demonstrate the strengths and weaknesses of the system. A design example and a description of the simulation program are also included. A brief tutorial on beamformers and neural networks is also provided. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1990
Accession Number
ADA231668

Entities

People

  • Cary Cox

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Angle Of Arrival
  • Artificial Intelligence
  • Automata Theory
  • Bandwidth
  • Computational Science
  • Computer Programming
  • Computers
  • Digital Signal Processing
  • Electrical Engineering
  • Frequency
  • Frequency Bands
  • Geometry
  • Mathematical Analysis
  • Neural Networks
  • Pattern Recognition
  • Signal Processing
  • Three Dimensional

Fields of Study

  • Engineering

Readers

  • Neural Network Machine Learning.
  • Phased Array Antenna Design.
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks