3D Mesh Ray Path Computation Using Geodesics and Neural Inference
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computational electromagnetics methods, such as Geometric Theory of Diffraction (GTD) and Uniform Theory of Diffraction (UTD), struggle to accurately determine ray paths on complex geometries due to high computational complexity and time requirements, especially for large and complex structures.
Innovation Solution
A computing system that combines heat transfer methods, Eikonal equations, and artificial intelligence/machine learning (AI/ML) to efficiently compute ray paths, using trained neural networks and greedy search algorithms to overcome the limitations of traditional approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GTD/UTD methods are used to compute ray paths, then electromagnetic simulation accuracy is maintained, but computational time and complexity increase significantly
Solution Approach 1:
The patent pre-computes and stores geodesic paths on the mesh surface before electromagnetic simulation. By using algorithms like Fast Marching Method or Dijkstra's algorithm to establish a geodesic distance map in advance, the system avoids repeated complex calculations during ray tracing, thus reducing computational time while maintaining accuracy.
Solution Approach 2:
The patent divides the ray path computation into two separate segments: geodesic path computation on the mesh surface and free-space ray tracing. This segmentation allows each part to be optimized independently - the geodesic portion uses efficient graph algorithms while the free-space portion uses traditional electromagnetic methods, reducing overall computational complexity.
2Measurement precision
If traditional ray tracing algorithms are used, then accurate ray paths are obtained, but device complexity and computational cost increase
Solution Approach 1:
The patent introduces an intermediary data structure - a geodesic distance map or pre-computed path database - that mediates between the mesh geometry and the ray tracing process. This intermediary stores pre-calculated geodesic information, allowing rapid query during simulation without re-computing complex shortest paths, thus reducing system complexity.
Solution Approach 2:
The patent replaces traditional iterative mechanical ray tracing algorithms with a two-stage approach: first using efficient graph theory algorithms (Fast Marching Method, Dijkstra's algorithm) to compute geodesics, then using simple vector operations for free-space propagation. This substitution of computational mechanics reduces algorithmic complexity while maintaining accuracy.
3Measurement precision
If mesh density is increased to improve ray path accuracy, then measurement precision improves, but computational complexity increases
Solution Approach 1:
The patent performs preliminary mesh analysis to identify critical regions where high accuracy is needed, and applies adaptive mesh refinement only in those areas. By pre-computing geodesic paths on the mesh, the system can work with coarser meshes while maintaining accuracy through the mathematical properties of geodesic computation, reducing overall mesh complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A computing system (10) including a processor (14) configured to receive a mesh (30) of a three-dimensional geometry (38). The processor is further configured to receive a source antenna location (40) and a destination antenna location (42) on the mesh. The processor is further configured to compute a ray path (60) as an estimated shortest path between the source antenna location and the destination antenna location. The ray path includes a geodesic path (62) over the mesh and a free space path (64) outside the mesh. The ray path is computed at least in part by computing the geodesic path at least in part by performing inferencing at a trained neural network (52). Computing the ray path further includes computing the free space path at least in part by performing raytracing from a launch point (66) located at an endpoint of the geodesic path. The processor is further configured to output the ray path to an additional computing process (70).