基于运动状态自适应感知的相控阵雷达轨迹跟踪与体征监测研究

周宏伟; 张东恒; 耿瑞旭; 李嘉木; 陈彦

doi:10.12000/JR26032

基于运动状态自适应感知的相控阵雷达轨迹跟踪与体征监测研究

DOI: 10.12000/JR26032 CSTR: 32380.14.JR26032

中国科学技术大学网络空间安全学院合肥 230026

基金项目: 国家自然科学基金(62201542)，中央高校基本科研业务费专项资金

详细信息

作者简介:
周宏伟，硕士生，主要研究方向为无线感知

张东恒，副研究员，主要研究方向为无线感知

耿瑞旭，博士生，主要研究方向为毫米波雷达成像

李嘉木，博士生，主要研究方向为信道建模

陈　彦，教授，主要研究方向为多模态感知、多媒体信号处理和数字健康

通讯作者:
张东恒 dongheng@ustc.edu.cn

责任主编：贾勇 Corresponding Editor: JIA Yong

中图分类号: TN957
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出版历程
- 收稿日期: 2026-01-28

Phased Array Radar Trajectory Tracking and Vital Signs Monitoring Based on Adaptive Motion State Sensing

School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China

Funds: The National Natural Science Foundation of China (62201542), The Fundamental Research Funds for the Central Universities

More Information

Corresponding author: ZHANG Dongheng, dongheng@ustc.edu.cn

摘要

摘要: 随着人口老龄化趋势加剧，居家养老安全与慢性病监护的需求日益凸显，基于雷达的室内人体轨迹跟踪与生命体征监测技术备受关注。现有研究多采用多输入多输出(MIMO)体制，存在信噪比较低和数据量冗余的局限。与此相比，相控阵雷达凭借更高的信噪比和更少的数据量，在复杂室内环境中表现出更强的感知鲁棒性。然而，现有室内感知系统在应用相控阵雷达时存在两方面局限：一是传统相控阵波束调度策略在跟踪室内近距离高机动人体时易丢失目标；二是难以同步实现轨迹跟踪与生命体征同时监测，且缺乏基于目标运动状态的自适应切换机制。针对以上问题，该文首先分析了MIMO雷达与相控阵雷达的差异以及不同波束调度策略跟踪室内人体轨迹的平均重访时间性能，并提出一种基于相控阵雷达的人体运动状态自适应实时监测方案。该方案根据人体运动状态自适应切换工作模式：在运动状态下，设计了“粗扫-自适应精扫-和差波束测角”策略实时跟踪人体轨迹；在静止状态下，切换至体征监测模式提取呼吸与心跳信息。实验结果表明，该方案能够在室内实现稳定轨迹跟踪与可靠生命体征监测，为室内智能健康监护奠定了基础。
- 相控阵雷达 /
- 轨迹跟踪 /
- 生命体征监测 /
- 任务调度 /
- 居家健康
Abstract: With the rapid aging of the population, the rising demand for home-based care and chronic disease monitoring in older adults has increased interest in radar-based technologies for indoor human trajectory tracking and vital sign detection. Existing studies mainly use multiple-input multiple-output (MIMO) systems, which face limitations such as low signal-to-noise ratio (SNR) and data redundancy. In contrast, phased array radars offer better sensing reliability in complex indoor environments, thanks to higher SNR and lower data volume. However, current indoor sensing systems encounter two main challenges when applying phased array radars. First, traditional beam scheduling strategies often lose targets when tracking close-range, highly maneuverable humans. Second, achieving simultaneous trajectory tracking and real-time vital sign detection remains difficult without adaptive switching mechanisms based on target movement. To address these issues, this paper first compares MIMO and phased array radars, along with the average revisit time of different beam-scheduling strategies for tracking indoor human movements. It also proposes an adaptive real-time monitoring system for human motion states based on phased array radar. This system dynamically switches modes based on human movement: during motion, it employs a strategy combining coarse scanning, adaptive fine scanning, and sum-and-difference beam angle measurement for real-time trajectory tracking; when stationary, it shifts to a vital sign monitoring mode to capture respiration and heartbeat signals. Experimental results show that the proposed system provides stable indoor trajectory tracking and reliable vital sign monitoring, laying the groundwork for home-based smart health monitoring systems.
- Phased array radar /
- Trajectory tracking /
- Vital signs monitoring /
- Task scheduling /
- Home Healthcare

