Analysis of nuclear quadrupole resonance signals from mixtures

Somasundaram, S.; Jakobsson, Andreas; Smith, J. A. S.

doi:10.1016/j.sigpro.2007.07.009

Cited by 17 publications

(5 citation statements)

References 25 publications

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“…For example, the explosive TNT exists in orthorhombic and monoclinic polymorphs, and the proportions are often not known [4]. Searching for monoclinic TNT when the explosive contains a mixture of both can severely deteriorate the detection peformance [17,18]. Sometimes the explosive is a mixture of several explosives, e.g., TNT and RDX [19].…”

Section: Signal Models and Data Acquisitionmentioning

confidence: 99%

“…Sometimes the explosive is a mixture of several explosives, e.g., TNT and RDX [19]. In [17,18], the authors proposed the following signal model for the mth echo of PSL data from a mixture of different explosives or polymorphs, or both:…”

Section: Signal Models and Data Acquisitionmentioning

confidence: 99%

“…Recently, more effective detectors have been proposed, exploiting more features in the NQR model. In [22], the authors proposed using the echo train model (2) together with a matched filter; in [11,15,17,23,24], generalized likelihood ratio tests were used in combination with the models presented in Section 2. Commonly, the amplitudes of the NQR signal were considered known to a multiplicative factor; however, in practice, this would not be the case in most realistic scenarios as the field at the sample will vary, causing variations in the NQR signal amplitudes.…”

Section: Detectorsmentioning

confidence: 99%

“…Furthermore, FETAML and FSAML are frequency selective. In order to utilize the possibly polymorphic structure of compounds, an extension of FETAML, termed FHETAML, was developed in [17]. FHETAML utilizes the polymorphic model in (4).…”

Section: Detectorsmentioning

confidence: 99%

See 3 more Smart Citations

An Overview of NQR Signal Detection Algorithms

Butt

Gudmundson

Jakobsson

2013

NATO Science for Peace and Security Series B: Physics and Biophysics

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Nuclear quadrupole resonance (NQR) is a solid-state radio frequency spectroscopic technique that can be used to detect the presence of quadrupolar nuclei, that are prevalent in many narcotics, drugs, and explosive materials. Similar to other modern spectroscopic techniques, such as nuclear magnetic resonance, and Raman spectroscopy, NQR also relies heavily on statistical signal processing systems for decision making and information extraction. This chapter provides an overview of the current state-of-the-art algorithms for detection, estimation, and classification of NQR signals. More specifically, the problem of NQR-based detection of illicit materials is considered in detail. Several single-and multi-sensor algorithms are reviewed that possess many features of practical importance, including (a) robustness to uncertainties in the assumed spectral amplitudes, (b) exploitation of the polymorphous nature of relevant compounds to improve detection, (c) ability to quantify mixtures, and (d) efficient estimation and cancellation of background noise and radio frequency interference.The authors are at

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Section: Signal Models and Data Acquisitionmentioning

confidence: 99%

Section: Signal Models and Data Acquisitionmentioning

confidence: 99%

Section: Detectorsmentioning

confidence: 99%

Section: Detectorsmentioning

confidence: 99%

See 2 more Smart Citations

An Overview of NQR Signal Detection Algorithms

Butt

Gudmundson

Jakobsson

2013

NATO Science for Peace and Security Series B: Physics and Biophysics

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“…From a signal processing standpoint, NQR detection presents the challenges of low signal-to-noise ratio (SNR) and susceptibility to RF noise and interferences (RFI), due to the very low substance response amplitude, which is in the order of tens of nV, comparable to the receiver's thermal noise level. Several signal processing solutions have been proposed to respond to these challenges and improve detection, ranging from energy detectors [3], that identify only one resonance frequency [4], to statistical algorithms [5][6][7]. The disadvantage of these solutions is their dependency on the estimation accuracy of the signal model's parameters which are used for taking the detection decision.…”

Section: Introductionmentioning

confidence: 99%

Multi-criteria decision algorithm for NQR signal detection

Monea

Iana

Ioniță

et al. 2020

2020 International Conference on Applied Electronics (AE)

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Nuclear quadrupole resonance is a spectroscopy technique used for chemical analysis, temperature measurement and detection of prohibited substances. It offers advantages like highly specific and non-invasive detection, but has the disadvantages of low signal-to-noise ratio and temperature dependence of the response signal, which are generally compensated by special hardware and signal processing solutions. This paper proposes a data processing algorithm based on multiple criteria designed to ensure nuclear quadrupole resonance detection in specific scenarios. In contrast with current algorithms, this solution does not require statistical estimation of the response's parameters. It is evaluated using a real data set composed of 8000 acquisitions and is shown to reach a detection probability of 94% that outperforms existing solutions for a specific detection threshold.

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Signal Processing and Analysis Techniques Applied in Nuclear Quadrupole Resonance

Monea

Bizon

2021

Signal Processing and Analysis Techniques for Nuclear Quadrupole Resonance Spectroscopy

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Analysis of nuclear quadrupole resonance signals from mixtures

Cited by 17 publications

References 25 publications

An Overview of NQR Signal Detection Algorithms

An Overview of NQR Signal Detection Algorithms

Multi-criteria decision algorithm for NQR signal detection

Signal Processing and Analysis Techniques Applied in Nuclear Quadrupole Resonance

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