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Data Reports

Reports containing either a description or a substantial amount of data, algorithms, and accompanying analyses for distribution and future reference.

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TALON13 dataset documentation TALON13 dataset documentation

Date added: 12/04/2014
Date modified: 12/04/2014
Filesize: Unknown

TALON13 dataset documentation. Horn, Steven A. ; Oddone, Manlio. CMRE-DA-2014-002. October 2014.

This dataset report presents a description of data collected during the 2013 TALON demonstration at the NATO Science and Technology Organization (STO) Centre for Maritime Research and Experimentation (CMRE). This dataset contains 8 days of data containing ship detections from marine radar, terrestrial Automatic Identification System (AIS), ship-borne AIS, and video camera sensors. Also included are the high-accuracy Global Positioning System (GPS) tracks of test boats used during the TALON demonstration. The purpose of this publication is to provide a reference multi-sensor dataset for the development and evaluation of processing algorithms. Potential research applications include multi-sensor data fusion, anomaly detection algorithms, traffic characterization, and visual analytics. The data is available on request from CMRE.

Vessel traffic dataset from ground-based AIS receiver Castellana: description and use Vessel traffic dataset from ground-based AIS receiver Castellana: description and use

Date added: 04/11/2014
Date modified: 04/11/2014
Filesize: Unknown

Vessel traffic dataset from ground-based AIS receiver Castellana: description and use. Pallotta, Giuliana ; Vespe, Michele. CMRE-DA-2014-001. March 2013.

This report provides a dataset (i.e., both raw data and processed data) consisting of positional AIS messages collected by CMRE using the Castellana receiver. The raw data can be used as a reference spatio-temporal dataset for Maritime Situational Awareness applications. Furthermore, the processed data illustrate the output of an unsupervised learning technique developed by CMRE (i.e., TREAD - Traffic Route Extraction and Anomaly Detection), able to inform patterns of life from traffic data. The goal of this document is to provide both real-world data to test algorithms for spatio-temporal data analysis and a benchmark (i.e., TREAD patterns of life) to compare the obtained results.

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