Globally Strictly Convex Cost Functional for a 1-D Inverse Medium Scattering Problem with Experimental Data

Michael V. Klibanov, Aleksandr E. Kolesov, Lam Nguyen, Anders Sullivan

SIAM Journal on Applied Mathematics · 2017 · 36 citations · 33 references

Concepts

Abstract

A new numerical method is proposed for a one-dimensional inverse medium scattering problem with multifrequency data. This method is based on the construction of a weighted cost functional. The weight is a Carleman weight function (CWF). In other words, this is the function which is present in the Carleman estimate for the undelying differential operator. The presence of the CWF makes this functional strictly convex on any a priori chosen ball with the center at \ 0\ in an appropriate Hilbert space. Convergence of the gradient minimization method to the exact solution starting from any point of that ball is proved. Computational results for both computationally simulated and experimental data show a good accuracy of this method.

References

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