We consider 2-D localization and noncontact vital sign monitoring (i.e., determining the 2-D locations and estimating the rates of respiration and heartbeat) of multiple human objects via developing an impulse radio ultra-wideband (IR-UWB) distributed multi-input multi-output (MIMO) prototype radar system. A modified back projection algorithm is used to localize multiple objects. We also formulate the chest skin range displacement estimation problem caused by respiration and heartbeat into a sinusoidal frequency estimation problem, which can be solved efficiently via the fast Fourier transform method. Then, the robust, high resolution, and low sidelobe iterative adaptive approach (IAA) is adopted to obtain the IAA spectrum of the chest skin range displacement signal. Both respiration and heartbeat rates can be reliably determined from the IAA spectral estimates. Further, we solve the random body movement problem by developing a 2 × 2 IR-UWB distributed MIMO prototype radar system to obtain measurements from both the front and back of the human torso simultaneously. Finally, numerical and experimental results based on the prototype hardware radar systems we develop are presented to demonstrate the performances of the proposed 2-D localization and noncontact vital sign monitoring systems and the corresponding algorithms.

中文翻译：

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使用 IR-UWB MIMO 雷达进行多目标定位和生命体征监测

我们通过开发脉冲无线电超宽带 (IR-UWB) 分布式多输入，考虑二维定位和非接触式生命体征监测（即，确定二维位置并估计多个人体物体的呼吸和心跳速率）多输出 (MIMO) 原型雷达系统。修改后的反投影算法用于定位多个对象。我们还将呼吸和心跳引起的胸部皮肤范围位移估计问题表述为正弦频率估计问题，可以通过快速傅立叶变换方法有效解决。然后，采用鲁棒、高分辨率、低旁瓣迭代自适应方法（IAA）获得胸部皮肤范围位移信号的IAA频谱。呼吸和心跳率都可以从 IAA 频谱估计中可靠地确定。此外，我们通过开发 2 × 2 IR-UWB 分布式 MIMO 原型雷达系统来解决随机身体运动问题，以同时获取人体躯干正面和背面的测量值。最后，提出了基于我们开发的原型硬件雷达系统的数值和实验结果，以证明所提出的二维定位和非接触式生命体征监测系统以及相应算法的性能。