论文标题
Lisboa：激光雷达统计Barnes目标分析，用于激光扫描的最佳设计和检索风统计。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
论文作者
论文摘要
提出了激光统计BARNES目标分析（LisboA），用于最佳的激光扫描和检索速度统计矩。利斯博亚代表了经典的Barnes方案的适应，用于对N维空间中非结构化实验数据进行统计分析，这是对通过扫描LIDARS采样标量字段的结构化笛卡尔网格进行评估的合适技术。通过应用于合成速度场的蒙特卡洛方法，对里斯本进行了验证和表征。这重新审视了Barnes目标分析的理论框架，可以制定制定LIDAR实验的最佳设计准则，并有效地应用Lisboa在LIDAR测量后进行后处理。 LIDAR扫描的最佳设计被配制为两个成本功能优化问题，包括最小化未用足够的空间分辨率对测量量的百分比最小化，以及在速度场平均值上的误差最小化。 LiDAR扫描的最佳设计还指导了平滑参数的选择以及用于Barnes方案的迭代总数。
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.
