Morphological degradation of DIM LiDAR spots induced by coupled atmospheric turbulence and noise

Abstract To address spot degradation and retrieval accuracy degradation in DIM LiDAR under coupled atmospheric turbulence and detector noise, a full-chain degradation model was established spanning turbulence phase screens, sub-aperture partitioning, focal-plane imaging, and Poisson-Gaussian mixed noise. Through numerical simulation, degradation characteristics were systematically examined under three conditions: turbulence alone, noise alone, and their coupling. Results indicate that under turbulence dominance, the retrieval error exhibits a two-stage characteristic-initially stable followed by rapid growth; under noise dominance, the error decreases rapidly with SNR before saturating; under coupling, three regions are formed along the C 2 n axis-weak turbulence, transition, and strong turbulence-wherein SNR exerts significant regulatory effect in the transition region but becomes nearly ineffective under strong turbulence. Based on these findings, a dual-indicator evaluation system comprising connected-domain energy fraction ρ and peak significance P s was proposed, which effectively screens degraded images and improves the retrieval qualification rate. This joint dual-criterion judgement requires no external calibration parameters and relies solely on spot image statistics, providing a quantitative basis for retrieval accuracy in DIM LiDAR detection.