Maritime Surveillance Using Multiple High-Frequency Surface-Wave Radars

Maresca, Salvatore; Braca, Paolo; Horstmann, Jochen; Grasso, Raffaele

doi:10.1109/tgrs.2013.2286741

Cited by 122 publications

(79 citation statements)

References 28 publications

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“…Other products that can be obtained by means of advanced signal processing include: winds (Heron and Rose, 1986;Shen et al, 2012), and tsunami (Lipa et al, 2006;Gurgel et al, 2011;Grilli et al, 2015). In addition, several works have proven the potential use of HFRs for ship detection (Ponsford et al, 2001;Dzvonkovskaya et al, 2008) and tracking (Maresca et al, 2014). An example of ship detection using HFR is provided in Figure 4.…”

Section: Basic Principles Of Hfr Operation and Data Specificationsmentioning

confidence: 99%

“…In general an HFR sends out modulated radio waves and listens to the returned signal, which is mainly affected by the surface waves propagating along radar look direction that are of the order of the transmitted wave length (Bragg scattering). From the measured backscatter several oceanic parameters can be obtained, such as: ocean surface currents (e.g., Paduan and Rosenfeld, 1996;Gurgel et al, 1999;Shrira et al, 2001), waves (e.g., Wyatt et al, 2006), winds (e.g., Shen et al, 2012), tsunami (e.g., Lipa et al, 2006) and discrete targets (ships) (e.g., Maresca et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

et al. 2017

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High Frequency Radar (HFR) is a land-based remote sensing instrument offering a unique insight to coastal ocean variability, by providing synoptic, high frequency and high resolution data at the ocean atmosphere interface. HFRs have become invaluable tools in the field of operational oceanography for measuring surface currents, waves and winds, with direct applications in different sectors and an unprecedented potential for the integrated management of the coastal zone. In Europe, the number of HFR networks has been showing a significant growth over the past 10 years, with over 50 HFRs currently deployed and a number in the planning stage. There is also a growing literature concerning the use of this technology in research and operational oceanography. A big effort is made in Europe toward a coordinated development of coastal HFR technology and its products within the framework of different European and international initiatives. One recent initiative has been to make an up-to-date inventory of the existing HFR operational systems in Europe, describing the characteristics of the systems, their operational products and applications. This paper offers a comprehensive review on the present status of European HFR network, and discusses the next steps toward the integration of HFR platforms as operational components of the European Ocean Observing System, designed to align and integrate Europe's ocean observing capacity for a truly integrated end-to-end observing system for the European coasts.

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Section: Basic Principles Of Hfr Operation and Data Specificationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

et al. 2017

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“…A similar approach for detecting changes using nonlinear stacked restricted Boltzmann machines is given in the work of Liu et al [20], while multilayered feature learning to improve detection accuracy of SAR images is described by Xie et al [21]. Furthermore, low-power HF surface-wave (HFSW) radars have demonstrated being a cost-effective long-range early-warning sensor for ship detection and tracking [22, 23]. A detailed description of various ways in which HFSW radar technology can be used for maritime surveillance is provided by Braca et al [24].…”

Section: Related Workmentioning

confidence: 99%

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Protopapadakis

Voulodimos

Doulamis

et al. 2017

Computational Intelligence and Neuroscience

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Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlier detection at over-the-horizon (OTH) distances. However, a number of disadvantages, such as their low spatial resolution and presence of clutter, have a negative impact on their accuracy. In this paper, we explore the applicability of deep learning techniques for detecting deviations from the norm in behavioral patterns of vessels (outliers) as they are tracked from an OTH radar. The proposed methodology exploits the nonlinear mapping capabilities of deep stacked autoencoders in combination with density-based clustering. A comparative experimental evaluation of the approach shows promising results in terms of the proposed methodology's performance.

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“…information, but also the navigation status like position, speed, and course, which could assist vessels and maritime authorities to track and monitor vessel movements so as to improve the ports management and maritime security [2,3,4]. The navigation information is generated by positioning devices like Global Navigation System (GNSS) technology, inertial navigation technology or other electronic navigation sensors.…”

Section: Introductionmentioning

confidence: 99%

Optimal Data Fusion Algorithm for Navigation Using Triple Integration of PPP-GNSS, INS, and Terrestrial Ranging System

Jiang

Rizos

2015

IEEE Sensors J.

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A good port management system must be able to perform safe, predictable and efficient execution of transport processes. In order to improve the quality of the port management, a robust navigation system is required, which enables to provide the positions of vessels 24/7 on either open or impeded environment. This paper describes a robust georeferencing system that could satisfy centimetre-level accuracy requirements in port environments. The design is based on the loosely-coupled integration of Global Navigation Satellite System (GNSS) technology, a terrestrial radio frequency ranging system known as "Locata", and an inertial navigation system (INS). GNSS observations are processed using the precise point positioning (PPP) approach instead of the conventional differential approach. To satisfy both accuracy and reliability requirements, three integration algorithms -centralised Kalman filtering (CKF), federated Kalman filtering (FKF) and global optimal filtering (GOF) -are investigated and implemented into a "triple-integrated" PPP-GNSS/Locata/INS system. A preliminary performance assessment, which is based on the analysis of real data, concludes that all the three integration algorithms are able to provide centimetre-level positioning solutions. The results show that the FKF and CKF algorithms have similar performance, whereas the GOF solution has higher accuracy. Moreover, outlier simulation is conducted and the result verifies the outlier fault-tolerant capability of the GOF based PPP-GNSS/Locata/INS integrated system.

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Maritime Surveillance Using Multiple High-Frequency Surface-Wave Radars

Cited by 122 publications

References 28 publications

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Optimal Data Fusion Algorithm for Navigation Using Triple Integration of PPP-GNSS, INS, and Terrestrial Ranging System

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