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Estimating the velocity of electromagnetic waves in the medium is essential for ground penetrating radar (GPR) to reconstruct target scenes. However, the existing velocity estimation methods based on imaging algorithms, e.g. the back-projection (BP)- and the Stolt migration-based methods, are susceptible to clutter and cannot strike a balance between depth independence and computational efficiency. Therefore, a velocity estimation method is proposed based on the vertex extraction-guided local BP algorithm. Initially, the high-order moment (HOM) is introduced into GPR data by analysing the distributions of target hyperbolas and clutter. Designed to avoid clutter, the proposed HOM sliding window extracts the hyperbola vertex at a high signal-to-clutter ratio region. By virtue of the extracted vertex, the local hyperbola region is subsequently extracted to reduce computation. Additionally, this paper adopts the depth-independent BP algorithm and further develops a local BP algorithm utilizing its imaging flexibility. Guided by the extracted vertex, the proposed local BP algorithm is iteratively performed on the local hyperbola region to estimate the velocity by a focus metric. Comprehensive experiments demonstrate the effectiveness and robustness of the proposed velocity estimation method. The proposed method outperforms the existing methods in clutter robustness, computational efficiency, and depth independence.

Vertex extraction-guided local back-projection algorithm for velocity estimation using ground penetrating radar data