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The probability of detection (Pd) of moving targets in visually c.! uttered 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 Report Documentation Page Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 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. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Public Release 18. NUMBER OF PAGES 27 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 The probability of detection (Pd) of moving targets in visually c.! uttered scenes is computed using the Fuzzy Logic

The probability of detection (Pd) of moving targets in visually c.! uttered 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 Report Documentation Page Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 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. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Public Release 18. NUMBER OF PAGES 27 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 The probability of detection (Pd) of moving targets in visually c.! uttered scenes is computed using the Fuzzy Logic

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