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

Zhaoguo Shu

doi:10.4236/jcc.2020.83007

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.

Highlights

In modern warfare, electronic intelligence reconnaissance has always been the focus of research
We propose a target ship model recognition algorithm based on comprehensive correlation discrimination and information entropy
The track of each radiation source detected is correlated by using the comprehensive correlation discrimination method, and the radiation source set belonging to the Emitter 1 Emitter 2 Emitter 3 Emitter 4 Emitter 5 Emitter 6

Summary

Introduction

Electronic intelligence reconnaissance has always been the focus of research. 2) Target platform recognition algorithm based on information entropy It is an urgent problem to be solved in radar countermeasure intelligence processing to study the potential association rules and knowledge between radar emitter and target platform, and how to transform the result of radar emitter recognition into platform discrimination more accurately and effectively. Electronic Support Measurement (ESM) sensor is a passive sensor that can provide angle information and emitters attribute information (carrier frequency, pulse width, pulse repetition interval, etc.) in the target position [5] These can obtain higher accuracy track correlation results, and provide a reliable basis for subsequent target ship model identification.

Track Autocorrelation Correlation Discrimination

Track-Related Decision Rules

Identification of Target Ship Model Based on Information Entropy

Case Analysis

Conclusion