Sengodan, Anand (2013) The SIMCA algorithm for processing ground penetrating radar data and ...

327 Pages·2013·40.71 MB·English

Sengodan, Anand (2013) The SIMCA algorithm for processing ground
penetrating radar data and its practical applications. PhD thesis.

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Glasgow Theses Service
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The SIMCA Algorithm for processing
Ground Penetrating Radar data and its
practical applications.
Anand Sengodan
Submittedinfulfilmentoftherequirementsforthe
DegreeofDoctorofPhilosophy
SchoolofComputingScience
CollegeofScienceandEngineering
UniversityofGlasgow
May,2012
(cid:13)c AnandSengodan
Abstract
The main objective of this thesis is to present a new image processing technique to improve the
detectabilityofburiedobjectssuchaslandminesusingGroundPenetratingRadar(GPR).Themain
challenge of GPR based landmine detection is to have an accurate image analysis method that is
capable of reducing false alarms. However an accurate image relies on having sufficient spatial
resolution in the received signal. An Antipersonnel mine (APM) can have a diameter as little as
2cm,whereasmanysoilshaveveryhighattenuationatfrequenciesabove450MHz.
In order to solve the detection problem, a system level analysis of the issues involved with the
recognitionoflandminesusingimagereconstructionisrequired. Thethesisillustratesthedevelop-
ment of a novel technique called the SIMCA (“SIMulated Correlation Algorithm”) based on area
or volume correlation between the trace that would be returned by an ideal point reflector in the
soil conditions at the site (obtained using the realistic simulation of Maxwell’s equations) and the
actual trace. During an initialization phase, SIMCA carries out radar simulation using the system
parametersoftheradarandthesoilproperties.
ThenSIMCAtakestherawdataastheradarisscannedoverthegroundandusesaclutterremoval
techniquetoremovevariousunwantedsignalsofcluttersuchascrosstalk,initialgroundreflection
andantennaringing. Thetracewhichwouldbereturnedbyatargetundertheseconditionsisthen
used to form a correlation kernel using a GPR simulator. The 2D GPR scan (B scan), formed by
abutting successive time-amplitude plots taken from different spatial positions as column vectors,
isthencorrelatedwiththekernelusingthePearsoncorrelationcoefficient resultinginacorrelated
imagewhichisbrightestatpointsmostsimilartothecanonicaltarget. Thisimageisthenraisedto
anoddpower>2toenhancethetarget/backgroundseparation.
The first part of the thesis presents a 2-dimensional technique using the B scans which have
been produced as a result of correlating the clutter removed radargram (’B scan’) with the kernel
produced from the simulation. In order to validate the SIMCA 2D algorithm, qualitative evidence
wasusedwherecomparisonwasmadebetweentheBscansproducedbytheSIMCAalgorithmwith
B scans from some other techniques which are the best alternative systems reported in the open
literature. It was found from this that the SIMCA algorithm clearly produces clearer B scans in
comparisontotheothertechniques.
Next quantitative evidence was used to validate the SIMCA algorithm and demonstrate that it
produced clear images. Two methods are used to obtain this quantitative evidence. In the first
methodanexpertGPRuserand4othergeneralusersareusedtopredictthelocationoflandmines
fromthecorrelatedBscansandvalidatetheSIMCA2Dalgorithm. Herehumanusersareaskedto
indicate the location of targets from a printed sheet of paper which shows the correlated B scans
produced by the SIMCA algorithm after some training, bearing in mind that it is a blind test. For
thesecondquantitativeevidencemethod,theAMIRAsoftwareisusedtoobtainvaluesoftheburial
depth and position of the target in the x direction and hence validate the SIMCA 2D algorithm.
Then the absolute error values for the burial depth along with the absolute error values for the
position in the x direction obtained from the SIMCA algorithm and the Scheers et al’s algorithm
whencomparedtothecorrespondinggroundtruthvalueswerecalculated.
Two-dimensionaltechniquesthatuseBscansdonotgiveaccurateinformationontheshapeand
dimensions of the buried target, in comparison to 3D techniques that use 3D data (’C scans’). As
aresultthenextpartofthethesispresentsa3-dimensionaltechnique. Theequivalent3Dkernelis
formed by rotating the 2D kernel produced by the simulation along the polar co-ordinates, whilst
the 3D data is the clutter removed C scan. Then volume correlation is performed between the
intersecting parts of the kernel and the data. This data is used to create isosurfaces of the slices
raisedtoanoddpower>2.
