Laser fuzes

with advantages such as compact size and high resolution

are widely used in munitions

and their dynamic detection capability determines damage effectiveness. Current laser detection has transitioned from single-point sensing to linear array scanning

but simulation studies are mostly limited to single scenarios

with insufficient dynamic simulation capabilities and real-time computational efficiency. This paper proposes a dynamic scanning detection model

a multi-material scattering model

and an efficient parallel computing method

and designs a full-chain laser linear array imaging simulation system based on these. By establishing a laser linear array push-broom model and a projectile-target engagement model

push-broom imaging under dynamic engagement scenarios is achieved. A multi-target bidirectional reflectance distribution function (BRDF) scattering model for camouflage coatings

desert terrains

and other materials is constructed

with key parameters calibrated based on experimental data

effectively reducing the average BRDF error. To enable efficient simulation of dynamic projectile-target encounter scenes

this study builds upon the aforementioned dynamic scanning detection model and multi-material scattering model by designing a parallel computing architecture. Utilizing the GPU+BVH approach

we optimized the intersection judgment logic between light rays and scene facets

significantly enhancing the simulation efficiency simulation efficiency for facet-based scenarios. The simulation results of echo power under different ground backgrounds align with the BRDF background relationships

demonstrating the model’s accuracy.