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ZHI Yuxiao, QIU Xiaohang, XU Jiangwan, et al. A horizon tracking algorithm for Chang’E-4 lunar surface penetrating radar based on dynamic search cente[J]. Journal of Radars, in press. doi: 10.12000/JR25216
Citation: ZHI Yuxiao, QIU Xiaohang, XU Jiangwan, et al. A horizon tracking algorithm for Chang’E-4 lunar surface penetrating radar based on dynamic search cente[J]. Journal of Radars, in press. doi: 10.12000/JR25216
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A Horizon Tracking Algorithm for Chang’E-4 Lunar Surface Penetrating Radar Based on Dynamic Search Center

DOI: 10.12000/JR25216 CSTR: 32380.14.JR25216
  • 1.

    Institute for Advanced Study Shenzhen University, Shenzhen 518060, China

  • 2.

    Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, China

  • 3.

    College of Civil Engineering and Transportation Shenzhen University, Shenzhen 518060, China

  • 4.

    Tiandu-Shenzhen University Deep Space Exploration Joint Laboratory Shenzhen University, Shenzhen 518060, China

  • 5.

    Key Laboratory of Lunar and Deep Space Exploration National Astronomical Observatories Chinese Academy of Sciences, Beijing 100012, China

  • 6.

    School of Astronomy and Space Science University of Chinese Academy of Sciences, Beijing 100049 China

Funds:  The National Natural Science Foundation of China (12473063, 12461160265, 62227901), Outstanding Young Scientists Fund of the Natural Science Foundation of Guangdong Province (26050000346), Shenzhen Science and Technology Innovation Commission ( JCYJ20240813141206009, JCYJ20250604182522029), Shenzhen University “2035 Pursuit of Excellence” Research Program (2024C009)
More Information
  • Corresponding author: DING Chunyu, dingchunyu@szu.edu.cn
  • Received Date: 2025-10-29
  • Rev Recd Date: 2026-01-11
    • Available Online: 2026-01-17
    Abstract
  • The Moon’s shallow subsurface structure provides crucial insights into its geological evolution, material composition, and space weathering processes. With the acquisition of extensive radar datasets from recent lunar exploration programs, such as the Chang’E missions, high-resolution characterization of the lunar regolith’s stratigraphic and physical properties has become a focus and challenge in lunar science. Conventional radar layer identification and tracking methods often suffer from instability in complex scattering environments, because of their sensitivity to noise and subsurface heterogeneity. To address these limitations, this study proposes an automatic layer-tracking algorithm based on a Dynamic Search Center (DSC) approach. This algorithm employs a Gaussian-weighted prediction mechanism to balance historical trajectory trends with local signal responses and uses a multifeatured fusion decision scheme to enhance tracking robustness under noisy conditions. Numerical simulations demonstrate that, with a search radius l = 20 and a historical window n = 20, the algorithm achieves a layer identification error of less than 2% for shallow strata (<140 ns). Meanwhile, for deep layers (>170 ns), with considerable signal attenuation, incorporating an edge-direction weighting term reduces the tracking error by over 30%. When applied to lunar penetrating radar data from the Chang’E-4 mission, the proposed method successfully realizes automatic stratigraphic tracing in lunar radar profiles, producing layer boundaries that are highly consistent with previous interpretations. Simulation and in-situ results confirm that the DSC-based algorithm accurately delineates real subsurface interfaces across media and structural morphologies, effectively suppressing noise, while maintaining smooth trajectories. Overall, the proposed method achieves low manual dependence, high robustness, and high precision in automatic radar layer tracking, thereby providing a valuable reference for analyzing radar data from upcoming missions such as Chang’E-7 and Martian shallow-subsurface explorations.

     

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