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Vessel Tracking and Anomaly Detection Using Level 0/1 and High-Level Information Fusion Techniques

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Soft Computing Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 357))

Abstract

In this paper, we survey state-of-the-art algorithms and processes that utilize synthetic aperture radar (SAR) and automatic identification system (AIS) as data sources with a goal of de-cluttering the operator’s workspace. The study differentiates between the use of soft computing techniques and other traditional ones and was broken down into two main sections, each describing a distinct aspect of the problem at hand. The first outlines the current Level 0/1 fusion techniques, while the second focuses on the high-level information fusion (HLIF) techniques. Advantages and drawbacks for the most relevant techniques are discussed and quantifiable metrics are disclosed.

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Author information

Authors and Affiliations

  1. Larus Technologies, Ottawa, Canada

    R. Abielmona & R. Falcon

  2. Defence R&D Canada, Ottawa, Canada

    P. W. Vachon

  3. University of Ottawa, Ottawa, Canada

    V. Z. Groza

Authors
  1. R. Abielmona
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  2. R. Falcon
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  3. P. W. Vachon
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  4. V. Z. Groza
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Corresponding author

Correspondence to V. Z. Groza .

Editor information

Editors and Affiliations

  1. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad Faculty of Engineering, Arad, Romania

    Valentina Emilia Balas

  2. Faculty of Science and Technology, Data Science Institute, Bournemouth University, Poole, United Kingdom

    Lakhmi C. Jain

  3. University of Belgrade, Belgrade, Serbia

    Branko Kovačević

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© 2016 Springer International Publishing Switzerland

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Abielmona, R., Falcon, R., Vachon, P.W., Groza, V.Z. (2016). Vessel Tracking and Anomaly Detection Using Level 0/1 and High-Level Information Fusion Techniques. In: Balas, V., Jain, L., Kovačević, B. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-319-18416-6_60

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  • DOI: https://doi.org/10.1007/978-3-319-18416-6_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18415-9

  • Online ISBN: 978-3-319-18416-6

  • eBook Packages: EngineeringEngineering (R0)

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