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What the Data Looks Like

From Raw Signal to Micro-Doppler Heatmap​

Radar data starts as raw analog signals received from moving targets. These signals are converted to digital samples by an Analog-to-Digital Converter (ADC). Each radar frame contains thousands of these complex samples.

Step 1: FFT Processing​

To turn those samples into meaningful data, the radar performs several Fast Fourier Transforms (FFTs):

  • Range FFT - determines how far away the object is.
  • Doppler FFT - measures how fast it’s moving toward or away from the radar.
  • Angle FFT - estimates the direction or angle of arrival.

The result is a radar cube, a 3D structure containing information about:

  • Range (distance)
  • Velocity (Doppler shift)
  • Angle of arrival (AoA)

Each cell in this cube represents radar energy reflected from a specific range, direction, and velocity.

Step 2: Object Tracking​

The radar identifies peaks in the radar cube which are potential targets.
Over multiple frames, it tracks the motion of these peaks, forming a “point cloud” of moving objects.

Step 3: The Micro-Doppler Heatmap​

After tracking an object, the radar extracts a small region around that target in each frame and records the Doppler spectrum

The Doppler spectrum is basically a velocity profile for the target

By combining spectra from consecutive frames, we build a micro-Doppler vs. time heatmap, which shows how motion changes over time.

For example :

Frame (Time)Velocity Range (m/s)Energy Concentration (Signal Strength)
Frame 1-2 → +2Strong peak near +0.8 (limb moving toward radar)
Frame 2-2 → +2Peak shifts to -0.6 (limb moving away)
Frame 3-2 → +2Peak returns to +0.9 (next limb swing)

This repeating pattern of alternating positive and negative velocities forms the distinctive “wave” of human motion.

Step 4: Visualizing the Data​

If plotted as an image:

  • X-axis: Time (in frames or seconds)
  • Y-axis: Doppler velocity (m/s)
  • Color intensity: How strong the reflected signal is at that speed

Bright streaks represent active motion, and darker regions correspond to stillness.
The resulting heatmap visually captures how a person moves. The heatmap is fairly unique to an individual. This will be the basis of how we go about identifying individuals.