Frequency modulated continuous wave (FMCW) radar, which can detect the range and small displacement of a target, has been used for contactless vital information extraction. For accurate vital sign (respiration and heartbeat) measurement, a precise selection of the target range bin, where vital information exists, is important. In this paper, an effective method for selecting the range bin with accurate vital information is proposed. The proposed method is based on the newly introduced magnitude-phase coherency (MPC) index. The experimental results show that the vital information extracted by the proposed method is more accurate than those by conventional methods, indicating that the proposed range bin selection based on MPC is an effective method for extracting accurate respiration and heartbeat rates.

In order to establish a reliable map of the road environment, this paper aims to classify the stationary and moving objects unlike the previous researches which generally focus on object recognition. The characteristics of the radar signals of stationary and moving objects were analyzed and the relation between the slope of pattern in radar time-frequency spectrum and relative velocity of the object was described mathematically. To discriminate the stationary and moving objects, the difference between the measured velocity by the slope and the velocity of the ego-vehicle was proposed as a feature. The statistical characteristics of stationary and moving objects according to the proposed feature were modeled using Gaussian model. To investigate the performance of the proposed method, the similarity between modeling of stationary and moving objects was quantified. Additionally, the receiver operating characteristics (ROC) curve and the correlation coefficient between the proposed feature and the ground-truth feature map was applied to verify the performance. INDEX TERMS Automotive radar, radar signal processing, road environment map, FMCW radar, object classification.

We propose a novel range-bin selection method, temporal phase coherency (TPC), to improve the accuracy of heartbeat extraction by using the frequency-modulated continuous wave (FMCW) radar.The FMCW radar has a range-resolution, and the micro-displacement at each range bin can be analyzed by calculating the phase corresponding to the range. To extract accurate heartbeat signal, selecting the range bin is important. However, the heartbeat signal, whose displacement is minute, is hard to be detected. To select the range bin with accurate heartbeat signal, we quantified the unique characteristic of heartbeat, sinus rhythm, as TPC index. In experimental results, we evaluated the accuracy of extracted heart rates for various subjects and experimental situations. The results showed that the TPC can select the range bin with more accurate heartbeat compared to the conventional methods, indicating that the TPC would be useful for the FMCW radar based vital-sign monitoring.

In this paper, we provide the results of multi-passenger occupancy detection inside a vehicle obtained using a single-channel frequency-modulated continuous-wave radar. The physiological characteristics of the radar signal are analyzed in a time-frequency spectrum, and features are proposed based on these characteristics for multi-passenger occupancy detection. After clutter removal is applied, the spectral power and Wiener entropy are proposed as features to quantify physiological movements arising from breathing and heartbeat. Using the average means of both the power and Wiener entropy at seats 1 and 2, the feature distributions are expressed, and classification is performed. The multi-passenger occupancy detection performance is evaluated using linear discriminant analysis and maximum likelihood estimation. The results indicate that the proposed power and Wiener entropy are effective features for multi-passenger occupancy detection.

Respiration and heartbeat are basic indicators of the physiological state of human beings. Frequency-modulated continuous wave (FMCW) radar can sense micro-displacement in the human body surface without contact, and is used for vital-sign (respiration and heartbeat) monitoring. For the extraction of vital-sign, it is essential to select the target range containing vital-sign information. In this paper, we exploit the coherency of phase in different range-bins of FMCW radar to effectively select the range-bins that contain accurate signals for remote monitoring of human respiration and heartbeat. To quantify coherency, the spatial phase coherency (SPC) index is introduced. The experimental results show that the SPC can select a range-bin containing more accurate vital-sign signals than conventional methods. This result demonstrates that the proposed method is accurate for monitoring of vital signs by using FMCW radar.