Accelerated, Memory-Efficient Far-Field Scattering Computation with Monte Carlo SBR
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914147864674304 |
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| author | Audia, Samuel Manocha, Dinesh Zwicker, Matthias |
| author_facet | Audia, Samuel Manocha, Dinesh Zwicker, Matthias |
| contents | We introduce a Monte Carlo integration-based Shooting and Bouncing Ray (SBR) algorithm for electromagnetic scattering, specifically targeting complex dielectric materials. Unlike traditional deterministic SBR methods, our approach is the first to reformulate the SBR integral equations using Monte Carlo techniques and advanced variance reduction strategies adapted from photorealistic rendering. This enables efficient, massively parallel computation on modern GPUs, resulting in up to a 10-15x reduction in memory usage and a 4x speed up in runtime, particularly for multilayer dielectric structures. Our method emphasizes high-energy propagation paths, efficiently capturing long multipath and interreflection effects. Verification on canonical 3D geometries and ISAR imaging of both conducting and dielectric representative aircraft models demonstrates that our Monte Carlo SBR achieves high accuracy while maintaining low noise, making it suitable for downstream imaging and analysis tasks. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2511_07586 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Accelerated, Memory-Efficient Far-Field Scattering Computation with Monte Carlo SBR Audia, Samuel Manocha, Dinesh Zwicker, Matthias Computational Engineering, Finance, and Science We introduce a Monte Carlo integration-based Shooting and Bouncing Ray (SBR) algorithm for electromagnetic scattering, specifically targeting complex dielectric materials. Unlike traditional deterministic SBR methods, our approach is the first to reformulate the SBR integral equations using Monte Carlo techniques and advanced variance reduction strategies adapted from photorealistic rendering. This enables efficient, massively parallel computation on modern GPUs, resulting in up to a 10-15x reduction in memory usage and a 4x speed up in runtime, particularly for multilayer dielectric structures. Our method emphasizes high-energy propagation paths, efficiently capturing long multipath and interreflection effects. Verification on canonical 3D geometries and ISAR imaging of both conducting and dielectric representative aircraft models demonstrates that our Monte Carlo SBR achieves high accuracy while maintaining low noise, making it suitable for downstream imaging and analysis tasks. |
| title | Accelerated, Memory-Efficient Far-Field Scattering Computation with Monte Carlo SBR |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2511.07586 |