Genetic Algorithm Receiver Optimization for Passive, Bi-Static Synthetic Aperture Radar

Abstract

Utilizing communication transmissions within an urban environment for passive radar has seen a huge surge in interest over the past decade. While the feasibility of using signals of opportunity for passive radar has been shown, very little research has been done for the optimization of passive transmitter/receiver pairings within urban environments. This research provides a receiver design based optimization of passive transmitter/receiver pairing using non-dominated sorting genetic algorithm (NSGA-II) to solve a constrained multi-objective model. Comparing the results of an exhaustive search and the genetic algorithm (GA), the efficiency and effectiveness of using a GA for mixed variables over non-continuous, non-convex objectives associated with bi-static synthetic aperture radar (SAR)is demonstrated.

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Document Details

Document Type
Technical Report
Publication Date
Sep 14, 2017
Accession Number
AD1055539

Entities

People

  • Chad N. Chamberlain

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • 4G Wireless Networks
  • Air Force
  • Algorithms
  • Computational Complexity
  • Computer Programming
  • Department Of Defense
  • Electrical Engineering
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Governments
  • Multiobjective Optimization
  • Passive Radar
  • Radar
  • Synthetic Aperture Radar
  • Target Recognition
  • Two Dimensional
  • United States Government

Fields of Study

  • Environmental science

Readers

  • Operations Research
  • Radar Systems Engineering.

Technology Areas

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