Signal Processing and Analysis Techniques for Nuclear Quadrupole Resonance Spectroscopy

190 Pages·2022·5.669 MB·English

by  Cristian Monea · Nicu Bizon

Signals and Communication Technology
Cristian Monea
Nicu Bizon
Signal Processing and
Analysis Techniques
for Nuclear
Quadrupole
Resonance
Spectroscopy
Signals and Communication Technology
SeriesEditors
EmreCelebi,DepartmentofComputerScience,UniversityofCentralArkansas,
Conway,AR,USA
JingdongChen,NorthwesternPolytechnicalUniversity,Xi’an,China
E.S.Gopi,DepartmentofElectronicsandCommunicationEngineering,National
InstituteofTechnology,Tiruchirappalli,TamilNadu,India
AmyNeustein,LinguisticTechnologySystems,FortLee,NJ,USA
H.VincentPoor,DepartmentofElectricalEngineering,PrincetonUniversity,
Princeton,NJ,USA
Thisseriesisdevotedtofundamentalsandapplicationsofmodernmethodsofsignal
processingandcutting-edgecommunicationtechnologies.Themaintopicsareinfor-
mationandsignaltheory,acousticalsignalprocessing,imageprocessingandmulti-
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cationnetworks.Volumesintheseriesaddressresearchersinacademiaandindustrial
R&D departments. The series is application-oriented. The level of presentation of
eachindividualvolume,however,dependsonthesubjectandcanrangefrompractical
toscientific.
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For general information about this book series, comments or suggestions, please
contact Mary James at [email protected] or Ramesh Nath Premnath at
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Moreinformationaboutthisseriesathttp://www.springer.com/series/4748
·
Cristian Monea Nicu Bizon
Signal Processing
and Analysis Techniques
for Nuclear Quadrupole
Resonance Spectroscopy
CristianMonea NicuBizon
ResearchandDevelopmentDepartment FacultyofElectronics,Communications
MiraTechnologiesGroup andComputerScience
Voluntari,Romania UniversityofPitesti
Pitesti,Arges,Romania
DoctoralSchoolofElectronics,
TelecommunicationsandInformation DoctoralSchoolofElectronics,
Technology TelecommunicationsandInformation
PolitehnicaUniversityofBucharest Technology
Bucharest,Romania PolitehnicaUniversityofBucharest
Bucharest,Romania
ISSN1860-4862 ISSN1860-4870 (electronic)
SignalsandCommunicationTechnology
ISBN978-3-030-87860-3 ISBN978-3-030-87861-0 (eBook)
https://doi.org/10.1007/978-3-030-87861-0
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Foreword
This book brings new literature reviews on nuclear quadrupole resonance (NQR)
techniques,appropriatesignalprocessingtechniquesproposedforNQRspectrome-
tersandimplementedNQRspectrometersdevelopedtodate.
ThesignalsobtainedfromNQRspectroscopyaresimulatedtoproposeanNQR
signalmodeltobeusedonthecomparativeanalysis(basedonanewsetofperfor-
mance indicators proposed here) of the main signal processing methods that have
beendevelopedintheliterature.
So,thisbookproposesanewapproachtodetectingtheNQRsignalbyusingarti-
ficial intelligence methods (such as deep learning techniques and other proposed
advanced techniques). As a result of this study, the best performing solutions
are selected, adapted for NQR detection and implemented in a customized NQR
spectrometerand,finally,theNQR-basedequipmentwasevaluatedinrealconditions.
Thedatasetwasacquiredunderdifferentoperatingconditionsandwasanalysed
toevaluatetheperformanceofthecustom-designedNQRspectrometer.
Itisworthmentioningthattheimplementationofthedetectionsystemisdetailed
inthisbookfrombothahardwareandasoftwarepointofview,andtheinitialdeep
learningtechniqueproposedisfurtherimprovedinthepenultimatechapterbyusing
transfer learning and autoencoders to allow its use in other spectrometers and at
differentnoiselevels.
Thus,thecontentofthisbookisinterdisciplinary,involvingknowledgeofphysics,
electricalandelectronicsengineering,signalprocessing,signalanalysisandartificial
intelligence(machinelearning,deeplearning,etc.)andoptimization.
