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.
Automatic Radar Antenna Scan Type Recognition in Electronic Warfare
IEEE Transactions on Aerospace and Electronic Systems ; 48 , 4 ; 2908-2931
2012-10-01
5754578 byte
Article (Journal)
Electronic Resource
English
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