中国激光, 2018, 45 (11): 1110005, 网络出版: 2018-11-15   

低信噪比下相干多普勒激光雷达风场矢量反演算法 下载: 887次

Wind-Field Vector Retrieval Method at Low Signal-to-Noise Ratio for Coherent Doppler Lidar
作者单位
北京理工大学光电学院, 北京 100081
摘要
为了能在低信噪比情况下获得高精度矢量风速,采用非线性最优化理论中的序列二次规划(SQP)求解滤波正弦波拟合(FSWF),实现了速度方位显示(VAD)算法中矢量风场的反演。基于模拟数据进行仿真实验,以反演结果的均方根误差作为评价指标,对比直接正弦波拟合(DSWF)和SQP-FSWF两种算法,结果表明在低信噪比条件下SQP-FSWF算法的反演效果优于DSWF算法。在FSWF计算中,基于风场反演结果的时空连续性,对比SQP算法和无约束最优化算法中的拟牛顿法,结果表明,SQP算法在低信噪比下效果更好。开展了激光雷达和探空气球的风场测量对比实验,获取了真实的激光雷达回波信号和同步探空气球数据,以进一步评估算法的可靠性。实验结果显示,SQP-FSWF算法得到的风速反演结果,同作为对比对象的探空气球的测量结果(水平风速、水平风向),两者间的相关系数分别为0.993和0.988,平均误差分别为0.2 m/s和3.28°,均方根误差分别为0.28 m/s和4.62°。对比分析反演结果的时空连续性发现,所提出方法在低信噪比下时空连续性更好,与模拟数据实验结果的效果表现一致。
Abstract
In this study, the sequential quadratic programming (SQP) in nonlinear optimization theory is used to solve the filtered sine wave fitting (FSWF). Based on the speed azimuth display (VAD) algorithm, high-precision inversion of the vector wind field is achieved at low signal-to-noise ratio (SNR). In the simulation experiment, the root mean square errors of the inversion results are used as the evaluation index, and the direct sine wave fitting (DSWF) algorithm and the SQP-FSWF algorithm are compared. In the FSWF calculation, based on the spatial-temporal continuity of the wind field inversion results, the SQP algorithm and the quasi-Newton method in the unconstrained optimization algorithm are compared. The comparison results show that the inversion effect of SQP-FSWF is better than those of DSWF and the quasi-Newton method at low SNR. To further evaluate the reliability of the proposed algorithm, we perform the wind field measurement contrast experiments based on lidar and synchronous sounding balloon, in which we obtain the real echo signal of lidar and the wind field data of synchronous sounding balloon. The wind speed inversion results simulated by the SQP-FSWF algorithm and the results measured by synchronous sounding balloon as the comparison object are compared. It can be seen that for horizontal wind speed, the correlation coefficient, the average error, the root mean square error are 0.993, 0.2 m/s, 0.28 m/s; for horizontal wind direction, the correlation coefficient, the average error, the root mean square error are 0.988, 3.28°, 4.62°, respectively. Based on the comparison between the spatial-temporal continuity of the wind retrieval results, the proposed method at low SNR is advantageous, which is consistent with the results of the simulated data.

赵萌, 郭磐, 芮训豹, 陈思颖, 张寅超, 陈和. 低信噪比下相干多普勒激光雷达风场矢量反演算法[J]. 中国激光, 2018, 45(11): 1110005. Zhao Meng, Guo Pan, Rui Xunbao, Chen Siying, Zhang Yinchao, Chen He. Wind-Field Vector Retrieval Method at Low Signal-to-Noise Ratio for Coherent Doppler Lidar[J]. Chinese Journal of Lasers, 2018, 45(11): 1110005.

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