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Tesi etd-04092008-103620
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Tipo di tesi Tesi di dottorato di ricerca
Autore GIOMPAPA, SOFIA
URN etd-04092008-103620
Titolo Analysis, Modelling, and Simulation of an Integrated Multisensor System for Maritime Border Control
Settore scientifico disciplinare INGEGNERIA DELL'INFORMAZIONE: ELETTRONICA, INFORMATICA, TELECOMUNICAZIONI -
Corso di studi INGEGNERIA DELL'INFORMAZIONE
Commissione
Nome Commissario Qualifica
Prof. Fulvio Gini Relatore
Dr. Alfonso Farina Relatore
Prof. Lucio Verrazzani Relatore
Prof. Marco Luise Relatore
Parole chiave
  • threat evaluation
  • command and control
  • coastal surveillance
  • classification
Data inizio appello 2008-06-10
Disponibilità mixed
Data di rilascio2048-06-10
Riassunto analitico
In this dissertation a notional multi-sensor system acting in a maritime border control
scenario for Homeland Security (HS) is analyzed, modelled, and simulated. The functions
performed by the system are the detection, tracking, identification and classification of
naval targets that enter a sea region, the evaluation of their threat level and the selection of a suitable reaction to them. The emulated system is composed of two platforms carrying multiple sensors: a land based platform, located on the coast, and an air platform, moving on an elliptic trajectory in front of the coast. The land based platform is equipped with a Vessel Traffic Service (VTS) radar, an infrared camera (IR) and a station belonging to an Automatic Identification System (AIS). The air platform carries an Airborne Early Warning Radar (AEWR) that can operate on a spotlight Synthetic Aperture Radar (SAR) mode, a
video camera, and a second IR camera. A Command and Control (C2) centre, located on the coast, coordinates the surveillance operation. In the maritime scenario four classes of naval targets are considered: high speed dinghy, immigrant boat, fishing boat, and oil tanker. A classification algorithm is also proposed which exploits an analytical approach based on the
confusion matrix (CM) of the imaging sensors that belong to the system. The performance
of the integrated system is evaluated in terms of its Measures of Effectiveness (MoE), which
are the system metrics on the detection, classification, threat level evaluation, and selection of the intervention. These metrics are evaluated considering both the cases where an ideal error free classification process and a non-ideal classification process are performed.
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