On-line data transmission implementation tracking monitoring ground positioning system

Abstract

The invention relates to data transmission tracking and positioning, in particular to an on-line data transmission implementation tracking monitoring ground positioning system, which comprises the following steps of: determining positioning data sources of a terminal side, a network side and an associated identifier, acquiring and preprocessing original data, and generating a clean positioning data set; associating the transmission state data, extracting indexes with geographic tags, and obtaining a time-space aggregation index data set through time-space aggregation; the method comprises the following steps of: matching the data to a GIS (Geographic Information System), marking nodes, drawing links, and constructing and optimizing a topology model; establishing a link segmentation rule, dividing segments, matching indexes, analyzing association and marking an exception generation record table; and screening and sorting abnormal segments based on a record table, refining a range, speculating inducements, locking the range, and collecting and accurately positioning abnormal points on site. According to the invention, deep fusion from data to geographic space is realized, the accuracy and efficiency of online data transmission tracking monitoring and abnormal positioning are improved, and the problems of data fragmentation and fuzzy positioning are solved.

Description

Technical Field

[0001] This invention relates to a data transmission tracking and positioning system, specifically an online data transmission implementation tracking and monitoring ground positioning system. Background Technology

[0002] In online data transmission, ground-based positioning and tracking monitoring are crucial for ensuring data security and efficient transmission. Traditional technologies suffer from problems such as data fragmentation and ambiguous positioning, making it difficult to accurately pinpoint anomalies.

[0003] With the development of the digital economy, the requirements for data transmission stability in scenarios such as the industrial internet and government cloud have increased dramatically. Once a transmission anomaly occurs, it can easily cause significant losses. By integrating multi-source data and constructing a geographic topology model, a coherent process from data collection to anomaly location can be realized, providing support for rapid fault diagnosis and transmission path optimization. This is of great significance for ensuring the continuity of critical business and improving the reliability of data transmission. Therefore, there is an urgent need for an online data transmission implementation tracking and monitoring ground positioning system that combines the above methods. Summary of the Invention

[0004] The purpose of this invention is to address the problems existing in the background technology by proposing an online data transmission implementation tracking and monitoring ground positioning system.

[0005] The technical solution of the present invention: an online data transmission implementation tracking and monitoring ground positioning system, comprising:

[0006] S1. Determine the key positioning data sources, identify the terminal side, network side and associated identification data and form a list, collect raw positioning data in real time and preprocess it to generate a clean positioning dataset.

[0007] S2. Based on the clean location dataset, correlate the transmission status data, extract geographically labeled indicators and supplement features hierarchically. After spatiotemporal aggregation and anomaly verification, a spatiotemporal aggregated indicator dataset is formed for building a topology model.

[0008] S3. Adapt the spatiotemporal aggregation index dataset to the GIS system, extract and label transmission nodes, draw the geographical path of the transmission link, and integrate, construct, and verify the optimized topology model.

[0009] S4. First, formulate link segmentation rules and boundaries based on the geographic transmission path topology model, then divide the link into segments and record information, match transmission indicators with segments; analyze the correlation between geographic and indicator characteristics, set thresholds and mark anomalies based on the set thresholds, and generate an anomaly record table.

[0010] S5. Based on the abnormal record table, filter and sort abnormal segments, refine the scope by combining their geographical information, infer the cause based on the correlation between geography and indicators, lock the range of abnormal points, and finally accurately locate the abnormal points through on-site collection.

[0011] Preferably, S1 includes:

[0012] S11. Based on the carrier of online data transmission, identify the location-related data sources that need to be collected, and obtain a list of location data sources, including the type and collection interface of each data source;

[0013] S12. Based on the data sources and interfaces in the list, collect raw data in real time or near real time using automated tools to obtain the raw location dataset; where the automated tools can be, for example, data collection scripts or IoT gateways.

[0014] S13. Clean and standardize the original location dataset to obtain a clean location dataset; the clean location dataset includes the transmission session ID.