Therefore,thecontentofthisbookisaddressedtoresearchersstudyingthereso-
nance of nuclear quadrupoles and its applications, and NQR equipment manufac-
turers and readers in the multidisciplinary fields mentioned above, who want to
understandtheNQRspectrometerandthetechniquesusedinitsdesign.
So,bothresearchers(physicists,engineersandcomputerscientists)andengineers
working for manufacturers of security or laboratory equipment based on the NQR
technique,aswellasmaster’sanddoctoralstudentsstudyingandresearchingNQR
detection techniques, will all be interested to read this book because it proposes
(i) a new and performant NQR signal detection techniques based on improved
deep learning methods and (ii) a detailed description regarding the hardware and
v
vi Foreword
software implementation of an NQR detection equipment that implements the
above-mentionedsolutions.
Inconclusion,itisnoteworthythatthecontentofthechaptersispresentedgrad-
uallyandtheoreticallyindetailasnecessarytounderstandtheproblemsandeffec-
tivetechniquesforimplementingtheNQR,beinghighlyrecommendedforstudyin
educationandresearch.
Baku,Azerbaijan ArifM.Hashimov
April2021
Preface
Inrecentyears,globalterrorismandorganizedcrime,especiallyinthefieldofdrug
trafficking, have increased enormously, with more than 10,000 incidents per year
reported in the global terrorism database since 2017. For example, in 2017, over
140 tons of cocaine and 5 tons of heroin were confiscated inthe European Union,
andthenumberofconfiscationshasincreasedeveryyear.Inthiscontext,anumberof
prohibitedsubstancecontrolsystemshavebeendevelopedandinstalledworldwide
(atairports,customs,postofficesandbordercheckpoints)tocombatillegalactivity
andensurethesafetyofcitizens.
Therefore,thisbookaddressestheissueofimprovingthedetectionofprohibited
substancesusingthenuclearquadrupoleresonance(NQR)techniqueandtakesinto
accounttheadvancedsignalprocessingtechniquesrecentlyproposedintheliterature,
includingbytheauthorsofthisbook.
NQRisaconfirmedanalysistechniqueandrecognizedasasolutionthatmeetsthe
performancestandardsimposedforsecuritycheckpoints.Inshort,theNQRtechnique
isbasedonscanningtheobject(packageandluggage)whichmaycontainasubstance
of interest. An electromagnetic pulse train (called the excitation sequence) is used
forscanning,andtheresponseisreceivedattheendoftheexcitationsequence.The
NQR technique has the advantage of a high specificity relative to a substance of
interest,butitisalsoworthmentioningthatitisverydifficulttodetecttheresponse
(theweaksignalemittedbythesubstance).
Thisbookanalysesandproposesnewsignalprocessingandanalysismethodsfor
thedetectionofdangerousorcontrabandsubstances(suchasexplosives,narcotics
or toxic substances). Also, the hardware solutions implemented in a custom NQR
spectrometer(detector)aredescribed,andtheperformancesobtainedarecompared
withsimilaronesreportedintheliterature.
The identification of prohibited substances by nuclear quadrupole resonance
dependsonthephysicalprincipleusedanddeploymentlocationoftheNQRequip-
ment,becausethereceivedsignalhasalowsignal-to-noiseratioandissusceptible
toradiointerferenceinthesamefrequencyband.Inaddition,thespectrallinesare
dependentonthesubstance’stemperature.
Becausethedetectiontimeiscriticalandthenumberoffalse-positiveandfalse-
negativealarmsmustbeminimized,themainsignalprocessingchallengesarerelated
vii
viii Preface
totheabilitytodetecttheresponsesignalusingalimitednumberofacquisitions,to
performreal-timeanalysisoftheresponsesignal’scharacteristicsinordertocancel
radiofrequencynoiseandcompensatethetemperaturedependenceofspectrallines,
withtheultimategoalofmaximizingthedetectionaccuracy.
