Evaluation of algorithms for accurate micro-doppler effects measurement in FMCW radar

Abstract: Micro-Doppler effects are phenomena that occur because of micro-motion. A micro-motion is either a vibration, rotation, or acceleration which is small relative to the motion of the target. These effects can be used in order to characterize a target through their signature movement. These effects were captured using a Frequency Modulated Continous Wave (FMCW) radar on several targets with a distinct signature. The targets were a four-armed drone, a cyclist, and a pedestrian. Using conventional- and super-resolution algorithms allows the user to process the captured data. To best be able to determine these signatures, different algorithms were used, Short-Time Fourier Transform (STFT), Smoothed Pseudo-Wigner-Ville Distribution (SPWVD), Pade Fourier approximation (PFA), and MUltiple SIgnal Classification (MUSIC). The comparison of the algorithms on the measured data was done in MATLAB where the best possible scenario was taken. From the comparison, it was noticed that in order to capture the most details, the MUSIC, PFA, STFT, and SPWVD performed the best with a decreasing order.