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Inversion probability enhancement of all-fiber CDWL by noise modeling and robust fitting
Optics Express ( IF 3.2 ) Pub Date : 2020-09-21 , DOI: 10.1364/oe.401054
Tianwen Wei , Haiyun Xia , Yunbin Wu , Jinlong Yuan , Chong Wang , Xiankang Dou

Accurate power spectrum analysis of weak backscattered signals are the primary constraint in long-distance coherent Doppler wind lidar (CDWL) applications. To study the atmospheric boundary layer, an all-fiber CDWL with 300µJ pulse energy is developed. In principle, the coherent detection method can approach the quantum limit sensitivity if the noise in the photodetector output is dominated by the shot noise of the local oscillator. In practice, however, abnormal power spectra occur randomly, resulting in error estimation and low inversion probability. This phenomenon is theoretically analyzed and shown to be due to the leakage of a time-varying DC noise of the balanced detector. Thus, a correction algorithm with accurate noise modeling is proposed and demonstrated. The accuracy of radial velocity, carrier-to-noise ratio (CNR), and spectral width are improved. In wind profiling process, a robust sine-wave fitting algorithm with data quality control is adopted in the velocity-azimuth display (VAD) scanning detection. Finally, in 5-day continuous wind detection, the inversion probability is tremendously enhanced. As an example, it is increased from 8.6% to 52.1% at the height of 4 km.

中文翻译:

通过噪声建模和鲁棒拟合提高全光纤CDWL的反演概率

弱反向散射信号的精确功率谱分析是长距离相干多普勒风激光雷达(CDWL)应用中的主要限制。为了研究大气边界层,开发了具有300µJ脉冲能量的全光纤CDWL。原则上,如果光电探测器输出中的噪声由本地振荡器的散粒噪声控制,则相干检测方法可以达到量子极限灵敏度。然而,实际上,异常功率谱是随机发生的,从而导致误差估计和低反转概率。从理论上分析了此现象,并表明这是由于平衡检测器的时变直流噪声泄漏所致。因此,提出并证明了具有精确噪声建模的校正算法。径向速度的精度,载噪比(CNR),和光谱宽度得到改善。在风廓线过程中,在速度方位角显示(VAD)扫描检测中采用了具有数据质量控制的鲁棒正弦波拟合算法。最后,在5天连续风探测中,反演概率大大提高。例如,它在4 km的高度处从8.6%增加到52.1%。
更新日期:2020-09-28
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