Probability of Detection for a Go CFAR Radar Processor Using Envelope Detection Approximation

Abstract

The greatest-of logic for a constant false alarm rate processor (GO CFAR) is a commonly used method for the adaptive setting of a radar detection threshold in the presence of clutter edges. Instead of using a true envelope detector x = I2 + Q2, which is difficult to implement, envelope detection approximations of the form Xe = aMax (I),(Q) + bMin (I),(Q) and xe = a(I)+b(Q) (no Max and Min operators) where a and b are constants, are often used to detect a signal decomposed into its in-phase (I) and quadrature (Q) components. Closed form expressions are derived for the probability density function (pdf) of a radar range cell containing a detected target signal in the presence of noise using both approximations. These can then be used to calculate the probability of detection (PD). They can also be used to calculate the probability of false alarm (PFA) if the means of I and Q are set to zero. Closed form expressions are obtained analytically and by curve-fitting the numerically derived pdf of the target cell. Finally, using Monte Carlo techniques, this thesis also compares the GO CFAR detection performance using envelope detection approximations xe, xe and the true envelope detector x for zero mean white Gaussian noise input samples I and Q.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1994
Accession Number
ADA286211

Entities

People

  • Joseph J. Hache

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Convolution Integrals
  • Curve Fitting
  • Detection
  • Detectors
  • Distribution Functions
  • Electrical Engineering
  • Engineering
  • False Alarms
  • Probability
  • Probability Density Functions
  • Radar
  • Random Variables
  • Signal Processing
  • Simulations
  • Step Functions
  • Target Detection
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Radar Systems Engineering.
  • Statistical inference.