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has been cited by the following article:

• TITLE: Target Ship Identification Algorithm Based on Comprehensive Correlation Discriminant and Information Entropy

  AUTHORS: Zhaoguo Shu

  KEYWORDS: Multi-Passive Sensor, Information Entropy, Target Ship Identification, Association Identification

  JOURNAL NAME: Journal of Computer and Communications, Vol.8 No.3, March 9, 2020

  ABSTRACT: Ship type identification is an important part of electronic reconnaissance. However, in the existing methods, such as statistical-based methods and fuzzy-mathematics-based methods, the information acquired by the passive sensor is not fully utilized, and there is a certain ambiguity in the assignment relationship of the emitters-ship. They can’t conclude the accurate and reliable assignment relationship of the emitters-ship. Therefore, this paper proposes a comprehensive correlation discriminant method to obtain a more reliable and comprehensive emitters-ship assignment, and then uses information entropy method to identify the type of the target ship on the basis of this association and assign the credibility. The simulation results show that this algorithm can effectively solve the problem of target ship type identification using the information of multi-passive sensors.