A Fast Iterative Interpolation Method in f-k Domain for 3-D Irregularly Sampled GPR Data

Li Yi, Kazunori Takahashi, Motoyuki Sato

    Research output: Contribution to journalArticlepeer-review

    8 Citations (Scopus)


    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 of the image from sparsely sampled data that violate the Nyquist criterion. The method can fully use 3-D information and works well with irregularly sampled data. Compared to other iterative interpolation methods, the proposed method needs many fewer iterations and can avoid aliasing. The algorithm is demonstrated with both synthetic data and real GPR measurements from a sand pit experiment. In the latter, the target could still be well reconstructed after 80% of the traces were randomly removed. The average spatial interval of the resampled data was 12 cm, which is much larger than the necessary interval as calculated using the Nyquist criterion. Detailed discussions on the large gap recovery issue and aliasing issue are also provided. The results indicate that it should be possible to reduce the data acquisition density in many GPR applications.

    Original languageEnglish
    Article number7307974
    Pages (from-to)9-17
    Number of pages9
    JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Issue number1
    Publication statusPublished - 2016 Jan


    • Ground penetrating radar (GPR)
    • interpolation
    • radar data processing

    ASJC Scopus subject areas

    • Computers in Earth Sciences
    • Atmospheric Science


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