Title :
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
fDate :
10/1/2012 12:00:00 AM
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;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2012.6324669