Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/6216
AuthorsLeoncini, D.* 
Decherchi, S.* 
Faggioni, O.* 
Gastaldo, P.* 
Soldani, M.* 
Zunino, R.* 
TitleLinear SVM for Underwater Magnetic Signals Based Port Protection
Issue Date2010
Series/Report no.4/5 (2010)
URIhttp://hdl.handle.net/2122/6216
Keywordsunderwater detection systems
port protection
magnetic signal processing
Support Vector Machine
Subject Classification04. Solid Earth::04.05. Geomagnetism::04.05.04. Magnetic anomalies 
04. Solid Earth::04.05. Geomagnetism::04.05.08. Instruments and techniques 
05. General::05.01. Computational geophysics::05.01.01. Data processing 
05. General::05.01. Computational geophysics::05.01.05. Algorithms and implementation 
AbstractThe classical approach used to solve the underwater port protection problem is the acoustic based technique (sonar sensors). It has been shown that integrating a sonar system with an auxiliary array of magnetic sensors can improve the overall effectiveness of the intruder detection system. One of the major problems that arise from the use of magnetic systems is the interpretation of the magnetic signals coming from the sensors. In this paper a machine learning approach is explored for the detection of divers or, in general, of underwater magnetic sources that should ultimately support an automatic detection system. Currently this task requires a human online monitoring or an offline signal processing procedure. The proposed research, by windowing the sensed signals, uses Linear Support Vector Machines for classification, as tool for the detection problem. Preliminary empirical results show the viability of the method.
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