A ground lightning ground point identification system and method

Abstract

The present invention discloses a ground lightning ground point identification system and method. The method eliminates the return points whose semi-major axis SMA is greater than a set threshold, and calculates the sum of the distances between all the return points and the semi-major axis SMA in the positioning results after the error points are eliminated to obtain the distance vector and the semi-major axis vector; the comparison results of the distance vector and the semi-major axis vector are grouped; the grouped positioning results are clustered and analyzed by a clustering method to obtain the center point coordinates and the sum of the cluster grouping distances d total ; Select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates.

Description

Technical Field

[0001] The present invention relates to a ground-to-ground lightning grounding point identification system and method, and in particular to a ground-to-ground lightning grounding point identification method based on lightning location data and using error ellipse analysis and k-means clustering. Background Art

[0002] The phenomenon of lightning ground flash discharge with multiple return strokes and multiple grounding points. According to statistics, negative ground flashes have an average of 3-5 return strokes, and 80%-90% of negative ground flashes have multiple return strokes. Most positive ground flashes have single return strokes, and only 10% of positive ground flashes have multiple return strokes. The maximum number of return strokes of negative ground flashes recorded so far is 26. Multiple return strokes of ground flashes may hit the same position on the ground along the same discharge channel, or they may hit different positions on the ground along different discharge channels. Ground flashes with multiple grounding positions in the same ground flash are called multiple ground contacts cloud-to-ground lightning.

[0003] The multiple return strokes of ground lightning are a form of charge release from thunderstorm clouds to the ground. After the first return stroke occurs, the charged cloud particles in the thunderstorm cloud are reorganized and adjusted under the combined action of airflow and electric field forces, forming a new charge structure around the discharge channel. When the conditions are right, subsequent return strokes occur. Whether the subsequent return strokes can discharge along the first return stroke channel is related to the above-mentioned reorganization and adjustment time interval and the thunderstorm cloud's ability to supplement the charge of the discharge channel, as well as the connection leaders developed on the ground. Therefore, the multiple return strokes and multiple grounding point discharge characteristics of ground lightning are determined by the combined action of thunderstorm climate characteristics and underlying surface characteristics, and vary from region to region.

[0004] Understanding the discharge characteristics of multiple return strokes and multiple grounding points of ground lightning can more accurately assess the spatiotemporal distribution of lightning strike risks, which is beneficial to lightning fault analysis and lightning protection design of target objects. At present, scholars at home and abroad have carried out some related research work. Thottappillil et al. observed 22 ground lightning strikes (33 return strokes in total) in Florida, USA with a camera, and found that their strike locations were 0.3km-7.3km apart, with a geometric mean of 1.7km. Kong et al. observed multiple return stroke ground lightning strikes in Qinghai and Guangdong using a high-speed camera, and the return stroke distance interval was 0.2km-1.9km. Stall et al. analyzed the characteristics of ground lightning strikes at multiple grounding points in Arizona, USA based on video recordings and data from the National Lightning Location Network of the United States. The analysis results of 59 sets of data showed that the average distance between different grounding points of negative ground lightning strikes was 2.3km, the standard deviation was 1.7km, and the median was 2.1km.

[0005] The lightning location system can locate the occurrence time and ground-to-ground position of each return stroke of ground lightning, with a positioning accuracy of less than 1 km, and less than 200 m in high-precision coverage areas. At present, the collection of return strokes to ground lightning has been realized by using a specific time and space window, so as to better distinguish the first return stroke from subsequent return strokes. Considering the current positioning accuracy level of the lightning location system and the characteristics of ground lightning with multiple grounding points, the lightning location system can theoretically also be used to identify the locations of multiple grounding points of ground lightning. Summary of the invention

[0006] The purpose of the present invention is to provide a ground-to-ground lightning grounding point identification system and method, based on the positioning principle of the lightning location system, using error ellipse analysis and k-means clustering, to identify ground-to-ground lightning multiple grounding points through lightning location data. The method of the present invention is expected to realize the automatic acquisition of the coordinates of multiple grounding points of ground lightning, which can provide support for the refined ground-to-ground lightning spatial distribution analysis and lightning disaster accident analysis and judgment. By improving the time series retrieval algorithm, the distribution network data retrieval needs can be better met.

