Radar target classification using improved Dempster–Shafer theory

Autor: Parth Mehta, Anindita De, Dayalan Shashikiran, Kamla Prasan Ray
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: The Journal of Engineering (2019)
Druh dokumentu: article
ISSN: 2051-3305
DOI: 10.1049/joe.2019.0676
Popis: 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.
Databáze: Directory of Open Access Journals