Recursive Least Squares algorithm dedicated to early recognition of explosive compounds thanks to multi-technology sensors

A. Mayoue (1) , A. Martin (1) , G. Lebrun (1) , A. Larue (1)

1 LADIS (CEA, LIST) - Laboratoire d'analyse des données et d'intelligence des systèmes (CEA, LIST)

In this paper, a novel gas identification approach based on the Recursive Least Squares (RLS) algorithm is proposed. We detail some adaptations of RLS to be applied to a sensor matrix of several technologies in optimal conditions. The low complexity of the algorithm and its ability to process online samples from multi-sensor make the real-time identification of volatile compounds possible. The effectiveness of this approach to early detect and recognize explosive compounds in the air has been successfully demonstrated on an experimentally obtained dataset.

Mots clés: Electronic NOSE; Explosive compounds; Multi-dimensional analysis; Optimal conditions; Real-time identification; Recursive least square (RLS); Recursive least squares algorithms; Volatile compounds; Algorithms; Explosives; Pattern recognition; Sensors; Signal processing; Volatile organic compounds; Explosives detection

Domaines: Traitement du signal et de l'image [eess.SP]; Chemo-informatique; Chimie analytique; Méthodologie [stat.ME]

A. Mayoue, A. Martin, G. Lebrun, A. Larue. Recursive Least Squares algorithm dedicated to early recognition of explosive compounds thanks to multi-technology sensors. 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2013, Vancouver, BC, Canada. pp.8761-8765, ⟨10.1109/ICASSP.2013.6639377⟩. ⟨cea-01830772⟩