Drift Invariant Gas Recognition Technique for On Chip Tin Oxide Gas Sensor Array

The purpose of this paper is the study of the robustness of a new low complexity recognition method based on the measurement issued from an on chip 4times4 Tin oxide gas sensor array. The recognition system is based on a vector angle similarity measure between the query gas and the representatives of the different gas classes. The latter are obtained using a clustering algorithm based on the same measure within the training data set. Experimented results show more than 98% of good recognition and the robustness of the proposed approach is tested by recognizing gas measurements with simulated drift. Less than 1% of performance degradation is noted at the worst case.