空间方差构建在激光雷达光子计数数据堆栈修正中的应用

Application of Spatial Variance Construction in Correction of Pile-Up Effects of Lidar Photon-Counting Data

激光雷达近场回波信号较强,容易使光子计数系统产生数据堆栈现象,而死区时间是修正数据堆栈的重要因子。构建了一种激光雷达光子计数数据廓线的空间方差数学计算模型,用于评价光子计数数据的泊松分布质量。利用计算分析结果估算激光雷达光子计数系统死区时间,进而修正光子计数数据中遭受数据堆栈的数据。计算结果表明,激光雷达远场信号基本符合泊松分布,而近场信号不符合,但是死区时间修正后的光子计数数据的泊松分布特性可得到明显改善。通过最小化数据方差与均值的偏离程度,估算系统死区时间以修正数据堆栈现象,使得光子计数数据最大化地服从泊松分布。研究结果表明,长距离扫描激光雷达系统所应用的Licel数据记录仪TR40-160光子计数系统的死区时间约为3.402ns,修正后的激光雷达数据堆栈现象得到明显改善。

Due to the strong intensity of lidar return signal in the near field,the photon-counting system in lidar applications suffers from the pile-up effect,which can be corrected by the parameter of dead time.A mathematical model is constructed to calculate the spatial variance,which is used to evaluate the quality of Poisson distribution of lidar data.Furthermore,the analysis results of the spatial variance are utilized to estimate the dead time of the lidar photon-counting system and to correct the pile-up effect.The calculation results indicate that the photon-counting data in the far field of lidar conforms to the Poisson distribution,but the data in the near field does not.However,the Poisson distribution characteristic of the photon-counting data can be improved notably by the dead time correction.Therefore,the system dead time can be estimated by minimizing the deviation between the variance and the mean of lidar data.One can correct the pile-up effect of photon-counting data and make the data profile conform to the Poisson distribution at the maximum degree.The results show that the dead time of the photon-counting system in Licel transient recorder TR40-160 is approximately 3.402 ns,which is estimated by using the photon-counting data in the application of long-range scanning lidar.The pile-up effect in the presented photon-counting data is improved obviously.