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Electromagnetic subsurface prospecting by a multifocusing inexact Newton method within the second-order Born

Marco Salucci, Giacomo Oliveri, Andrea Randazzo

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|July 1, 2014

Summary

This study reconstructs shallow buried objects using electromagnetic inverse scattering. Combining the inexact Newton method with iterative multiscaling improves accuracy and robustness for subsurface imaging.

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Area of Science:

Geophysics and Remote Sensing
Electromagnetic Theory
Computational Imaging

Background:

Reconstructing shallow buried objects is challenging due to signal attenuation and scattering.
Electromagnetic inverse scattering methods offer a non-invasive approach for subsurface object detection.
Addressing nonlinearity and ill-posedness is crucial for accurate inversion.

Purpose of the Study:

To develop and validate an electromagnetic inverse scattering method for shallow buried object reconstruction.
To integrate the inexact Newton (IN) method with an iterative multiscaling approach.
To leverage the second-order Born approximation for enhanced imaging.

Main Methods:

The proposed approach combines the inexact Newton (IN) method with an iterative multiscaling strategy.
The second-order Born approximation is employed to model electromagnetic scattering.
Numerical simulations are used for validation and comparison.

Main Results:

The integrated approach demonstrates improved accuracy and robustness in object reconstruction.
The combination effectively mitigates the inherent nonlinearity and ill-posedness of the inversion problem.
Comparisons show advantages over the standard "bare" approach in terms of accuracy, noise tolerance, and computational efficiency.

Conclusions:

The proposed electromagnetic inverse scattering method, integrating IN and multiscaling, is effective for shallow buried object reconstruction.
This combined strategy offers superior performance compared to conventional methods.
The approach shows significant potential for practical applications in subsurface imaging and detection.