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
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.
9782917490204
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/457036
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