Automatic Radar Antenna Scan Type Recognition in Electronic Warfare

Author

Barshan, Billur ; Eravci, Bahaeddin

Author_Institution

Dept. of Electr. & Electron. Eng., Bilkent Univ., Ankara, Turkey

Volume

48

Issue

4

fYear

2012

fDate

10/1/2012 12:00:00 AM

Firstpage

2908

Lastpage

2931

Abstract

We propose a novel and robust algorithm for antenna scan type (AST) recognition in electronic warfare (EW). The stages of the algorithm are scan period estimation, preprocessing (normalization, resampling, averaging), feature extraction, and classification. Naive Bayes (NB), decision-tree (DT), artificial neural network (ANN), and support vector machine (SVM) classifiers are used to classify five different ASTs in simulation and real experiments. Classifiers are compared based on their accuracy, noise robustness, and computational complexity. DT classifiers are found to outperform the others.

Keywords

Bayes methods; computational complexity; decision trees; electronic warfare; feature extraction; military computing; neural nets; radar antennas; radar computing; radar signal processing; signal classification; signal sampling; support vector machines; ANN; AST recognition; DT classifier; EW; NB; SVM classifier; artificial neural network; automatic radar antenna scan type recognition; classification; computational complexity; decision-tree; electronic warfare; feature extraction; naive Bayes; noise robustness; resampling; scan period estimation; support vector machine; Classification algorithms; Radar antennas; Radar tracking; Receiving antennas;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2012.6324669

Filename

6324669