Radar Vital Signs Detection Based on Improved SO-CFAR and ACA-VMD Algorithms

In this paper, we propose a method for detecting vital signs based on the modified least selected constant false alarm (SO-CFAR) and ant colony variational modal decomposition (ACA-VMD) algorithms, and validate the accuracy of the algorithm through simulations and experiments. The ACA-VMD algorithm is firstly used to obtain clean radar I/ Q data by pre-processing the IF echo signal of 77 GHz millimeter wave radar, and then the power level of the front and rear windows is adjusted to allow the cell-minimum constant false alarm detection to accurately extract the target under noise. The signalto- noise ratio of respiration and heartbeat is improved by 1. 765 dB, and the respiration and heartbeat are effectively separated and extracted to achieve the accurate detection of human vital signs.