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Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System Data Integration Algorithm

Authors :
Dejan Nikolic
Nikola Stojkovic
Nikola Lekic
Source :
Sensors; Volume 18; Issue 4; Pages: 1147, Sensors, Vol 18, Iss 4, p 1147 (2018), Sensors (Basel, Switzerland)
Publication Year :
2018
Publisher :
Multidisciplinary Digital Publishing Institute, 2018.

Abstract

To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data.

Details

Language :
English
ISSN :
14248220
Database :
OpenAIRE
Journal :
Sensors; Volume 18; Issue 4; Pages: 1147
Accession number :
edsair.doi.dedup.....da1545baeedf775136ce9b568426df23
Full Text :
https://doi.org/10.3390/s18041147