基于弹性变分模态提取的时间相关单光子计数信号去噪  

A time-correlated single photon counting signal denoising method based on elastic variational mode extraction

作　　者：汪书潮 苏秀琴[1,3] 朱文华 陈松懋 张振扬 徐伟豪 王定杰 Wang Shu-Chao;Su Xiu-Qin;Zhu Wen-Hua;Chen Song-Mao;Zhang Zhen-Yang;Xu Wei-Hao;Wang Ding-Jie(Key Laboratory of Space Precision Measurement Technology,Xi’an Institute of Optics and Precision Mechanics,Chinese Academy of Sciences,Xi’an 710119,China;University of Chinese Academy of Sciences,Beijing 100049,China;Pilot National Laboratory for Marine Science and Technology,Qingdao 266237,China)

机构地区：[1]中国科学院西安光学精密机械研究所,中国科学院空间精密测量技术重点实验室,西安710119 [2]中国科学院大学,北京100049 [3]青岛海洋科学与技术试点国家实验室,青岛266237

出　　处：《物理学报》2021年第17期153-162,共10页Acta Physica Sinica

基　　金：中国博士后科学基金(批准号:2020M683600);中国科学院战略高技术创新项目(批准号:GQRC-19-19)资助的课题.

摘　　要：单光子激光雷达的回波信号具有极低的信噪比,有效地消除噪声和提取出回波信号特征是提升单光子激光雷达测距精度的关键,变分模态分解算法需要使用者依据经验确定分解本征模态函数数量,不具有适用性和通用性.为此,本文基于时间相关单光子计数信号特点,提出了在变分模态分解中让信号按照指定频率进行聚类分解的变分约束条件,并采用弹性网回归重构不适定问题的求解模型,提出了弹性变分模态提取算法.实验结果表明,在波段850 nm、平均发射功率为25 nW、背景噪声平均功率为19.51μW的条件下,利用该方法,得到了时间相关单光子计数信号重建精度的均方根误差为1.414 ns.同时在不同的累积时间下,能够稳定且快速地提取出回波信号特征,有效地提高了算法的去噪能力和特征提取的性能.The performance of the method of measuring the time-correlated single photon counting signal is the key to improving the ranging accuracy of single photon light detection and ranging(LiDAR)technique,where noise elimination is a critically essential step to obtain the characteristics of signal.In this paper,a new method called elastic variational mode extraction(EVME)is proposed to extract the feature of the reflected photons from noisy environment.The method takes into account the characteristic of photon counting signal,and improves variational mode decomposition(VMD)method by adopting a new assumption that the extractive mode signal should be compact around desired center frequency.The proposed method also uses the elastic net regularization to solve ill-posed problem instead of Tikhonov regularization mentioned in VMD.Elastic net regularization takes into account both L2-norm regularization and L1-norm regularization,which can add an extra analysis dimension compared with the Tikhonov regularization.The method is validated with real data which are acquired on condition that average transmitting power is 25 nW while the average background noise power is 19.51μW.The root mean square error of the reconstruction accuracy reaches 1.414 ns.Furthermore,compared with VMD,Haar wavelet,Hibert envelope,empirical mode decomposition(EMD)and complete ensemble empirical mode decomposition method based on adaptive noise(CEEMDAN)under different conditions,the proposed method show fast and stable performance under an extreme case.

关 键 词：弹性变分模态提取 时间相关单光子计数 去噪 特征提取 

分 类 号：TN957.51[电子电信—信号与信息处理]