Numerical Simulation of the Chang’E-7 Pseudo-Random Coded Lunar Penetrating Radar Data Using gprMax

The Chang’e-7 mission targets the lunar south pole, where complex stratigraphy and potential ice–regolith interfaces impose significant challenges for radar interpretation. To enhance detection depth and dynamic range, the mission’s Lunar Penetrating Radar (LPR) employs a pseudo-random coded transmission scheme with pulse compression, representing a significant departure from the carrier-free impulse systems of Chang’e-3 and Chang’e-4 . However, this transition introduces substantial simulation challenges: unlike simple impulses, the Chang’e-7 waveforms consist of extended Manchester-encoded Golay complementary sequences designed to shift spectral energy and suppress sidelobes . Simulating the transmission of these long-duration coded trains directly in time-domain solvers is computationally prohibitive, as the expanded time window drastically increases the required iteration steps. Moreover, standard approximations using simple wavelets fail to capture the specific spectral shaping and decoding characteristics inherent to the new hardware design.

To address these issues, this study proposed an efficient simulation framework based on the finite-difference time-domain (FDTD) method in gprMax. By treating the radar–subsurface interaction as a linear time-invariant (LTI) system, the proposed approach separated the electromagnetic propagation from the signal modulation. First, the system impulse response was extracted using a short-duration excitation. Subsequently, a software-defined signal processing module synthesized Manchester-encoded Golay complementary sequences to replicate the specific spectral shifting characteristics observed in the instrument’s design. These sequences were convolved with the impulse response and processed via the instrument's hybrid sampling logic to reconstruct wideband echoes . Finally, matched filtering and coherent accumulation were applied to achieve pulse compression. This strategy substantially reduced computational costs while maintaining high temporal–spectral fidelity and physical interpretability. Validation using a 2D numerical model with layered media and subsurface targets confirmed that weak reflections, initially masked by strong direct waves, became distinguishable after decoding. These findings demonstrated that the impulse-response synthesis approach captured the essential operating characteristics of the Chang’e-7 LPR, providing a practical numerical tool for data interpretation and parameter optimization in the complex lunar polar environment.