HIGHLIGHTS• The proposed method effectively cancels complicated interference which can be strong, nonstationary, and have frequencies close to that of signal of interest.• The proposed method facilitates a valid detection of the NQR signal severely polluted by interference.• The proposed method performs better than general frequency selective methods of interference cancellation. AbstractNuclear 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.

If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.

Interference cancelation is a very important aspect of Nuclear Quadrupole Resonance (NQR) signal detection, and can become really difficult when the interference is considerably time-varying. We propose a novel wavelets method to effectively remove (or reduce) time-varying interference in the data and facilitate a valid detection of the NQR signal. The proposed algorithm uses an extended Gabor-Morlet wavelets basis to approximate interference with complicated time-varying properties. The proposed algorithm utilizes our well designed cost function to extract the interference components out from NQR data strategically.Mathematical derivations and numerical results from both simulated and measured data demonstrate that the proposed algorithm can precisely cancel strong time-varying interference without distorting signal of interest improving NQR detection, even when interference and signal of interest are severely overlapped.The proposed algorithm is beyond normal wavelets methods such as standard wavelets denoising methods, and exhibits better performance than normal Fourier analysis and related frequency selective methods and adaptive filtering methods.

An advanced beamforming approach based on two-channel echotrain system to cancel interference within an NQR signal resonance spectrum. SIGNAL PROCESSING.Please cite this article as: Weihang Shao, Jamie Barras, Panagiotis Kosmas, An advanced beamforming approach based on two-channel echo-train system to cancel interference within an NQR signal resonance spectrum, Signal Processing (2018), doi: https://doi.• This paper introduces a two-channel echo-train (TE) data acquisition system used in NQR signal detection and discovers/proves the beamforming characteristics of the TE system.• A novel beamforming approach based on this TE system is proposed which can nicely cancel interference within NQR resonance spectrum.• The proposed algorithm has excellent performance on detecting NQR signal polluted by interference and is superior to previously proposed algorithms, including the classical beamforming algorithms/detectors constructed on the TE system. AbstractInterference can be a huge challenge for Nuclear Quadrupole Resonance (NQR) signal detection in real life settings. The problem is particularly challenging when interference is strong around the resonant frequency band of the targeted NQR signal (to which we refer as the NQR band). This paper first proves the beamforming characteristics of a designed two-channel echo-train (TE) data acquisition system, and then presents a novel beamforming approach which is based on the TE system and is able to cancel interference effectively within the NQR band. After interference cancellation, NQR signal detection can be done successfully by applying an "echo train" approximate maximum likelihood (ETAML) algorithm to the residual data. The proposed algorithm is shown to be superior to previously proposed algorithms, including the classical beamforming algorithms/detectors constructed on the TE system, for detecting NQR signal polluted by interference.

Nuclear Quadrupole Resonance (NQR) signal detection is a promising explosives detection technology with applications to humanitarian demining. NQR works in the radiofrequency range, and one challenge to using it in such an application is coping with radiofrequency interference. We herein present an algorithm that cancels strong and complex radiofrequency interference (either stationary or nonstationary) improving the utility of NQR-based landmine detection in humanitarian demining. The algorithm has been tested on both simulated and measured data, and demonstrates good performance in NQR detection, in the presence of strong and complex interference.