基于毫米波雷达的人流量检测方法OA

Aiming at the shortcomings of existing video surveillance-based crowd flow statistics schemes such as high cost,complex algorithms and poor privacy protection,a crowd flow detection method based on millimeter-wave radar is proposed by taking advantage of its small size,low cost and high resolution.Firstly,the position and angle information of target points as well as the corresponding Doppler frequency shift are obtained through Fourier transform to form point cloud data.Then,the cell averaging-constant false alarm rate(CA-CFAR)algorithm is adopted to eliminate clutter scattering points.Finally,the density-based spatial clustering of applications with noise(DBSCAN)algorithm is used to conduct clustering analysis on the filtered data,and the system is tested via a GUI interface.Experimental results show that the proposed method achieves a higher target detection rate compared with existing methods.