[0015] Preferably, S2 includes:

[0016] S21. Using the transmission session ID as the core association key and the timestamp as the auxiliary association item, collect the real-time status data of the corresponding transmission session, including: performance indicators and link information; performance indicators include data transmission rate, round-trip delay, packet loss rate and retransmission count; link information includes source IP address, destination IP address, transmission protocol and network node identifiers passed through.

[0017] S22. Bind the location information with the same session ID and timestamp in the clean location dataset with the transmission status data to generate an associated dataset;

[0018] S23. Extract independent transmission status indicator fields from the associated dataset, attach corresponding geographic labels to each transmission status indicator value, and generate a set of transmission status indicators with geographic labels; geographic labels include precise location and fuzzy location.

[0019] Preferably, S2 further includes:

[0020] S24. Classify the label accuracy level according to the positioning method, including L1 level, L2 level and L3 level; associate basic geographic features with L1 and L2 level labels to generate a hierarchical geographic label-transmission index set;

[0021] S25. Perform time-dimensional aggregation on the hierarchical geographic label-transmission indicator set, including statistical analysis of indicators for the same geographic label by fixed time window, calculating mean, extreme values ​​and variance; merging indicators of adjacent geographic regions; and adding time window identifiers and spatial identifiers to the aggregation results to generate a spatiotemporal aggregated indicator dataset.

[0022] Preferably, S3 includes:

[0023] S31. Filter out relevant information about transmission nodes from the spatiotemporal aggregation index dataset, including network nodes and terminal devices corresponding to source IP and destination IP, and extract the latitude and longitude or core point coordinates of the geographical label from their geographic labels; add attribute information to each node and generate a geographical distribution map of transmission nodes.

[0024] S32. Based on the spatiotemporal aggregation index dataset and the geographical distribution map of transmission nodes, obtain the transmission link relationship between nodes and determine the main link and backup link, and obtain the geographical path map of the transmission link path, status and index.

[0025] S33. Integrate the geographical distribution map of transmission nodes and the geographical path map of transmission links to form a preliminary geographical transmission path topology; obtain the role of nodes in the transmission process, and divide the topology into levels based on the node roles;

[0026] S34. Specially identify the backup link and mark the primary / backup switching conditions to generate a geographical transmission path topology model; the geographical transmission path topology model includes hierarchical nodes, links and associated status indicators.

[0027] Preferably, S4 includes:

[0028] S41. Based on the attributes of the links in the model, distinguish different types of links and formulate corresponding segmentation rules. In the geographic transmission path topology model, combine the geographic information of the GIS system to determine the segmentation boundaries of each link, mark the starting point and ending point coordinates of each segment, and generate a list of link segmentation boundaries containing the segmentation rules and segmentation boundary coordinates of each link.

[0029] S42. Match the segment boundaries in the link segment boundary list with the links in the geographic transmission path topology model to clarify the segment boundaries corresponding to each link;

[0030] In a GIS system, each link is divided into multiple short segments according to segment boundaries, and a unique identifier is assigned to each segment. The relevant information of each segment is recorded, including the link identifier, the coordinates of the starting and ending points, the length, and the corresponding geographical region. The resulting geographic information table of the segmented links is output, which contains detailed geographic information and identifiers for each segment.

[0031] S43. Extract the time window and corresponding geographic label of each transmission indicator from the spatiotemporal aggregated indicator dataset. Based on the time window and geographic label, match the transmission indicator to the corresponding link segment in the GIS system. Create a link segment-transmission indicator association table to record the transmission indicator and the time window corresponding to each segment.

[0032] Preferably, S4 also includes:

[0033] S44. Based on the requirements of transmission monitoring, determine the types of transmission indicator feature values ​​to be calculated. For each link segment, calculate each feature value based on the transmission indicator data in the link segment-transmission indicator association table within different time windows. Record the calculated transmission indicator feature values ​​of each segment in different time windows to obtain the link segment indicator feature value table.

[0034] S45. Associate the link segmentation indicator characteristic value table with the link segmentation geographic information table, analyze the impact of different geographic environments on the segmentation transmission indicator characteristic values, and analyze the pattern of link segmentation transmission indicator characteristic values ​​changing with geographic regions, and generate a link segmentation geographic-indicator characteristic analysis report.

