Computing the Probability of Target Detection in Dyanmic Visual Scenes Containing Clutter Using Fuzzy Logic Approach

Abstract

The probability of detection (Pd) of moving targets in visually cluttered scenes is computed using the Fuzzy Logic Approach (FLA). The FLA is presented by the authors as a robust method for the computation and prediction of the Pd of targets in cluttered scenes with sparse data. A limited data set of visual imagery has been used to model the relationships between several input parameters; the contrast, vehicle camouflage, range, aspect, width, and experimental Pd. The fuzzy and neuro-fuzzy models gave predicted Pd values that had 0.9 correlation to the experimental Pd's. The results obtained indicate the robustness of the fuzzy-based modeling techniques and the potential applicability of the FLA to those types of problems having to do with the modeling of aided or unaided detection of a signal (acoustic, electromagnetic) in any spectral regime.

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Document Details

Document Type
Technical Report
Publication Date
Feb 24, 1998
Accession Number
ADA576438

Entities

People

  • Bill Pibil
  • Darryl Bryk
  • David Bednarz
  • Euijung Sohn
  • Regina Kistner
  • Thomas Meitzler

Organizations

  • Tank-automotive and Armaments Command

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Computer Programs
  • Contrast
  • Data Sets
  • Detection
  • Fuzzy Logic
  • Fuzzy Sets
  • Logic
  • Moving Targets
  • Perception
  • Probability
  • Set Theory
  • Target Acquisition
  • Target Detection
  • Targets
  • Test Methods

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Sensor Fusion and Tracking Systems.