To validate the algorithm an objective validation process which compares the actual target
volume to that produced by the re-construction process is used. The SIMCA 3D technique and
theScheersetal’s(thebestalternativesystemreportedintheopenliterature)techniqueareusedto
image a variety of landmines using GPR scans. The types of mines included plastic, wooden and
glassones. InallcasesclearimageswereobtainedwithSIMCA.IncontrastScheers’algorithm,the
presentstate-of-the-art,failedtoprovideclearimagesofnonmetalliclandmines.
Forthisthesis,theabovealgorithmshavebeentestedforlandminedataandforlocatingfounda-
tionsindemolishedbuildingsandtovalidateanddemonstratethattheSIMCAalgorithmsarebetter
thanexistingtechnologiessuchastheScheersetal’smethodandtheREFLEXW commercialsoft-
ware.
Acknowledgements
Firstly I would like to thank my PhD supervisor, Dr. W. Paul Cockshott for his guidance, support
and patience throughout the course of this PhD. It is unlikely I would have come this far without
himandthetime,adviceandencouragementhededicatedtomyPhDaregratefullyacknowledged.
Iwouldalsoliketothankmysecondsupervisor,Dr. J.PaulSiebertforallhisguidanceandsupport.
I would like also to take this opportunity to express my sincere appreciation to all the staff at
UniversityofGlasgowfortheirsupportandvaluableassistancethroughoutmyPhD.
Iwouldliketoexpressmysincerethankstomyexternalandinternalexaminersandtheconvenor
for taking the time to study this thesis extensively, agreeing to examine me and also for taking
interestinthiswork.
TheauthorwouldliketothankMr. MattGuyandMr. ChrisLeechofGeomatrixEarthScience
Ltd, Dr. George Tuckwell (RSK) and Professor John M. Reynolds (Reynolds International Ltd)
for reading my thesis and for their time, effort and suggestions and to the various people in the
commercial arena for giving their time to review my work and offer me constructive feedback to
helpinthesuccessofthisPhD.
Furthermore, the author would like to extend his deepest gratitude to Dr. David J. Daniels of
Cobham Plc. (formerly ERA Technologies) and for Dr. Erica Utsi for their input into the work
completed in this PhD and for Dr. David J. Daniels for giving me the opportunity to undertake a
workplacementprogramunderhim.
SinceregratitudeisexpressedtoDr. DeanGoodmanofGeophysicalArchaeometryLaboratory
Inc, for providing me a student version of the GPR-SLICE software, and for answering questions
regardingGPRapplications.
ToMs. CarmenCuenca-Garcia,oftheDepartmentofArchaeologyattheUniversityofGlasgow
forherguidance,supportandtocompletethecarparksurveywhichprovidedthedatathatenabled
metotestmyalgorithminthecaseoflocatingfoundationsindemolishedbuildings.
Also to the European researchers and researchers at the Indian Institute of Technology for
providingmewiththelandminedata.
IwouldliketoacknowledgetheEngineeringandPhysicalSciencesResearchCouncil(EPSRC)
andtheUniversityofGlasgowforfundingthisPhD.
To the Knowledge Transfer Scotland: Policy and Practice Conference 2010 (Heriot-Watt Uni-
versity), for Thales Group (Thales Scottish Technology Prize 2010), and finally to the School of
Computing Science at the University of Glasgow for giving me runner up prices. To SET for Bri-
tain 2012 for short listing my PhD work to be showcased at the UK House of Parliament. To the
ICTPioneersCompetition2012judgesforawardingmethefinalistprizeinthetransformingsociety
category.
Last,butbynomeansleast,tomyparentsfortheirunconditionallove,supportandencourage-
mentovertheyears. WithouttheirhelpandsupportIwouldnothavebeenabletotravelthisjourney
and to complete my PhD. For this I dedicate this PhD to them, because without them, life would
nothaveanymeanings. MyhopeisalsothatthesuccessfulcompletionofthisPhDwillbringgood
healthtomyfatherandmotherandthatthehappinesswillmakethemlivemuchlonger.
Finally to the innocent victims of landmines, both civilians and the armed forces. I hope the
technology developed by this PhD can be used by civilian mine clearing teams, and also by the
armedforcestohelpaddresstheproblemofburieddevices.

OriginalityAnnouncement
’I hereby declare that this submission is my own work and to the best of my know-
ledge it contains no materials previously published or written by another person, or
substantial proportions of material which have been accepted for the award of any
otherdegreeordiplomaattheUniversityofGlasgoworanyothereducationalinsti-
tution, except where due acknowledgement is made in the thesis. Any contribution
madetotheresearchbyothers,withwhomIhaveworkedattheUniversityofGlas-
goworelsewhere,isexplicitlyacknowledgedinthethesis.’
