This code example demonstrates Infineon's radar presence solution to detect human presence within a configurable distance. Powered by the XENSIV™ 60-GHz radar, this solution provides extremely high accuracy in detecting both micro and macro motions. The ability to detect micro motion offers unique benefits over conventional technologies deployed to detect human presence, thus making it perfect for user interaction with devices.
This code example is ported from official ModusToolbox™ code example on Github/Infineon. For Operation instructions, please refer to the original README.md for more details.
conda create --name envconda activate espmkdir espcd esp- ESP-IDF Toolchain Setup
git clone https://github.com/espressif/esp-idf.gitcd esp-idf./install.sh all. ./export.shcd examples- Copy this radar folder inside example folder
idf.py build- Flash the files
idf.py flash- Monitor the output
idf.py monitor- To modify the WiFi, go to menuconfig and change the configuration
idf.py menuconfig- To change the radar settings, go to ./main/radar settings folder, find the target settings, copy and paste the target setting in the ./main/radar_settings_tr13.h
- Go to scripts folder and run the udp server
python run_tcp_server.py --port=3333- Go to main folder and run
idf.py monitorto monitor Esp32 - Your radar data will be saved as csv file inside the scripts folder
This code example adopts the following versioning convention: a.b.c+esp32-#, where
a.b.crefers to the upstream official version it's ported fromesp32refers to the MCU platform#refers to the build ID
This is a complete code example with sdkconfig for esp32 MCU platform.
Tested in esp-idf-v5.0.1 with VSCode on Windows using ESP-IDF extension
Tested with the following hardware:
- Adafruit ESP32 Feather V2 (Product ID 5400)
- CSK Radar Wing Board with TR13C
- CSK Radar Adaptor Wing Board + TR13C Shiled
- CSK Radar Adaptor Wing Board + UTR11 Shield