https://github.com/alexismotet/modradar

Speed measurements of runners using FMCW radars.
https://github.com/alexismotet/modradar

arduino fft fmcw-radar opencv raspberry-pi-4 redis

Last synced: 11 days ago
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Speed measurements of runners using FMCW radars.

• Host: GitHub
• URL: https://github.com/alexismotet/modradar
• Owner: AlexisMotet
• Created: 2023-09-10T14:57:20.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-08T20:12:35.000Z (about 1 year ago)
• Last Synced: 2024-10-18T04:42:05.804Z (about 1 month ago)
• Topics: arduino, fft, fmcw-radar, opencv, raspberry-pi-4, redis
• Language: HTML
• Homepage:
• Size: 35.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ModRADAR (2021 - 2022)

The aim of this engineering school project was to display the speeds of track and field runners in real time.

It uses 3 FMCW embedded radars (https://urad.es/en/) on Raspberry Pi 4 and Arduino Uno boards.

The radars deposit the raw measurements (IQ signal) on a Redis server and a Python server retrieves and processes them to get the speeds and positions of the runners.

https://github.com/AlexisMotet/ModRADAR/assets/84445302/d53f624c-56a4-40a6-b9de-c92200e4b1b3

At the same time, the Python server receives a video stream from a mobile phone filming the track. It detects people moving around using the background subtraction technique. Finally, it associates the radar measurements with the bouding boxes of the detected people using the vectors that the user places on the web interface.

The web interface also displays the Fourier transforms of the raw signals in real time and the technique used to eliminate ghost targets (signal processing). Radar measurements and signal are random in the video below.

https://github.com/AlexisMotet/ModRADAR/assets/84445302/e1d54d20-99dd-406a-bff6-8ba74e7ad0fe