When people think about high-fidelity radar simulation, they typically imagine one thing: a detailed 3D environment. Geometry, meshes, materials, everything needs to be modeled, prepared, and maintained before a single ray can be traced. But what if you could get the same physical fidelity without requiring a predefined 3D scene at all?

Simulating lidar sounds straightforward at first: send out light, measure the distance, and construct the point cloud. In practice, however, the challenge lies in what happens in between. The way infrared light interacts with the world is anything but simple, and without modeling that interaction correctly, even the best sensor model will fall short.

We apply a development method that embeds continuous verification & validation (V&V) into every iteration of our perception sensor model development, so lidar and radar models become more credible, traceable, and automation‑ready as they evolve.

The automotive and mobility industry is embracing virtual testing at scale. To make these simulations realistic and interoperable, standardization is key. That’s why we created the Standardized Co-Simulation Demo , an open-source example of how to combine scenario execution, sensor simulation, and multi-domain orchestration using OpenMCx , esmini , and our own physical sensor models , all aligned with ASAM OpenX standards . Check out the GitHub repository here . Co-simulatio