Error assessment of microwave holography inversion for shallow buried objects
Holographic imaging is a technique that uses microwave energy to create a three-dimensional image of an object or scene. This technology has potential applications in land mine detection, as the long-wavelength microwave energy can penetrate the ground and create an image of hidden objects without the need for direct physical contact. However, the inversion algorithms commonly used to digitally reconstruct 3D images from holographic images, such as Convolution, Angular Spectrum, and Fresnel, are known to have limitations and can introduce errors in the reconstructed image. Despite these challenges, the use of holographic radar at around 2 GHz in combination with holographic imaging techniques for land mine detection allows to recover size and shape of buried objects. In this paper, we estimate the reconstruction error for the convolution algorithm based on hologram imaging simulation and assess these errors recommending an increase in the scanner area, considering the limitations that the system has and the expected error reduction.
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