The Italian Aerospace Research Center UAV program aims at realizing a High Altitude Long Endurance unmanned flying laboratory, with fully autonomous flight functions. Within this program the development of the technologies needed to support the flight autonomy is the target of the project entitled TECVOL. This project aims at performing flight tests of prototype hardware systems developed to assess UAV autonomy. These systems are installed onboard a Very Light Aircraft named Flight Laboratory for Aeronautical Research Experiments in order to be tested in flight. A hardware/software prototype integrating autonomous obstacle Detect, Sense, and Avoid capability, has been designed and realized in collaboration with the Department of Aerospace Engineering of the University of Naples “Federico II”. Safe execution of autonomous collision avoidance provides the driving requirements for on-board sensors. They regard the scan envelope, the scan rate, the detection range, the range and angular resolution, the performance in bad weather conditions. This paper presents the development process of the original onboard sensor suite for autonomous detection and tracking of flying obstacles. First of all, system architecture is reported. The unit is composed by a Ka-band airborne pulsed radar, a visible panchromatic high-resolution camera, a visible color high-resolution camera, two thermal infra red cameras, and a processing unit for sensor data fusion. Subsequently, original technical strategies to realize an efficient system are discussed such as the high accuracy procedure for Electro Optical sensor alignment to aircraft body reference frame, the ground segment developed to monitor test flight in real time, the selected encounter geometries to validate the system, and the analysis of the effects of altitude on radar ground clutter. Finally, data from preliminary flight tests are presented and discussed.

An innovative sensor system for collision avoidance

FASANO, GIANCARMINE;ACCARDO, DOMENICO;MOCCIA, ANTONIO;
2008

Abstract

The Italian Aerospace Research Center UAV program aims at realizing a High Altitude Long Endurance unmanned flying laboratory, with fully autonomous flight functions. Within this program the development of the technologies needed to support the flight autonomy is the target of the project entitled TECVOL. This project aims at performing flight tests of prototype hardware systems developed to assess UAV autonomy. These systems are installed onboard a Very Light Aircraft named Flight Laboratory for Aeronautical Research Experiments in order to be tested in flight. A hardware/software prototype integrating autonomous obstacle Detect, Sense, and Avoid capability, has been designed and realized in collaboration with the Department of Aerospace Engineering of the University of Naples “Federico II”. Safe execution of autonomous collision avoidance provides the driving requirements for on-board sensors. They regard the scan envelope, the scan rate, the detection range, the range and angular resolution, the performance in bad weather conditions. This paper presents the development process of the original onboard sensor suite for autonomous detection and tracking of flying obstacles. First of all, system architecture is reported. The unit is composed by a Ka-band airborne pulsed radar, a visible panchromatic high-resolution camera, a visible color high-resolution camera, two thermal infra red cameras, and a processing unit for sensor data fusion. Subsequently, original technical strategies to realize an efficient system are discussed such as the high accuracy procedure for Electro Optical sensor alignment to aircraft body reference frame, the ground segment developed to monitor test flight in real time, the selected encounter geometries to validate the system, and the analysis of the effects of altitude on radar ground clutter. Finally, data from preliminary flight tests are presented and discussed.
9781563479458
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/306354
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