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AWR1843AOP: tracker configuration

Part Number: AWR1843AOP

Tool/software:

Hello All, 
I would like to get help about setting the tracker parameters.
We played a lot with the tracker parameters to fix the situation but we couldn't fix it.
  • there is a difference between points and track position.
  • even though the dots are coming, the track start is late.
Any chance you can help us to fix these situations?
below you can find the tracker parameters and I also add a video to show the stuations.
 {"sensorPosition 1.0 0 0 0 \n\r"},
 {"staticBoundaryBox -15 0 0.25 4 0.25 3 \n\r"},
 {"boundaryBox -15 0 0 0.25 5 0.25 3 \n\r"}, 
 {"gatingParam 10 4 4 4 4 10 \n\r"}, 
 {"stateParam 3 3 3 3 3 3 3 3 10 \n\r"},
 {"allocationParam 50 50 0 5 4 2 \n\r"},
 {"maxAcceleration 10 10 0.1 \n\r"},
 {"trackingCfg 1 2 500 20 100 346 200 \n\r"},
 {"presenceBoundaryBox -15 0 0.25 5 0.25 3 \n\r"},
Good work. Have a nice day
.
  • Hi,

    We can review the configuration and will provide you feedback.

    That being said, the performance of the tracker is related to the detection performance. 

    If the sensor is used in an environment where the detection is not optimal the performance of the tracker will not be optimal

    thank you

  • Hi Emre,

    Is this a custom board? Could you provide some more information the test setup (what is the object)? 

    Thank you,

    Jin

  • Hello, Jin Lee,

    Yes, this is a borad we designed. The test object is an adult riding a bicycle. You can see from the points in the video that we have no problem with detection. This is our interface but we communicate in exactly the same tlv and points structure. There is a problem here because the track position is not exactly on the points for some reason, I shared information to solve this, only tracker specific. If you want additional information, I can share it again.

    we have changes in some commands compared to standard ti commands, but in general it is the same.

    {"sensorStop \n\r"},
    {"flushCfg \n\r"},
    {"dfeDataOutputMode 1 \n\r"},
    {"channelCfg 15 7 0 \n\r"},
    {"adcCfg 2 1 \n\r"},
    {"adcbufCfg -1 0 1 1 1 \n\r"},
    {"bpmCfg -1 0 0 1 \n\r"},
    {"profileCfg 0 77 6 6 49 0 0 24 1 128 3000 0 0 48\n\r"},
    {"chirpCfg 0 0 0 0 0 0 0 3 \n\r"},
    {"chirpCfg 1 1 0 0 0 0 0 6 \n\r"},
    {"frameCfg 0 1 172 0 200 1 0\n\r"},
    {"lowPower 0 0 \n\r"},
    {"guiMonitor -1 1 0 0 0 0 0 \n\r"},
    {"cfarCfg -1 0 2 8 4 3 0 15 0 \n\r"},
    {"cfarCfg -1 1 0 4 2 3 1 10 0 \n\r"},
    {"multiObjBeamForming -1 0 0.5 \n\r"},
    {"clutterRemoval -1 0 \n\r"},
    {"calibDcRangeSig -1 0 -5 8 256 \n\r"},
    {"aoaFovCfg -1 -15 0 0 15 -2 1 -0.2 0.2 0 0.3 -0.3 0.3 -90 0\n\r"},
    {"cfarFovCfg -1 0 0.25 15 \n\r"},
    {"cfarFovCfg -1 1 -8 8 \n\r"},
    {"CQRxSatMonitor 0 3 15 125 0 \n\r"},
    {"CQSigImgMonitor 0 115 6 \n\r"},
    {"analogMonitor 0 0 \n\r"},
    {"ransacCfg 70 0.2 \n\r"},
    {"lvdsStreamCfg -1 0 0 0 \n\r"},
    {"dbscanCfg 4 3 20 20 2 256 0 \n\r"},
    {"compRangeBiasAndRxChanPhase 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 \n\r"},
    {"measureRangeBiasAndRxChanPhase 0 1. 0.2 \n\r"},
    {"calibData 0 0 0 \n\r"},
    {"extendedMaxVelocity -1 0\n\r"},
    {"sensorPosition 1.0 0 0 \n\r"},
    {"staticBoundaryBox -15 0 0.25 4 0.25 3 \n\r"},
    {"boundaryBox -15 0 0.25 5 0.25 3 \n\r"}, 
    {"gatingParam 10 4 4 4 10 \n\r"}, 
    {"stateParam 3 3 3 3 3 10 \n\r"},
    {"allocationParam 50 50 0 5 4 2 \n\r"},
    {"maxAcceleration 10 10 0.1 \n\r"},
    {"trackingCfg 1 2 500 20 100 346 200 \n\r"},
    {"presenceBoundaryBox -15 0 0.25 5 0.25 3 \n\r"},
    {"sensorStart \n\r"}

    Thank you.

  • Hi Emre, 

    Thanks for the details. Given that you are testing with a person on a bicycle, I might start by looking at the following parameters: 

    • gatingParam: the physical dimension of the object that the tracker is expecting is set to 4m x 4m x 4m, which seems quite large.
    • allocationParam: the SNR thresholds (50, 50) seems quite large for pedestrian/bike detection. 
    • maxAcceleration: the max acceleration values in the X and Y directions (10, 10) may be a bit high. Setting too large a value makes the prediction less reliable. 

    For a detailed description of the gtrack algorithm and parameter tuning, please refer to the Tuning Guide: /cfs-file/__key/communityserver-discussions-components-files/1023/3D_5F00_people_5F00_counting_5F00_detection_5F00_layer_5F00_tuning_5F00_guide.pdf

    Thank you,

    Jin