A second generation 3-D ray-tracing model using rough surface scattering

Anderson, Harry R.

doi:10.1109/vetec.1996.503405

Cited by 11 publications

(3 citation statements)

References 11 publications

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“…Therefore, a scattering model must be implemented in the simulation. This can be either a stochastic scattering approach or a micro-facet-based scattering model as shown in [20]. By using these field-propagation models in the simulation environment, unprocessed environment sensor data with physical attributes are generated.…”

Section: Classification Of Virtual Sensor Modelsmentioning

confidence: 99%

Evaluation Methodology for Physical Radar Perception Sensor Models Based on On-Road Measurements for the Testing and Validation of Automated Driving

et al. 2022

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In recent years, verification and validation processes of automated driving systems have been increasingly moved to virtual simulation, as this allows for rapid prototyping and the use of a multitude of testing scenarios compared to on-road testing. However, in order to support future approval procedures for automated driving functions with virtual simulations, the models used for this purpose must be sufficiently accurate to be able to test the driving functions implemented in the complete vehicle model. In recent years, the modelling of environment sensor technology has gained particular interest, since it can be used to validate the object detection and fusion algorithms in Model-in-the-Loop testing. In this paper, a practical process is developed to enable a systematic evaluation for perception–sensor models on a low-level data basis. The validation framework includes, first, the execution of test drive runs on a closed highway; secondly, the re-simulation of these test drives in a precise digital twin; and thirdly, the comparison of measured and simulated perception sensor output with statistical metrics. To demonstrate the practical feasibility, a commercial radar-sensor model (the ray-tracing based RSI radar model from IPG) was validated using a real radar sensor (ARS-308 radar sensor from Continental). The simulation was set up in the simulation environment IPG CarMaker® 8.1.1, and the evaluation was then performed using the software package Mathworks MATLAB®. Real and virtual sensor output data on a low-level data basis were used, which thus enables the benchmark. We developed metrics for the evaluation, and these were quantified using statistical analysis.

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Section: Classification Of Virtual Sensor Modelsmentioning

confidence: 99%

Evaluation Methodology for Physical Radar Perception Sensor Models Based on On-Road Measurements for the Testing and Validation of Automated Driving

et al. 2022

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“…A rough surface can scatter incident sound waves, provided its texture size is comparable to or much larger than the wavelength of the sound. Modelling this reflection can be done using methods such as the Boundary Element Method (BEM) [8] [9], ray tracing [10] [11] [12] or the image-source method [13] [14]. In the case of ray tracing and the image-source method, the reflections are typically assumed to be specular.…”

Section: Introductionmentioning

confidence: 99%

An acoustic image-source characterisation of surface profiles

Dawson

Sena

Naylor

2018

2018 26th European Signal Processing Conference (EUSIPCO)

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The image-source method models the specular reflection from a plane by means of a secondary source positioned at the source's reflected image. The method has been widely used in acoustics to model the reverberant field of rectangular rooms, but can also be used for general-shaped rooms and nonflat reflectors. This paper explores the relationship between the physical properties of a non-flat reflector and the statistical properties of the associated cloud of image-sources. It is shown here that the standard deviation of the image-sources is strongly correlated with the ratio between depth and width of the reflector's spatial features.

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“…A second solution consists in using an empirical scattering function [13] which gives the scattering field according to the roughness level and the difference in angle between the specular component and the angle to the receiver. The major drawback of this technique comes from its empirical formulation which limits its use to some specific indoor environments and wave propagation conditions.…”

Section: Introductionmentioning

confidence: 99%

A New Ray-Tracing Based Wave Propagation Model Including Rough Surfaces Scattering

Cocheril¹,

Vauzelle²

2007

PIER

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Abstract-This paper presents a complete ray-tracing based model which takes into account scattering from rough surfaces in indoor environments. The proposed model relies on a combination between computer graphics and radar techniques. The paths between the transmitter and the receiver are found thanks to a Bi-Directional Path-Tracing algorithm, and the scattering field after each interaction between the electromagnetic wave and the environment is computed according to the Kirchhoff Approximation. This propagation model is implemented as a plug-in in an existing full 3-D ray-tracing software. Thus, we compare the results of classical ray-tracing with those of our model to study the influence of the scattering phenomenon on the wave propagation in typical indoor environments.

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A second generation 3-D ray-tracing model using rough surface scattering

Cited by 11 publications

References 11 publications

Evaluation Methodology for Physical Radar Perception Sensor Models Based on On-Road Measurements for the Testing and Validation of Automated Driving

Evaluation Methodology for Physical Radar Perception Sensor Models Based on On-Road Measurements for the Testing and Validation of Automated Driving

An acoustic image-source characterisation of surface profiles

A New Ray-Tracing Based Wave Propagation Model Including Rough Surfaces Scattering

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