GNSS-R: a useful tool for sea target detection in near real-time

• Published in: 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI)
• Main Authors: Di Simone, Alessio, Iodice, Antonio, Riccio, Daniele, Camps Carmona, Adriano José, Hyuk, Park
• Other Authors: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. Departament de Física, Universitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció, Universitat Politècnica de Catalunya. CTE-CRAE - Grup de Recerca en Ciències i Tecnologies de l'Espai
• Format: Conference Object
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE) 2017
• Subjects: Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços; Artificial satellites in navigation; Global Navigation Satellite System-Reflectometry (GNSS-R); Target detection; Maritime surveillance; Sea state; Constant false alarm rate (CFAR); Satèl·lits artificials en navegació; Sea ice
• Online Access: http://hdl.handle.net/2117/129669; https://doi.org/10.1109/RTSI.2017.8065958

This paper investigates a novel application of Global Navigation Satellite System-Reflectometry (GNSS-R) in the fields of maritime surveillance and safety, and climate change analysis, namely sea target detection in near real-time. Potentialities of the recent GNSS-R technology in the detection of targets over the sea (large ships, sea ice sheets) in near real-time are explored by: 1) computing the revisit time achieved with constellations of GNSS-R satellites; 2) deriving, implementing and testing a sea target detection algorithm. The global average revisit time is evaluated by mission simulation in two realistic scenarios and is shown as a function of the number of parallel receiver channels and the number of GNSS-R satellites in orbit. The sea target detection algorithm consists of four steps - pre-processing, pre-screening, selection, and geolocation - and is tested using actual UK TechDemoSat-1 data. Peer Reviewed Postprint (published version)