Preliminary Study of a Hybrid Genetic Algorithm/Expert System for Modeling Complex Radar Signatures

Abstract

I made an initial study of a hybrid genetic algorithm/expert system (HGAES) to model targets with nonlinear radar imaging effects caused by features such as cavities and canopies. The model for the nonlinear parameters was relatively simple, so it should be suitable for incorporation into hardware-in-the-loop and software-in-the-loop simulations that currently use point scatter models. I demonstrated the algorithm on simulated two-dimensional (2-D) inverse synthetic aperture radar (ISAR) images using a simple technique to determine the initial scattering centers. Many of the ideas used in developing the algorithm can be extended to more complex targets and from 2-D to 3-D images. A major issue in the development of an HGAES is knowledge representation. My conclusions are that models determined using this technique have the potential to enhance the accuracy of weapon systems simulations; thus, this technique is worth further investigation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1999
Accession Number
ADA371056

Entities

People

  • Geoffrey H. Goldman

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Computer Programming
  • Computer Programs
  • Computers
  • Detection
  • Expert Systems
  • Genetic Algorithms
  • Radar
  • Radar Signatures
  • Scattering
  • Simulations
  • Target Signatures
  • Three Dimensional
  • Two Dimensional
  • Weapon Systems

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Biotechnology