Human parameter estimation Based on sparse reconstruction

Target estimation has a crucial role in the field of radar signal processing. In this paper, we combine time-frequency analysis and sparse signal processing methods to investigate the human target parameter estimation. Firstly, we construct an over-complete dictionary in the sparse time-frequency domain; and then, we reconstruct the time-frequency image of the target signal; lastly, based on the time-frequency graph of the reconstructed signal, we obtain important parameters of the human target such as the motion speed and gait period. By comparing the parameters obtained from our method with other time-frequency analysis methods, the results show that our method has more accurate and robust. We also find that noise has little effect on the reconstructed time-frequency image. We apply the reconstructed time-frequency image in the actual road environment. The radar echo data show that reconstructed time-frequency image has promising performance.