[0035] S46. Based on the characteristic patterns summarized in the link segment geographic-indicator characteristic analysis report, and in combination with the requirements of transmission services, determine the normal range of transmission indicators for each link segment.

[0036] Preferably, S5 includes:

[0037] S51. Based on the link segmentation-index threshold and anomaly record table, filter out all link segments marked as abnormal, and integrate the identifier of the abnormal link segment, the link to which it belongs, the abnormal index, and the time window in which the anomaly occurred.

[0038] An evaluation standard is established based on the degree of impact of anomalies on transmission services. Based on the evaluation standard, the selected anomaly segments are prioritized to obtain an anomaly segment priority list.

[0039] S52. Match the abnormal segment identifiers in the abnormal segment list with the link segment geographic information table to obtain the starting and ending coordinates of each abnormal segment and the detailed geographic information of the corresponding geographic area.

[0040] Based on the geographic information of the anomaly segments and combined with the high-precision map in the GIS system, the geographic range where the anomaly segments are located is divided into smaller sub-regions. The geographic characteristics of each sub-region are recorded, and a detailed table of geographic sub-regions of the anomaly segments is generated, which includes the refined geographic sub-regions of the anomaly segments and the characteristics of each sub-region.

[0041] Preferably, S5 also includes:

[0042] S53. Based on the correlation between geographical and indicator features summarized in the link segment geographical-indicator feature analysis report, for the geographical sub-regional features of each abnormal segment, make preliminary inferences about possible causes of the anomaly, and generate an anomaly cause prediction table containing possible causes of each abnormal segment.

[0043] S54. Based on the possible causes in the anomaly cause prediction table, and combined with the details of the anomaly segmented geographical sub-regions, lock the possible range of ground anomaly points, mark the locked range of ground anomaly points with boundary lines, record the coordinate information of the boundary, and output the possible range map of ground anomaly points and the corresponding range coordinate information.

[0044] S55. According to the data acquisition plan, conduct on-site data acquisition within the locked possible range, record the acquired data and corresponding location coordinates, analyze the on-site acquired data, and determine the precise location coordinates of anomalies.

[0045] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial technical effects:

[0046] By combining geographic tags and transmission indicators, a topological model is constructed through a GIS system to refine the geographic scope. By combining multi-dimensional data, anomalies are accurately located, achieving deep integration from data to geospatial data. This improves the accuracy and efficiency of online data transmission tracking and monitoring and anomaly location, and solves the problems of data fragmentation and ambiguous positioning in existing technologies. Attached Figure Description

[0047] Figure 1 This is a method block diagram of an embodiment of the present invention. Detailed Implementation

[0048] Examples, such as Figure 1 As shown, the present invention proposes an online data transmission implementation tracking and monitoring ground positioning system, comprising:

[0049] S1. Determine the key positioning data sources, identify the terminal side, network side and associated identification data and form a list, collect raw positioning data in real time and preprocess it to generate a clean positioning dataset.

[0050] S11. Based on the carrier of online data transmission, identify the location-related data sources that need to be collected, and obtain a list of location data sources, including the type and collection interface of each data source;

[0051] S12. Based on the data sources and interfaces in the list, collect raw data in real time or near real time using automated tools to obtain the raw location dataset; where the automated tools can be, for example, data collection scripts or IoT gateways.

[0052] S13. Clean and standardize the original location dataset to obtain a clean location dataset; the clean location dataset includes the transmission session ID.

[0053] S2. Based on the clean location dataset, correlate the transmission status data, extract geographically labeled indicators and supplement features hierarchically. After spatiotemporal aggregation and anomaly verification, a spatiotemporal aggregated indicator dataset is formed for building a topology model.

[0054] S21. Using the transmission session ID as the core association key and the timestamp as the auxiliary association item, collect the real-time status data of the corresponding transmission session, including: performance indicators and link information; performance indicators include data transmission rate, round-trip delay, packet loss rate and retransmission count; link information includes source IP address, destination IP address, transmission protocol and network node identifiers passed through.

