Stanford EE259 I Waveform orthogonality in MIMO radar, radar noise and interference I 2023 I Lec. 14

Stanford EE259 I Waveform orthogonality in MIMO radar, radar noise and interference I 2023 I Lec. 14

Introduction

  • The video discusses the process of analyzing radar data using digital signal processing (DSP).
  • The main goal is to identify the range, velocity, and direction of targets detected by the radar.

Data processing steps

  • Range Doppler Maps: The video suggests averaging the amplitudes of multiple range Doppler Maps to create one average map for analysis.
  • 2D C4 processing: The range and velocity indices of the targets are determined using 2D C4 processing on the average range Doppler map.
  • DOA Processing: The antenna index P is converted to a DOA index Q using a point FFT.
  • Target DOA Detection: Another peak search is performed to determine which DOA indices correspond to the actual directions of the targets.
  • Mapping indices to physical quantities: The range, velocity, and DOA indices of the targets are converted to physical quantities such as meters and radians.
  • Visualization: The radar data can be visualized as a point cloud, with targets represented as dots in a 2D or 3D space.

Radar data cube visualization

  • The video provides examples of different visualizations of a radar data cube.
  • Velocity Angle Heat Map: A 2D heat map with velocity on one axis and angle on the other axis. The hot zone represents the location of the target.
  • Range Velocity Heat Map: Another 2D heat map with range on one axis and velocity on the other. The target's range and velocity can be determined from this map.
  • Range and Azimuth Angle: A black slice in the data cube that shows the target's range and azimuth angle.
  • Point Cloud: By converting the target's polar coordinates (R and Theta) to Cartesian coordinates (X and Y), a point cloud representation of the targets can be created.

Conclusion

  • The DSP process for radar data analysis can be implemented with just a few lines of code.
  • It is important to consider the assumptions made throughout the process and explore more sophisticated algorithms for better performance in radar analysis.

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