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Título | Optimal estimation techniques to reduce false alarms in railway obstacle detection |
Tipo de publicación | Conference Paper |
Año de publicación | 2005 |
Autores | Garcia, JJ, Losada-Gutiérrez, C, Espinosa, F, Ureña, J, Hernández, Á, Mazo, M, Marzziani, CD, Jimenez, A, Álvarez, FJ |
Idioma de publicación | English |
Conference Name | IEEE International Conference on Industrial Technology, 2005. ICIT 2005. |
Páginas | 459 - 464 |
Conference Location | Hong Kong |
Fecha de publicación | 12/2005 |
Numero ISBN | 0-7803-9484-4 |
Palabras clave | collision avoidance, filtering theory, Hinfin control, Kalman filters, principal component analysis, railway accidents |
DOI | 10.1109/ICIT.2005.1600682 |
URL | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1600682&isnumber=33650 |
Resumen | 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. |
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ICIT-2005-JJ.pdf | 5.57 MB |