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Special Issue "Remote Sensing for Maritime Safety and Security"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 1 October 2019

Special Issue Editor

Guest Editor
Dr. Raffaella Guida

Surrey Space Centre, University of Surrey, Guildford, GU2 7XH, UK
Website | E-Mail
Interests: Microwave remote sensing, Synthetic Aperture Radar, Data fusion, Electromagnetic modeling

Special Issue Information

Dear Colleagues,

Maritime safety and security is one of the most fundamental, critical and urgent goals of political agendas, as able to threaten, when at risk, in-country stability and international relationships. An accurate and real-time monitoring of seas and oceans is highly required to provide relevant organizations, governments and agencies with data and tools to support decision-making processes. From multi-sensor satellites to small-sats constellations, from emerging video to more standard optical and SAR data, from data fusion frameworks to single-dataset-based detectors, manifold are the remote sensing technologies, techniques and processing solutions able to support  a safe navigation, the control of maritime traffic and borders, the detection of illegal activities, the prosecution of responsible parties, the marine environment safeguard.

Researchers in the field are invited to contribute to this special issue on Remote Sensing for Maritime Safety and Security with innovative and game-changing remote sensing solutions (in the technologies, techniques or data processing) in any of the maritime applications mentioned above.

.

Dr. Raffaella Guida
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • maritime safety
  • security
  • surveillance
  • remote sensing
  • ship detection and tracking
  • wake detection
  • oil spill detection
  • modeling
  • data fusion

Published Papers (1 paper)

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Research

Open AccessArticle
A Geometric Barycenter-Based Clutter Suppression Method for Ship Detection in HF Mixed-Mode Surface Wave Radar
Remote Sens. 2019, 11(9), 1141; https://doi.org/10.3390/rs11091141
Received: 10 April 2019 / Revised: 9 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
PDF Full-text (5544 KB) | HTML Full-text | XML Full-text
Abstract
The nonhomogeneous clutter is a major challenge for ship detection in high-frequency mixed-mode surface wave radar. In this paper, a geometric barycenter-based reduced-dimension space-time adaptive processing method is proposed to suppress the clutter. Given the measured dataset, the range correlation of sea clutter [...] Read more.
The nonhomogeneous clutter is a major challenge for ship detection in high-frequency mixed-mode surface wave radar. In this paper, a geometric barycenter-based reduced-dimension space-time adaptive processing method is proposed to suppress the clutter. Given the measured dataset, the range correlation of sea clutter is first investigated. Then, joint domain localized processing is applied to solve the training samples starve scenario in a practical system. The geometric barycenter-based training data selector is presented to select valid training samples and improve the accuracy of the clutter covariance matrix estimation. Finally, the validity of the proposed method is verified using the experimental data and the results show that it outperforms the conventional method in the nonhomogeneous environment of a practical system. Full article
(This article belongs to the Special Issue Remote Sensing for Maritime Safety and Security)
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