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Performance Assessment of Multistatic/Multi-Frequency 3D GPR Imaging by Linear Microwave Tomography
Performance Assessment of Multistatic/Multi-Frequency 3D GPR Imaging by Linear Microwave Tomography
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Performance Assessment of Multistatic/Multi-Frequency 3D GPR Imaging by Linear Microwave Tomography
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Performance Assessment of Multistatic/Multi-Frequency 3D GPR Imaging by Linear Microwave Tomography
Performance Assessment of Multistatic/Multi-Frequency 3D GPR Imaging by Linear Microwave Tomography
Journal Article

Performance Assessment of Multistatic/Multi-Frequency 3D GPR Imaging by Linear Microwave Tomography

2025
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Overview
The advent of multichannel ground-penetrating radar systems capable of acquiring multiview, multistatic, and multifrequency data is offering new possibilities to improve subsurface imaging performance. However, this raises the need for reconstruction approaches capable of handling such sophisticated configurations and the resulting increase in the data volume. Therefore, the challenge lies in identifying proper measurement configurations that balance image quality with the complexity and duration of data acquisition. As a contribution to this topic, the present paper focuses on a measurement system working in reflection mode and composed of an array of antennas, consisting of a transmitting antenna and several receiving antennas, whose spatial offset is comparable to the probing wavelength. Therefore, for each position of the transmitting antenna, a single-view/multistatic configuration is considered. The imaging task is solved by adopting a linear microwave tomographic approach, which provides a qualitative reconstruction of the investigated scenario. In particular, a 3D inverse scattering problem is tackled for an isotropic, homogeneous, lossless, and non-magnetic medium under the Born approximation, considering both single- and multi-frequency data. A preliminary analysis, referring to a 3D free-space reference scenario, is performed in terms of the spectral content of the scattering operator and the system’s point spread function. Finally, an experimental validation under laboratory conditions is presented in order to verify the expected imaging capability of the inversion approach.