[0055] S22. Bind the location information with the same session ID and timestamp in the clean location dataset with the transmission status data to generate an associated dataset;

[0056] S23. Extract independent transmission status index fields from the associated dataset, attach corresponding geographic labels to each transmission status index value, and generate a set of transmission status indexes with geographic labels; geographic labels include precise location and fuzzy location; for example, if the positioning type is GNSS / BeiDou, directly associate latitude and longitude and add precise location labels; if the positioning type is base station / IP resolution, mark the location range and add fuzzy location labels.

[0057] S24. Classify the label accuracy level according to the positioning method, including L1, L2 and L3 levels; associate basic geographic features with L1 and L2 level labels to generate a hierarchical geographic label-transmission index set; for example, the altitude = 50 meters, is a plain; the terrain type is a densely populated urban area.

[0058] S25. Perform time-dimensional aggregation on the hierarchical geographic label-transmission indicator set, including statistical analysis of indicators for the same geographic label by fixed time window, calculating mean, extreme values ​​and variance; merging indicators of adjacent geographic regions; and adding time window and spatial identifiers to the aggregation results to generate a spatiotemporal aggregated indicator dataset.

[0059] S3. Adapt the spatiotemporal aggregation index dataset to the GIS system, extract and label transmission nodes, draw the geographical path of the transmission link, and integrate, construct, and verify the optimized topology model.

[0060] S31. Filter out relevant information about transmission nodes from the spatiotemporal aggregation index dataset, including network nodes and terminal devices corresponding to source IP and destination IP, and extract the latitude and longitude or core point coordinates of the geographical label from their geographic labels; add attribute information to each node and generate a geographical distribution map of transmission nodes.

[0061] S32. Based on the spatiotemporal aggregation index dataset and the geographical distribution map of transmission nodes, obtain the transmission link relationship between nodes and determine the main link and backup link, and obtain the geographical path map of the transmission link path, status and index.

[0062] S33. Integrate the geographical distribution map of transmission nodes and the geographical path map of transmission links to form a preliminary geographical transmission path topology; obtain the role of nodes in the transmission process, and divide the topology into levels based on the node roles;

[0063] S34. Specially identify the backup link and mark the primary / backup switching conditions to generate a geographic transmission path topology model; the geographic transmission path topology model includes hierarchical nodes, links, and associated status indicators.

[0064] S4. First, formulate link segmentation rules and boundaries based on the geographic transmission path topology model, then divide the link into segments and record information, match transmission indicators with segments; analyze the correlation between geographic and indicator characteristics, set thresholds and mark anomalies based on the set thresholds, and generate an anomaly record table.

[0065] S41. Based on the attributes of the links in the model, distinguish different types of links and formulate corresponding segmentation rules. In the geographic transmission path topology model, combine the geographic information of the GIS system to determine the segmentation boundaries of each link, mark the starting point and ending point coordinates of each segment, and generate a list of link segmentation boundaries containing the segmentation rules and segmentation boundary coordinates of each link.

[0066] S42. Match the segment boundaries in the link segment boundary list with the links in the geographic transmission path topology model to clarify the segment boundaries corresponding to each link;

[0067] In a GIS system, each link is divided into multiple short segments according to segment boundaries, and a unique identifier is assigned to each segment. The relevant information of each segment is recorded, including the link identifier, the coordinates of the starting and ending points, the length, and the corresponding geographical region. The resulting geographic information table of the segmented links is output, which contains detailed geographic information and identifiers for each segment.

[0068] S43. Extract the time window and corresponding geographic label of each transmission indicator from the spatiotemporal aggregated indicator dataset. Based on the time window and geographic label, match the transmission indicator to the corresponding link segment in the GIS system. Create a link segment-transmission indicator association table to record the transmission indicator and the time window corresponding to each segment.

[0069] S44. Based on the requirements of transmission monitoring, determine the types of transmission indicator feature values ​​to be calculated. For each link segment, calculate each feature value based on the transmission indicator data in the link segment-transmission indicator association table within different time windows. Record the calculated transmission indicator feature values ​​of each segment in different time windows to obtain the link segment indicator feature value table.