AnandSengodan
Contents
1 Introduction 1
1.1 ContextandMotivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 ClassificationofMines . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.1.1 Anti-tankMine(ATM) . . . . . . . . . . . . . . . . . . . . . . 6
1.2.1.2 Anti-personnelMine(APM) . . . . . . . . . . . . . . . . . . . 6
1.2.2 TypesofGPRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.4 ThesisContributionsandPublications . . . . . . . . . . . . . . . . . . . . . . . . 10
1.4.1 WorkpublishedinConferenceproceedings . . . . . . . . . . . . . . . . . 12
1.4.2 WorktoappearinJournalproceedings . . . . . . . . . . . . . . . . . . . . 12
1.4.3 Prizeswon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.4.4 PATENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.5 OverviewofThesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2 BackgroundandLiteratureReview 15
2.1 HistoryofLandmines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 LayingofLandmines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.2 LayingofLandminesusedbytheGermanArmy . . . . . . . . . . . . . . 18
2.3 Historyofdeminingtechniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.1 ManualdeminingandMetaldetectors . . . . . . . . . . . . . . . . . . . . 20
2.3.2 AcousticSensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.3 InfraredImaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.4 DogsandRodentdetection . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3.5 GroundPenetratingRadar . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.4 Typicalprotocolusedintheclearanceoflandmines . . . . . . . . . . . . . . . . . 24
2.5 SinglearrayandMulti-arraySystemsavailableinthemarket . . . . . . . . . . . . 25
2.5.1 Hand-heldsingle-arraysystem . . . . . . . . . . . . . . . . . . . . . . . . 27
2.5.1.1 HSTAMIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.5.1.2 VallonMINEHOUNDVMR3 . . . . . . . . . . . . . . . . . . . 28
vii
CONTENTS viii
2.5.1.3 Advanced landmine imaging system (ALIS) - Hand-held GPR
Metaldetectorsystem . . . . . . . . . . . . . . . . . . . . . . . 28
2.5.2 Vehiclebasedmulti-arraysystem . . . . . . . . . . . . . . . . . . . . . . 30
2.5.2.1 Vehiclebasedmulti-arrayroboticsystem . . . . . . . . . . . . . 34
2.6 GPRandGlobalPositioningSystems . . . . . . . . . . . . . . . . . . . . . . . . 35
2.7 SoilpropertiesandtheireffectonGPRperformance . . . . . . . . . . . . . . . . . 36
2.8 GPRdataprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.8.1 ClutterRemoval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.8.1.1 Signalidentificationandanalysis . . . . . . . . . . . . . . . . . 47
2.8.2 GPRMAX2D/3Dv1.5usedforforwardmodelling . . . . . . . . . . . . . 48
2.9 MigrationtechniquetoprocessGPRdata . . . . . . . . . . . . . . . . . . . . . . 51
2.9.1 Explodingsourcemodel . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
2.9.2 Differenttypesofmigration . . . . . . . . . . . . . . . . . . . . . . . . . 53
2.9.2.1 Diffraction-summationMigration . . . . . . . . . . . . . . . . . 54
2.9.2.2 KirchhoffMigration . . . . . . . . . . . . . . . . . . . . . . . . 55
2.9.2.3 Finite-DifferenceMigration . . . . . . . . . . . . . . . . . . . . 56
2.9.2.4 Frequency-WavenumberMigration . . . . . . . . . . . . . . . . 56
2.9.2.5 Phase-shiftMigration . . . . . . . . . . . . . . . . . . . . . . . 57
2.9.2.6 Migrationbydeconvolution . . . . . . . . . . . . . . . . . . . . 57
2.10 CommercialsoftwareavailableforGPRdataprocessing. . . . . . . . . . . . . . . 61
2.10.1 GPR-SLICEsoftware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
2.10.2 REFLEXWsoftware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
2.11 SummaryandDiscussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3 SIMCA2Danditsvalidation 68
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.2 Calculatingdepthandvelocityofpropagation . . . . . . . . . . . . . . . . . . . . 71
3.3 Scheersetal’smigrationbydeconvolutionmethod . . . . . . . . . . . . . . . . . 72
3.4 DevelopmentoftheSIMCA2Dtechnique . . . . . . . . . . . . . . . . . . . . . . 73
3.4.1 GPRSimulationscarriedouttodevelopthekernels . . . . . . . . . . . . . 75
3.4.2 RemovalofclutterfromtherawGPRdata . . . . . . . . . . . . . . . . . . 78
3.4.3 ConvolutionandCorrelation . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.5 Resultsusingsimulateddata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.6 Experimentaldatasourceusedinthelaboratorytoobtainthelandminedatausedto
testtheSIMCA2Dalgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
I ResultsobtainedbyusingtheSIMCA2Dalgorithmonlandminedataobtained
fromGPRexperimentsconductedbyEuropeanresearchers. 83
3.7 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
3.8 GenerationofKernels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
viii