高分辨率变焦式连续波测风激光雷达设计与实验

CUI Tong,CHEN Xiangcheng,DAI Guangyao,ZHANG Hongwei,WANG Qichao,WU Songhua

Journal of Atmospheric and Environmental Optics（2022）

Cited 0|Views11

Abstract

为实现近场风场的非接触式高分辨、高精度测量,弥补脉冲相干测风激光雷达在近场风场测量存在盲区的缺陷,选用对人眼安全的1550 nm工作波长的高功率连续波光纤激光器作为光源,基于激光多普勒相干测风原理,通过改变连续波激光聚焦位置实现风场不同位置的风速探测.为提高系统的信噪比(SNR),优化选取了当前系统本振光功率参数;并通过优化设计"有效频谱质心"算法,对连续波测量体积内存在多个速度分量数据进行处理,从而提高数据反演精度.使用该激光雷达系统与超声波风速计进行对比实验,风速数据相关性为0.98,标准差为0.16 m.s-1.在此基础上,利用该激光雷达系统进行长期风速观测实验,选取不同天气气溶胶含量差别较大的多组数据进行分析,同时对近地面及近建筑物风场内风速的变化进行了探究.局地风速观测实验结果表明,该激光雷达系统的风速测量区间为0.3～18 m·s-1,风场测量位置2～30 m,能够实现风场风速梯度的连续测量.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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