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We apply the L1 norm approaches on sparsely acquired data of the array ground penetrating radar (GPR) system YAKUMO. Due to the limitation of the antenna size of YAKUMO system, the antenna offsets between each element are much larger than the wavelength. Such sparsely acquired data may introduce strong artifacts to the imaging results such as synthetic aperture radar (SAR) processing and the velocity...
We propose a new iterative interpolation method for ground penetrating radar (GPR) data based on projection onto convex sets (POCS) and frequency-wavenumber (f-k) zone-pass filtering. The main purpose of this method is to simplify the three-dimensional (3-D) GPR data acquisition; it can also be used for conventional GPR data that include some missing traces. This approach allows the reconstruction...
We investigated a velocity analysis algorithm for the new array Ground Penetrating Radar (GPR) system “Yakumo”. The common mid-point (CMP) data, which is used to estimate the vertical profile of subsurface velocity can be acquired easily with this system. However, each CMP data set acquired by Yakumo includes only 8 GPR traces with more than 20 cm trace interval. In order to estimate the velocity...
This paper focuses on 3-dimensional (3D) image reconstruction by ground penetrating radar (GPR) data. Conventionally, we acquired a GPR gridded dataset with a fine interval, which satisfies the Nyquist spatial sampling criterion for an antenna. However, it takes long time for data acquisition. In this study, we tried two different approaches to reconstruct the image with sparse data that violated...
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