A Monotonicity-Based Regularization Approach to Shape Reconstruction for the Helmholtz Equation
By: Sarah Eberle-Blick, Bastian Harrach, Xianchao Wang
Potential Business Impact:
Finds hidden objects by measuring how they affect waves.
We consider an inverse boundary value problem for determining unknown scatterers, which is governed by the Helmholtz equation in a bounded domain. To address this, we develop a novel convex data-fitting formulation that is capable of reconstructing the shape of the unknown scatterers.Our formulation is based on a monotonicity relation between the scattering index and boundary measurements. We use this relation to obtain a pixel-wise constraint on the unknown scattering index, and then minimize a data-fitting functional defined as the sum of all positive eigenvalues of a linearized residual operator. The main advantages of our new approach are that this is a convex data-fitting problem that does not require additional PDE solutions. The global convergence and stability of the method are rigorously established to demonstrate the theoretical soundness. In addition, several numerical experiments are conducted to verify the effectiveness of the proposed approach in shape reconstruction.
Similar Papers
Inverse elastic obstacle scattering problems by monotonicity method
Analysis of PDEs
Find hidden shapes using sound waves.
A variational Lippmann-Schwinger-type approach for the Helmholtz impedance problem on bounded domains
Analysis of PDEs
Helps find hidden things by studying how waves bounce.
On the recovery of two function-valued coefficients in the Helmholtz equation for inverse scattering problems via inverse Born series
Numerical Analysis
Find hidden things using sound waves.