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时频分析在激光雷达中的应用进展

Application Progress of Time-Frequency Analysis for Lidar

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摘要

激光雷达对于实现隐形目标或大气、海洋、陆地领域目标等方面的高分辨率多参数探测具有重要意义。相对于传统的单独时域或频域处理, 时频分析在激光雷达信号分析、解译和处理等方面可以提供更多的信息。时频分析在激光雷达中的具体应用包括大气参数的特征分析与提取、信号去噪、运动目标成像与检测以及微多普勒特征分析等。在简要阐述各种时频分析原理特性基础上, 着重介绍时频分析在激光雷达中的最新应用进展。

Abstract

Lidar is vital for the high-resolution and multi-parameter detection of concealed objects, objects in the ares like atmosphere, oceans, lands, and so on. Compared with the traditional time-domain or frequency-domain methods, time-frequency analysis can provide more insight into the analysis, interpretation, and processing of lidar signals. Time-frequency analysis has been widely used, including in feature analysis and extraction of atmospheric parameters, signal denoising, moving target imaging and detection, and micro-Doppler classification analysis. The methods used for the time-frequency analysis of lidar are further developed based on the basic principles and characteristics of time-frequency analysis.

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中图分类号:TN958.98

DOI:10.3788/LOP55.120005

所属栏目:综述

收稿日期:2018-05-01

修改稿日期:2018-06-01

网络出版日期:2018-07-05

作者单位    点击查看

刘燕平:中国科学技术大学地球和空间科学学院, 安徽 合肥 230026
王冲:中国科学技术大学地球和空间科学学院, 安徽 合肥 230026
夏海云:中国科学技术大学地球和空间科学学院, 安徽 合肥 230026

联系人作者:刘燕平(yanping@mail.ustc.edu.cn); 王冲(wcltr@163.com); 夏海云(hsia@ustc.edu.cn);

【1】Lefsky M A, Cohen W B, Parker G G, et al. Lidar remote sensing for ecosystem studies[J]. BioScience, 2002, 52(1): 19-30.

【2】Wu S H, Zhai X C, Liu B Y, et al. Characterization of aircraft dynamic wake vortices and atmospheric turbulence by coherent doppler lidar[C]∥The 28th International Laser Radar Conference, June 25-30, 2017, Bucharest, Romania. Amsterdam: EDP Sciences, 2018, 176: 06001.

【3】Wang C, Xia H Y, Shangguan M J, et al. 1.5 μm polarization coherent lidar incorporating time-division multiplexing[J]. Optics Express, 2017, 25(17): 20663-20674.

【4】Ma X M,Tao Z M, Zhang L L, et al. Ground layer aerosol detection technology during daytime based on side-scattering lidar[J]. Acta Optica Sinica, 2018, 38(4): 0401005.
麻晓敏, 陶宗明, 张璐璐, 等. 侧向散射激光雷达探测白天近地面气溶胶探测技术[J]. 光学学报, 2018, 38(4): 0401005.

【5】Ye G H, Deng S S, Xu W B, et al. Application of airborne LiDAR technology in dune deformation monitoring[J]. Laser & Optoelectronics Progress, 2018, 55(5): 052802.
叶光豪, 邓愫愫, 徐文兵, 等. 机载激光雷达技术应用于沙丘变形监测的研究[J]. 激光与光电子学进展, 2018, 55(5): 052802.

【6】Cohen L. Time-frequency distributions-a review[J]. Proceedings of the IEEE, 1989, 77(7): 941-981.

【7】Feng Z P, Liang M, Chu F L. Recent advances in time-frequency analysis methods for machinery fault diagnosis: a review with application examples[J]. Mechanical Systems and Signal Processing, 2013, 38(1): 165-205.

【8】Boashash B. Time-frequency signal analysis and processing: a comprehensive reference[M]. New York: Academic Press, 2015.

【9】Gabor D. Theory of communication. Part 1: The analysis of information[J]. Journal of the Institution of Electrical Engineers-Part III: Radio and Communication Engineering, 1946, 93(26): 429-441.

【10】Potter R K, Kopp G A, Green H C. Visible speech[M]. New York: Van Nostrand and Company, 1947.

【11】Grossmann A, Morlet J. Decomposition of hardy functions into square integrable wavelets of constant shape[J]. SIAM Journal on Mathematical Analysis, 1984, 15(4): 723-736.

【12】Stockwell R G, Mansinha L, Lowe R P. Localization of the complex spectrum: the S transform[J]. IEEE Transactions on Signal Processing, 1996, 44(4): 998-1001.

【13】Namias V. The fractional order Fourier transform and its application to quantum mechanics[J]. IMA Journal of Applied Mathematics, 1980, 25(3): 241-265.

【14】Cohen L. Time-frequency analysis[M]. New Jersey: Prentice Hall PTR, 1995.

