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A novel wavelets method for cancelling time-varying interference in NQR signal detection

机译:消除NQR信号检测中时变干扰的小波新方法

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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 general adaptive filtering methods. (C) 2018 Elsevier B.V. All rights reserved.
机译:干扰消除是核四极子共振(NQR)信号检测的一个非常重要的方面,当干扰随时间变化很大时,可能会变得非常困难。我们提出了一种新颖的小波方法,可以有效地消除(或减少)数据中随时间变化的干扰并有助于有效检测NQR信号。所提出的算法使用扩展的Gabor-Morlet小波基础来近似具有复杂时变特性的干扰。所提出的算法利用我们精心设计的成本函数从策略上从NQR数据中提取干扰分量。来自仿真和测量数据的数学推导和数值结果表明,即使干扰和目标信号严重重叠,该算法也可以精确消除强烈的时变干扰,而不会扭曲目标信号,从而改善了NQR检测。所提出的算法超越了常规小波方法,例如标准小波去噪方法,并且表现出比常规傅立叶分析和相关频率选择方法以及通用自适应滤波方法更好的性能。 (C)2018 Elsevier B.V.保留所有权利。

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