基于线型预测频谱估计的相干激光雷达功率谱分析方法  

Power spectrum analysis method of coherent Doppler lidar based on linear prediction spectrum estimation

作　　者：陈沛 张洪玮 刘晓英 张芯瑜 张开俊 陈丽晶 伏龙延 吴松华[1,2,6] Chen Pei;Zhang Hongwei;Liu Xiaoying;Zhang Xinyu;Zhang Kaijun;Chen Lijing;Fu Longyan;Wu Songhua(College of Marine Technology,Faculty of Information Science and Engineering,Ocean University of China,Qingdao 266100,China;Institute for Advanced Ocean Study,Ocean University of China,Qingdao 266100,China;Key Laboratory of Space Laser Information Transmission and Detection Technology,Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800,China;Gansu Branch of Northwest Air Traffic Management Bureau China,Civil Aviation,Lanzhou 730087,China;College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000,China;Laboratory for Regional Oceanography and Numerical Modeling,Laoshan Laboratory,Qingdao 266237,China)

机构地区：[1]中国海洋大学信息科学与工程学部海洋技术学院,山东青岛266100 [2]中国海洋大学海洋高等研究院,山东青岛266100 [3]中国科学院上海光学精密机械研究所中国科学院空间激光信息传输与探测技术重点实验室,上海201800 [4]中国民用航空西北地区空中交通管理局甘肃分局,甘肃兰州730087 [5]兰州大学大气科学学院,甘肃兰州730000 [6]崂山实验室区域海洋动力学与数值模拟功能实验室,山东青岛266237

出　　处：《红外与激光工程》2023年第11期78-93,共16页Infrared and Laser Engineering

基　　金：国家自然科学基金项目(42106182,61975191,41905022);山东省自然科学基金青年项目(ZR2021QD052);中国海洋大学联合研究项目(#2021-GT-133)。

摘　　要：基于多普勒效应的相干激光雷达广泛应用于测风等大气探测领域,实际应用于风场观测时,由于噪声杂波干扰、回波信号较弱和风场不均匀性等影响了多普勒频移估计的精度。为准确估计激光雷达弱回波信号中的多普勒频移,提升相干测风激光雷达的探测距离和探测精度,文中开展了基于激光雷达功率谱信号的多普勒频移估计算法以及探测性能提升的评估研究。在快速傅里叶变换的基础上,提出了一种结合线性预测频谱估计与导数增强方法的功率谱分析方法,通过与常用的最大似然离散谱峰值频移估计算法(ML DSP算法)进行比较,验证了文中方法在相干测风激光雷达微弱信号频移估计过程中的优势。风速数据的时间及空间相关性分析结果表明,功率谱分析方法具有更好的风速估计稳定性,有效风场探测距离相较ML DSP算法提升了73%。与超声风速计对比结果表明,文中提出的综合算法在弱信号情况下的风速测量精度高,风速结果与超声风速计的标准偏差相较ML DSP算法降低了0.23 m/s,偏离率BIAS降低了0.3 m/s,有效提高了低信噪比范围内多普勒频移估计的精度。Objective In the data processing of wind field detection by coherent Doppler lidar,the Doppler frequency shift is extracted as the target for wind speed calculation,and the accuracy of Doppler frequency estimation directly affects the performance of wind field detection by coherent Doppler lidar.The accuracy of wind measurement is greatly affected by the interference of noise clutter,weakness of reflection signal,and wind field inhomogeneity,thus limiting the detection performance of the system,resulting in wind speed estimation outliers and detection range faults.The existing research on the power spectrum analysis method lacks the targeted research and multiangle optimization attempts under the key technical limitations of weak signals.Therefore,effective peak retrieval of the power spectrum plays a decisive role in achieving accurate inversion of the wind field under the application limitation.Therefore,a power spectrum analysis method is proposed to improve the accuracy and detection performance of coherent Doppler lidar wind speed retrieval.Methods In order to improve the peak detection accuracy of the target signal under weak signal conditions and obtain the accurate frequency estimation of signal spectrum for wind speed inversion,the optimization of the frequency shift estimation algorithm and peak detection are explored.Specific optimization measures include the smoothing processing of the original power spectrum baseline:background noise removal algorithm(Fig.1-2),the resolution enhancement peak detection algorithm for the target signal(Fig.3),and the quality assessment of peak retrieval to achieve frequency estimation correction(Fig.4-5).A power spectrum analysis method based on nonlinear least squares noise fitting,combining linear prediction spectrum estimation and derivative enhancement algorithm is proposed(Fig.6).Results and Discussions The commonly used maximum likelihood discrete spectrum peak estimation algorithm based on Fast Fourier Transform and the proposed frequency estimation synthesis alg

关 键 词：相干多普勒激光雷达 多普勒频移估计 弱信号识别 峰值检索 

分 类 号：TN958.98[电子电信—信号与信息处理]