Modeling of cluster formation and laser echo characteristics in complex diffusion media

Laser detection in complex scattering environments is often affected by distributed fibrous media, where clustering phenomena significantly alter the backscattered echo characteristics. This work develops a high-precision diffusion model of fibrous scattering clouds under atmospheric conditions, incorporating both free fiber motion and cluster formation. A clustering algorithm based on Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) is introduced to identify dense fiber groups, which are then embedded into a Monte Carlo framework to simulate pulsed laser backscatter. Numerical simulations reveal that clustered structures generate stronger, more continuous echo signals with reduced pulse widths compared to isolated fibers. The simulation results are further validated through controlled experiments, demonstrating good agreement and confirming the reliability of the proposed model. This study provides a practical modeling framework for analyzing and mitigating backscatter interference in short-range laser detection systems.