TIDUF00 November   2021

 

  1.   Description
  2.   Resources
  3.   Features
  4.   Applications
  5.   5
  6. 1System Description
    1. 1.1 Why Radar?
    2. 1.2 Key System Specifications
  7. 2System Overview
    1. 2.1 Block Diagram
      1. 2.1.1 Automated Parking Software Block Diagram
    2. 2.2 Highlighted Products
      1. 2.2.1 AWR1843AOP Single-Chip Radar Solution
      2. 2.2.2 mmWave SDK
    3. 2.3 System Design Considerations
      1. 2.3.1 Usage Case Geometry and Sensor Considerations
      2. 2.3.2 AWR1843AOP Antenna
      3. 2.3.3 Processing Chain
    4. 2.4 Chirp Configuration Profile
  8. 3Hardware, Software, Testing Requirements, and Test Results
    1. 3.1 Required Hardware and Software
      1. 3.1.1 Hardware
      2. 3.1.2 Software and GUI
    2. 3.2 Testing and Results
      1. 3.2.1 Test Setup
      2. 3.2.2 Test Results
        1. 3.2.2.1 Use Case – Vehicle, Bicycle, Pedestrian Detection
        2. 3.2.2.2 Use Case – Traffic Cone, Grocery Cart, Sign Pole, Pipe, Shrub
        3. 3.2.2.3 Use Case – Pedestrian Standing in Empty Parking Space
        4. 3.2.2.4 Use Case – Pedestrian Standing Next to Car
        5. 3.2.2.5 Use Case – Empty Parking Space
        6. 3.2.2.6 Use Case – Cross Traffic Alert
        7. 3.2.2.7 Use Case – Parking Block, Curb Detection
  9. 4Design Files
    1. 4.1 Design Database
    2. 4.2 Schematic, Assembly, and BOM
  10. 5Software Files
  11. 6Related Documentation
    1. 6.1 Trademarks

3.2.2.4 Use Case – Pedestrian Standing Next to Car

In this test we use the capabilities of the ultra-short range (0m-10m) sub-frame to detect a pedestrian standing next to a car. The processing chain is configured to perform 3D MIMO detection (azimuth and elevation, 1 Tx enabled at a time) with a maximum range of 10m. The sensor is placed at bumper height at 45 degrees. Testing is performed with both static and moving sensor. The setup is shown in Figure 3-6.

GUID-20211102-SS0I-QTZW-DTWW-MJQDZXB40VWG-low.jpg Figure 3-6 Pedestrian Standing Next to Car

Figure 3-7 shows the point cloud for static detection. The sensor, the car, and pedestrian in the parking space are all static. This is the most challenging detection case.

GUID-20211102-SS0I-19T1-P8W9-NHJ46HNJZLCH-low.png Figure 3-7 Point Cloud for Static Detection

When there is movement in the scene, the detection is better because Doppler information is used to detect movement.