CEEMDAN-ICA-Based Radar Monitoring of Adjacent Multi-Target Vital Signs

In recent years, radar, especially frequency-modulated continuous wave (FMCW) has been extensively used in non-contact vital signs (NCVS) research. However, current research does not work when multiple human targets are close to each other, adjacent lie the same resolution cell. this paper, a novel method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)–independent component analysis (ICA) was proposed obtain vital-sign information (including respiratory rate and heart rate) of by using single FMCW radar. Firstly, data observed at angle were decomposed CEEMDAN separation algorithm construct virtual multi-angle observations. It can effectively transform undetermined blind source (UBSS) problem into an overdetermined (BSS) problem. Thus, BSS FastICA be reconstruct person’s signal then calculate their rate/heart rate. To validate effectiveness method, experiments measured conducted results show that multi-target even they