[0007] To achieve this purpose, the present invention designs a ground lightning ground point identification system, including a positioning result error point elimination module, a positioning result grouping module, a positioning result clustering module and a ground point identification module; the positioning result error point elimination module adopts a semi-major axis SMA threshold setting method to obtain m positioning results after eliminating the error points; the positioning result grouping module is used to calculate the distance vector and the semi-major axis vector of the m positioning results output by the positioning result error point elimination module, and group the m positioning results according to the comparison result of the distance vector and the semi-major axis vector to obtain n types of grouped positioning results; the positioning result clustering module adopts a clustering method to perform cluster analysis on the n types of grouped positioning results output by the positioning result grouping module to obtain n types of center point coordinates and the sum of cluster group distances d total The ground point identification module compares the sum of the n clustering grouping distances d output by the positioning result clustering module total , select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates.

[0008] A method for identifying a ground lightning ground point comprises the following steps:

[0009] Step 1, using the semi-major axis SMA threshold setting method to obtain m positioning results after eliminating error points;

[0010] Step 2, calculating the distance vectors and semi-major axis vectors of the m positioning results output in step 1, and grouping the m positioning results according to the comparison results of the distance vectors and the semi-major axis vectors to obtain n types of grouped positioning results;

[0011] Step 3: Use clustering method to perform cluster analysis on the n types of group positioning results output in step 2 to obtain the sum of n center point coordinates and cluster group distances d total ;

[0012] Step 4: Compare the sum of the distances d of the n clustering groups output in step 3 total , select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates.

[0013] The beneficial effects of the present invention are as follows: the present invention automatically clusters and distinguishes grounding points and extracts the coordinates of grounding points based on the return stroke position, semi-major axis of error ellipse and other parameters provided by lightning location data, without visualizing the return stroke point, thereby realizing the automatic identification of ground-to-ground lightning grounding points based on lightning location system data and the automatic acquisition of the coordinates of multiple grounding points of ground-to-ground lightning, which can provide support for refined ground-to-ground lightning spatial distribution analysis and lightning disaster accident analysis and judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a system structure diagram of the present invention;

[0015] Figure 2 is a schematic diagram of an error ellipse according to an embodiment of the present invention;

[0016] Figure 3 is a flow chart of the method of the present invention;

[0017] Figure 4 A schematic diagram of a return strike positioning position and a 50% error ellipse according to an embodiment of the present invention;

[0018] Figure 5 This is a schematic diagram of the grouping of 12 responses when k is 1 to 5 according to an embodiment of the present invention;

[0019] Figure 6 Schematic diagram of three types of multiple grounding point identification results according to an embodiment of the present invention;

[0020] Among them, 1-positioning result error point elimination module, 2-positioning result grouping module, 3-positioning result clustering module and 4-grounding point identification module. DETAILED DESCRIPTION

[0021] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0022] A ground lightning ground point identification system, such as Figure 1 As shown, it includes a positioning result error point elimination module 1, a positioning result grouping module 2, a positioning result clustering module 3 and a grounding point identification module 4;

[0023] The positioning result error point elimination module 1 adopts the method of setting the semi-major axis SMA threshold to obtain m positioning results after eliminating the error points; the method of setting the semi-major axis SMA threshold of the positioning result error point elimination module 1 is: calculating the semi-major axis SMA of the confidence error ellipse of each hit point in the positioning result to be analyzed, and eliminating the hit points whose semi-major axis SMA is greater than the set threshold s, in this embodiment, s is preferably 10km, and in this embodiment, the confidence error ellipse is preferably a 50% confidence error ellipse;

[0024] The positioning result grouping module 2 is used to calculate the distance vector and the semi-major axis vector of the m positioning results output by the positioning result error point elimination module 1, and group the m positioning results according to the comparison results of the distance vector and the semi-major axis vector to obtain n types of grouped positioning results;

