In the process of detecting human respiration and heart rate using millimeter wave radar, the static clutter in the environment makes it extremely difficult for the radar to discriminate the information about the movement of the human chest cavity, which affects the separation of respiration and heart rate signals. At the same time, it is difficult to separate the harmonic components of the respiration signal in the high-frequency band and the heartbeat signal in the low-frequency band because the frequencies of the harmonic components in the high-frequency band are similar.To solve the above problems, this paper proposes a joint modal spatial domain estimation detection method, which mainly adopts an single ensemble empirical modal decomposition (SEEMD） algorithm to decompose the thoracic phase signal into each modal component to eliminate the influence of static noise on the respiratory heartbeat signal, and then uses a multiple signal classification (MUSIC) algorithm to convert the heartbeat modal component signals from the time domain to the spatial domain to estimate their frequencies to eliminate the influence of respiratory harmonics.The experimental results show that the accuracy of respiratory rate under the detection of this paper’s method is 95.76%,and the accuracy of heart rate is 98.76%.Compared with the traditional algorithms, the proposed method is more accurate in estimating respiratory rate and heart rate. [ABSTRACT FROM AUTHOR]