Computer Simulation of an Integrated Multi-Sensor System for Maritime Border Control

Giompapa, Sofia; Farina, A.; Gini, Fulvio; Graziano, A.; Stefano, R. Di

doi:10.1109/radar.2007.374233

Cited by 12 publications

(7 citation statements)

References 6 publications

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“…Data fusion techniques have been used for a long time in the MS domain. The majority of studies focused on target tracking, tactical situation awareness and threat assessment (Akselrod, Tharmarasa, Kirubarajan, Zhen Ding, & Ponsford, 2009;Bick & Barock, 2005;Danu, Sinha, Kirubarajan, Farooq, & Brookes, 2007;Di Lallo et al, 2006;Gad, 2009;Giompapa, Farina, Gini, Graziano, & Di Stefano, 2007;Giompapa et al, 2008;Hatch, Kaina, Mahler, & Myre, 1998;Henrich, Kausch, & Opitz, 2004;Jouan, Valin, Gagnon, & Bosse, 1999;Lefebvre & Helleur, 2001;Maresca et al, 2010;. Typically, in these works the combination of two or more sensors such as: Automatic Identification System (AIS), Infrared (IR), video camera, Synthetic Aperture Radar (SAR), Vessel Traffic Service (VTS) radar, Over The Horizon (OTH) radar, High Frequency Surface Wave Radar (HFSWR) and microwave radar is used and the surveillance area is limited to the coastal regions.…”

Section: Related Workmentioning

confidence: 99%

Open data for anomaly detection in maritime surveillance

Kazemi

Abghari

Lavesson

et al. 2013

Expert Systems with Applications

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Context Maritime Surveillance (MS) has received increased attention from a civilian perspective in recent years. Anomaly detection (AD) is one of the many techniques available for improving the safety and security in the MS domain. Maritime authorities utilize various confidential data sources for monitoring the maritime activities; however, a paradigm shift on the Internet has created new sources of data for MS. These newly identified data sources, which provide publicly accessible data, are the open data sources. Taking advantage of the open data sources in addition to the traditional sources of data in the AD process will increase the accuracy of the MS systems. Objectives The goal is to investigate the potential open data as a complementary resource for AD in the MS domain. To achieve this goal, the first step is to identify the applicable open data sources for AD. Then, a framework for AD based on the integration of open and closed data sources is proposed. Finally, according to the proposed framework, an AD system with the ability of using open data sources is developed and the accuracy of the system and the validity of its results are evaluated. Methods In order to measure the system accuracy, an experiment is performed by means of a two stage random sampling on the vessel traffic data and the number of true/false positive and negative alarms in the system is verified. To evaluate the validity of the system results, the system is used for a period of time by the subject matter experts from the Swedish Coastguard. The experts check the detected anomalies against the available data at the Coastguard in order to obtain the number of true and false alarms. Results The experimental outcomes indicate that the accuracy of the system is 99%. In addition, the Coastguard validation results show that among the evaluated anomalies, 64.47% are true alarms, 26.32% are false and 9.21% belong to the vessels that remain unchecked due to the lack of corresponding data in the Coastguard data sources. Conclusions This thesis concludes that using open data as a complementary resource for detecting anomalous behavior in the MS domain is not only feasible but also will improve the efficiency of the surveillance systems by increasing the accuracy and covering some unseen aspects of maritime activities.

