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An Overview of NQR Signal Detection Algorithms

Butt, Naveed LU ; Gudmundson, Erik LU and Jakobsson, Andreas LU (2014) In Magnetic Resonance Detection of Explosives and Illicit Materials part 1. p.19-33
Abstract
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... (More)
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. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Magnetic Resonance Detection of Explosives and Illicit Materials
volume
part 1
pages
19 - 33
publisher
Springer
external identifiers
  • Scopus:84888352231
ISBN
978-94-007-7265-6
978-94-007-7264-9 (Print)
DOI
10.1007/978-94-007-7265-6-2
language
English
LU publication?
yes
id
f51b3ce0-f9ab-425c-a7c4-67e5d09d9067 (old id 4092849)
date added to LUP
2013-11-18 14:28:13
date last changed
2017-01-01 07:58:04
@inbook{f51b3ce0-f9ab-425c-a7c4-67e5d09d9067,
  abstract     = {Nuclear quadrupole resonance (NQR) is a solid-state radio frequency<br/><br>
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<br/><br>
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<br/><br>
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.},
  author       = {Butt, Naveed and Gudmundson, Erik and Jakobsson, Andreas},
  isbn         = {978-94-007-7265-6},
  language     = {eng},
  pages        = {19--33},
  publisher    = {Springer},
  series       = {Magnetic Resonance Detection of Explosives and Illicit Materials},
  title        = {An Overview of NQR Signal Detection Algorithms},
  url          = {http://dx.doi.org/10.1007/978-94-007-7265-6-2},
  volume       = {part 1},
  year         = {2014},
}