Volume 64, pp. 109-124, 2025.

Shape reconstruction of inclusions based on noisy data via monotonicity methods for the time-harmonic elastic wave equation

Sarah Eberle-Blick

Abstract

In this paper, we extend our research concerning the standard and linearized monotonicity methods for the inverse problem of the time-harmonic elastic wave equation and introduce modifications of these methods for noisy data. In more detail, the methods must provide consistent results when using noisy data in order to be able to perform simulations with real-world data, e.g., laboratory data. We therefore consider the disturbed Neumann-to-Dirichlet operator and modify the bound for the eigenvalues in the monotonicity tests for reconstructing unknown inclusions with noisy data. In doing so, we show that there exists a noise level $\delta_0$ such that the inclusions are correctly detected and their shape is reconstructed for all noise levels $\delta<\delta_0$. Finally, we present some numerical simulations based on noisy data.

Full Text (PDF) [2.3 MB], BibTeX , DOI: 10.1553/etna_vol64s109

Key words

inverse problems, time-harmonic elastic wave equation, inclusion detection, noisy data, monotonicity methods

AMS subject classifications

35R3, 74B05