[0025] The positioning result grouping module 2 is used to calculate the distance d between all the hit points in the m positioning results output by the positioning result error point elimination module 1. ij , d ij is the distance between the ith hit point and the jth hit point in the m positioning results, and finally the distance vector D = (d ij ) m×m At the same time, the sum of the semi-major axes SMA between all the hit points in the m positioning results output by the positioning result error point elimination module 1 is calculated s ij ,s ij is the sum of the semi-major axis SMA between the ith hit point and the jth hit point in the m positioning results. Finally, the semi-major axis vector S = (s ij ) m×m According to formula d ij ≤k·s ij , where k is the adjustment coefficient, compared with d ij With s ij And grouping is performed according to the comparison results, where k = 1, 2, 3, ..., n, and finally n types of grouping positioning results can be obtained;

[0026] The positioning result clustering module 3 uses a clustering method to perform cluster analysis on the n types of grouped positioning results output by the positioning result grouping module 2 to obtain the sum of the n types of center point coordinates and cluster grouping distances d total ,In this embodiment, the k-means clustering method is selected;

[0027] The ground point identification module 4 compares the sum of the n clustering grouping distances d output by the positioning result clustering module 3 total , select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates.

[0028] In the above technical solution, the method for calculating the semi-major axis SMA of the hit point confidence error ellipse by the positioning result error point elimination module 1 comprises the following steps:

[0029] The location and time of the ground lightning strike backstroke finally located by the lightning location system are somewhat different from the actual situation. If a strike backpoint in the location result is X = (t, x, y), where t represents the time of occurrence of the strike backpoint, x represents the longitude coordinate of the strike backpoint, and y represents the latitude coordinate of the strike backpoint, then the distribution of the longitude coordinate x and latitude coordinate y of the strike backpoint obeys the probability density function f(x, y):

[0030]

[0031] in, is the expectation of x, is the expectation of y, and ρ is the correlation coefficient:

[0032]

[0033] σ xy , σ x and σ y It is calculated by the covariance matrix A of the position variable. The calculation formula of the covariance matrix A is:

[0034]

[0035] The covariance matrix A is obtained when the lightning location system performs a location operation;

[0036] The error ellipse is the surface contour of the probability density function f(x, y), that is, f(x, y) = C; when C = 0.5, the 50% confidence error ellipse is obtained, and the semi-major axis and semi-minor axis of the standard error ellipse are calculated by the following formula:

[0037]

[0038] The angle between the major axis of the error ellipse and the x-axis of the coordinate system is calculated by the following formula:

[0039]

[0040] When C = 0.5, the 50% confidence error ellipse is obtained, and its semi-major axis and semi-minor axis are 1.1774 times that of the standard error ellipse, while the semi-major axis and semi-minor axis of the 95% error ellipse are 2.4477 times that of the standard error ellipse;

[0041] Randomly generate two sets of normally distributed series, x~N(-0.22,6.57), y~N(-0.12,1.050, both of which contain 221 elements. Use (x,y) to represent the plane point set, and use the above method to calculate the standard error ellipse, 50% error ellipse and 95% error ellipse, as shown in the following figure: Figure 2 shown.

[0042] In the above technical solution, the distance vector calculation method in the positioning result grouping module 2 is: calculate the distance d between all the hit points in the m positioning results output by the positioning result error point elimination module 1 ij , d ij is the distance between the ith hit point and the jth hit point in the m positioning results, and finally the distance vector D = (d ij ) m×m ;

[0043] The calculation method of the semi-major axis vector in the positioning result grouping module 2 is: calculate the sum s of the semi-major axis SMA between all the return points in the m positioning results output by the positioning result error point elimination module 1 ij , the ij is the sum of the semi-major axis SMA between the ith hit point and the jth hit point in the m positioning results. Finally, the semi-major axis vector S = (s ij ) m×m .

