Fuzzy classification algorithm as applied to signal discrimination for navy theater-wide missile defense

Craig O. Savage; Hai-Wen Chen; Jack G. Riddle; Harry A. Schmitt

doi:10.1117/12.403619

13 October 2000 Fuzzy classification algorithm as applied to signal discrimination for navy theater-wide missile defense

Craig O. Savage, Hai-Wen Chen, Jack G. Riddle, Harry A. Schmitt

Author Affiliations +

Proceedings Volume 4120, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III; (2000) https://doi.org/10.1117/12.403619
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

Given a set of training data and a feature extraction tool, fuzzy membership functions are created using regression analysis on the extracted features. These membership functions are then used to classify a signal into one of two basic classes (namely, threat or non-threat). Alternatively, the dat can be classified into M groups, as desired. For this paper, the training data form a set of modeled infrared intensities for subpixel objects, of the types expected for a prototypical ballistic missile defense engagement scenario. The feature extraction took used is a form of local discriminant bases, as described by Coifman and Saito⁴. The top N features (typically two to four) are then piped pairwise through a regression tool to determine if any statistically significant trends occur. If a trend is discovered, then a membership function is created for the relationship; otherwise, membership functions are created for each feature independently. An example of each is given. Results indicate great flexibility in managing misclassification of targets (Leakage) versus classifying a non-target as a target (False Alarms), depending on the choice of membership functions. Results for using seven extracted features on performance data show < 1% Leakage corresponding to 13% False Alarms.

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Craig O. Savage, Hai-Wen Chen, Jack G. Riddle, and Harry A. Schmitt "Fuzzy classification algorithm as applied to signal discrimination for navy theater-wide missile defense", Proc. SPIE 4120, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III, (13 October 2000); https://doi.org/10.1117/12.403619

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