【15】Bertrand J, Bertrand P. Affinetime-frequency distributions[C]∥1990 Special Conference on Time-Frequency Signal Analysis/International Symp on Signal Processing and its Applications, 1990, Gold Coast Australia. Melbourne: Longman Cheshire, 1992: 118-140.

【16】Auger F, Flandrin P. Improving the readability of time-frequency and time-scale representations by the reassignment method[J]. IEEE Transactions on Signal Processing, 1995, 43(5): 1068-1089.

【17】Jeong J, Williams W J. Kernel design for reduced interference distributions [J]. IEEE Transactions on Signal Processing, 1992, 40(2): 402-412.

【18】Wigner E. On the quantum correction for thermodynamic equilibrium[J]. Physical Review, 1932, 40(5): 749-759.

【19】Ville J. Theorie et application de la notion de signal analytique[J]. Cables et Transmission, 1948, 2(1):61-74.

【20】Bastiaans M J. A sampling theorem for the complex spectrogram, and Gabor′s expansion of a signal in Gaussian elementary signals[J]. Optical Engineering, 1981, 20(4): 204594.

【21】Claasen T, Mecklenbrauker W F G. The Wigner distribution—a tool for time-frequency signal analysis[J]. Philips Journal of Research, 1980, 35(3): 217-250.

【22】Flandrin P, Martin W. A general class of estimators for the Wigner-Ville spectrum of non-stationary processes[M]∥Bensoussan A, Lions J L. Analysis and Optimization of Systems. Berlin, Heidelberg: Springer, 1984: 15-23.

【23】Born M, Jordan P. Zur quantenmechanik[J]. Zeitschriftfür Physik, 1925, 34(1): 858-888.

【24】Choi H I, Williams W J. Improved time-frequency representation of multicomponent signals using exponential kernels[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1989, 37(6): 862-871.

【25】Zhao Y, Atlas L E, Marks R J. The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990, 38(7): 1084-1091.

【26】Page C H. Instantaneous power spectra[J]. Journal of Applied Physics, 1952, 23(1): 103-106.

【27】Rihaczek A. Signal energy distribution in time and frequency[J]. IEEE Transactions on Information Theory, 1968, 14(3): 369-374.

【28】Margenau H, Hill R N. Correlation between measurements in quantum theory[J]. Progress of Theoretical Physics, 1961, 26(5): 722-738.

【29】Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. Proceedings: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995.

【30】Huang N E. Hilbert-Huang transform and its applications[M]. 2nd ed. New Jersey: World Scientific, 2014.

【31】Qian S E, Chen D P. Signal representation using adaptive normalized Gaussian functions[J]. Signal Processing, 1994, 36(1): 1-11.

【32】Mallat S G, Zhang Z F. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12): 3397-3415.

【33】Képesi M, Weruaga L. Adaptive chirp-based time-frequency analysis of speech signals[J]. Speech Communication, 2006, 48(5): 474-492.

【34】Brousmiche S. Simulation of coherent Doppler LIDAR signals and their analysis with the Cohen′s class: application to algorithms design for wake vortex detection and characterization[D]. Belgium: UCL-Université Catholique de Louvain, 2010.

【35】Renard W, Goular D, Valla M, et al. Beyond 10 km range wind-speed measurement with a 1.5 μm all-fiber laser source[C]∥2014 Conference on Lasers and Electro-Optics (CLEO)-Laser Science to Photonic Applications, June 8-13, 2014, San Jose, CA, USA. New York: IEEE, 2014: 14822367.

【36】Dolfi-Bouteyre A, Canat G, Lombard L, et al. Long-range wind monitoring in real time with optimized coherent lidar[J]. Optical Engineering, 2017, 56(3): 031217.

【37】Qiu J H, Shen S P, Xu G Y. Short-term wind speed forecasting by combination of masking signal-based empirical mode decomposition and extreme learning machine[C]∥2016 11th International Conference on Computer Science & Education (ICCSE), August 23-25, 2016, Nagoya, Japan. New York: IEEE, 2016: 581-586.

【38】Chen C, Chu X Z. Two-dimensional Morlet wavelet transform and its application to wave recognition methodology of automatically extracting two-dimensional wave packets from lidar observations in Antarctica[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2017, 162: 28-47.

【39】Chen C, Chu X Z, Zhao J, et al. Lidar observations of persistent gravity waves with periods of 3-10 h in the Antarctic middle and upper atmosphere at McMurdo (77.83°S, 166.67°E)[J]. Journal of Geophysical Research: Space Physics, 2016, 121(2): 1483-1502.

【40】Cézard N, Liméry A, Bertrand J, et al. New lidar challenges for gas hazard management in industrial environments[J]. Proceedings of SPIE, 2017, 10429: 1042903.