[0044] In the above technical solution, the specific method of the positioning result grouping module 2 to obtain n types of grouped positioning results is:

[0045] Compare the distance vector D and the semi-major axis vector S to each corresponding value d ij and ij , if the formula d is satisfied ij ≤k·s ij , then the corresponding reply numbers i and j are extracted to form a reply number pool. If there is an identical reply number in the reply number pool, the reply points with the identical reply number are grouped into one group, and the other reply points without the identical reply number are grouped into another group, where k is the adjustment coefficient, k = 1, 2, 3, …, n.

[0046] In the above technical solution, the value of n in the adjustment coefficient k in the positioning result grouping module 2 includes two cases:

[0047] When ∑D>∑S, Among them, round(.) indicates rounding operation;

[0048] When ∑D≤∑S, n=1;

[0049] Considering that the distance between return strokes is generally no more than 10 km, and the positioning error is generally in the order of hundreds of meters when the performance of the wide-area lightning location system is good, the value range of n is n≤20.

[0050] In the above technical solution, the method by which the positioning result clustering module 3 performs cluster analysis on each grouped positioning result to be clustered and analyzed output by the positioning result grouping module 2 is:

[0051] Assume that the grouping location results to be clustered include x groups, select the hit point with the smallest semi-major axis SMA in each group as the cluster seed of each group, use the k-means clustering method to calculate the coordinates of the center point of each group, and calculate the sum of the distances d from each hit point in each group to the center point group , get the sum of the distances of the x groups d group , sum the distances of the x groups d group Add up to get the total distance d of cluster grouping total .

[0052] A method for identifying the ground lightning ground point, such as Figure 3 As shown, the following steps are included:

[0053] Step 1, using the semi-major axis SMA threshold setting method to obtain m positioning results after eliminating error points;

[0054] Step 2, calculating the distance vectors and semi-major axis vectors of the m positioning results output in step 1, and grouping the m positioning results according to the comparison results of the distance vectors and the semi-major axis vectors to obtain n types of grouped positioning results;

[0055] Step 3: Use clustering method to perform cluster analysis on the n types of group positioning results output in step 2 to obtain the sum of n center point coordinates and cluster group distances d total ;

[0056] Step 4: Compare the sum of the distances d of the n clustering groups output in step 3 total , select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates.

[0057] Taking a 12-stroke negative ground lightning located by the wide-area lightning location system of my country's power grid as an example, the grounding point identification is carried out. Table 1 lists the detailed information of the 12 strokes. Figure 4 Twelve hitbacks are shown with corresponding 50% confidence error ellipses.

[0058] Table 1 The results of locating the return strokes of a 12-return negative ground lightning by the wide-area lightning location system of the power grid

[0059]

[0060] Calculate the distance d between each hit point ij , the sum of the semi-major axes s ij , we get the distance vector D and vector S. After calculation, In order to better compare and analyze the differences in clustering results caused by different grouping methods, n is set to 5.

[0061] When the sum of the distance between two return shots and the semi-major axis satisfies the relation d ij ≤k·s ij When , it is considered that there is a "connection" between the i-th response and the j-th response, and they can be grouped together. Figure 5 The figure shows the grouping of 12 responses when k is 1 to 5. It can be seen from the figure that when k = 1 or 2, the 12 responses are divided into 3 groups; when k = 3 or 4, the 12 responses are divided into 2 groups; when k = 5, the 12 responses are divided into 1 group. When k>5, it will be the same as when k = 5, and all 12 responses will be divided into 1 group.

[0062] After the grouping is completed, the number of groups is calculated, and the return position with the smallest positioning error in each group is used as the cluster "seed", which is used as the input condition of the k-means cluster analysis to obtain the clustering result.

[0063] Table 2 lists the clustering results obtained by this method when k is adjusted from 1 to 5, including the number of grounding points, grounding point coordinates, and total distance d total .

[0064] Table 2 Ground point identification results when k is 1 to 5

[0065]

[0066] As can be seen from Table 2, when k is 1 or 2, 3 grounding points can be clustered, and the sum of the distances from the return shots of each group to the grounding point coordinates is 5.4 km; when k increases to 3 or 4, the number of grounding points decreases to 2, and the sum of the distances increases to 20.38 km; when k further increases to 5, 12 return shots are considered to have all hit the same grounding point, and the sum of the distances increases to 31.55 km. When k is greater than 5, the clustering result will be the same as when k is 5 because the grouping situation remains unchanged. Based on the screening principle of the minimum sum of distances, the identification result when k is 1 or 2 is selected as the final result.

