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IWR1443BOOST: Demo Limitations Clarifications and Visualiser Source query.

Part Number: IWR1443BOOST

Hi,

So I'm trying to develop a new application for IWR devices, and I've so far been testing out the demo program and some of the Industrial Toolbox labs. The device I have is the IWR1443BOOST ES2.0

I'm trying to write a program which reads information from the EVM and automatically processes it further on the computer into a format I can use for other elements of a process. I was wondering if there's any source available for the Demo Visualiser so that I can see how it captures the UART data and transforms it?

The application is in surface mapping, but the out of the box demo documentation seems to show that the identification of objects in the CFAR algorithms relies on Range/Velocity and doesn't distinguish objects sharing these at different azimuth positions? Is this correct? Or is there a way to alter the demo to consider range and azimuth as the parameters to distinguish objects, so that I may detect 'objects' as points along a surface. Alternatively if this is not possible, is it correct that the radarcube information can in the (range, azimuth, elevation) data be analagous to a 3D heatmap? This is the impression given to me by the responses here. . If so, is it possible to extract this information directly from the IWR1443BOOST (with or without extra equipment) to process the  3D cube in my own external program?

Additionally I noted this haloing effect when viewing a heatmap, and wondered if this is caused by a lack of angular resolution in the chip we have? (there is some rusting)

Many Thanks,

Lachlan

  • Former Member
    0 Former Member
    Hello,

    Please refer to these two threads regarding parsing of the OOB demo UART stream:
    e2e.ti.com/.../758231
    e2e.ti.com/.../752834

    Range, azimuth, elevation is not radar cube but rather the data set that forms a 3D point cloud which is extracted from radar cube.
    For more information regarding radar cube and data processing please refer to the videos in the mmWave training series.
    training.ti.com/mmwave-training-series


    You can either implement your own processing algorithms on the device or by using a DCA1000 to capture raw data. The DCA1000 is advisable to give you more flexibility and ease in testing new algorithms.

    Amanda