Signal-Filter Design and System Performance for Polarimetric Radar

Abstract

Relatively simple expressions for the polarimetric scattering function of randomly oriented dipoles have yielded expressions for SIR in some simple but important cases, and these expressions have been analyzed in order to interpret the computational results. Some important insights have been obtained from the SIR expression for distributed planar targets and randomly oriented dipole clutter, i.e, for the typical target in chaff problem. These insights have resulted in the design of a new polarimetric clutter canceller which theoretically allows a polarimetric radar to see through chaff. Signal-to- interference ratio (SIR) maximization has been used to obtain an optimum signal- filter pair for polarimetric radar when targets and/or clutter exhibit random polarization modulation. The results can easily be extended to include the design of a likelihood ratio receiver for the same problem. Considerable insight into the theoretical solutions has been obtained by implementation and test of a computer program to yield the maximum SIR and Bayesian systems, i.e., the best signal and receiver configurations in each case.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1987
Accession Number
ADA189257

Entities

People

  • Hanxiao Liu
  • James R. Miller
  • Kishan G. Mehrotra
  • Richard A. Altes
  • Stephen F. Connelly

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computer Programs
  • Data Science
  • Detection
  • Detectors
  • Doppler Effect
  • Electromagnetic Scattering
  • Equations
  • Gaussian Noise
  • Information Science
  • Network Science
  • Pattern Recognition
  • Random Variables
  • Simplex Method
  • Statistics
  • Two Dimensional
  • Waveforms
  • Waves

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Radar Systems Engineering.

Technology Areas

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