38 research outputs found

    GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection

    Get PDF
    Representing maritime traffic patterns and detecting anomalies from them are key to vessel monitoring and maritime situational awareness. We propose a novel approach-referred to as GeoTrackNet-for maritime anomaly detection from AIS data streams. Our model exploits state-of-the-art neural network schemes to learn a probabilistic representation of AIS tracks, then uses a contrario detection to detect abnormal events. The neural network helps us capture complex and heterogeneous patterns in vessels' behaviors, while the a contrario detection takes into account the fact that the learned distribution may be location-dependent. Experiments on a real AIS dataset comprising more than 4.2 million AIS messages demonstrate the relevance of the proposed method

    AIS-based Evaluation of Target Detectors and SAR Sensors Characteristics for Maritime Surveillance

    No full text
    International audienceThis paper studies the performances of different ship detectors based on adaptive threshold algorithms. The detec- tion algorithms are based on various clutter distributions and assessed automatically with a systematic methodology. Evaluation using large datasets of medium resolution SAR images and AIS (Automatic Identification System) data as ground truths allows to evaluate the efficiency of each detector. Depending on the datasets used for testing, the detection algorithms offer different advantages and disadvantages. The systematic method used in discriminating real detected targets and false alarms in order to determine the detection rate, allows us to perform an appropriate and consistent comparison of the detectors. The impact of SAR sensors characteristics (incidence angle, polarization, frequency and spatial resolution) is fully assessed, the vessels' length being also considered. Experiments are conducted on Radarsat-2 and CosmoSkymed ScanSAR datasets and AIS data acquired by coastal stations

    Maritime information sharing environment deployment using the advanced multilayered Data Lake capabilities: EFFECTOR project case study

    Get PDF
    Establishing an efficient information sharing network among national agencies in maritime domain is of essential importance in enhancing the operational performance, increasing the situational awareness and enabling interoperability among all involved maritime surveillance assets. Based on various data-driven technologies and sources, the EU initiative of Common Information Sharing Environment (CISE), enables the networked participants to timely exchange information concerning vessel traffic, joint SAR & operational missions, emergency situations and other events at sea. In order to host and process vast amounts of vessels and related maritime data consumed from heterogeneous sources (e.g. SAT-AIS, UAV, radar, METOC), the deployment of big data repositories in the form of Data Lakes is of great added value. The different layers in the Data Lakes with capabilities for aggregating, fusing, routing and harmonizing data are assisted by decision support tools with combined reasoning modules with semantics aiming at providing a more accurate Common Operational Picture (COP) among maritime agencies. Based on these technologies, the aim of this paper is to present an end-to-end interoperability framework for maritime situational awareness in strategic and tactical operations at sea, developed in EFFECTOR EU-funded project, focusing on the multilayered Data Lake capabilities. Specifically, a case study presents the important sources and processing blocks, such as the SAT-AIS, CMEMS, UAV components, enabling maritime information exchange in CISE format and communication patterns. Finally, the technical solution is validated in the project’s recently implemented maritime operational trials and the respective results are documented

    Sentinel-1 instruments status and product performance update for 2023

    Get PDF
    The Copernicus program, and particularly Sentinel-1, are among the largest Earth Observation SAR data providers, serving an ever-increasing number of services, users, and applications. A key aspect of the program is the constant provision of quality data, which requires long term engagement to carefully monitor, preserve, and even improve the system performances. These tasks are mainly carried out within the SAR Mission Performance Cluster (SAR-MPC), an international consortium of SAR experts in charge of the continuous monitoring of the Sentinel-1 instruments status and of the L1 and L2 products quality. This paper provides an update on the monitoring and the actions implemented by the SAR-MPC during 2022 and 2023. The analysis regards the monitoring of the instrument status, the evaluation of the instrument radiometric and geometric accuracy, and the updates of the S-1 Instrument Processing Facility

    Copernicus Cal/Val Solution - D3.2 - Recommendations for R&D on Cal/Val Methods

    Get PDF
    This document presents a gap analysis of the methods used in the calibration and validation of Earth Observation satellites relevant to the Copernicus programme and suggests recommendations for the research and developments required to fulfil this gap when/where possible. The document identifies the gaps and limitations of the CalVal methods, used for calibration and validation (CalVal) activities for the current Copernicus missions. It will also address the development needs for future Copernicus missions. Four types of missions are covered based on the division used in the rest of the CCVS project: optical, altimetry, radar and microwave and atmospheric composition. Finally, it will give a prioritized list of recommendations for R&D activities on the CalVal methods. The information included is mainly collected from the deliverables of work packages 1 and 2 in the CCVS project and from the consortium experts in CalVal activities

    Copernicus Cal/Val Solution - D3.1 Recommendations for R&D activities on Instrumentation Technologies

    Get PDF
    The Document identifies the gaps in instrumentation technologies for pre-flight characterisation, onboard calibration and Fiducial Reference Measurements (FRM) used for calibration and validation (Cal/Val) activities for the current Copernicus missions. It also addresses the measurement needs for future Copernicus missions and gives a prioritised list of recommendations for R&D activities on instrumentation technologies. Four types of missions are covered based on the division used in the rest of the CCVS project: optical, altimetry, radar and microwave and atmospheric composition. It also gives an overview of some promising instrumentation technologies in each measurement field for FRM that could fill the gaps for requirements not yet met for the current and future Copernicus missions and identifies the research and development (R&D) activities needed to mature these example technologies. The Document does not provide an exhaustive list of all the new technologies being developed but will give a few examples for each field to show what efforts are being made to fill the gaps. None of the examples is promoted as the best possible solutions. The selection is based on the authors' knowledge during the preparation of the Document. The information included is mainly collected from the deliverables of work packages 1 and 2 in the CCVS project. The new technologies are primarily from the interviews with various measurement networks and campaigns carried out in tasks 2.4 and 2.5. Reference documents can be found in section 1.3
    corecore