Target Detection in Gaussian Noise Using Artificial Neural Systems

Abstract

Radar signal processing with multilayered perceptrons was investigated. Networks with no hidden layer and a single hidden layer were tested on field collected millimeter wave target returns that have been corrupted with artificial Gaussian noise at a signal to noise level of 3 dB. Performance as a function of network architecture was characterized. Keywords: Radar signal processing, Multilayered perceptrons, Single hidden layer, Field collected millimeter wave target.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1990
Accession Number
ADA223983

Entities

People

  • George Rogers
  • Jeffrey L. Solka

Organizations

  • Naval Surface Warfare Center

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Classification
  • Computing System Architectures
  • Detection
  • Gaussian Noise
  • Millimeter Waves
  • Network Architecture
  • Radar Signals
  • Signal Processing
  • Standards
  • Surface Warfare
  • Target Detection

Readers

  • Electronics Engineering
  • Neural Network Machine Learning.

Technology Areas

  • 5G
  • 5G - Internet of Things