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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。
Lidar near field echo signal is strong, easy to make the photon counting system data stack phenomenon, and dead time is an important factor to correct the data stack. A mathematic model of space variance for photon counting data profile of laser radar is constructed to evaluate the Poisson distribution quality of photon counting data. The results of the calculation and analysis are used to estimate the dead time of the laser photon counting system, and then the data of the data in the photon counting data is corrected. The calculation results show that the far-field laser radar signal basically conforms to the Poisson distribution, but the near-field signal does not accord with this method. However, the Poisson distribution of the photon counting data with dead-time correction can be significantly improved. By minimizing the deviation of the data variance from the mean, the system dead time is estimated to correct the data stack phenomenon, maximizing the photon count data to follow the Poisson distribution. The results show that the dead time of the TR40-160 photon counting system of the Licel data logger used in the long-range scanning Lidar system is about 3.402ns, and the corrected data stack of the Lidar has been significantly improved.