Detecting NQR signals severely polluted by interference

Nuclear Quadrupole Resonance (NQR) signal detection can be severely obstructed by interference in real life settings, especially when the interference is strong, nonstationary, and its frequencies are close to that of the NQR signal. A novel algorithm is proposed to effectively remove (or reduce) interference components in the data and facilitate a valid detection of the NQR signal. The proposed method exhibits better performance compared to the previously proposed ETAML and FETAML algorithms, when applied to both simulated and measured data. Importantly, the present algorithm directly operates on the original primary data, without requiring any secondary data (NQR signal-free data) for acquiring prior knowledge of the interference. © 2017 Elsevier B.V. All rights reserved.