基于时差和聚类算法的闪电定位方法

闪电的监测与定位对减少雷电灾害具有重要的意义,定位精度是闪电定位系统的关键指标。 针对传统定位方法的定位 精度受到数据粗差、站网布局影响大的问题,提出一种基于时差和聚类算法的定位方法。 基于到达时间差原理对闪电定位数据 进行组合定位,采用 K-means 对组合定位数值进行分类并剔除离群点得到最终精确定位值。 以江苏省闪电探测网为例,定量研 究了区域内定位误差的数值分布、测时精度和站网布局对定位误差的影响。 结果表明,相对传统的到达时间差方法,该方法计 算的区域定位误差由 5 km 减小为 2 km;四站定位的均方根误差由 0. 89 km 减少为 0. 07 km;定位误差受到测时误差的急剧增 加变为缓慢增加,且网站布局对定位误差的影响明显减小。

Lightning location method based on time difference and clustering algorithm

The lightning monitoring and location are of great significance to reduce the lightning disaster, and the location accuracy is the key index of the lightning location system. Aiming at the problem that the positioning accuracy of traditional positioning methods is greatly affected by gross error of data and station network layout, a positioning method based on time difference and clustering algorithm is proposed. The lightning positioning data is combined based on the principle of time difference of arrival, K-means clustering algorithm is used to classify the combined positioning values and remove outliers to obtain the final accurate positioning value. Taking the lightning detection network in Jiangsu Province as an example, the numerical distribution of location error, the time measurement accuracy and the influence of station network layout on the location error are quantitatively studied. The results show that compared with the traditional arrival time difference method, the regional positioning error calculated by this method is reduced from 5 km to 2 km; The root mean square error of four station positioning is reduced from 0. 89 km to 0. 07 km; The location error is slowly increased due to the sharp increase of the time measurement error, and the impact of website layout on the location error is significantly reduced.