Radar target classification using improved Dempster–Shafer theory. Issue 21 (18th September 2019)

• Record Type: Journal Article
• Authors: Mehta, Parth; De, Anindita; Shashikiran, Dayalan; Ray, Kamla Prasan
• Is Part Of: Journal of engineering. Volume 2019:Issue 21(2019)
• Page Start: 7872
• Page End: 7875
• Publication Date: 2019-09-18
• Subjects: uncertainty handling -- inference mechanisms -- fuzzy logic -- radar target recognition; real‐time systems -- Dempster–Shafer theory -- mass functions -- fuzzy logic -- multifunction radar -- coarse classification -- radar target classification; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2019.0676
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : 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.