Veoneer has signed an agreement with pioneering LiDAR company Baraja to industrialize their Spectrum-Scan™ LiDAR technology for the next market wave of L2+ through L4 autonomous vehicle applications.

Under the non-exclusive agreement, Veoneer will develop, market and integrate a scalable Spectrum-Scan™ platform from Baraja to serve the automotive market.

Veoneer chose to partner with Baraja after extensive testing, as Baraja offers robust technology and a roadmap that lends itself to be amongst the smallest size lidars to enable vehicle integration.

Baraja’s Spectrum-Scan™ LiDAR connects a wavelength-tunable laser to prism-like optics, deflecting the light in different directions to achieve scanning with higher reliability and lower cost. Baraja’s RMCW technology enables industry leading interference rejection and the ability to measure instantaneous velocity which distinguishes it from traditional Time of Flight (ToF) approaches.

Spectrum-Scan™ enables Level 4 autonomy

Baraja Spectrum-Scan™ LiDAR completely rethinks the way autonomous vehicles see the world around them. Instead of relying on fragile moving parts and oscillating mirrors, it uses dispersive optics to scan the environment, significantly improving reliability and robustness compared to traditional FMCW or spinning LiDAR.

Baraja’s Spectrum-Scan™ LiDAR creates high-resolution pointclouds to accurately detect objects at more than 250 meters away at speed, while remaining immune to interference from other sensors or light sources. The technology is also more tolerant to factors that have hindered traditional LiDAR systems such as heat, shock and vibration. Baraja has tested its LiDAR in the harshest conditions, from the Australian outback to arctic tundra, to ensure it works in any condition.

This technology will be complimented with Veoneer’s decades-long industry experience in developing automotive grade sensing solutions for driver assistance and autonomy applications to create a new generation of LiDAR systems enabling automakers to detect and classify objects faster and with more precision.