Ground Penetrating Radar (GPR) is a powerful tool for detecting concealed elements within concrete structures and subsurface environments. Its application has become an essential part of modern construction workflows, empowering engineers and site personnel with the ability to identify embedded features that are otherwise invisible. This capability plays a critical role in informing structural decisions and maintaining site safety. Traditional GPR systems equipped with a single antenna generate one-dimensional vertical profiles, which can limit interpretation by isolating targets from their broader spatial context. In contrast, multichannel GPR arrays utilize multiple closely spaced antennas to replicate numerous parallel scans in a single pass. This configuration not only speeds up the scanning process but also improves spatial resolution and data accuracy. The result is greater reliability for all parties involved, from field technicians to project engineers and asset owners. This paper explores the fundamental principles behind Multi-Channel Ground Penetrating Radar (MCGPR), focusing on the impact of channel quantity, antenna orientation (polarisation), and frequency range selection on detection performance. It highlights how these variables influence the visibility of embedded objects and the clarity of the resulting data. Beyond detection, the discussion extends to how systematically collected GPR data at scale enables more advanced applications. These include AI-driven analysis for structural condition evaluation and the integration of subsurface data with surface models—such as those produced by terrestrial LiDAR and photogrammetry—to generate accurate digital twins. These comprehensive visualisations support informed decision-making across various stakeholders, even those without a technical background.
Barnes et al. (Thu,) studied this question.