2021•IEEE Transactions on Antennas and PropagationRequires access

Advancing Accuracy of Shooting and Bouncing Rays Method for Ray-Tracing Propagation Modeling Based on Novel Approaches to Ray Cone Angle Calculation

Stephen Kasdorf, Blake Troksa, Cam Key, Jake Harmon, Branislav M. Notaroš

Open publisher page 66 citations

Abstract

We propose and evaluate several improvements to the accuracy of the shooting and bouncing ray (SBR) method for ray-tracing (RT) electromagnetic modeling. We propose per-ray cone angle calculation, with the maximum separation angle between rays calculated for every individual ray, based on a set of local neighbors rather than a single global maximum. This allows the smallest theoretical error of the SBR method, adaptive ray spawning procedures, and a unique analysis of the effect of ray cone sizes on the accuracy of the method. For the conventional uniform angular distribution of rays, a less general and versatile but more expeditious approach, we derive an analytical expression for the optimal choice of cone angle to again maximize the overall accuracy of the SBR computation. Both approaches are derived using icosahedral ray spawning geometry and adjacent ray sets, which are also used for our double counted rays identification and removal technique that avoids complicated ray path searches. The results demonstrate that the advanced shooting and bouncing RT method--using both proposed ray cone generation approaches--can perform wireless propagation modeling of tunnel environments with the same accuracy as image theory RT, a dramatically less efficient but traditionally considerably more accurate solver.

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What this paper is about

We propose and evaluate several improvements to the accuracy of the shooting and bouncing ray (SBR) method for ray-tracing (RT) electromagnetic modeling. We propose per-ray cone angle calculation, with the maximum separation angle between rays calculated for every individual ray, based on a set of local neighbors rather than a single global maximum. This allows the smallest theoretical error of the SBR method, adaptive ray spawning procedures, and a unique analysis of the effect of ray cone sizes on the accuracy of the method. For the conventional uniform angular distribution of rays, a less general and versatile but more expeditious approach, we derive an analytical expression for the optimal choice of cone angle to again maximize the overall accuracy of the SBR computation. Both approaches are derived using icosahedral ray spawning geometry and adjacent ray sets, which are also used for our double counted rays identification and removal technique that avoids complicated ray path searches. The results demonstrate that the advanced shooting and bouncing RT method--using both proposed ray cone generation approaches--can perform wireless propagation modeling of tunnel environments with the same accuracy as image theory RT, a dramatically less efficient but traditionally considerably more accurate solver.

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Available abstract

We propose and evaluate several improvements to the accuracy of the shooting and bouncing ray (SBR) method for ray-tracing (RT) electromagnetic modeling. We propose per-ray cone angle calculation, with the maximum separation angle between rays calculated for every individual ray, based on a set of local neighbors rather than a single global maximum. This allows the smallest theoretical error of the SBR method, adaptive ray spawning procedures, and a unique analysis of the effect of ray cone sizes on the accuracy of the method. For the conventional uniform angular distribution of rays, a less general and versatile but more expeditious approach, we derive an analytical expression for the optimal choice of cone angle to again maximize the overall accuracy of the SBR computation. Both approaches are derived using icosahedral ray spawning geometry and adjacent ray sets, which are also used for our double counted rays identification and removal technique that avoids complicated ray path searches. The results demonstrate that the advanced shooting and bouncing RT method--using both proposed ray cone generation approaches--can perform wireless propagation modeling of tunnel environments with the same accuracy as image theory RT, a dramatically less efficient but traditionally considerably more accurate solver.

Key concepts: Ray tracing (physics), Solver, Ligand cone angle, Computation, Cone (formal languages), Computer science, Algorithm, Detector

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