Micro-Doppler parameter estimation based on improved time-frequency analysis

Micro-Doppler effect refers to the additional Doppler frequencies around main Doppler frequency which is caused by the micro-motion. Radar targets' motion parameters are useful for characterizing the target and become inputs to automatic target recognition algorithms, which means parameters estimation is fundamental and vital for the target recognition. To improve the instance frequency (IF) estimation accuracy, this paper proposes a new time-frequency analysis (TFA) method combining Choi-Williams Distribution (CWD) and cross Wigner-Ville distribution (XWVD). Firstly, Hadamard product of T-F distribution matrix from T-F distributions of CWD and XWVD is calculated. Then we apply peak value detection (PVD) to get the IF estimation. The simulation results prove its effectiveness and good performance under low SNR. The proposed method not only has better T-F congregation, but also works well even at low SNR, compared to the traditional method of WVD based PVD.