Near-field beamforming divides the space directly in front of the microphone array into a 64圆4圆4 grid of 5cm voxels, and can locate a sound source in that 3d space. This performs one of two beamforming operations. That data is fed into a GPU Kernel written with Triton, an Open Source alternative to CUDA. Packetizing all those microphones into UDP packets winds up pushing a whopping 715 Mbps, which manages to fit nicely on a Gigabit Ethernet connection. This former pixel controller can be used for a wide variety of projects, thanks to an Open Sourced reverse engineering effort, and is even supported by the Project Trellis toolchain, which was used for this effort, too. Then to pull all that data in, a Colorlight is used as a general purpose FPGA with a convenient form factor. About half of the spokes were dead on arrival, with the individual mics having a tendency to short the shared clock line to either ground or the power supply line. The first data capture problem was due to the odd PCBs pushing the manufacturing process to its limits. You might imagine that capturing the data from 192 microphones all at once is a challenge in itself, and that seems to be an accurate assessment. In this case, it’s 192 of them, arranged on long PCBs working as the spokes of a wall-art wheel.

The secret sauce isn’t a sophisticated microphone, but a whole bunch of really simple ones. It seems that discovered how to make that particular trick a reality, but with audio instead of video.

Remember the scene from Blade Runner, where Deckard puts a photograph into a Photo Inspector? The virtual camera can pan and move around the captured scene, pulling out impossible details.

Grid lines in paint 3d