Liang Li, Lei Yong, Zhang Shuaichi, et al. Lightning location algorithm based on DBSCAN and grid search. J Appl Meteor Sci, 2019, 30(3): 267-278. DOI:  10.11898/1001-7313.20190302.
Citation: Liang Li, Lei Yong, Zhang Shuaichi, et al. Lightning location algorithm based on DBSCAN and grid search. J Appl Meteor Sci, 2019, 30(3): 267-278. DOI:  10.11898/1001-7313.20190302.

Lightning Location Algorithm Based on DBSCAN and Grid Search

DOI: 10.11898/1001-7313.20190302
  • Received Date: 2018-12-06
  • Rev Recd Date: 2019-03-14
  • Publish Date: 2019-05-31
  • Lightning location system can monitor the time and location of lightning in real time, supporting disaster early warning and post-disaster treatment in meteorology, power, aerospace, forest fire prevention and other fields. The location algorithm directly affects the accuracy of lightning detection results. Traditional location algorithms may often fall into the local optimum and needs a large amount of calculation. The practical application is limited by the computer capability and the anti-error interference ability is poor. A new lightning location algorithm DG-LLA (DBSCAN and Grid-Search Lighting Location Algorithm) is proposed. The algorithm is verified by a lightning accident example and regional simulation, and then by locating historical data detected in the national lightning monitoring network. The performance of the new algorithm is compared and further analyzed from three aspects:Lightning frequency temporal distribution, lightning spatial distribution and regional spatial distribution.Simulation results of lightning example show that the location error of TDOA (time difference of arrival) method is the largest, reaching 1314 m. Taylor series expansion method is a classical iterative algorithm with an error of 881 m. The error of proposed DG-LLA algorithm is significantly reduced to 84 m. Examples of artificial lightning initiation show that the new algorithm DG-LLA is more accurate than the national lightning monitoring network, and the average location error is 32.2% lower than operational network. Lightning location algorithm based on adaptive DBSCAN and grid-search optimization can effectively identify noise data and enhance the ability of anti-error interference. Regional simulation result shows that TDOA method and Taylor series expansion method have large positioning errors, with the RMSE (root mean square error) of 982 m and 668 m, respectively. When DBSCAN is added to location, the RMSE is significantly reduced to 406 m. After DBSCAN and grid search are added, the RMSE is further reduced to 349 m. Lightning location algorithm based on adaptive DBSCAN and grid search optimization improves the local searching ability and global searching ability of space and overcomes shortcomings of traditional iterative algorithm, such as easy divergence and local optimum of optimization algorithm, and solve the lightning strike point stably and accurately, and it performances better than operational network. The utilization rate of return data increases from 43.4% to 51.5%. The radar echo around new locations has stronger characteristics and higher locating accuracy. It provides a new method for lightning location.
  • Fig. 1  Flow of DG-LLA algorithm

    Fig. 2  Clustering results of lightning case

    Fig. 3  Comparison of location error distribution

    (a)TDOA method, (b)Taylor series expansion method, (c)DBSCAN, (d)DG-LLA

    Fig. 4  Root mean square error of lightning location and time standard deviation

    Fig. 5  Daily distribution of cloud-to-ground lightning on 1 Aug 2018

    (a)positive cloud-to-ground lightning, (b)negative cloud-to-ground lightning

    Fig. 6  Distribution of positive cloud-to-ground lightning on 1 Aug 2018

    (a)national lightning monitoring network, (b)DG-LLA

    Fig. 7  Distribution of negative cloud-to-ground lightning on 1 Aug 2018

    (a)national lightning monitoring network, (b)DG-LLA

    Fig. 8  Distribution of cloud-to-ground lightning in Hubei during 0900-1600 BT 1 Aug 2018

    Fig. 9  Cloud-to-ground lightning location results and radar combined reflectivity factor in Hubei on 1 Aug 2018

    Table  1  Comparison of location results of artificially triggered lightning return stroke

    闪电 到达时间/s 探测站大地坐标 国家雷电监测网 DG-LLA
    定位结果 误差/m 定位结果 误差/m
    1 0.0857547 23.183°N,114.288°E 23.640°N, 113.594°E 133.58 23.638°N, 113.596°E 66.79
    0.0858466 24.670°N,113.608°E
    0.0858582 23.630°N,112.435°E
    0.0859659 22.275°N,113.567°E
    2 0.6785874 23.630°N,112.435°E 23.637°N, 113.416°E 204.38 23.637°N, 113.563°E 156.69
    0.6785959 23.183°N,114.288°E
    0.6786434 24.670°N,113.608°E
    0.6787589 22.275°N,113.567°E
    0.6789672 24.423°N,111.508°E
    3 0.4382787 23.1833°N,114.2880°E 23.640°N,113.595°E 122.45 23.638°N, 113.596°E 89.06
    0.4383708 24.6704°N,113.6080°E
    0.4383826 23.6304°N,112.4349°E
    0.4384902 22.2750°N,113.5670°E
    DownLoad: Download CSV

    Table  2  Comparison of location under different number of stations

    探测站数量 国家雷电监测网 DG-LLA
    定位
    数量
    参与定位回击
    数据数量
    定位结果与探测站
    间的平均距离/km
    定位
    数量
    参与定位回
    击数据数量
    定位结果与探测站
    的平均距离/km
    3站 26604 79812 159.66 37610 112830 148.26
    4站 18594 74376 183.45 25275 101100 172.16
    4站以上 60042 306210 271.21 69018 414108 242.23
    DownLoad: Download CSV

    Table  3  Comparison of regional radar combination reflectivity factor in Hubei on 1 Aug 2018

    时间 区域范围 组合反射率因子
    平均值/dBZ
    定位结果次数
    国家雷电监测网 DG-LLA
    09:10 29°~30°N, 109°~110°E 19.8 4 8
    10:40 29°~30°N, 110°~111°E 20.6 1 10
    11:50 29°~30°N, 109°~110°E 15.2 7 16
    14:20 29°~30°N, 113°~114°E 42.7 12 45
    15:10 29°~30°N, 110°~111°E 26.5 6 23
    15:40 29°~30°N, 110°~111°E 32.3 4 18
    DownLoad: Download CSV
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    • Received : 2018-12-06
    • Accepted : 2019-03-14
    • Published : 2019-05-31

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