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图 1 相控阵雷达原理图

Figure 1. Schematic diagram of phased array radar

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图 2 MIMO雷达原理图

Figure 2. Schematic diagram of MIMO radar

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图 3 相控阵雷达与MIMO雷达信噪比仿真对比(收发天线阵元数为8)

Figure 3. Simulation comparison of signal-to-noise ratio between two radar

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图 4 相控阵雷达与MIMO雷达数据量仿真对比

Figure 4. Simulation comparison of data volume between two radar

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图 5 边搜索边跟踪工作原理图

Figure 5. Working principle diagram of TWS

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图 6 搜索加跟踪工作原理图

Figure 6. Working principle diagram of TAS

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图 7 CASD 波束调度策略

Figure 7. CASD beam scheduling strategy

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图 8 TWS、各更新率TAS与CASD策略对于人体类圆周、类正弦、横向和斜向运动的平均重访时间仿真统计

Figure 8. Simulation statistics of average revisit time for human quasi-circular, quasi-sinusoidal, lateral, and oblique motions under TWS, TAS with various update rates, and CASD strategies

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图 9 基于人体运动自适应实时监测示意图

Figure 9. Schematic diagram of adaptive real-time monitoring based on human motion

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图 10 基于人体运动自适应实时监测方案

Figure 10. Adaptive real-time monitoring scheme based on human motion

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图 11 轨迹跟踪模式下，人体运动与静止时差分结果对比

Figure 11. Comparison of differential results between human motion and stationary states in trajectory tracking mode

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图 12 实验场景

Figure 12. Experimental scenario

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图 13 CN0566相控阵雷达原理图

Figure 13. Schematic diagram of the CN0566 phased array radar

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图 14 Coarse-TWS，高更新率的TAS策略以及CASD策略探测的角度距离图

Figure 14. Angle-Range Maps of the Coarse-TWS, high-update-rate TAS strategy, and CASD strategy

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图 15 TAS 策略、Coarse-TWS 与 CASD 策略对于人体 U 型、横向、斜向运动轨迹的跟踪结果

Figure 15. Tracking results of TAS, Coarse-TWS, and CASD strategies for human U-shaped, lateral, and oblique motion trajectories

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图 16 不同位置人体正常呼吸时雷达监测呼吸心跳信号与PowerLab真值对比

Figure 16. Comparison of respiration and heartbeat signals monitored by radar with PowerLab ground truth at different locations during normal human breathing

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图 17 人体U型/横向/斜向运动与静止时差分结果

Figure 17. Differential results during human U-shaped, lateral, and oblique motions and stationary states

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图 18 人体U型/横向/斜向运动轨迹跟踪与静止时体征监测实验结果

Figure 18. Experimental results of human U-shaped, lateral, and oblique motion trajectory tracking and vital signs monitoring in stationary states

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图 19 多人场景下的 CASD 策略

Figure 19. CASD strategy in multi-person scenarios

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图 20 相控阵雷达同时监测多人运动轨迹实验

Figure 20. Experiment on simultaneous multi-person trajectory tracking using phased array radar

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图 21 相控阵雷达同时监测多人生命体征实验

Figure 21. Experiment on simultaneous multi-person vital signs monitoring using phased array radar

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表 1 轨迹跟踪与体征监测模式下各参数设置

Table 1. Parameter settings in trajectory tracking and vital signs monitoring modes

工作模式	轨迹跟踪	体征监测
采样率	1 MHz	1 MHz
信号频率	10 GHz	10 GHz
Chirp总时间	0.5 ms	0.5 ms
上升时间	0.3 ms	0.3 ms
带宽	800MHz	800MHz
SDR增益	40 dB	40 dB
SDR中心频率	2.1 GHz	2.1 GHz
“粗扫”间隔	10°	——
“精扫”间隔	5°	——
每帧Chirp数	32	128
差分阈值	50	5

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