mmWave Radar Point Cloud Processing Pipeline

This project is a Python-based processing pipeline for mmWave radar data. It takes raw ADC data (.bin files), processes it to detect objects, and generates a 3D point cloud visualization video (.mp4).

How to Run

1. Clone the Repository

   git clone [https://github.com/YourUsername/YourRepoName.git](https://github.com/YourUsername/YourRepoName.git)
   cd YourRepoName

2. Download the Data

   • The download link for the required raw .bin data file is located in the text file: bin files/download_link.txt
   • Download the data and place the .bin file(s) inside the bin files/ folder.

3. Install Requirements

   • It is recommended to use a virtual environment.
   • Install all necessary Python libraries from the requirements.txt file:

   pip install -r requirements.txt

4. Run the Pipeline

   • The main.py script will run the entire process from start to finish.

   python main.py

5. Get Output

   • Processed Data: The intermediate point cloud data will be saved as .csv files in the csv/ folder.
   • Final Video: The final 3D animations will be saved as .mp4 files in the vid/ folder.

Project Structure & Key Files

• main.py: The main executable script that runs the entire pipeline. It calls main_processing.py first, then maker_3D.py.

• main_processing.py: (Formerly Raw_Csv.py) This is the core processing logic of the project. It reads the raw .bin data, performs the Range-FFT, Doppler-FFT, CFAR detection, and Angle-FFT to detect objects and generate a point cloud.

• maker_3D.py: This script reads the processed .csv files and uses matplotlib to generate and save the final 3D point cloud animations.

• resources/: This folder contains the original C code. The logic in these files was used as a reference and guide to create the Python-based processing algorithms in main_processing.py.

• bin files/: This folder is for the raw .bin data files. It contains a download_link.txt with a link to the sample data.

• csv/: This is the output folder for the processed .csv point cloud data.

• vid/: This is the final output folder for the generated .mp4 videos.