Abstract Simulating the effects of atmospheric turbulence for imaging systems operating over long distances is a significant challenge for optical and computer graphics models. Physically‐based ray tracing over kilometers of distance is difficult due to the need to define a spatio‐temporal volume of varying refractive index. Even if such a volume can be defined, Monte Carlo rendering approximations for light refraction through the environment would not yield real‐time solutions needed for video game engines or online dataset augmentation for machine learning. While existing simulators based on procedurally‐generated noise or textures have been proposed in these settings, these simulators often neglect the significant impact of scene depth, leading to unrealistic degradations for scenes with substantial foreground‐background separation. This paper introduces a novel, physically‐based atmospheric turbulence simulator that explicitly models depth‐dependent effects while rendering frames at interactive/near real‐time (> 10 FPS) rates for image resolutions up to 1024 × 1024 (real‐time 35 FPS at 256× 256 resolution with depth or 512×512 at 33 FPS without depth). Our hybrid approach combines spatially‐varying wavefront aberrations using Zernike polynomials with pixel‐wise depth modulation of both blur (via Point Spread Function interpolation) and geometric distortion or tilt. Our approach includes a novel fusion technique that integrates complementary strengths of leading monocular depth estimators to generate metrically accurate depth maps with enhanced edge fidelity. DAATSim is implemented efficiently on GPUs using Py‐Torch incorporating optimizations like mixed‐precision computation and caching to achieve efficient performance. We present quantitative and qualitative validation demonstrating the simulator's physical plausibility for generating turbulent video. DAAT‐Sim is made publicly available and open‐source to the community: https://github.com/Riponcs/DAATSim .
Saha et al. (Wed,) studied this question.