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摘要: 全球老龄化趋势日益加剧，健康生活理念深入人心，居民对居家健康监测的需求也随之而来。为了减少健康监测对日常活动的影响，非接触式监测系统的需求量激增。然而，目前主流的检测方法存在隐私信任度低、电磁兼容性差和制造成本高等问题。对此，该文提出一种基于超声波雷达的非接触式生命体征信号测量系统——U-Sodar，包括一套基于3发4收MIMO架构的硬件和一套信号处理算法。其中U-Sodar本振采用分频技术，相位噪声低，检测精度高；接收机采用前端直接采样技术，在简化结构的同时有效减少外部噪声；发射采用可调PWM直接驱动，可发射多种超声波形，具备软件定义超声波系统特性。U-Sodar的信号处理算法采用信号弦长的图处理技术，利用图片滤波后重构的方法可在5 dB信噪比下实现信号相位的准确恢复。试验测试了U-Sodar系统的抗干扰性能与穿透性能，证明了超声穿透是依赖材料孔隙而非跨介质振动传导。并推导了给定信噪比与正确解调概率下的最小可测量位移。实际生命体征信号测量实验中，U-Sodar可分别在3.0 m和1.5 m距离内实现呼吸率和心率的准确测量，在1.0 m内可测得心跳波形。实验结果证明了U-Sodar超声波雷达在非接触式生命体征检测应用中的可行性及发展潜力。Abstract: Amidst the global aging trend and a growing emphasis on healthy living, there is an increased demand for unobtrusive home health monitoring systems. However, the current mainstream detection methods in this regard suffer from low privacy trust, poor electromagnetic compatibility, and high manufacturing costs. To address these challenges, this paper introduces a noncontact vital signal collection device using Ultrasonic radar (U-Sodar), including a set of hardware based on a three-transmitter four-receiver Multiple Input Multiple Output (MIMO) architecture and a set of signal processing algorithms. The U-Sodar local oscillator uses frequency division technology with low phase noise and high detection accuracy; the receiver employs front-end direct sampling technology to simplify the involved structure and effectively reduce external noise, and the transmitter uses an adjustable PWM direct drive to emit various ultrasonic waveforms, possessing software-defined ultrasonic system characteristics. The signal processing algorithm of U-Sodar adopts the graph processing technique of signal chord length and realizes accurate recovery of signal phase under 5 dB Signal-to-noise ratio (SNR) using picture filtering and then reconstruction. Experimental tests on the U-Sodar system demonstrated its anti-interference and penetration capabilities, proving that ultrasonic penetration relies on material porosity rather than intermedium vibration conduction. The minimum measurable displacement for a given SNR with correct demodulation probability is also derived. The results of actual human vital sign signal measurement experiments indicate that U-Sodar can accurately measure respiration and heartbeat at 3.0 m and 1.5 m, respectively, and the heartbeat waveforms can be measured within 1.0 m. Overall, the experimental results demonstrate the feasibility and application potential of U-Sodar in noncontact vital sign detection.
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Key words:
- Non-contact detection /
- Vital signals detection /
- CW radar /
- Ultrasound /
- U-Sodar
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图 1 基于U-Sodar的人体生命体征信号测量示意图
Figure 1. Overview of U-Sodar vital signal monitoring system
图 3 回波信号基带组成的星座图示意图
Figure 3. Constellation diagram depicting the baseband composition of the echo signal
图 4 含噪信号在相位解调中的解调误差示意图
Figure 4. Schematic of demodulation error in phase demodulation of noise-containing signals
图 5 给定信噪比与解调正确概率下的最小可测量相差图
Figure 5. The minimum measurable phase difference for a given SNR and probability of correct demodulation
图 8 U-Sodar方向图测试场景布置
Figure 8. Arrangement of the test scene for U-Sodar directional diagram testing
图 15 各通道测量静止墙面信号矢量图
Figure 15. Measurement of stationary wall signal vector diagram for each channel
图 20 不同信噪比信号处理结果对比
Figure 20. Comparison of signal processing results with different signal-to-noise ratios
图 21 不同体动幅度模拟结果对比
Figure 21. Comparison of simulation results for different body movement distances
图 22 基于U-Sodar的生命体征测量实验场景示意图
Figure 22. Schematic of the experimental setup for measuring vital signs with U-Sodar
表 1 各类型非接触测量方案比较
Table 1. Comparing various types of non-contact measurement schemes
类型 可见光/红外光 微波雷达 声学信号 U-Sodar 隐私保护 – • – • 毫米级位移测量 – • – • 信号来向区分 • • – • 抗电磁干扰 • – • • 无电磁辐射 • – • • 穿透能力 – • • • 环境适应能力 – • – – 目前设备体积 • • • – 设备成本 – – • • 注：•为优秀，–为较差。 
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表 2 U-Sodar系统的关键芯片型号
Table 2. U-Sodar system key chip models
芯片功能 芯片型号 主控芯片 STM32F030F4P6 发射驱动芯片 SRV8837 接收放大器芯片 MS8051 LDO电源芯片 RT9193 逻辑门芯片 SN74LVC1G02DCKR USB串口转换芯片 CH340N 收发换能器探头 TCT40-16
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表 3 受试者信息
Table 3. Volunteer information
受试者编号 性别 年龄 身高(cm) 体重(kg) BMI (kg/m2) 标识色 1 男 26 173 60.0 20.0 棕 2 男 24 180 78.5 24.2 蓝 3 男 23 178 71.0 22.4 红 4 女 24 166 63.0 22.9 绿 5 女 22 155 46.0 19.1 紫 注：根据中国BMI标准：≤18.4为偏瘦、18.5～23.9为正常、24.0～27.9为过重、≥28为肥胖。
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