Fast high-resolution 3D point cloud imaging method of millimeter wave radar

Aiming at the problem that the existing three-dimensional point cloud imaging methods for millimeter-wave radar are difficult to give consideration to both high resolution performance and computing speed, a fast high resolution three-dimensional point cloud imaging method combining adaptive grid evolution and SAMV is presented. Based on the range image obtained by FFT, the range bin of the target detected by CFAR is used to estimate the distance of the target. Then, the adaptive mesh evolution method of dividing coarse mesh-power spectrum estimation-detection-mesh refinement is used for the azimuth-elevation angle of each range bin with the target to obtain the refined mesh of interest. After estimating the power spectrum for these thinned grids, the detection is performed again to quickly obtain the three-dimensional point cloud image of the target. The power spectrum of the grid is estimated by using 2D SAMV before and after grid splitting, which improves the information accuracy and resolution. The results show that the proposed method can increase the speed of generating three-dimensional point clouds to about 10 times that of the 2D SAMV method while maintaining the angular resolution of 4 degrees. © 2022 Science Press. All rights reserved.