Fusão de Dados com Sensores com Geometria e Granularidade Distintas em Ambiente de Alta Taxa de Eventos

One of the biggest challenges faced in multiple sensors systems is to provide an efficient combining data method to obtain information of interest as accurately as possible. This work presents a linear technique to combine the information from redundant sensors, in order to minimize the effects of noise. Results obtained using sensors from the Hadronic Calorimeter of the ATLAS Experiment (CERN, Switzerland), to detect muon particles, have shown a reduction of 6% in the noise from the combination of neighboring channels. The method is also very effective in detecting and removing bad channels, increasing the robustness of the system.