[0067] Figure 6 Three types of multiple ground point identification results are shown. Figure 6 (a) The identification results, combined with Figure 3It can be seen that the first four of the 12 return hits hit the same grounding point, the fifth hit a single grounding point, and the next seven hits hit the third grounding point. The distances between the three grounding points are 7.8km, 7.6km, and 3.2km, respectively, which is consistent with the existing observations of multiple grounding points.

[0068] The contents not described in detail in this specification belong to the prior art known to those skilled in the art. It should be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0069] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0070] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0071] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims of the invention.

Claims

1. A lightning ground point identification system, characterized by: include: A positioning result error point elimination module (1), a positioning result grouping module (2), a positioning result clustering module (3) and a grounding point identification module (4); The positioning result error point elimination module (1) adopts a semi-major axis (SMA) threshold setting method to obtain m positioning results after eliminating error points; The positioning result grouping module (2) is used to calculate the distance vectors and semi-major axis vectors of the m positioning results output by the positioning result error point elimination module (1), and group the m positioning results according to the comparison results of the distance vectors and the semi-major axis vectors to obtain n types of grouped positioning results; The positioning result clustering module (3) uses a clustering method to perform cluster analysis on the n types of grouped positioning results output by the positioning result grouping module (2) to obtain the n types of center point coordinates and the sum of cluster grouping distances d total ; The ground point identification module (4) compares the sum of the n types of cluster grouping distances d output by the positioning result clustering module (3) total , select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates; The method for setting the semi-major axis SMA threshold of the positioning result error point elimination module (1) is: calculating the semi-major axis SMA of the confidence error ellipse of each hit point in the positioning result to be analyzed, and eliminating the hit points whose semi-major axis SMA is greater than the set threshold s; The calculation method of the distance vector in the positioning result grouping module (2) is as follows: the distance d between each pair of all the hit points in the m positioning results output by the positioning result error point elimination module (1) is calculated. ij , d ij is the distance between the ith hit point and the jth hit point in the m positioning results, and finally the distance vector D = (d ij ) m×m ; The method for calculating the semi-major axis magnitude in the positioning result grouping module (2) is as follows: the sum s of the semi-major axis SMA between all the return points in the m positioning results output by the positioning result error point elimination module (1) is calculated. ij , the ij is the sum of the semi-major axis SMA between the ith hit point and the jth hit point in the m positioning results. Finally, the semi-major axis vector S = (s ij ) m×m ; The method for the positioning result grouping module (2) to obtain n types of grouped positioning results is: Compare the distance vector D and the semi-major axis vector S to each corresponding value d ij and ij , if the formula d is satisfied ij ≤k·s ij , then the corresponding reply numbers i and j are extracted to form a reply number pool. If there is an identical reply number in the reply number pool, the reply points with the identical reply number are grouped into one group, and the other reply points without the identical reply number are grouped into another group, where k is the adjustment coefficient, k = 1, 2, 3, …, n.

2. A lightning ground point identification system according to claim 1, characterized in that: The method for calculating the semi-major axis SMA of the return point confidence error ellipse includes the following steps: A hit point in the positioning result to be analyzed is X=(t,x,y), where t represents the occurrence time of the hit point, x represents the longitude coordinate of the hit point, and y represents the latitude coordinate of the hit point. The distribution of the longitude coordinate x and the latitude coordinate y of the hit point obeys the probability density function f(x,y): in, is the expectation of x, is the expectation of y, and ρ is the correlation coefficient: σ xy , σ x and σ y It is calculated by the covariance matrix A of the position variable. The calculation formula of the covariance matrix A is: The covariance matrix A is obtained when the lightning location system performs a location operation; The error ellipse is the surface contour of the probability density function f(x, y) = C, and the semi-major axis of the standard error ellipse is calculated by the following formula:

3. A lightning ground point identification system according to claim 1, characterized in that: The value of n in the adjustment coefficient k in the positioning result grouping module (2) includes two cases: When ∑D>∑S, Among them, round(.) indicates rounding operation; When ∑D≤∑S, n=1.

