目的 提出一种非接触辨识人与动物的生物雷达信号处理算法，以增强辨识准确性和鲁棒性。方法 采用中心频 率7.29 GHz、带宽1.4 GHz的片上超宽带生物雷达系统采集人体与动物在自由空间条件下的雷达信号，经直流滤波、低通滤 波、自适应滤波算法进行信号预处理后，从频率和能量角度提取增强型呼吸与心跳能量比特征。结果 人与动物辨识结果显 示，与传统的呼吸与心跳能量比特征相比，本文所提的增强型呼吸与心跳能量比特征具有高准确率、高鲁棒性的特点，可 以消除因个体差异而导致辨识误判的现象。结论 基于生物雷达信号提取的增强型呼吸与心跳能量比特征能更准确辨识人体 和动物目标，该方法可作为非接触智能化健康监测设备的底层基础性技术，帮助其辨识目标，进而确保信号来源的准确性 和可靠性，应用价值较高。

Objective To propose a non-contact biological radar signal processing algorithm for identifying human and animal so as to enhance the accuracy and robustness of identification. Methods An ultra-wideband (UWB) radar on a chip with 7.29 GHz center frequency and 1.4 GHz band width was utilized to collect radar signals from human and animals in free-space condition. After signal preprocessing of direct current filtering, low-pass filtering, adaptive filtering, an improved feature of respiratory and heartbeat energy ratio was extracted from aspects of frequency and energy. Results Human and animals identification results showed that compared with the traditional respiration and heartbeat energy ratio characteristics, the proposed feature in this paper of improved respiratory and heartbeat energy ratio owned higher accuracy and higher robustness, and could eliminate the phenomenon of identification and misjudgment caused by individual differences. Conclusion The improved feature of respiratory and heartbeat energy ratio extracted from UWB radar signals can identify human and animal targets more accurately. The method can be employed as the underlying technology of the non-contact intelligent health monitoring equipment to help it identify the target, thereby ensuring the accuracy and reliability of the signal source. Thus, it has significant value in applications.