Metawave has received the Direct-to-Phase II Small Business Innovation Research (SBIR) grant from the US Army to develop perception sensing solutions for off-road autonomous vehicles.

Valued at approximately $1.7m, the SBIR Phase II contract will require Metawave to address four main areas of challenge related to perception sensing for autonomous ground systems.

These areas feature adverse weather sensing, long-range sensing and reduction of the processing burden for ground vehicles, and off-road sensing.

The contract will allow Metawave to enhance its Carson radar technology platform to provide off-road perception sensing and other advanced capabilities to the future autonomous ground vehicles and systems.  

Named Hudson, the resulting radar platform will leverage the company’s all-weather and long-range detection, tracking, and perception capabilities, supported by Metawave’s other patented solutions and NVIDIA’s enhanced processing units.

The patented solutions include integrated Antenna-in-Package (AiP) modules, phased array beamforming and steering front-end Marconi chips, and high-resolution radar algorithms.

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This latest contract also includes an additional Phase III follow-on option for the development and deployment of the solution.

Metawave founder and CEO Dr Maha Achour said: “The power of phased array radar is well-known to the defence sector, but rapid innovation and advancements in millimetre, semiconductor-enabled radar solutions for safe, driverless automotive technologies have become increasingly attractive for mission-critical military operations.”

Apart from Hudson, the company will also develop a proprietary Recursive Neural Network Machine Learning software, called Anthem, to support sensing and perception radar platforms.

Anthem, an integral part of Hudson, will include camera, light detection and ranging (Lidar), and fusion stacks.

This platform can be trained to support several off-road terrain missions, including identifying the difference between real and negative obstacles, dense and thin trees, and shrubs and rocks, thereby enabling the autonomous vehicles to safely operate in unknown landscapes.