激光雷达探测信号数据融合算法

Gluing Method of Detected Signal Based on Lidar

提出基于二次多项式拟合的数据融合算法用于激光雷达信号探测.充分考虑模拟探测和光子计数的非线性关系,选择有效增大数据融合区间;分析云对区间内的模拟探测和光子计数数据质量的影响并进行质量控制,获得稳定的融合系数;同时利用模拟探测和光子计数的非线性关系校正脉冲堆积引入光子计数信号的非线性误差.以直接探测多普勒激光雷达为例,开展与探空气球的同步对比实验.结果显示:本文算法较之现有商用算法,风速相关系数从0.8提高到0.85,均方根误差从3.37 m/s降低至2.41 m/s,偏差从0.60 m/s降低至0.06 m/s,证明改进后的融合算法能够有效提高直接探测多普勒激光雷达风场探测的精度,可更好地应用于大气探测激光雷达的远场和近场信号的融合处理.

A data gluing method of quadratic polynomial fitting for lidar signal detection is proposed referring to the small gluing region and singular points. The data gluing region is extended to fully take the non-linear relationship between analog-to-digital and photon counting into account. The influence of cloud height on data quality is analyzed and the quality control is implemented to obtain stable gluing coefficient. The pile-up photon counting data is corrected according to the computational non-linear relationship between analog-to-digital and photon counting data. The synchronous comparison experiment between direct-detection Doppler lidar and balloon was carried out to verify this modified gluing method. The result shows that correlation coefficient increases from 0. 80 to 0. 85,the root mean square error decreased from 3. 37 m/s to 2. 41 m/s,and the deviation decreased from 0. 60 m/s to 0. 06 m/s. The result demonstrates that the modified gluing method could improve the accuracy of wind field detected by direct-detection Doppler lidar and is useful for atmosphere detection lidar to glue far-field and near-field signal.