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

摘要

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.