【41】Kaifler N, Kaifler B, Ehard B, et al. Observational indications of downward-propagating gravity waves in middle atmosphere lidar data[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2017, 162: 16-27.

【42】Wang C, Xia H Y, Liu Y P, et al. Spatial resolution enhancement of coherent Doppler wind lidar using joint time-frequency analysis[J]. Optics Communications, 2018, 424: 48-53.

【43】Boyo H, Fujiwara M, Moshnyaga V G, et al. Algorithm based on joint time-frequency analysis to eliminate noise from stratospheric laser data[J]. Proceedings of SPIE, 2003, 4891: 515-523.

【44】Wu S H, Liu Z S, Liu B Y. Enhancement of lidar backscatters signal-to-noise ratio using empirical mode decomposition method[J]. Optics Communications, 2006, 267(1): 137-144.

【45】Li L, Si X C, Chai J F, et al. Parameters estimation for LFM radar signal based on reassigned wavelet-Radon transform[J]. Systems Engineering and Electronics, 2009, 31(1): 74-77.
李利, 司锡才, 柴娟芳, 等. 基于重排小波-Radon变换的LFM雷达信号参数估计[J]. 系统工程与电子技术, 2009, 31(1): 74-77.

【46】Zhang Y K, Ma X C, Hua D X, et al. An EMD-based denoising method for lidar signal[C]∥2010 3rd International Congress on Image and Signal Processing, October 16-18, 2010, Yantai, China. New York: IEEE, 2010: 4016-4019.

【47】Chen D, Wang J A, Kang S. Comparison of backscattering lidar signal denoising methods[J]. Ship Science and Technology, 2011, 33(4): 93-97.
陈冬, 王江安, 康圣. 脉冲激光雷达信号降噪方法对比[J]. 舰船科学技术, 2011, 33(4): 93-97.

【48】He J F, Liu W Q, Zhang Y J, et al. New method of lidar ceilometer backscatter signal processing based on Hilbert-Huang transform[J]. Infrared and Laser Engineering, 2012, 41(2): 397-403.
何俊峰, 刘文清, 张玉钧, 等. HHT在激光云高仪后向散射信号处理中的应用[J]. 红外与激光工程, 2012, 41(2): 397-403.

【49】Stephenson J H, Greenwood E. Effects of vehicle weight and true versus indicated airspeed on BVI noise during steady descending flight[C]∥71st Annual AHS Forum and Technology Display, May 5-7, 2015, Virginia Beach, VA, USA. 2015.

【50】Saeed U, Rocadenbosch F, Crewell S. Adaptive estimation of the stable boundary-layer height using backscatter LiDAR data and a Kalman filter[C]∥2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 26-31, 2015, Milan, Italy. New York: IEEE, 2015: 3591-3594.

【51】Zhang H Y, Lv T, Yan C H. The novel role of arctangent phase algorithm and voice enhancement techniques in laser hearing[J]. Applied Acoustics, 2017, 126: 136-142.

【52】Wang Y F, Cao X M, Zhang J, et al. Detection and analysis of all-day atmospheric water vapor Raman lidar based on wavelet denoising algorithm[J]. Acta Optica Sinica, 2018, 38(2): 0201001.
王玉峰, 曹小明, 张晶, 等. 基于小波去噪算法的全天时大气水汽拉曼激光雷达探测与分析[J]. 光学学报, 2018, 38(2): 0201001.

【53】Chang J H, Zhu L Y, Li H X, et al. Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty[J]. Optics Communications, 2018, 407: 290-295.

【54】Olsson, A. Target recognition by vibrometry with a coherent laser radar: LITH-ISY-EX-3050-2003[R/OL].(2003-05-13)[2018-05-01]. http:∥www.ep.liu.se/exjobb/isy/2003/3050/.

【55】Amzajerdian F, Pierrottet D, Tolson R H, et al. Development of a coherent LiDAR for aiding precision soft landing on planetary bodies[C]∥13th Coherent Laser Radar Conference, October 16-21, 2005, Kamakura, Japan. 2005: 20050240846.

【56】Falkowski M J, Smith A M S, Hudak A T, et al. Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data[J]. Canadian Journal of Remote Sensing, 2006, 32(2): 153-161.

【57】Wei H, Bartels M. Unsupervised segmentation using Gabor wavelets and statistical features in LIDAR data analysis[C]∥18th International Conference on Pattern Recognition, August 20-24, 2006, Hong Kong, China. New York: IEEE, 2006: 667-670.

【58】van Gaalen J F, Kruse S E, Burroughs S M, et al. Time-frequency methods for characterizing cuspate landforms in lidar data[J]. Journal of Coastal Research, 2009, 25(5): 1143-1148.

【59】Allen J D, Yuan J B, Liu X W, et al. A compressed sensing method with analytical results for lidar feature classification[J]. Proceedings of SPIE, 2011, 8055: 80550G.

