Radar target classification using improved Dempster-Shafer theory

This study considers the problem of coarse classification of targets using multifunction radar. Several methods are available for classification such as decision trees, Dempster-Shafer, Bayes, neural networks, etc. A different approach to assign the mass functions based on fuzzy logic in the Dempster-Shafer framework is proposed in this study. The method is evaluated for classification of different kinds of targets like aircraft, ballistic missiles, satellites, chaff and actual clouds, and unknown targets. With the proposed method, improvement in classification accuracy is observed, compared to existing mass functions. The technique is found to be computationally efficient and suitable for real-time systems.