Volume 47 Issue 12
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Liu Yanping, Wang Chong, Wu Yunbin, Shangguan Mingjia, Xia Haiyun. Application of joint time-frequency analysis in coherent Doppler wind lidar[J]. Infrared and Laser Engineering, 2018, 47(12): 1230001-1230001(8). doi: 10.3788/IRLA201847.1230001
Citation: Liu Yanping, Wang Chong, Wu Yunbin, Shangguan Mingjia, Xia Haiyun. Application of joint time-frequency analysis in coherent Doppler wind lidar[J]. Infrared and Laser Engineering, 2018, 47(12): 1230001-1230001(8). doi: 10.3788/IRLA201847.1230001

Application of joint time-frequency analysis in coherent Doppler wind lidar

doi: 10.3788/IRLA201847.1230001
  • Received Date: 2018-08-10
  • Rev Recd Date: 2018-09-28
  • Publish Date: 2018-12-25
  • With high accuracy, high spatial-temporal resolution, large scale coverage, coherent Doppler lidar has been widely applied in the detection of wind shear, aircraft vortex, wind power generation, atmosphere turbulence and so on. For lidar signal processing, the key issue is how to extract weak Doppler frequency shift in the weak backscatter signal. Based on the atmospheric slices model, the simulated echo signal of coherent Doppler lidar was processed by different time-frequency methods. Simulation results show that the adaptive optimal-kernel time frequency representation outperforms the others, having the advantages of lower computation cost, suppressing cross terms efficiently and higher resolution in both time and frequency domains. Then the adaptive optimal-kernel time frequency representation was applied to the field experiment data derived from a 1.5m Coherent Doppler lidar in Hefei, Anhui Province in March, 2017. The retrieved wind velocity results were compared with that derived from the fast Fourier transform algorithm. Experimental results show that the range resolution is 1.2 meter within 3 kilometers, and maintains the continuity of wind speed retrieved form weak signal using a 50-points window in the far field over 3 kilometers. Furthermore it can track the wind details better and enhance the detection range to 6 kilometers as the temporal resolution is set to 1 second.
  • [1] Shangguan M, Xia H, Wang C, et al. All-fiber upconversion high spectral resolution wind lidar using a Fabry-Perot interferometer[J]. Optics Express, 2016, 24(17):19322-19336.
    [2] Yang F, He Y, Shang J, et al. Development of an all-fiber heterodyne lidar for range and velocity measurements[J]. Chinese Optics Letters, 2010, 8(7):713-716.
    [3] Liu J, Zhu X, Diao W, et al. All-fiber airborne coherent Doppler lidar to measure wind profiles[C]//EPJ Web of Conferences, EDP Sciences, 2016, 119:10002.
    [4] Shi Chenglong, Liu Jiqiao, Bi Decang, et al. Errors analysis of dioxide carbon concentrations measurement by airborne lidar[J]. Infrared and Laser Engineering, 2016, 45(5):0530001. (in Chinese)史成龙, 刘继桥, 毕德仓, 等. 机载激光雷达测量二氧化碳浓度误差分析[J]. 红外与激光工程, 2016,45(5):0530001.
    [5] Lu Xianyang, Li Xuebin, Qin Wubin, et al. Retrieval of horizontal distribution of aerosol mass concentration by micropulse lidar[J]. Optics and Precision Engineering, 2017, 25(7):1697-1704. (in Chinese)鲁先洋, 李学彬, 秦武斌, 等. 微脉冲激光雷达反演气溶胶的水平分布[J]. 光学精密工程, 2017,25(7):1697-1704.
    [6] Liu Zhiqing, Li Pengcheng, Chen Xiwei, et al. Classification of airbone Lidar point cloud data based on information vector machine[J]. Optics and Precision Engineering, 2016, 24(1):210-219. (in Chinese)刘志青, 李鹏程, 陈小卫, 等. 基于信息向量机的机载激光雷达点云数据分类[J]. 光学精密工程, 2016, 24(1):210-219.
    [7] Qu Yi. Technical status and development tendency of atmosphere optical remote and monitoring[J]. Chinese Optics, 2013, 6(6):834-840. (in Chinese)曲艺. 大气光学遥感监测技术现状与发展趋势[J]. 中国光学, 2013, 6(6):834-840.
    [8] Li Li, Wang Canzhao, Xie Yafeng, et al. Wind field inversion technique for scanning wind lidar[J]. Chinese Optics, 2013, 6(2):251-258. (in Chinese)李丽, 王灿召, 谢亚峰, 等. 扫描式测风激光雷达的风场反演[J]. 中国光学, 2013, 6(2):251-258.
    [9] Wang C, Xia H, Shangguan M, et al. 1.5m polarization coherent lidar incorporating time-division multiplexing[J]. Optics Express, 2017, 25(17):20663-20674.
    [10] Liu J, Zhu X, Diao W, et al. All-fiber airborne coherent doppler lidar to measure wind profiles[C]//EPJ Web of Conferences. EDP Sciences, 2016, 119:10002.
    [11] Zhai X, Wu S, Liu B. Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness[J]. Optics Express, 2017, 25(12):A515-A529.
    [12] Deng Pan, Zhang Tianshu, Chen Wei, et al. Estimating noise scale factor and SNR of atmospheric lidar[J]. Infrared and Laser Engineering, 2016, 45(S1):S13003. (in Chinese)邓潘, 张天舒, 陈卫, 等. 大气探测激光雷达噪声比例因子及信噪比的估算[J]. 红外与激光工程, 2016, 45(S1):S13003.
    [13] Bai Xue, Guo Pan, Chen Siying, et al. Simulation in the time domain and time-frequency analysis for coherent doppler wind Lidar[J]. Chinese Journal of Lasers, 2015, 42(1):0114003. 白雪, 郭磐, 陈思颖, 等. 相干多普勒测风激光雷达时域信号仿真及时频分析[J]. 中国激光, 2015, 42(1):0114003.
    [14] Salamitou P, Dabas A, Flamant P H. Simulation in the time domain for heterodyne coherent laser radar[J]. Applied Optics, 1995, 34(3):499-506.
    [15] Baraniuk R G, Jones D L, Baraniuk R G, et al. A signal-dependent time-frequency representation:Optimal kernel design[J]. IEEE Transactions on Signal Processing, 1993, 41(4):1589-1602.
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Application of joint time-frequency analysis in coherent Doppler wind lidar

