Contactless vital signs monitoring, such as respiration and heartbeat, can be a signiicant tool for applications in the ields of health care, surveillance and emergency. Among vital signs detection methods, Doppler Radar (Ra- dio Detection and Ranging) has shown promising performance in various applications. Doppler Radar detects vital signs by transmitting a Radio Frequency (RF) signal towards the human body. Transmitted RF signal is phase mod- ulated by the periodic movements caused by different body parts including chest and heart movements. Then, the Radar receiver captures the relected signal and demodulates it to extract the vital signs' components. Since RF signals could easily be affected by every movement in the environment, studies in this area have reported limited accuracy, especially for heartbeat detection. This study presents a novel solution for this problem by developing a non-contact, non-invasive and unconstrained vital sign monitoring system. A low-cost prototype system using 24 GHz Continuous Wave (CW) Doppler radar is developed. By sampling the Radar signal for every 40 millisec- onds, a time series signal is generated, and then is further divided into 30 seconds-length windows. First, for each window, an adaptive threshold method is used to ilter noises generated either by random body movements or electronics artifacts. Then, convolution with a plank taper window -the frequency bands are taken as [0.7, 2.5] for the heartbeat, and [0.1, 0.5] for respiration- is applied. Finally, a peak detection algorithm is used to calculate heartbeat and respiration rates. Experiments are performed according to different daily life scenarios considering different sides of healthy subjects at different distances, up to 2 meters, from the system. A total of 100 minutes of recordings from 10 healthy subjects were used to validate the proposed system and its ability to measure vi- tal signs for different subjects. The proposed system achieves 97.7 accuracies for respiration detection and 95.3 accuracy for heartbeat detection. The accuracy is determined by comparing the system results in highly accurate biometric sensors. By the end of this study, it has been proved that with this very low-cost design, a highly accurate vital signs detection system can be developed. Such a system could be utilized as a fundamental subsystem in a variety of applications; especially those designed for daily home usage.