一种基于自适应相关熵的生命探测方法

基于雷达的生命迹象探测在灾后救援和病人监护中有着广泛的应用。尽管近年来该领域中已经取得了一些重要成果，遮挡目标的有效探测却一直是一个难以解决的问题。对此，本文在步进频连续波雷达体制下，提出了一种基于自适应相关熵的生命迹象探测方法。该算法利用预检测得到目标可能出现的距离单元及对应的幅度，以此为基础自适应地调节相关熵的参数。通过这种改进的相关熵处理，实现了对弱目标的增强，最终在距离-多普勒（Range-Doppler, RD）平面得到了所有人体目标的呼吸频率和距离信息。仿真和实测结果证明了该算法的有效性。

A Novel Method for Vital Sign Detection Based on Adaptive Correlation Entropy

Noncontact detection of human vital signs based on radar system can be widely used in rescue and healthcare applications. Although significant progresses have been achieved in recent years, the occluded target detection remains a technical challenge. In this paper, a novel vital sign detection method based on modified correlation entropy is proposed utilizing the stepped-frequency continuous wave radar system. Firstly,pre-detection is used to obtain the amplitude and distance of the potential target. In order to enhance the weak target, we modify the correlation entropy process by adaptively estimating the parameters based on the amplitude of the potential target. Finally, the respiration frequencies and the range information of all targets can be obtained in the range-Doppler (RD) domain. Simulation and experimental results validate the proposed algorithm.