DocumentCode :
3342342
Title :
Optimal estimation techniques to reduce false alarms in railway obstacle detection
Author :
Garcia, Juan J. ; Losada, Cristina ; Espinosa, Felipe ; Urena, J. ; Hernandez, Alvaro ; Mazo, Manuel ; De Marziani, Carlos ; Jimenez, J.A. ; Jimenez, Ana ; Alvarez, Fernando
Author_Institution :
Dept. of Electron., Alcala Univ., Madrid
fYear :
2005
fDate :
14-17 Dec. 2005
Firstpage :
459
Lastpage :
464
Abstract :
This work presents some methods to reduce false alarms in railway obstacle detection. The sensorial system is based on one barrier of infrared emitters and another of receivers, placed on opposing sides of the railway. Obstacle detection is achieved by the lack of reception in the detectors. On the one hand, the efficiency of the system is achieved with the geometrical distribution of the sensorial system and the codification used in the emitting and receiving stages. On the other hand, optimal estimation techniques have been proposed to avoid false alarms, based on Kalman and Hinfin filtering. Principal component analysis is developed to validate the obstacle detection, and to improve the accuracy of the system. A high reliability under adverse conditions is obtained with the barrier, it being possible to detect the presence of obstacles, and to report on their position
Keywords :
Hinfin control; Kalman filters; collision avoidance; filtering theory; principal component analysis; railway accidents; Hinfin filtering; Kalman filtering; false alarm reduction; geometrical distribution; infrared emitters; optimal estimation techniques; principal component analysis; railway obstacle detection; sensorial system; Accidents; Bellows; Bridges; Filtering; Infrared detectors; Infrared sensors; Optical receivers; Rail transportation; Railway safety; Terrain factors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2005. ICIT 2005. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-9484-4
Type :
conf
DOI :
10.1109/ICIT.2005.1600682
Filename :
1600682
Link To Document :
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