4. A lightning ground point identification system according to claim 1, characterized in that: The method by which the positioning result clustering module (3) performs cluster analysis on each grouped positioning result to be clustered and analyzed output by the positioning result grouping module (2) is as follows: The grouping positioning results to be clustered include x groups. The hit point with the smallest semi-major axis SMA in each group is selected as the cluster seed of each group. The center point coordinates of each group are calculated using the clustering method, and the sum of the distances d from each hit point in each group to the center point is calculated. group , get the sum of the distances of the x groups d group , sum the distances of the x groups d group Add up to get the total distance d of cluster grouping total .

5. A method for identifying ground lightning ground points based on the system of claim 1, characterized in that: It includes the following steps: Step 1, using the semi-major axis SMA threshold setting method to obtain m positioning results after eliminating error points; Step 2, calculating the distance vectors and semi-major axis vectors of the m positioning results output in step 1, and grouping the m positioning results according to the comparison results of the distance vectors and the semi-major axis vectors to obtain n types of grouped positioning results; Step 3: Use clustering method to perform cluster analysis on the n types of group positioning results output in step 2 to obtain the sum of n center point coordinates and cluster group distances d total ; Step 4: Compare the sum of the distances d of the n clustering groups output in step 3 total , select the sum of cluster grouping distances d total The smallest grouping clustering solution is the final clustering result, and the center point coordinates corresponding to the final clustering result are determined as the grounding point coordinates.

6. A method for identifying ground lightning ground points according to claim 5, characterized in that: The method for setting the semi-major axis SMA threshold in step 1 is: calculating the semi-major axis SMA of the confidence error ellipse of each hit point in the positioning result to be analyzed, and eliminating the hit points whose semi-major axis SMA is greater than the set threshold s; The method for calculating the semi-major axis SMA of the hit point confidence error ellipse comprises the following steps: A hit point in the positioning result to be analyzed is X=(t,x,y), where t represents the occurrence time of the hit point, x represents the longitude coordinate of the hit point, and y represents the latitude coordinate of the hit point. The distribution of the longitude coordinate x and the latitude coordinate y of the hit point obeys the probability density function f(x,y): in, is the expectation of x, is the expectation of y, and ρ is the correlation coefficient: σ xy , σ x and σ y It is calculated by the covariance matrix A of the position variable. The calculation formula of the covariance matrix A is: The covariance matrix A is obtained when the lightning location system performs a location operation; The error ellipse is the surface contour of the probability density function f(x, y) = C. When C = 0.5, a 50% confidence error ellipse is obtained. The semi-major axis of the standard error ellipse is calculated by the following formula:

7. A method for identifying ground lightning ground points according to claim 5, characterized in that: The distance vector calculation method in step 2 is: calculate the distance d between all the hit points in the m positioning results output in step 1 ij , d ij is the distance between the ith hit point and the jth hit point in the m positioning results, and finally the distance vector D = (d ij ) m×m ; The method for calculating the semi-major axis vector in step 2 is: calculate the sum s of the semi-major axis SMA between all the return points in the m positioning results output in step 1 ij , the ij is the sum of the semi-major axis SMA between the ith hit point and the jth hit point in the m positioning results. Finally, the semi-major axis vector S = (s ij ) m×m ; The method for obtaining n types of group positioning results in step 2 is: Compare the distance vector D and the semi-major axis vector S to each corresponding value d ij and ij , if the formula d is satisfied ij ≤k·s ij , then the corresponding reply numbers i and j are extracted to form a reply number pool. If there is an identical reply number in the reply number pool, the reply points with the identical reply number are grouped into one group, and the other reply points without the identical reply number are grouped into another group, where k is the adjustment coefficient, k = 1, 2, 3, …, n.

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