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Section: Related Workmentioning

confidence: 99%

Open data for anomaly detection in maritime surveillance

Kazemi

Abghari

Lavesson

et al. 2013

Expert Systems with Applications

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“…The study of the classification process described here is part of a wider research activity finalized to the development of a software simulator that emulates the main functions of an integrated multisensor system acting in the field of maritime border control [4]. The mission of this multisensor system is the detection, the tracking, and the identification of multiple naval targets that enter a coastal region, the evaluation of their threat level and the selection of an appropriate intervention on them.…”

Section: Problem Statement and Methodologymentioning

confidence: 99%

Naval target classification by fusion of IR and EO sensors

et al. 2007

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This paper describes the classification function of naval targets performed by an infrared camera (IR) and an electrooptical camera (EO) that operate in a more complex multisensor system for the surveillance of a coastal region. The following naval targets are considered: high speed dinghy, motor boat, fishing boat, oil tanker. Target classification is automatically performed by exploiting the knowledge of the sensor confusion matrix (CM). The CM is analytically computed as a function of the sensor noise features, the sensor resolution, and the dimension of the involved image database. For both the sensors, a database of images is generated exploiting a three-dimensional (3D) Computer Aided Design (CAD) of the target, for the four types of ship mentioned above. For the EO camera, the image generation is simply obtained by the projection of the 3D CAD on the camera focal plane. For the IR images simulation, firstly the surface temperatures are computed using an Open-source Software for Modelling and Simulation of Infrared Signatures (OSMOSIS) that efficiently integrates the dependence of the emissivity upon the surface temperature, the wavelength, and the elevation angle. The software is applicable to realistic ship geometries. Secondly, these temperatures and the environment features are used to predict realistic IR images. The local decisions on the class are made using the elements of the confusion matrix of each sensor and they are fused according to a maximum likelihood (ML) rule. The global performance of the classification process is measured in terms of the global confusion matrix of the integrated system. This analytical approach can effectively reduce the computational load of a Monte Carlo simulation, when the sensors described here are introduced in a more complex multisensor system for the maritime surveillance.

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“…Analysing current solutions shows that there is no single technology that performs best in all situations and a need for integrating multiple technologies to achieve high level of security. According to Giompapa et al, 5 there are five factors that must be considered when developing a border monitoring system:…”

Section: Requirements Of An Effective Border Surveillance Systemmentioning

confidence: 99%

“…The coverage must be combined with real-time delivery of information; late data delivery will result in the failure of the surveillance mission as most situations require spontaneous intervention and response. 5 Another major challenge is the line-of-sight factor that curtails functioning and prevents monitoring behind walls or, in fact, or any type of physical obstacle. Many existing systems suffer from this defect, which degrades their performance not just in terms of long-range detection, but also in terms of the expenditure incurred due to repetitive installation of surveillance units.…”

Section: Requirements Of An Effective Border Surveillance Systemmentioning

confidence: 99%

Assessing the effectiveness of flying ad hoc networks for international border surveillance

Fayez

Hammoudeh

Adebisi

et al. 2019

International Journal of Distributed Sensor Networks

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International border security operations are diverse and include tasks to facilitate the legitimate movement of goods, thwart crime, maintain safety around borders and safeguard natural resources. All these operations are vital and enduring; however, three operations are currently of exceptional concern to countries around the world: counterterrorism, illegal drug control and illegal migration. The usage of flying ad hoc networks promises new ways for both military and civilian applications, such as border surveillance and remote sensing. Many systems were developed to assist border authorities with more effective surveillance and reliable decision-making support. Such systems vary in terms of the used technology, accuracy, types of events that can be detected and monitoring continuity. This article investigates the technical capabilities of existing and emerging surveillance technologies used for international border monitoring applications. It describes the effectiveness of these systems along with the technological infrastructure required for their implementation. Particular attention has been given to identifying the strengths and weaknesses of these systems and their ability to meet current and future challenges. Our analysis shows that flying ad hoc networks can be used to deliver a rapidly deployable, self-configurable, flexible and relatively small operating cost network for border surveillance.

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Computer Simulation of an Integrated Multi-Sensor System for Maritime Border Control

Cited by 12 publications

References 6 publications

Open data for anomaly detection in maritime surveillance

Open data for anomaly detection in maritime surveillance

Naval target classification by fusion of IR and EO sensors

Assessing the effectiveness of flying ad hoc networks for international border surveillance

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