[0070] S45. Associate the link segment indicator characteristic value table with the link segment geographic information table to analyze the impact of different geographic environments on the segment transmission indicator characteristic values, and analyze the variation of link segment transmission indicator characteristic values ​​with geographic regions, generating a link segment geographic-indicator characteristic analysis report. The purpose of the association is to make the transmission indicator characteristic values ​​of each segment correspond to its geographic information, such as the region and geographic environment. Examples of analyzing the impact of different geographic environments on segment transmission indicator characteristic values ​​include comparing the average transmission rate differences of the same type of link in different geographic regions. Examples of analyzing the variation of link segment transmission indicator characteristic values ​​with geographic regions include: in a certain type of geographic region, the latency of link segments is generally high, and the packet loss rate fluctuates greatly.

[0071] S46. Based on the characteristic patterns summarized in the link segment geographic-indicator characteristic analysis report, and in combination with the requirements of transmission services, determine the normal range of transmission indicators for each link segment.

[0072] Set thresholds for various transmission indicators for each link segment, compare the indicator feature values ​​in the link segment indicator feature value table with the set thresholds, mark segments that exceed the thresholds as abnormal, record the time window of the abnormality, and output a link segment - indicator threshold and abnormal record table containing the indicator thresholds and abnormality marks for each link segment.

[0073] S5. Based on the abnormal record table, filter and sort the abnormal segments, refine the scope by combining their geographical information, infer the cause according to the correlation between geography and indicators, lock the range of abnormal points, and finally accurately locate the abnormal points through on-site collection.

[0074] S51. Based on the link segmentation-index threshold and anomaly record table, filter out all link segments marked as abnormal, and integrate the identifier of the abnormal link segment, the link to which it belongs, the abnormal index, and the time window in which the anomaly occurred.

[0075] An evaluation standard is established based on the degree of impact of anomalies on transmission services. Based on the evaluation standard, the selected anomaly segments are prioritized to obtain an anomaly segment priority list.

[0076] S52. Match the abnormal segment identifiers in the abnormal segment list with the link segment geographic information table to obtain the starting and ending coordinates of each abnormal segment and the detailed geographic information of the corresponding geographic area.

[0077] Based on the geographic information of the anomaly segments, and combined with the high-precision map in the GIS system, the geographic range where the anomaly segments are located is divided into smaller sub-regions. The geographic characteristics of each sub-region are recorded, and a detailed table of geographic sub-regions of the anomaly segments is generated, which includes the refined geographic sub-regions of the anomaly segments and the characteristics of each sub-region. For example, the division is based on road grids or terrain units.

[0078] S53. Based on the correlation patterns between geographical and indicator characteristics summarized in the link segment geographical-indicator characteristic analysis report, for the geographical sub-regional characteristics of each abnormal segment, make preliminary inferences about possible causes of the anomaly, and generate an anomaly cause prediction table containing possible causes for each abnormal segment; for example, if the abnormal wireless link segment is located in a sub-region with tall buildings, it may be caused by signal obstruction; if the abnormal fiber optic link segment is located in a construction area, it may be caused by damage to the fiber optic cable.

[0079] S54. Based on the possible causes in the anomaly cause prediction table, and combined with the details of the anomaly segmented geographical sub-regions, lock the possible range of ground anomaly points, mark the locked range of ground anomaly points with boundary lines, record the coordinate information of the boundary, and output the possible range map of ground anomaly points and the corresponding range coordinate information.

[0080] S55. According to the data collection plan, conduct on-site data collection within the locked possible range, record the collected data and corresponding location coordinates, analyze the on-site collected data, and determine the precise location coordinates of anomalies.

[0081] By combining geographic tags and transmission indicators, and constructing a topological model through a GIS system to refine the geographic scope, and by combining multi-dimensional data to accurately locate anomalies, a deep integration from data to geospatial data is achieved. This improves the accuracy and efficiency of online data transmission tracking and monitoring and anomaly location, and is superior to the problems of data fragmentation and ambiguous location in existing technologies.

