Title :
Aircraft Classification Using a Microwave Barrier
Author :
Cristaldi, L. ; Antona, D.G. ; Faifer, M. ; Ferrero, A. ; Ottoboni, R.
Author_Institution :
Dipt. di Elettrotecnica, Politecnico di Milano
Abstract :
In the airport area, a runway incursion is represented by any situation in which a moving object (aircraft, car, person, animal, etc.) on the ground should produce a risk of collision. Due to its potentially catastrophic effects, the prevention and detection of runway incursion is a very important aim for any airport. This aim represents a multi-dimensional issue that can be faced only with a multi-dimensional and multi-task approach. From a measurement point of view, a fundamental role in this context is played by the sensors network employed in the airport area. Developing a cooperative sensor network able to carry out a real time, accurate and reliable information about the airport ground status is mandatory. This work presents the activity developed by the authors focused on the improvement of the measurement characteristic of a sensor system employed in an Italian airport for the surveillance of stop bars areas. A method, based on a classifier, which permits to extract new and high-level information from the sensor signals, is proposed. This method allows to classify the type of transiting object, discriminating therefore the intrusions from the authorized passages. In this way, by a simple retro fitting to existing system, a significant improvement of the safety of the traffic control process has been achieved
Keywords :
Bayes methods; air traffic control; airports; collision avoidance; distributed sensors; feature extraction; ground support systems; microwave technology; object detection; signal classification; surveillance; target tracking; Bayesian optimal decision; aircraft classification; airport ground status; catastrophic effects; collision risk; cooperative sensor network; high-level information extraction; microwave barrier; moving object; retro fitting; runway incursion detection; runway incursion prevention; signal classification; stop bars area surveillance; target detection; traffic control process safety; Aircraft; Airports; Animals; Area measurement; Bars; Data mining; Face detection; Sensor phenomena and characterization; Sensor systems; Surveillance; Bayesian optimal decision; Target detection; signal classification;
Conference_Titel :
Measurement Systems for Homeland Security, Contraband Detection and Personal Safety, Proceedings of the 2006 IEEE International Workshop on
Conference_Location :
Alexandria, VA
Print_ISBN :
1-4244-0241-7
Electronic_ISBN :
1-4244-0241-7
DOI :
10.1109/MSHS.2006.314349