This paper focuses on test results from an Airborne Obstacle Tracking system for Unmanned Aerial System (UAS) See and Avoid applications that is based on Particle Filtering algorithm. It performs data fusion of airborne forward looking radar and electro-optical camera by exploiting data gathered during a Sense and Avoid flight experiment at Italian Aerospace Research Centre (CIRA). The developed model resulted adequate for tracking aircraft trajectories, thus overcoming the non-gaussian and non-linear form of the most widely adopted target dynamics models.
Obstacle Tracking Results: Cartesian vs. Spherical Particle Filter / Tirri, ANNA ELENA; Accardo, Domenico; Fasano, Giancarmine; Moccia, Antonio. - ELETTRONICO. - (2012), pp. 229-231. (Intervento presentato al convegno 2nd International Conference on Application and Theory of Automation in Command and Control Systems (ATACCS 2012) tenutosi a London UK nel 29-31 May 2012).
Obstacle Tracking Results: Cartesian vs. Spherical Particle Filter
TIRRI, ANNA ELENA;ACCARDO, DOMENICO;FASANO, GIANCARMINE;MOCCIA, ANTONIO
2012
Abstract
This paper focuses on test results from an Airborne Obstacle Tracking system for Unmanned Aerial System (UAS) See and Avoid applications that is based on Particle Filtering algorithm. It performs data fusion of airborne forward looking radar and electro-optical camera by exploiting data gathered during a Sense and Avoid flight experiment at Italian Aerospace Research Centre (CIRA). The developed model resulted adequate for tracking aircraft trajectories, thus overcoming the non-gaussian and non-linear form of the most widely adopted target dynamics models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
