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IWR1443 static heatmap to Matlab

Hello,

I am a new user of this prouct and I have a question about the static heatmap produced by the device.

Reading the doxygen documentation I saw that static heatmap is organized in a matrix whit in the column the antenna read (real and imaging part) and in the row the range of the device.

What I would like to know is how can I use this matrix on Matlab to plot the static heatmap with the goal to se something similar to what I see on the mmWave demo Visualizer?

I've just found the matrix in the packageall cell but I'm not sure how to manage this matrix and with which data i have to correlate it for a plot.

Thanks for your help,

Best Regards

  • Hi Elia,

    try to understand what the Visualizer does with the data you already have. The source code of the Visualizer is accessible, e.g., using GUI Composer. The function of interest to you is processAzimuthHeatMap found in mmWave.js.

    Best regards

  • Hi,

    thank you very much for you reply,

    Sorry but i'm not sure i understood what you mean.Could you please explain me what you mean?

    Maybe my questione was not clear.

    What i mean is that i have to work with matlab, i have the raw data of static heatmap but i'm not sure in which way i have to use them? Because i am not sure that the way in which i've plotted the data is the right one.

    How can GUI composer help me?

    And why the Visualizer code can help me?

    Where can I download GUI composer?I have to download CCS first? 

    Best regards

  • GUI Composer is just a cloud platform in which you can import the recent Visualizer. Follow this link and choose "Import to GUI Composer": https://dev.ti.com/gallery/. From there, you can easily download the whole project including the mentioned source code containing mmWave.js. You just need to login with your TI account. 

    Then, inside the processAzimuthHeatMap-function you can see what the Visualizer does with the raw data to plot it in the way you strive. Once you've understood what's going on, you can easily recreate the process in MATLAB.

    Best regards