What is the micro-Doppler signature of a pedestrian and how does automotive radar detect it?

The micro-Doppler signature of a pedestrian is the unique pattern of Doppler frequency shifts produced by the periodic motion of a walking person's body parts (arms, legs, torso) relative to the automotive radar. While the torso provides the main Doppler shift corresponding to the pedestrian's overall velocity, the swinging arms and legs create additional Doppler components that oscillate around the main Doppler at the cadence frequency (step rate, typically 1.5-2.5 Hz for normal walking). An automotive radar detects these micro-Doppler features by: collecting coherent data over a sufficient observation time (100-500 ms, covering 2-5 walking cycles), computing a time-frequency analysis (short-time Fourier transform or spectrogram) of the radar return from the pedestrian target, extracting the micro-Doppler features (the spectrogram shows the sinusoidal Doppler modulations caused by the swinging limbs around the constant torso velocity; the arm swing produces Doppler excursions of approximately ±0.5-1.5 m/s around the body velocity, and the leg swing produces larger excursions of ±1-3 m/s), and classifying the target using the extracted features (comparing the micro-Doppler pattern against known signatures for pedestrian, cyclist, vehicle, and animal targets using a classifier algorithm such as SVM, random forest, or deep neural network). The micro-Doppler signature is distinctive because: vehicles produce a single Doppler component (no periodic limb motion), cyclists produce a characteristic pedaling signature (periodic leg motion at a different cadence than walking), and stationary objects produce zero Doppler. This classification enables the automotive radar to distinguish pedestrians from other road users, which is critical for autonomous emergency braking (AEB) systems.