【60】He J, Zhang Q, Yang X Y, et al. Imaging algorithm for inverse synthetic aperture imaging LADAR[J]. Infrared and Laser Engineering, 2012, 41(4): 1094-1100.
何劲, 张群, 杨小优, 等. 逆合成孔径成像激光雷达成像算法[J]. 红外与激光工程, 2012, 41(4): 1094-1100.

【61】Sobolev I, Babichenko S. Analysis of the performances of hyperspectral lidar for water pollution diagnostics[J]. EARSeL eProceedings, 2013, 12(2): 113-123.

【62】Deuge M D, Quadros A, Hung C, et al. Unsupervised feature learning for classification of outdoor 3D scans[C]∥Proceedings of the 2013 Australasian Conference on Robitics and Automation, December 2-4, 2013, University of New South Wales, Sydney Australia. Australian Robotics and Automation Association, 2013, N/A: 98586.

【63】Wu Y H, Ruan H, Yu D B. Inverse synthetic aperture laser radar imaging algorithm for maneuvering targets[C]∥2014 7th International Congress on Image and Signal Processing (CISP), October 14-16, 2014, Dalian, China. New York: IEEE, 2014: 569-574.

【64】Vercesi V, Onori D, Laghezza F, et al. Frequency-agile dual-frequency lidar for integrated coherent radar-lidar architectures[J]. Optics Letters, 2015, 40(7): 1358-1361.

【65】Konsoer K, Rhoads B, Best J, et al. Length scales and statistical characteristics of outer bank roughness for large elongate meander bends:the influence of bank material properties, floodplain vegetation and flow inundation[J]. Earth Surface Processes and Landforms, 2017, 42(13): 2024-2037.

【66】Wang N, Wang R, Mo D, et al. Inverse synthetic aperture LADAR demonstration: system structure, imaging processing, and experiment result[J]. Applied Optics, 2018, 57(2): 230.

【67】Youmans D G. Joint time-frequency transform processing for linear and sinusoidal FM coherent ladars[J]. Proceedings of SPIE, 2003, 5087: 46-57.

【68】Wang X Q, Dong Y Q, Yuan S, et al. Study on simulation of micro-Doppler effect in lidar[J]. Laser Technology, 2007, 31(2): 117-119, 146.
王学勤, 董艳群, 原帅, 等. 激光雷达微多普勒效应的仿真研究[J]. 激光技术, 2007, 31(2): 117-119,146.

【69】Gueguen P, Jolivet V, Michel C, et al. Comparison of velocimeter and coherent lidar measurements for building frequency assessment[J]. Bulletin of Earthquake Engineering, 2010, 8(2): 327-338.

【70】He J, Zhang Q, Luo Y, et al. Analysis of micro-doppler effect and feature extraction of target in inverse synthetic aperture imaging ladar[J]. Acta Electronica Sinica, 2011, 39(9): 2052-2059.
何劲, 张群, 罗迎, 等. 逆合成孔径成像激光雷达微多普勒效应分析及特征提取[J]. 电子学报, 2011, 39(9): 2052-2059.

【71】Zhu F, Zhang Q, Feng Y Q, et al. Compressed sensing identification approach for avian with inverse synthetic aperture lidar[J]. Infrared and Laser Engineering, 2013, 42(1): 256-261.
朱丰, 张群, 冯有前, 等. 逆合成孔径激光雷达鸟类目标压缩感知识别方法[J]. 红外与激光工程, 2013, 42(1): 256-261.

【72】Tahmoush D. Extracting and analyzing micro-Doppler from ladar signatures[J]. Proceedings of SPIE, 2015, 9461: 94611F.

【73】Wang Y P, Hu Y H, Lei W H, et al. Aircraft target classification method based on texture feature of laser echo time-frequency image[J]. Acta Optica Sinica, 2017, 37(11): 1128004.
王云鹏, 胡以华, 雷武虎, 等. 基于激光回波时频图纹理特征的飞机目标分类方法[J]. 光学学报, 2017, 37(11): 1128004.

引用该论文

Liu Yanping,Wang Chong,Xia Haiyun. Application Progress of Time-Frequency Analysis for Lidar[J]. Laser & Optoelectronics Progress, 2018, 55(12): 120005

刘燕平,王冲,夏海云. 时频分析在激光雷达中的应用进展[J]. 激光与光电子学进展, 2018, 55(12): 120005

被引情况

【1】谢若晗,何思远,朱国强,张云华. 基于目标属性散射中心模型的正向参数化建模. 激光与光电子学进展, 2019, 56(12): 122901--1

【2】侯春萍,蒋天丽,郎玥,杨阳. 基于卷积神经网络的雷达人体动作与身份多任务识别. 激光与光电子学进展, 2020, 57(2): 21009--1

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