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Presence detection with 60-GHz Radar: Touchless control

10/07/2025 Radar Resources

In smart environments, detecting even the slightest motion is essential. Radar-based presence and gesture recognition offers a reliable, touchless alternative when traditional sensors are ineffective.

The RAB3 – Radar from Rutronik System Solutions can detect both micro and macro motions, such as subtle gestures, head movements, and stationary humans (e.g., breathing or blinking), as well as larger movements, like entering a room. It is ideal for smart homes, offices, and automotive applications. 

System architecture and component selection 
At its core is the Infineon BGT60TR13C radar sensor. The chip includes antennas and signal conditioning. The microcontroller processes raw ADC samples transmitted via SPI (18.75 MHz) using digital signal processing to detect presence. If the Adapter Board RAB3 is combined with the Base Board RDK, which support Bluetooth Low Energy (BLE), the results can be sent directly to iOS/Android apps. Firmware is available on GitHub and via Infineon's Modus Toolbox. 

The radar features and their advantages: 

  • No machine learning required
  • Real-time detection with low latency
  • Robust against environmental noise
  • Compact integration with embedded antennas 

Range optimization formula 
The theoretical maximum detection range is calculated as follows: 
Rₘₐₓ = (Samples per chirp / 2) × (c / (2 × Bandwidth)) 
Actual performance is influenced by environmental noise and algorithm thresholds. Engineers can improve detection range and reliability by tuning software parameters. Future enhancements may include integration with lighting, audio control, or smart infrastructure. 

Experience radar in action and register for free for the Rutronik AI³ Connect in Munich: AI³ Connect by Rutronik – AI in Automotive & Industry 

And feel free to explore evaluation kits, firmware, and more at rutronik.com/radar. 

FAQ

This parameter directly affects the radar's theoretical maximum detection range. The formula used is: 
Rₘₐₓ = (Samples per chirp / 2) × (c / (2 × Bandwidth)) 
However, this range is theoretical because environmental noise and signal quality can significantly impact actual performance.

Increasing the number of chirps per frame improves the speed resolution of the radar system. This means the radar can distinguish objects moving at different speeds more easily.

This parameter determines the maximum speed that the radar can detect. Shorter repetition times allow the system to capture faster movements.

Although frame rate does not directly impact measurement accuracy, higher frame rates enable more frequent data collection. This enables better noise reduction and smoother tracking through post-processing.

These frequencies define the radar signal's bandwidth, which influences range resolution. Range resolution determines how precisely the radar can determine the distance to a target.

Yes, by adjusting parameters such as the thresholds in the presence detection algorithm and the maximum range bin. These adjustments can reduce false positives and improve accuracy, especially in noisy environments.