[0082] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A ground positioning system for online data transmission, tracking, and monitoring, characterized in that, Includes the following steps: S1. Determine the key positioning data sources, identify the terminal side, network side and associated identification data and form a list, collect raw positioning data in real time and preprocess it to generate a clean positioning dataset. S2. Based on the clean location dataset, correlate the transmission status data, extract geographically labeled indicators and supplement features hierarchically. After spatiotemporal aggregation and anomaly verification, a spatiotemporal aggregated indicator dataset is formed for building a topology model. S3. Adapt the spatiotemporal aggregation index dataset to the GIS system, extract and label transmission nodes, draw the geographical path of the transmission link, and integrate, construct, and verify the optimized topology model. S4. First, formulate link segmentation rules and boundaries based on the geographic transmission path topology model, then divide the link into segments and record information, match transmission indicators with segments; analyze the correlation between geographic and indicator characteristics, set thresholds and mark anomalies based on the set thresholds, and generate an anomaly record table. S5. Based on the abnormal record table, filter and sort abnormal segments, refine the scope by combining their geographical information, infer the cause based on the correlation between geography and indicators, lock the range of abnormal points, and finally accurately locate the abnormal points through on-site collection.

2. The online data transmission implementation tracking and monitoring ground positioning system according to claim 1, characterized in that, S1 includes: S11. Based on the carrier of online data transmission, identify the location-related data sources that need to be collected, and obtain a list of location data sources, including the type and collection interface of each data source; S12. Based on the data sources and interfaces in the list, collect raw data in real time or near real time using automated tools to obtain the raw location dataset; where the automated tools can be, for example, data collection scripts or IoT gateways. S13. Clean and standardize the original location dataset to obtain a clean location dataset; the clean location dataset includes the transmission session ID.

3. The online data transmission implementation tracking and monitoring ground positioning system according to claim 2, characterized in that, S2 includes: S21. Using the transmission session ID as the core association key and the timestamp as the auxiliary association item, collect the real-time status data of the corresponding transmission session, including: performance indicators and link information; performance indicators include data transmission rate, round-trip delay, packet loss rate and retransmission count; link information includes source IP address, destination IP address, transmission protocol and network node identifiers passed through. S22. Bind the location information with the same session ID and timestamp in the clean location dataset with the transmission status data to generate an associated dataset; S23. Extract independent transmission status indicator fields from the associated dataset, attach corresponding geographic labels to each transmission status indicator value, and generate a set of transmission status indicators with geographic labels; geographic labels include precise location and fuzzy location.

4. The online data transmission implementation tracking and monitoring ground positioning system according to claim 3, characterized in that, S2 also includes: S24. Classify the label accuracy level according to the positioning method, including L1 level, L2 level and L3 level; associate basic geographic features with L1 and L2 level labels to generate a hierarchical geographic label-transmission index set; S25. Perform time-dimensional aggregation on the hierarchical geographic label-transmission indicator set, including statistical analysis of indicators for the same geographic label by fixed time window, calculating mean, extreme values ​​and variance; merging indicators of adjacent geographic regions; and adding time window identifiers and spatial identifiers to the aggregation results to generate a spatiotemporal aggregated indicator dataset.

5. The online data transmission implementation tracking and monitoring ground positioning system according to claim 4, characterized in that, S3 includes: S31. Filter out relevant information about transmission nodes from the spatiotemporal aggregation index dataset, including network nodes and terminal devices corresponding to source IP and destination IP, and extract the latitude and longitude or core point coordinates of the geographical label from their geographic labels; add attribute information to each node and generate a geographical distribution map of transmission nodes. S32. Based on the spatiotemporal aggregation index dataset and the geographical distribution map of transmission nodes, obtain the transmission link relationship between nodes and determine the main link and backup link, and obtain the geographical path map of the transmission link path, status and index. S33. Integrate the geographical distribution map of transmission nodes and the geographical path map of transmission links to form a preliminary geographical transmission path topology; obtain the role of nodes in the transmission process, and divide the topology into levels based on the node roles; S34. Specially identify the backup link and mark the primary / backup switching conditions to generate a geographical transmission path topology model; the geographical transmission path topology model includes hierarchical nodes, links and associated status indicators.

