Trajectory-Guided Photon Accumulation for Photon-Efficient LiDAR Remote Sensing in Low-SBR Dynamic Scenes

Photon-efficient LiDAR provides an active remote sensing pathway for long-range, low-light three-dimensional observation, but photon-limited reconstruction remains difficult when background events dominate sparse returns. In dynamic scenes, line-of-sight motion further disperses weak-target photons across range-time bins and broadens fixed-bin accumulation. Existing methods mainly exploit histogram statistics, spatial priors, or learned representations, whereas explicit range-time migration constraints for interframe photon alignment remain insufficiently explored. We present a range-time trajectory-guided photon accumulation method for a 1064 nm InGaAs/InP 64×64 GM-APD array. The method combines range-dependent background correction, multi-scale photon statistics, bounded trajectory parameter optimization using PSO, trajectory-aligned accumulation, and confidence-weighted spatial-range fusion. At -12.34 dB in simulation, SSIM, RMSE (range bins), PSNR, IoU, and FPR were 0.61, 223.22, 6.36 dB, 0.74, and 0.10%, respectively. Across 19 experimentally generated low-SBR evaluation cases derived from measured GM-APD LiDAR sequences, the corresponding mean values were 0.541±0.165, 332.93±79.60, 8.60±2.49 dB, 0.702±0.061, and 0.33±0.08%. Under the tested conditions, range-time guidance preserved spatial structure and pixel-wise range information while suppressing background responses, supporting photon-limited reconstruction in active remote sensing.