A NEWT Lab research thrust, 24–77 GHz and beyond
The Internet of Radar Things
Millions of mmWave radars already ship in cars, phones, thermostats, and door locks, each one sensing alone. We make them sense together.
Commodity radars are cheap, private, and see what cameras can't: through darkness, motion at millimeter scale, and the material beneath a surface. Networked coherently, they become one instrument: a distributed imaging system hiding in plain sight.
Why one radar isn't enough
A single radar measures range, not position. Watch the ambiguity collapse as radars join the network, then let the room fight back.
Drag the target, or grab the radars themselves and rearrange the network. Black is truth; red is the network's belief. On the reflector, white notches are the glints single radars see alone; the red stretch is surface only the coordinated network can image.
One radar knows only how far away you are: a whole ring of places you might be. A second radar shrinks the ring to two candidates, but a ghost remains. A third pins you down, in an empty world.
The world is not empty. To a millimeter wave, a metal panel, a whiteboard, or a window is a mirror: energy bounces off it specularly and arrives late, as if from a second target standing behind the surface. Turn multipath on and watch the dashed returns agree on a phantom: a mirror-image target that even three honest radars will lock, because naive trilateration cannot tell a reflection from a body.
The mirror cuts both ways. A flat surface glints: a lone radar sees the panel only at one specular point, the white notch straight across from it, which is why walls all but vanish from single-radar point clouds. Let the radars coordinate, with each one listening to the others' echoes, and every pair contributes another specular point: the network images the red stretch of the panel that no radar could see alone.
Both tricks, rejecting the phantom and imaging the surface, take more than geometry: coherent phase across devices, Doppler consistency, polarization. Off-the-shelf radars share no cables, no clock, and no common oscillator, so making them cooperate at that level, turning cheap, independent radars into one coherent aperture, is the core problem of this thrust.
The thrust
Coherence without cables. MulDar showed that the direct channel between two commodity radars, a signal every prior system threw away as interference, carries exactly the timing and phase information needed to combine them coherently. Distributed COTS radars stop being a collection of sensors and start being one large one.
Imaging in motion. A radar waved by a human hand can form synthetic-aperture images, but hand tremor ruins focus. TwinFocus recovers sharp handheld SAR imagery by anchoring the motion estimate to physical and digital twin references, no motion-capture rig required.
Seeing material, not just shape. POLySight turns a pair of commodity radars into a bi-static polarimetric imager: the polarization of the reflected wave reveals what an object is made of (metal, wood, liquid), opening radar to inspection tasks from aerospace parts to hidden defects.
Akshay presented this vision as an invited talk, "Internet of Radar Things," at IoT Day at ACM MobiSys 2026 in Cambridge, UK.
Projects
The color on this page is the research.
MulDar
Distributed COTS mmWave radar, made coherent by exploiting the cross-device channel. MobiSys 2026.
TwinFocus
Autofocus for handheld mmWave SAR imaging via physical and digital twin references. MobiSys 2026.
POLySight
Practical bi-static polarimetric imaging for material sensing with commodity radars. SenSys 2026.
Publications in this thrust
Lab members in bold. The full lab record lives on the main page.
TwinFocus: Autofocus for Handheld mmWave SAR Imaging via Physical and Digital Twin References
POLySight: Towards Practical Bi-Static Polarimetric Imaging using Commodity mmWave Radars for Material Sensing
Towards Practical mmWave Sensing: A Distributed and Coherent Radar Approach
Towards Mobile High-Resolution mmWave SAR Imaging via Prior-Guided Autofocus
Demo: Unleashing the Potential of Distributed COTS mmWave Radar by Exploiting Cross-Device Channels
mmWave Polarimetric Imaging and Interferometry for Detecting Defects in Aerospace Parts
2026–2027. PI: Akshay Gadre. Joint Center for Aerospace Technology Innovation
Two ACM MobiSys Rising Stars 2026 (Xinghua Sun and Yadong Li), Best Demo Award at the UW ECE Research Showcase 2025 (sponsored by Apple), and a MobiSys Rising Star talk on distributed coherent radar.
The radar thrust, recognized
