基于PSO-VMD算法的生命探测方法研究  

The life detection method via PSO-VMD algorithm

作　　者：陆鑫 陈志敏[1,2] LU Xin;CHEN Zhimin(School of Electronic and Information Engineering,Shanghai DianJi University,Shanghai 201306,China;State Key Laboratory of Millimeter Waves,Southeast University,Nanjing 210096,China)

机构地区：[1]上海电机学院电子信息学院,上海201306 [2]东南大学毫米波国家重点实验室,南京210096

出　　处：《空间电子技术》2022年第2期48-54,共7页Space Electronic Technology

基　　金：上海市自然科学基金面上项目(编号:22ZR1425200);毫米波国家重点实验室开放课题(编号:K202029)。

摘　　要：生命探测雷达在航空航天领域有着重要的应用,通过探测飞行员的呼吸、心跳、肢体动作等微弱信号,实现对飞行员的生命监测。针对实际场景中生命体微弱信号检测困难的问题,提出一种将包络熵作为粒子群算法适应度函数的变分模态分解(variational mode decomposition,VMD)参数优化算法。首先,利用粒子群算法对适应度函数进行选择,确定VMD算法中固有模态分量的分解层数以及惩罚因子个数的组合;其次,通过频谱分析选择特定层数的固有模态分量并重构雷达回波信号;最终达到去除噪声,提取生命体弱信号的目的。对比实验表明,所提出的方法相比经验模态分解算法能够更加准确地提取生命体信息,仿真结果验证了算法的有效性。Life detection radar has important applications in the field of aerospace.By detecting weak signals such as breathing,heartbeat and body movements,it can realize life monitoring of pilot.In order to solve the problem of weak signal detection of living bodies,a parameter optimization algorithm of variational mode decomposition(VMD)using envelope entropy as the fitness function of particle swarm optimization is proposed in this paper.Firstly,the particle swarm optimization algorithm was used to select the fitness function,and the combination of the number of decomposition layers of the intrinsic mode component and the number of penalty factors in the VMD algorithm was determined.Secondly,the intrinsic mode components of a certain number of layers are selected through spectrum analysis and the radar echo signal is reconstructed,so as to remove the noise and extract the weak signal.Comparison experiments show that the proposed method can extract the life information more accurately than the EMD algorithm,and the simulation results verify the effectiveness of the proposed algorithm.

关 键 词：变分模态分解 粒子群算法 参数优化 生命探测雷达 

分 类 号：V7[航空宇航科学技术]