Spatiotemporal Weighted Micro-Doppler Spectrum Design for Soft Synchronization FMCW Radar

With the attention paid to privacy protection, human motion recognition (HMR) based on radars has attracted more and more attention. A soft synchronization frequency modulated continuous wave (SS-FMCW) radar has a wider application prospect in HMR by virtue of its signal diversity and structural flexibility. In this article, a new spatiotemporal weighted micro-Doppler (SWMD) spectrum is proposed, which is more competitive for the application of the SS-FMCW radar in HMR. First, to facilitate the understanding of the SWMD spectrum construction method, we introduce the principle behind the SS-FMCW radar based on intermittent ramp signals. Specifically, the SWMD spectrum is constructed by a weighted data fusion algorithm and a time series data fusion algorithm. In addition, we collect data from six different motions from eight testers and demonstrate and analyze the validity of the SWMD spectrum by multiple dimensions. The experimental results show that compared with the conventional time micro-Doppler (MD) spectrum, the accuracy of the SWMD spectrum in HMR is improved by about 7.2%, which is an average of multiple comparison experiments of different classification algorithms with different features.