Simulated radar detects objects and exchanges data at 240 km/h

At 240 km/h, a simulated vehicle radar had to do two jobs at once: detect objects and exchange data with other vehicles or road infrastructure. A team led by senior researcher Bongseok Kim at DGIST’s Future Mobility Research Division says its receiver method handled both tasks through a single processing structure.

The technique targets a practical bottleneck in integrated sensing and communication, or ISAC—the use of one system to perceive the road and share information. Conventional approaches require multiple signal-processing units as transmitted data grows, increasing system complexity and computational load. Kim’s team instead applied the Fractional Fourier Transform, a mathematical method for analyzing signals whose frequency changes over time, to automotive radar’s received signals.

The FRFT concentrates signal energy that is dispersed across the radar signal into a single point. That makes the communication information easier to identify, while also compensating for signal spreading that can affect radar measurements. The team tested the approach in a simulated 77 GHz automotive-radar environment with high-speed movement and severe multipath propagation, where radio waves reflect through complex surroundings.

The reported results were distance errors of less than 1 m and a target detection rate approaching 100% when sufficient signal strength was available. The team also found more stable communication performance than with conventional approaches under those conditions. These figures come from the researchers’ simulated experiments.

So what changes in practice? If the method transfers beyond simulation, vehicle makers could add simultaneous communication and sensing without substantially redesigning existing automotive-radar hardware. That could reduce receiver-side processing demands in autonomous and connected vehicles, while also offering a route for drones and unmanned vehicles.