doi: 10.3788/IRLA201847.1230001
  • 1. School of Earth and Space Science,University of Science and Technology of China,Hefei 230026,China

Abstract: With high accuracy, high spatial-temporal resolution, large scale coverage, coherent Doppler lidar has been widely applied in the detection of wind shear, aircraft vortex, wind power generation, atmosphere turbulence and so on. For lidar signal processing, the key issue is how to extract weak Doppler frequency shift in the weak backscatter signal. Based on the atmospheric slices model, the simulated echo signal of coherent Doppler lidar was processed by different time-frequency methods. Simulation results show that the adaptive optimal-kernel time frequency representation outperforms the others, having the advantages of lower computation cost, suppressing cross terms efficiently and higher resolution in both time and frequency domains. Then the adaptive optimal-kernel time frequency representation was applied to the field experiment data derived from a 1.5m Coherent Doppler lidar in Hefei, Anhui Province in March, 2017. The retrieved wind velocity results were compared with that derived from the fast Fourier transform algorithm. Experimental results show that the range resolution is 1.2 meter within 3 kilometers, and maintains the continuity of wind speed retrieved form weak signal using a 50-points window in the far field over 3 kilometers. Furthermore it can track the wind details better and enhance the detection range to 6 kilometers as the temporal resolution is set to 1 second.

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