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相干测风激光雷达通常采用周期图最大值法,但在远场低信噪比区域是有偏估计,因而会增加风速测量误差。距离门功率谱基线漂移现象作为误差源之一,会偏置谱峰分布基准,并干扰峰值频率检测。为了校正基线漂移,提出了基于正则化惩罚最小二乘法的先验平滑估计频谱基线方法。经过大气测风实验应用,结果表明,该方法能有效校正基线漂移,从而显著提高远场风速的估计精度,并最终提升了测风激光雷达的探测距离。
Coherent wind lidar usually uses the maximum value method of the periodic graph, but the low signal-to-noise ratio region in the far field is a biased estimator, which increases the wind speed measurement error. One of the sources of error from the gate power spectrum baseline drift is to bias the peak distribution criteria and interfere with the peak frequency detection. In order to correct the baseline drift, a priori smoothing spectral baseline method based on regularization penalty least square method is proposed. After the atmospheric wind experiment, the results show that this method can effectively correct the baseline drift, so as to significantly improve the estimation accuracy of the far-field wind speed and ultimately improve the detection range of the wind-lidar.