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Detection of illegal narcotics using NQR

Swärd, Johan and Kronvall, Ted LU (2012) In Master's Theses in Mathematical Sciences
Abstract
This masters thesis deals with mathematical signal detection in the field of NQR,
Nuclear Quadrapole Resonance, which is a non-invasive spectroscopic technique used
to identify specific substances. The thesis has two main focuses, where the first is
to propose novel methods for parameter estimation, especially for identification of
unknown signals. These extend the existing Capon and APES methods for spectral
estimation to take the data model used for NQR signals into account. The less
general of them, named ETCAPA, works reasonably well for strong measurements.
This algorithm is a continuation of the ETCAPES method also derived during this
master thesis. The more general one, ETCapon, works less well for... (More)
This masters thesis deals with mathematical signal detection in the field of NQR,
Nuclear Quadrapole Resonance, which is a non-invasive spectroscopic technique used
to identify specific substances. The thesis has two main focuses, where the first is
to propose novel methods for parameter estimation, especially for identification of
unknown signals. These extend the existing Capon and APES methods for spectral
estimation to take the data model used for NQR signals into account. The less
general of them, named ETCAPA, works reasonably well for strong measurements.
This algorithm is a continuation of the ETCAPES method also derived during this
master thesis. The more general one, ETCapon, works less well for multi peak signals.
To the benefit of the algorithms, the number of frequency components must
not be defined in advance, which is the case for parametric models like ETAML
and least squares based estimation. The main contribution of these algorithms is to
find suitable search regions and to define the number of frequency components in
the signal, making it possible to use parametric algorithms for better estimation. A
pure interference canceling algorithm is also proposed, that uses a secondary data
set to remove any deterministic sinusoidal signals from the primary data. Initial
simulations indicate that this may work efficiently for simple interference signals.
The second focus of this thesis addresses the issue of detecting the illegal narcotic
methamphetamine in various situations. Together with the Itozaki Lab of
Osaka University and Tokyo Customs Lab in Japan, experiments have been made
possible in order to classify methamphetamine by identifying the parameters in the
data model, specific for the substance, and to find reasonable experimental settings
from which good detection can be made. It has also been confirmed that for quite
weak signals the ETAML detector is far superior to the commonly used FFT-based
method. (Less)
Please use this url to cite or link to this publication:
author
and
supervisor
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publishing date
type
Thesis
publication status
published
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in
Master's Theses in Mathematical Sciences
issue
2012:E34
pages
45 pages
ISSN
1404-6342
language
English
LU publication?
yes
id
961aa90e-591c-474a-bca7-4c5e5987cc42
alternative location
https://lup.lub.lu.se/student-papers/search/publication/3123371
date added to LUP
2025-03-12 11:44:20
date last changed
2025-04-14 11:50:26
@misc{961aa90e-591c-474a-bca7-4c5e5987cc42,
  abstract     = {{This masters thesis deals with mathematical signal detection in the field of NQR,<br/>Nuclear Quadrapole Resonance, which is a non-invasive spectroscopic technique used<br/>to identify specific substances. The thesis has two main focuses, where the first is<br/>to propose novel methods for parameter estimation, especially for identification of<br/>unknown signals. These extend the existing Capon and APES methods for spectral<br/>estimation to take the data model used for NQR signals into account. The less<br/>general of them, named ETCAPA, works reasonably well for strong measurements.<br/>This algorithm is a continuation of the ETCAPES method also derived during this<br/>master thesis. The more general one, ETCapon, works less well for multi peak signals.<br/>To the benefit of the algorithms, the number of frequency components must<br/>not be defined in advance, which is the case for parametric models like ETAML<br/>and least squares based estimation. The main contribution of these algorithms is to<br/>find suitable search regions and to define the number of frequency components in<br/>the signal, making it possible to use parametric algorithms for better estimation. A<br/>pure interference canceling algorithm is also proposed, that uses a secondary data<br/>set to remove any deterministic sinusoidal signals from the primary data. Initial<br/>simulations indicate that this may work efficiently for simple interference signals.<br/>The second focus of this thesis addresses the issue of detecting the illegal narcotic<br/>methamphetamine in various situations. Together with the Itozaki Lab of<br/>Osaka University and Tokyo Customs Lab in Japan, experiments have been made<br/>possible in order to classify methamphetamine by identifying the parameters in the<br/>data model, specific for the substance, and to find reasonable experimental settings<br/>from which good detection can be made. It has also been confirmed that for quite<br/>weak signals the ETAML detector is far superior to the commonly used FFT-based<br/>method.}},
  author       = {{Swärd, Johan and Kronvall, Ted}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  month        = {{09}},
  number       = {{2012:E34}},
  series       = {{Master's Theses in Mathematical Sciences}},
  title        = {{Detection of illegal narcotics using NQR}},
  url          = {{https://lup.lub.lu.se/student-papers/search/publication/3123371}},
  year         = {{2012}},
}