LiSBOA：LiDAR统计Barnes客观分析，用于LiDAR扫描的最佳设计和风统计数据的检索。第一部分：理论框架
LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part I: Theoretical framework
摘要：
提出了一种用于激光雷达扫描优化设计和速度统计矩反演的统计Barnes客观分析（LiSBOA）。LiSBOA代表了经典Barnes方案在N维空间中用于非结构化实验数据的统计分析的适应，并且它是用于通过扫描LiDAR采样的标量场的统计的结构化笛卡尔网格上的评估的合适技术。LiSBOA的验证和特点是通过蒙特卡罗方法应用于合成速度场。重新审视的Barnes客观分析的理论框架使LiDAR实验的最佳设计和LiSBOA用于LiDAR测量的后处理的有效应用的指导方针的制定成为可能。LiDAR扫描的优化设计被配制成两个成本函数优化问题，包括最小化未以足够的空间分辨率采样的测量体积的百分比和最小化速度场的平均值的误差。LiDAR扫描的最佳设计还指导了Barnes方案的平滑参数和迭代总数的选择。
英文摘要：
A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for optimal design of LiDAR scans and retrieval of the velocity statistical moments is proposed. The LiSBOA represents an adaptation of the classical Barnes scheme for the statistical analysis of unstructured experimental data in N-dimensional spaces and it is a suitable technique for the evaluation over a structured Cartesian grid of the statistics of scalar fields sampled through scanning LiDARs. The LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. This revisited theoretical framework for the Barnes objective analysis enables the formulation of guidelines for optimal design of LiDAR experiments and efficient application of the LiSBOA for the post-processing of LiDAR measurements. The optimal design of LiDAR scans is formulated as a two cost-function optimization problem including the minimization of the percentage of the measurement volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field. The optimal design of the LiDAR scans also guides the selection of the smoothing parameter and the total number of iterations to use for the Barnes scheme.
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