In the last decade, numerous laboratory NQR detection systems have been
proposed and implemented for identifying prohibited substances, with detection
probabilitiesofupto90%.However,thedetectionperformancedecreasesgreatlyin
theoperationalenvironmentduetothecausesmentionedabove.So,newhardware
and software solutions are needed to increase the performance of NQR detection.
Therefore,thepurposeofthisbookistopresentsomehardwareandsoftwaresolu-
tions to improve the performance of the NQR technique for detecting prohibited
substances.
Thisbookisstructuredintenchapters,andChap.1introducesthetopicofnuclear
quadrupoleresonancedetectionofprohibitedsubstances.
Chapter 2 briefly presents the methods and equipment for the acquisition and
analysisofsignalsfordetectionofprohibitedsubstances.
Chapter 3 continues the analysis started in Chap. 2, focusing on nuclear
quadrupole resonance spectroscopy and presenting its physical principle, specific
signalacquisitionmethods,andlaboratoryandcommercialNQRequipment.
Chapter4presentsindetailthespecificpre-processing,post-processingandsignal
analysistechniquesproposedfornuclearquadrupoleresonancedetection.
Chapter 5 presents the test signals that will be used in the following chapter to
studytheperformanceofthealgorithmsproposedintheliteratureforNQRsignal
processingandanalysis.
The study of the performance of the NQR algorithms is presented in Chap. 6
in order to define a reference regarding the obtained performance. It considers
specific performance indicators and a multi-criteria classification algorithm based
onanobjectivefunctiontoimprovetheprobabilityofdetection.
The experimental results of the acquisition of nuclear quadrupole resonance
signalsarepresentedandanalysedinChap.7inordertoidentifynewandimproved
NQRdetectiontechniques.
Thus,Chap.8presentsnewsignalanalysisalgorithmsbasedonmachinelearning
anddemonstratestheirimprovedperformanceindetectingsubstancesusingtheNQR
techniquecomparedtothosepresentedinthepreviouschapter.
Chapter 9 describes techniques for enhancing the performance of the machine
learningalgorithmproposedinthepreviouschapterthatarebasedontransferlearning
andnoisereductionusingautoencoders.
ThelastchapterpresentstheimplementationofanNQRequipmentusedforsignal
acquisition,processingandanalysis.Thehardwareandsoftwareimplementationsare
detailed,andthesystem’sperformanceindifferentoperatingconditionsisevaluated.
Summarizing,thesalientfeaturesofthebookwouldbethefollowing:
– Presenting a detailed literaturereview of the methods and equipment for signal
acquisitionandanalysisforthedetectionofprohibitedsubstances,
– Presentingtheprincipleofnuclearquadrupoleresonancespectroscopy,
Preface ix
– Providing a detailed literature review of the signal processing and analysis
techniques applied in nuclear quadrupole resonance detection, with a new
classification,
– Performing a modeling of the signals used in nuclear quadrupole resonance
spectroscopy,withtheproposalofanewsignalmodel,
– Performingacomparativestudyofthesignalprocessingandanalysisalgorithms,
inordertoverifyandcreateitsownreferencefortheperformanceindicators,that
willbeofhelpforcomparingthenewlydevelopedsolutions,
– Performingananalysisofthesignalsacquiredfromnuclearquadrupoleresonance
experimentswiththeaimofaidingthedevelopmentofnewdetectionsolutions,
– Proposing new signal analysis algorithms based on artificial intelligence/deep
learninginordertoimprovethedetectionofsubstancesbyNQRtechnique,
– Proposing new features for the classification of NQR signals using artificial
intelligence/deeplearningalgorithms,
– Proposingnewartificialintelligence/deeplearningtechniquesforenhancingthe
performanceofsignalanalysisalgorithms,
– Detailing the hardware and software implementations of an NQR signal
processingandanalysissystem,
– Helpful for researchers and practitioners in the areas of electrical engineering,
signal processing and analysis, applied spectroscopy, as well as for security or
laboratoryequipmentmanufacturers.
In conclusion, electrical engineering students and specialists are eligible and
guidedtousethebookeffectivelyintheircurrentactivities.
Pitesti,Romania CristianMonea
April2021 NicuBizon