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Martina T Bevacqua1,2, Roberta Palmeri1

  • 1DIIES, Department of Information Engineering, Infrastructures and Sustainable Energy, Università Mediterranea di Reggio Calabria, via Graziella, Loc. Feo di Vito, 89124 Reggio Calabria, Italy.

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This study compares three qualitative methods for solving inverse obstacle problems using experimental data. The linear sampling, orthogonality sampling, and joint sparsity methods are evaluated for retrieving target properties from scattered fields.

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inverse obstacles probleminverse source problemjoint sparsitylinear sampling methodmicrowave imagingorthogonality sampling method

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Area of Science:

  • Computational electromagnetics
  • Inverse problems
  • Applied mathematics

Background:

  • Qualitative methods simplify inverse obstacle problems by reducing non-linearity and computational load.
  • Numerous qualitative approaches exist for retrieving target morphology from scattered fields.
  • Performance comparison of different qualitative methods is crucial for practical applications.

Purpose of the Study:

  • To compare the performance of three distinct qualitative methods for inverse obstacle problems.
  • To evaluate the effectiveness of linear sampling, orthogonality sampling, and a joint sparsity method.
  • To analyze the inversion of experimental data across various frequencies and scattering scenarios.

Main Methods:

  • Linear sampling method
  • Orthogonality sampling method
  • Joint sparsity and equivalence principles method
  • Analysis of experimental scattered field data

Main Results:

  • Performance evaluation of the three qualitative methods using experimental data.
  • Assessment across a range of working frequencies.
  • Consideration of different scattering experiment configurations.

Conclusions:

  • The study provides a comparative analysis of selected qualitative methods for inverse obstacle problems.
  • Findings are based on experimental data, offering practical insights.
  • The research contributes to understanding the efficacy of different qualitative approaches in real-world scenarios.