Accession Number:
ADA576440
Title:
Predicting the Probability of Target Detection in Static Infrared and Visual Scenes Using the Fuzzy Logic Approach
Descriptive Note:
Corporate Author:
TACOM RESEARCH DEVELOPMENT AND ENGINEERING CENTER WARREN MI
Personal Author(s):
Report Date:
1997-10-07
Pagination or Media Count:
16.0
Abstract:
The probability of detection PD of targets in static infrared and visually cluttered scenes is computed using the Fuzzy Logic Approach FLA. The FLA is presented as a robust method for the computation and prediction of the PD targets in cluttered scenes. The MamdaniAssilian, and Sugeno Neurofuzzy-based models have been investigated. A large set of infrared IR imagery and a limited set of visual imagery has been used to model the relationships between several input parameters the contrast, camouflage condition,range, aspect, width and experimental PD. The fuzzy and neuro-fuzzy models gave predicted PD values that had 0.98 correlation to the experimental PDs. The results obtained indicate the robustness of the fuzzy-based modeling techniques and the applicability of the FLA to those types of problems having to do with the modeling of human-in-the-loop target detection in any spectral regime.
Subject Categories:
- Statistics and Probability
- Target Direction, Range and Position Finding