Metawave Corporation, a US smart radar startup for the automotive industry, has raised an undisclosed amount of investment through its first Series A funding.
Metawave is developing an advanced analog beamsteering radar system Spektra, which is capable of making automated driving safer and smarter in all-weather conditions.
The company is also developing cellular systems, Turbo active repeaters and Echoes passive reflectors for faster, more efficient 5G and fixed wireless deployments.
Maha Achour – founder and CEO, Metawave said: “When I see our automotive partners excited about our radar capabilities and telecom customers demonstrating impressive results using our 5G solutions, I’m inspired and proud to lead a fearless team who has been delivering incredible results in less than 18 months from opening our development center in Carlsbad.
“Consumer expectations and business demands are increasing with the advent of new technologies, especially in mobility and connectivity, and being able to work closely with 5G and automotive leaders helps us visualize the future and continuously adapt as roads become safer and people strive to be more productive.”
The initial Series A funding round was led by mobility supplier DENSO while new participants included Mirae Asset Capital and NTT DOCOMO Ventures, and existing investor BOLD Capital Partners.
Tony Cannestra – director of Corporate Ventures, DENSO, and Metawave board member said: “Electronically beamsteering radar will fundamentally change the way automakers think about sensors and their ADAS fusion, and Metawave has a head start in solving this complicated problem with a robust and modular technology platform.
“DENSO is very excited to continue to support Metawave’s impressive technology development as we continuously seek new ways to create value in mobility.”
Automotive sector firms, Toyota, Hyundai, Infineon, and others have supported the wireless technology firm’s initial seed round of $17 million.
Metawave’s platforms leverage its proprietary AI software AWARE for object detection and classification, and for successful network planning and optimization.