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Robust Nuclear Quadrupole Resonance Signal Detection Allowing for Amplitude Uncertainties

机译:鲁棒的核四极共振信号检测,允许幅度不确定性

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Nuclear quadrupole resonance (NQR) is a solid-state radio frequency spectroscopic technique that can be used to detect compounds which contain quadrupolar nuclei, a requirement fulfilled by many high explosives and narcotics. Unfortunately, the low signal-to-noise ratio (SNR) of the observed signals currently inhibits the widespread use of the technique, thus highlighting the need for intelligent processing algorithms. In earlier work, we proposed a set of maximum likelihood-based algorithms enabling detection of even very weak NQR signals. These algorithms are based on derived realistic NQR data models, assuming that the (complex) amplitudes of the NQR signal components are known to within a multiplicative constant. However, these amplitudes, which are obtained from experimental measurements, are typically prone to some level of uncertainty. For such cases, these algorithms will experience a loss in performance. Herein, we develop a set of robust algorithms, allowing for uncertainties in the assumed amplitudes, showing that these offer a significant performance gain over the current state-of-the art techniques.
机译:核四极共振(NQR)是一种固态射频光谱技术,可用于检测包含四极核的化合物,许多高级炸药和麻醉品都满足该要求。不幸的是,目前观察到的信号的低信噪比(SNR)阻碍了该技术的广泛使用,因此突出了对智能处理算法的需求。在较早的工作中,我们提出了一组基于最大似然的算法,甚至可以检测非常弱的NQR信号。这些算法基于派生的逼真的NQR数据模型,假设NQR信号分量的(复数)幅度在乘法常数内是已知的。然而,从实验测量获得的这些幅度通常倾向于某种程度的不确定性。在这种情况下,这些算法会损失性能。本文中,我们开发了一组鲁棒的算法,可以考虑假设幅度的不确定性,表明与当前的最新技术相比,这些算法具有显着的性能提升。

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