LAUSR

This study presents a highly accurate range and Doppler-velocity extraction scheme for millimeter-wave (MMW) short-range sensing using the Doppler-velocity and $k$-space decomposition in a weighted kernel density (WKD) scheme. The WKD method has been developed as one of the most promising micro-Doppler analysis methods for human motion; however, an original WKD method requires a highly decomposed range profile to achieve its maximum performance. As the main contribution of this article, the proposed method introduces the Doppler velocity and k-space decomposition via the 4-D fast Fourier-transform process, which significantly improves the range resolution and reduces computational complexity. The numerical and experimental results show that the proposed method achieves significantly higher range and velocity accuracy and resolution, as well as higher noise-robustness at a lower computational cost.