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SUMMARY:Full-waveform inversion for ground penetrating radar via ensemble 
 Kalman inversion - Marco Iglesias (University of Nottingham)
DTSTART:20230201T123000Z
DTEND:20230201T131500Z
UID:TALK194536@talks.cam.ac.uk
DESCRIPTION:We develop a Bayesian full-waveform inversion approach for gro
 und penetrating radar. The\napproach uses waveform measurements to infer t
 he geometry of unknown metallic targets embedded in a host medium. The geo
 metry of targets is defined via the truncation of a levelset function that
  we infer together with the material properties of the medium. We employ a
  forward modelling setting where the unknown parameters (level-set and mat
 erial properties) are inputs for the open-source software gprMax which\, i
 n turn\, allows us to simulate electromagnetic wave propagation in dispers
 ive media and has built-in models of real antennas for ground penetrating 
 radar applications. The proposed Bayesian full-waveform\ninversion approac
 h is based on an Ensemble Kalman Inversion (EKI) algorithm that produces s
 ampling approximations of the posterior of the unknown level-set and mater
 ial properties. Numerical experiments with synthetic data show that\, unde
 r relatively small measurement errors\, EKI can accurately reconstruct the
  geometry of the targets within the regions of high probability produced b
 y the algorithm. We also show numerical results with real data from an exp
 eriment where steel rebars were embedded in a concrete slab. In this case\
 , the proposed approach was able to locate the rebars but with high uncert
 ainty due to large modelling errors of the simulation framework.
LOCATION:Seminar Room 1\, Newton Institute
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