Rapid advancements in autonomous driving demand improved radar perception and require large amounts of data to develop algorithms and validate results. Highly accurate large-scale radar environment simulations can precisely generate data in various scenarios to help OEMs and their suppliers ensure reliable performance.
Using electromagnetic simulation, objects in the virtual scenarios are usually converted into triangular facets before the simulation. However, representing a curvature with flat facets leaves small deviations between the actual shape and the generated facets. As a result, small errors occur depending on the meshing criteria.
This paper studies the effect of facetization criteria on the RCS accuracy of an object with a curved surface and explores potential solutions to increase the simulation accuracy.
Authors: Mohannad Saifo, Markus Clemens , Alexander Ioffe, Markus Stefer
Publication Date: May 2022
Published In: IEEE Xplore Digital Library
Research Areas: surface deviation, radar, sensors, Autonomous driving