scholarly journals The use of remote sensing for maritime surveillance for security and safety in Cyprus

2020 ◽  
Author(s):  
George Melillos ◽  
Kyriacos Themistocleous ◽  
Chris Danezis ◽  
Silas Michaelides ◽  
Diofantos Hadjimitsis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Maritime Surveillance

scholarly journals Applying an Adaptive Signal Identification Method to Improve Vessel Echo Detection and Tracking for SeaSonde HF Radar

2021 ◽  
Vol 13 (13) ◽  
pp. 2453
Author(s):  
Laurence Chuang ◽  
Yu-Ru Chen ◽  
Yu-Jen Chung
Keyword(s):  
Remote Sensing ◽  
Hf Radar ◽  
Automatic Identification ◽  
Identification System ◽  
Signal Identification ◽  
Identification Method ◽  
Maritime Surveillance ◽  
Detection And Tracking ◽  
Echo Detection ◽  
Adaptive Signal

To enhance remote sensing for maritime safety and security, various sensors need to be integrated into a centralized maritime surveillance system (MSS). High-frequency (HF) radar systems are a type of mainstream technology widely used in international marine remote sensing and have great potential to detect distant sea surface targets due to their over-the-horizon (OTH) capability. However, effectively recognizing targets in spectra with intrinsic strong disturbance echoes and random environmental noise is still challenging. To avoid the above problem, this paper proposes an adaptive signal identification method to detect target signals based on a rapid and flexible threshold. By integrating a watershed segmentation algorithm, the subsequent direction result can be used to automatically compute the direction of arrival (DOA) of the targets. To assist in the orientation of the object, forward intersections are integrated with the technique. Hence, the proposed technique can effectively recognize vessel echoes with automatic identification system (AIS) verification. Experiments have demonstrated the promising feasibility of the proposed method’s performance.

scholarly journals Parasitic Surveillance Potentialities Based on a GEO-SAR Illuminator

2021 ◽  
Vol 13 (23) ◽  
pp. 4817
Author(s):  
Fabrizio Santi ◽  
Giovanni Paolo Blasone ◽  
Debora Pastina ◽  
Fabiola Colone ◽  
Pierfrancesco Lombardo
Keyword(s):  
Remote Sensing ◽  
Regional Scale ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Signal Source ◽  
Maritime Surveillance ◽  
Radar Systems ◽  
The Earth ◽  
Different Types ◽  
Wide Availability

Synthetic aperture radar systems operating with satellites in geosynchronous orbits (GEO-SAR) can provide a permanent coverage of wide specific areas of the Earth’s surface. As well as for primary applications in remote sensing areas such as soil moisture and deformation monitoring, the wide availability of the signal emitted by a GEO-SAR on a regional scale makes it an appealing illuminator of opportunity for bistatic radars. Different types of receiving-only devices located on or near the Earth could exploit the same signal source, noticeably already conceived for radar purposes, for applications in the framework of both military and civil surveillance. This paper provides an overview of possible parasitic applications enabled by a GEO-SAR illuminator in different operative scenarios, including aerial, ground and maritime surveillance. For each selected scenario, different receiver configurations are proposed, providing an assessment of the achievable performance with discussions about the expected potentialities and challenges. This research aims at serving as a roadmap for designing parasitic systems relying on GEO-SAR signals, and also aims at extending the net of potential users interested in investing in GEO-SAR missions.

Machine learning-based ship detection and tracking using satellite images for maritime surveillance

2021 ◽  
Vol 13 (5) ◽  
pp. 361-371
Author(s):  
Yu Wang ◽  
G. Rajesh ◽  
X. Mercilin Raajini ◽  
N. Kritika ◽  
A. Kavinkumar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Satellite Images ◽  
Google Earth ◽  
Support Vector ◽  
Linear Discriminant ◽  
Ship Detection ◽  
Maritime Surveillance ◽  
Detection And Tracking ◽  
Multiple Hypothesis Tracking

The recent advancement in remote sensing technologies has resulted in the availability of different imaging modes and higher resolution satellite images. Accessibility of these remote sensing or satellite images, automatic ship detection and tracking has become an important research topic in the field of maritime surveillance. In this paper, a novel method for ship detection using satellite images is proposed. First the preprocessing is carried out to remove the noise from the images using Ship Detection and Tracking (SDT) filter. Then, the land masking (sea-land area separation) and cloud masking is carried out based on the gradient feature extraction using SDT edge detection, along with SDT segmentation. Finally, the ships are identified using the Machine Learning (ML) classifiers like Support Vector Machine (SVM), Random Forest Classifier (RFC), Linear Discriminant Analysis (LDA), Logistic Regression (LR), KNN, and Gaussian Naïve Bayes-based classifier based on the features extracted from Histogram of Oriented Gradients (HOG). The proposed work is cross validated using the Google earth data. Performance of our proposed method is evaluated using the recall and the precision values. Further, for tracking ships, an improved multiple hypothesis tracking (MHT) algorithm is proposed and tested using the Kaggle dataset.

