Abstract

In this paper, the Stolt migration algorithm is modified for impulse borehole radar in near-field imaging where the transceiver is widely separated with respect to the detection range. The original sample set is converted to a multidimensional virtual sample set. The relation between angular frequency and wavenumbers of transmitter and receiver is derived in the frame of virtual sample set, which provides the basis for the interpolation in angular frequency. By applying multidimensional inverse fast Fourier transform (IFFT) to the interpolated frequency-wavenumber spectrum of the virtual sample set, the energy of target responses will focus in some profile of the IFFT result, which can be extracted according to the separation between the transmitter and receiver. The proposed method is compared with the conventional Stolt migration algorithm, back projection method, and Kirchhoff migration algorithm on synthetic data. The results show that the developed Stolt migration is superior to the conventional methods in cross-range resolution, computational cost, and the ability to reconstruct locations and shapes of targets.

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