In the framework of a Sense and Avoid project, an integrated Radar and Electro-Optical (EO) sensors solution has been adopted to fulfill the situational awareness requirement, demanded by the FAA for integrating UAS in the civil airspace. In particular, the sensors architecture is hierarchical: radar is the main sensor, whilst EO cameras have an auxiliary role. This paper focuses on the developed data fusion algorithms and their performance evaluation on the basis of flight tests data. Thus, it discusses multi-sensor tracking results and it demonstrates how the EO system increases reliability in collision risk estimation.
UAS Collision Avoidance System: Multi-Sensor Tracking Results / Forlenza, Lidia; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio. - ELETTRONICO. - (2011), pp. 96-99. (Intervento presentato al convegno ATACCS’2011 1st International Conference on Application and Theory of Automation in Command and Control Systems tenutosi a Barcelona, Spain nel 26-27 May 2011).
UAS Collision Avoidance System: Multi-Sensor Tracking Results
FORLENZA, LIDIA;FASANO, GIANCARMINE;ACCARDO, DOMENICO;MOCCIA, ANTONIO
2011
Abstract
In the framework of a Sense and Avoid project, an integrated Radar and Electro-Optical (EO) sensors solution has been adopted to fulfill the situational awareness requirement, demanded by the FAA for integrating UAS in the civil airspace. In particular, the sensors architecture is hierarchical: radar is the main sensor, whilst EO cameras have an auxiliary role. This paper focuses on the developed data fusion algorithms and their performance evaluation on the basis of flight tests data. Thus, it discusses multi-sensor tracking results and it demonstrates how the EO system increases reliability in collision risk estimation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
