This paper is focused on the development and the flight performance analysis of an image-processing technique aimed at detecting flying obstacles in airborne panchromatic images. It was developed within the framework of a research project which aims at realizing a prototypical obstacle detection and identification System, characterized by a hierarchical multisensor configuration. This configuration comprises a radar, that is, the main sensor, and four electro-optical cameras. Cameras are used as auxiliary sensors to the radar, in order to increase intruder aircraft position measurement, in terms of accuracy and data rate. The paper thoroughly describes the selection and customization of the developed image-processing techniques in order to guarantee the best results in terms of detection range, missed detection rate, and false-alarm rate. Performance is evaluated on the basis of a large amount of images gathered during flight tests with an intruder aircraft. The improvement in terms of accuracy and data rate, compared with radar-only tracking, is quantitatively demonstrated.
This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d’Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed.
The Italian Aerospace Research Centre and the Department of Aerospace Engineering at University of Naples have been involved in a project for the development of an Obstacle Detection and Tracking suite for autonomous Collision Avoidance of Unmanned Aerial Systems. In this framework, a flight prototype of an autonomous Obstacle Detect Sense and Avoid system has been designed and realized. It is installed onboard a Very Light Aircraft named FLARE. The system is based on multiplesensor data integration and it includes several components, such as a Ka-band pulsed radar, four Electro Optical sensors and two processing units. A hierarchical sensor configuration has been chosen in which the radar is the main sensor while EO cameras are the auxiliary ones to increase accuracy and data rate.In order to maximize the outcome of flight tests, an indoor facility for Hardware-In-The-Loop tests has been developed. The indoor facility includes processing units dedicated to simulate aircraft and intruder dynamics that are provided as input to sensors. The radar is replaced by a simulator, while the real visible camera unit is used. Flight images are displayed on a LCD screen. The facility permits to test multiple critical flight configurations and different sensors combinations. Moreover, the availability of a well assessed simulator allows the research team to support several activities such as: i) tuning of the data fusion techniques (i.e. tracking based on Kalman filtering); ii) system performance validation for a wide range of scenarios; iii) evaluation of alternative architectures that are difficult to be reproduced during flights. Some results of hardware-in-the-loop tracking tests based on flight data are briefly summarized and expected flight performance of the electro-optical system as auxiliary sensor is discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.