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相干多普勒测风激光雷达通常会采用周期图最大值法(PM)提取不同距离门信号的多普勒频移(对应风速)信息。由于噪声和相干效率的影响,个别距离门信号会出现信噪比(SNR)突然降低的情况,从而导致系统的探测概率降低,影响系统整体的探测性能。为了解决个别距离门信号多普勒频移的错误估计问题,提出了一种新的非线性自适应多普勒频移估计方法。该方法利用风速的连续性,标定错误距离门,并自适应地利用强信噪比区域的多普勒频移统计数据来弥补信噪比变差而出现的估计错误。分别利用了仿真模型和一套1.54μm全光纤相干激光雷达系统获得了风场测量数据,对比了使用该技术前后反演得到的风速趋势,证明该方法能够有效地解决上述问题。
Coherent Doppler wind lidar usually uses the periodic map maximum method (PM) to extract the Doppler frequency shift (corresponding wind speed) information of different distance gate signals. Due to the influence of noise and coherence efficiency, the signal-to-noise ratio (SNR) of individual distance gate signals suddenly decreases, which leads to the decrease of the detection probability of the system and affects the overall detection performance of the system. In order to solve the problem of error estimation of Doppler shift of individual distance gate signals, a new nonlinear adaptive Doppler frequency shift estimation method is proposed. The method utilizes the continuity of wind speed, calibrates the error distance gate, and adaptively utilizes the Doppler shift statistics of the strong signal-to-noise ratio region to make up for the estimation error that occurs when the signal-noise ratio deteriorates. The wind field measurement data are obtained by using the simulation model and a set of 1.54μm all-fiber coherent laser radar system respectively. The trend of wind speed obtained by using this technique is contrasted. It is proved that this method can effectively solve the above problems.