Metrics for Emitter Selection for Multistatic Synthetic Aperture Radar

Abstract

A bistatic implementation of synthetic aperture radar (SAR) to form images of the ground from an aircraft makes use of separate emitters and receivers. When not using cooperative emitters, ground based communications systems can provide illumination. One way to improve performance of these waveforms, which are not designed for SAR, is a multistatic implementation, formed from multiple bistatic systems. This leads to the problem of selecting a subset from a potentially large set of emitters to use for image formation. A framework for this selection between sets of emitters is proposed using multiple objective optimization. This approach requires use of objective functions to score the inputs to the selection process. The four objective functions selected to score sets of emitters are: signal to noise ratio, waveform ambiguity function's integrated sidelobes , effective multistatic resolution area, and contrast ratio. To speed calculations, an approximation is found for the point spread function. Simulation is used to compare approximation with theory, showing its utility for emitter selection. Finally a qualitative example of emitter selection is presented.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA590484

Entities

People

  • Sean R. Stevens

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • 4G Wireless Networks
  • Air Force
  • Amplitude Modulation
  • Coordinate Systems
  • Digital Communications
  • Doppler Effect
  • Frequency Bands
  • High Definition Television
  • Mobile Phones
  • Modulation
  • Multistatic Radar
  • Orthogonal Frequency Division Multiplexing
  • Radar
  • Signal Processing
  • Synthetic Aperture Radar
  • Target Recognition
  • United States Government

Fields of Study

  • Engineering

Readers

  • Radar Systems Engineering.
  • Regression Analysis.