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Sounding the Development Potential of Data Analysis Methodology for Metal Dectors Joint Project HuMin

PT-DLR UF /GHK. ITEP Workshop BAMBerlin, 16/17 Dec 2003. HuMin/MD Outline of Presentation. Mission/ObjectivesReduction of MD false alarm rates of off-the-shelf MDMethodology of data analysis in subsurface sensingTasks/ApproachesApplication of advanced methods of signal analysisLocal 3D Electromagnetic Induction TomographyForward modelling (computational electrodynamics)Model-based data inversion (advanced mathematics)ConsortiumConclusions .

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Sounding the Development Potential of Data Analysis Methodology for Metal Dectors Joint Project HuMin

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    1. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 Sounding the Development Potential of Data Analysis Methodology for Metal Dectors Joint Project HuMin/MD (funded by BMBF) Gerd-Henning Klein PT-DLR

    2. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Outline of Presentation Mission/Objectives Reduction of MD false alarm rates of off-the-shelf MD Methodology of data analysis in subsurface sensing Tasks/Approaches Application of advanced methods of signal analysis Local 3D Electromagnetic Induction Tomography Forward modelling (computational electrodynamics) Model-based data inversion (advanced mathematics) Consortium Conclusions

    3. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Mission/Objectives For the sake of MD false alarm reduction, sounding of the development potential of A. Data analysis methodology for off-the-shelf, hand-held MD B. MD sensor technology (building on the results of A) Reconstruction of features of buried metallic objects shape, position, orientation: 3D EMIT (w/ data from local MD scan) other (e.g. metal type): signal analysis (statistics/informatics) Provision/production of necessary measurement data Virtual data: MD process modelling (diverse MD, targets and soils) Real data: MD primary/raw signals (diverse MD, targets and soils) Application-oriented basic research, with practical advice

    4. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Tasks/Approaches Signal analysis: advanced methods of statistics and/or informatics Forward modelling of the MD measurement process, using tools of computational electrodynamics 3D EMIT: model-based data inversion, with advanced methods of computer tomography Provision of add-on devices for MD data acquisition: for determination of position/orientation for sampling of raw signals and position/orientation data for real-time computation and data visualization

    5. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 Signal Analysis Features Extraction/Classification Data preprocessing, e.g. Noise reduction (FFT, difference spectra, etc.) Transformations (wavelets, etc.) Mathematical statistics, e.g. Principal components analysis Discriminance analysis Multi-dimensional scaling, etc. Machine learning, e.g. Neural networks Support vector machines Kernel-based learning (Vapnik 1998)

    6. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Electromagnetic Induction Tomography Data provision: Local scan around anomaly pin-pointed by MD: variation of position r??3, orientation W??3 and other parameters p??p (e.g. frequency of continous wave mode) For each configuration ci = (ri,Wi,pi)??p+6, i = 1,...,m, this scan yields a signal si(t). Data analysis: Forward modelling of the MD measurement process (direct problem) with computational electrodynamics tools (numerical solution of the relevant system of differential/integral equations Reconstruction of subsurface conductivity patterns from scan data (model-based inversion) with tomography tools. Resolution depends on (usually) irregular pattern of point set {c1,..., cm}.

    7. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Forward modelling Modelling of MD measurement process, building on the underlying physics (electromagnetic induction, eddy currents) Simulations under diverse conditions (MD models, MD operations, mines, soils), by numerical solution of discretized Maxwell equations (or derivates of them) Synthetization of virtual MD data, used as inputs for model-based inversion and for sensitivity analysis By-product: better understanding of MD performance (useful for further development of MD technology)

    8. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD 3D EMIT: 3 Approaches 3 approaches of local tomography followed in parallel: Iteration methods and decomposition method (methodologies of Colton, Kress, Potthast et al.) Linear sampling method and factorization method (methodologies of Colton, Kirsch, Hanke et al.) Equivalent sources and approximate inverses (methodologies of Louis, Natterer, Maa et al.)

    9. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Consortium 10 research/university institutes involved: # Applied/numerical mathematics (tomography, data inversion) 4 Computational electrodynamics (general forward modelling) 1 Exploration geophysics (parametric modelling; soil database) 2 Non-destructive testing science/technology (real data) 1 Environmental technology (informatics, signal analysis) 1 Production technology (project management, signal analysis) 1 Practical expertise provided by sub-contractors: on MD technology (manufacturers) on MD use for humanitarian demining

    10. PT-DLR UF /GHK ITEP Workshop BAM Berlin, 16/17 Dec 2003 HuMin/MD Conclusions Broad spectrum of rigorous mathematical methodologies: Computational electromagnetics: diverse discretization approaches Tomography: novel approaches for model-based data-inversion Signal analysis: novel approaches, e.g. kernel-based learning Ambitious goals, with several developmental risks, but: Proof-of-concept milestones (with stop-show criteria) 3D EMIT: robustness/resolution of imaging (for diverse soils) Signal analysis: robustness of classification (for diverse soils) Operations: computational speed (real time); operator interface Experiences potentially useful for RTD in MD technology A template for analysis of emerging sensor technologies?

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