scholarly journals Improved YOLOv3 Based on Attention Mechanism for Fast and Accurate Ship Detection in Optical Remote Sensing Images

2021 ◽  
Vol 13 (4) ◽  
pp. 660
Author(s):  
Liqiong Chen ◽  
Wenxuan Shi ◽  
Dexiang Deng
Keyword(s):  
Remote Sensing ◽  
High Efficiency ◽  
Attention Mechanism ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Optical Remote Sensing ◽  
Remote Sensing Images ◽  
Ship Detection ◽  
Maritime Surveillance ◽  
Detection Speed

Ship detection is an important but challenging task in the field of computer vision, partially due to the minuscule ship objects in optical remote sensing images and the interference of clouds occlusion and strong waves. Most of the current ship detection methods focus on boosting detection accuracy while they may ignore the detection speed. However, it is also indispensable to increase ship detection speed because it can provide timely ocean rescue and maritime surveillance. To solve the above problems, we propose an improved YOLOv3 (ImYOLOv3) based on attention mechanism, aiming to achieve the best trade-off between detection accuracy and speed. First, to realize high-efficiency ship detection, we adopt the off-the-shelf YOLOv3 as our basic detection framework due to its fast speed. Second, to boost the performance of original YOLOv3 for small ships, we design a novel and lightweight dilated attention module (DAM) to extract discriminative features for ship targets, which can be easily embedded into the basic YOLOv3. The integrated attention mechanism can help our model learn to suppress irrelevant regions while highlighting salient features useful for ship detection task. Furthermore, we introduce a multi-class ship dataset (MSD) and explicitly set supervised subclass according to the scales and moving states of ships. Extensive experiments verify the effectiveness and robustness of ImYOLOv3, and show that our method can accurately detect ships with different scales in different backgrounds, while at a real-time speed.

SWEDISH COAST GUARD STARTS USING THIRD GENERATION MARITIME SURVEILLANCE SYSTEM

1987 ◽  
Vol 1987 (1) ◽  
pp. 137-141
Author(s):  
Olov Fäst
Keyword(s):  
Remote Sensing ◽  
Coast Guard ◽  
Third Generation ◽  
Traffic Surveillance ◽  
Generation System ◽  
The Third ◽  
Sensing System ◽  
Maritime Surveillance ◽  
Main Ideas ◽  
Command Center

ABSTRACT Since 1981, the Swedish Coast Guard has been conducting daily oil spill surveillance patrols using small aircraft equipped with a remote sensing system. During this time, the use of the aircraft has widened to include a number of Coast Guard tasks such as fishery protection and sea traffic surveillance. This has necessitated the acquisition of aircraft with greater endurance and more loading capability. Two CASA 212 aircraft were delivered in 1986. In response to requests from Coast Guard operators, the remote sensing system has at the same time gone through a major revision. One of the main ideas in the third generation system is to give the operator computer aid in producing charts and reports for documenting routine missions, violations, and accidents. When necessary, as in the case of an accident, the charts can be immediately telecopied from the computer in the aircraft to a Coast Guard Command Center to ensure a quick and proper response.

The Sea from Space—Applying Remote Sensing to Societal Needs

2007 ◽  
Vol 41 (3) ◽  
pp. 4-15 ◽  
Author(s):  
Elena McCarthy ◽  
Flora Lichtman
Keyword(s):  
Remote Sensing ◽  
Health And Safety ◽  
Wind Farms ◽  
Offshore Wind ◽  
Marine Policy ◽  
National Defense ◽  
Offshore Wind Farms ◽  
Maritime Surveillance ◽  
Societal Needs ◽  
Remote Sensing Systems

The use of satellite-based remote sensing systems for observing marine environments is presented. Satellite observations of the marine environment, including weather, support efforts in economic development, national defense, resource management, and policy making, and contribute to the comfort, health, and safety of the public. Several emerging uses of remote sensing, with applications beyond the scope of conventional marine environmental monitoring, are presented, including: maritime surveillance, international treaty enforcement, oil prospecting, and siting of offshore wind farms. As a tool, satellite remote sensing has great potential to contribute to the development of sound marine policy and informed decision making.

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