6. The online data transmission implementation tracking and monitoring ground positioning system according to claim 5, characterized in that, S4 include: S41. Based on the attributes of the links in the model, distinguish different types of links and formulate corresponding segmentation rules. In the geographic transmission path topology model, combine the geographic information of the GIS system to determine the segmentation boundaries of each link, mark the starting point and ending point coordinates of each segment, and generate a list of link segmentation boundaries containing the segmentation rules and segmentation boundary coordinates of each link. S42. Match the segment boundaries in the link segment boundary list with the links in the geographic transmission path topology model to clarify the segment boundaries corresponding to each link; In a GIS system, each link is divided into multiple short segments according to segment boundaries, and a unique identifier is assigned to each segment. The relevant information of each segment is recorded, including the link identifier, the coordinates of the starting and ending points, the length, and the corresponding geographical region. The resulting geographic information table of the segmented links is output, which contains detailed geographic information and identifiers for each segment. S43. Extract the time window and corresponding geographic label of each transmission indicator from the spatiotemporal aggregated indicator dataset. Based on the time window and geographic label, match the transmission indicator to the corresponding link segment in the GIS system. Create a link segment-transmission indicator association table to record the transmission indicator and the time window corresponding to each segment.

7. The online data transmission implementation tracking and monitoring ground positioning system according to claim 6, characterized in that, S4 also includes: S44. Based on the requirements of transmission monitoring, determine the types of transmission indicator feature values ​​to be calculated. For each link segment, calculate each feature value based on the transmission indicator data in the link segment-transmission indicator association table within different time windows. Record the calculated transmission indicator feature values ​​of each segment in different time windows to obtain the link segment indicator feature value table. S45. Associate the link segmentation indicator characteristic value table with the link segmentation geographic information table, analyze the impact of different geographic environments on the segmentation transmission indicator characteristic values, and analyze the pattern of link segmentation transmission indicator characteristic values ​​changing with geographic regions, and generate a link segmentation geographic-indicator characteristic analysis report. S46. Based on the characteristic patterns summarized in the link segment geographic-indicator characteristic analysis report, and in combination with the requirements of transmission services, determine the normal range of transmission indicators for each link segment.

8. The online data transmission implementation tracking and monitoring ground positioning system according to claim 7, characterized in that, S5 include: S51. Based on the link segmentation-index threshold and anomaly record table, filter out all link segments marked as abnormal, and integrate the identifier of the abnormal link segment, the link to which it belongs, the abnormal index, and the time window in which the anomaly occurred. An evaluation standard is established based on the degree of impact of anomalies on transmission services. Based on the evaluation standard, the selected anomaly segments are prioritized to obtain an anomaly segment priority list. S52. Match the abnormal segment identifiers in the abnormal segment list with the link segment geographic information table to obtain the starting and ending coordinates of each abnormal segment and the detailed geographic information of the corresponding geographic area. Based on the geographic information of the anomaly segments and combined with the high-precision map in the GIS system, the geographic range where the anomaly segments are located is divided into smaller sub-regions. The geographic characteristics of each sub-region are recorded, and a detailed table of geographic sub-regions of the anomaly segments is generated, which includes the refined geographic sub-regions of the anomaly segments and the characteristics of each sub-region.

9. The online data transmission implementation tracking and monitoring ground positioning system according to claim 8, characterized in that, S5 also includes: S53. Based on the correlation between geographical and indicator features summarized in the link segment geographical-indicator feature analysis report, for the geographical sub-regional features of each abnormal segment, make preliminary inferences about possible causes of the anomaly, and generate an anomaly cause prediction table containing possible causes of each abnormal segment. S54. Based on the possible causes in the anomaly cause prediction table, and combined with the details of the anomaly segmented geographical sub-regions, lock the possible range of ground anomaly points, mark the locked range of ground anomaly points with boundary lines, record the coordinate information of the boundary, and output the possible range map of ground anomaly points and the corresponding range coordinate information. S55. According to the data acquisition plan, conduct on-site data acquisition within the locked possible range, record the acquired data and corresponding location coordinates, analyze the on-site acquired data, and determine the precise location coordinates of anomalies.

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