Real Time Data Capture Tool of mmWave Radar in Python

This is a real-time ADC sample capture tool to obtain the raw data of TI mmWave radar XWR1843 EVM cascading with DCA1000 EVM using Python. With the tool, real-time processing using Python to generate Range-Doppler and Range-Angle images under 1 Transmitter and 4 Receiver (in this version) setting without using mmWave studio is possible.

Required Python packages

• numpy
• serial
• pyqtgraph
• pyqt5
• PyQt5-sip
• pyserial

Platform

• Operating System:
  • Windows 10
• Device:
  • XWR1843 EVM
  • DCA1000

Program Functions

• send_cmd(): Send command to DCA1000.
• update_figure(): Refresh RDI and RAI.
• plot(): Perform the application that plots RDI and RAI.
• UdpListener(): Streaming out adc samples from DCA1000.
• DataProcessor(): Processing adc samples to generate RDI and RAI.
• SerialConfig(): Config XWR1843 EVM.

How to Use

This program is for XWR1843, if you use other radar EVM, you should modify the code. Execute by the following steps:

1. Use TI's tool "UniFlash" flash the radar EVM, make sure that the radar EVM is running with demo firmware.
2. Check and modify the config COM Port of radar EVM.
3. Check the host IP is 192.168.33.30, and the program is allowed to through the firewall.
4. Execute IWR1843_real_time_plot_RDI_RAI_app.py
5. Click the "Send Radar Config" button to start the real-time plotting.

Demo

• Demo Video: https://youtu.be/Z6rTQDMe6a4

Contact

• Jih-Tsun Yu E-mail:[email protected]
• Jyun-Jhih Lin E-mail:[email protected]

Acknowledgement

Thanks for TI, TI's e2e forum, and other people work on mmWave Radar make this happen. Also grateful for the help from Mr. Chieh-Hsun Hsieh

Credit: Cite This Tool

The tool is related to the real-time prototyping of the following paper:

J. Yu, L. Yen and P. Tseng, "mmWave Radar-based Hand Gesture Recognition using Range-Angle Image," 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), Antwerp, Belgium, 2020, pp. 1-5, doi: 10.1109/VTC2020-Spring48590.2020.9128573.

BibTex Form @INPROCEEDINGS{9128573, author={J. {Yu} and L. {Yen} and P. {Tseng}}, booktitle={2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)}, title={mmWave Radar-based Hand Gesture Recognition using Range-Angle Image}, year={2020}, pages={1-5}, doi={10.1109/VTC2020-Spring48590.2020.9128573} }