A Method and System for Analysis of Interference Impact Range Based on Multi-Station GNSS Data

Abstract

This invention discloses a method and system for analyzing the interference impact range based on multi-station GNSS data. The method includes: reading observation data from multiple stations, extracting elevation and azimuth angles, and extracting signal-to-noise ratio (SNR), multipath, and frequency band data according to signal type, and performing time alignment; employing a dynamic SNR threshold model associated with elevation angle to detect SNR anomalies, multipath anomalies, frequency band anomalies, and data missingness according to signal type, and calculating interference scores; grouping interference events by time windows, and calculating the spatial impact range of interference, including center location, radius of influence, and confidence level, when interference events exist at least at two stations within the same window. This invention improves interference identification accuracy and spatial positioning reliability through multi-station joint analysis, dynamic thresholding, and multi-dimensional interference detection, and is suitable for GNSS signal quality monitoring and interference source localization.

Description

Technical Field

[0001] This invention relates to the field of GNSS signal quality monitoring technology, specifically to a method and system for analyzing the interference impact range based on multi-station GNSS data, used to identify and locate the spatial distribution range of GNSS signal interference sources. Background Technology

[0002] GNSS technology is widely used in navigation and positioning, precision measurement, meteorological monitoring and other fields. However, GNSS signals are easily affected by various interferences during propagation, including electromagnetic interference, multipath effect, signal blockage, etc., which seriously affect positioning accuracy and system reliability. In the existing technology, the GNSS interference monitoring methods mainly have the following problems: (1) Traditional methods use fixed thresholds to judge signal quality anomalies, without considering the changes in signal propagation characteristics with elevation angle, resulting in insufficient interference identification accuracy in low elevation angle areas; (2) Existing methods do not distinguish between different signal types, and the data characteristics of different signals are mixed for analysis, affecting the accuracy of interference identification; (3) Existing methods mainly rely on data from a single station, and cannot make full use of the advantages of multi-station networks for spatial positioning of interference sources, resulting in limited positioning accuracy; (4) Existing methods are insufficient in detecting abnormal situations where signals are suddenly interrupted during satellite ascent and descent, which may miss important interference events; (5) Existing methods lack multi-dimensional and multi-level statistical analysis functions.

[0003] Therefore, how to provide a method and system that can accurately identify and locate the spatial impact range of GNSS signal interference in order to improve the accuracy and reliability of interference monitoring has become an urgent problem to be solved in the current technical field. Summary of the Invention

[0004] To address the problems of insufficient interference identification accuracy, signal type confusion, limited spatial positioning, and inadequate data detection in existing technologies, this invention proposes a method and system for analyzing the interference impact range based on multi-station GNSS data. This method organizes observation data from multiple CORS stations according to signal type, employs a dynamic signal-to-noise ratio threshold model to dynamically adjust thresholds based on elevation angle, and performs interference detection separately for each signal type. After grouping interference events by time window, it analyzes the center location, radius of influence, and confidence level of the interference's spatial impact range. Finally, it outputs the interference's spatial impact range, statistical results, and analysis report, improving the accuracy of interference identification and spatial positioning, enhancing interference detection capabilities, and making it suitable for GNSS signal quality monitoring and interference source localization.

[0005] According to one aspect of the present invention, a method for analyzing the interference impact range based on multi-station GNSS data is provided, comprising: Read observation data files from multiple stations, extract elevation angle and azimuth angle data, extract signal-to-noise ratio, multipath, and frequency band data according to signal type, and perform time alignment processing on all station data; A dynamic signal-to-noise ratio (SNR) threshold model associated with elevation angle is adopted, and SNR anomaly detection, multipath anomaly detection, frequency band number anomaly detection, and data missing detection are performed according to signal type. Interference score is calculated based on each detection result, and at least the station, time, signal type, elevation angle, azimuth angle, and interference score of each interference event are recorded. Interference events are grouped by time window, and interference events within each time window are grouped by station. When interference events exist at least at two stations within the same time window, the spatial influence range of the interference corresponding to that time window is calculated, including the center location, influence radius, and confidence level.

[0006] As a further technical solution, in the dynamic signal-to-noise ratio threshold model, the dynamic signal-to-noise ratio threshold is calculated based on the elevation angle of the current epoch, and the dynamic signal-to-noise ratio threshold changes linearly with the sine value of the elevation angle.

[0007] As a further technical solution, the data missing detection includes: constructing a complete time series for each signal type combination; if there is no observation value in the current epoch, but the most recent data epoch found in the epoch consistent with the current combination has an observation value, then it is initially determined to be data missing; if the corresponding elevation angle is within a preset effective range and the time interval meets the preset requirements, then it is confirmed to be data missing, and a data missing score is calculated based on the time interval.

[0008] As a further technical solution, the interference score calculation includes: adding the severity of signal-to-noise ratio (SNR) anomalies, the severity of multipath anomalies, the severity of frequency band anomalies, and the data missing score under the same epoch, station, and combination to obtain the interference score; wherein, the severity of SNR anomalies is determined based on the difference between the SNR threshold and the observed SNR value, the severity of multipath anomalies is determined based on the difference between the observed multipath value and the multipath threshold and has an upper limit, and the severity of frequency band anomalies is determined based on the difference between the minimum number of frequency points and the actual number of frequency points.

[0009] As a further technical solution, the calculation of the center location of the spatial influence range of interference includes: taking the sum of the interference scores of each station within the time window as the weight, and performing a weighted average of the longitude and latitude of the stations to obtain the center longitude and center latitude.

[0010] As a further technical solution, the calculation of the center position of the interference spatial influence range also includes: when the number of affected stations reaches a preset threshold, selecting several stations with the highest interference scores, calculating the azimuth ray based on the position and azimuth of each station, finding the intersection point of the ray and taking the average to obtain the center position, or averaging the center position with the center position obtained by weighted averaging to obtain the final center position.

[0011] As a further technical solution, the confidence level is calculated based on the number of affected stations in the current time window, the total number of stations participating in the analysis, and the average interference score in the time window.

[0012] According to one aspect of the present invention, an interference impact range analysis system based on multi-station GNSS data is provided, comprising: The data reading and processing module is used to read observation data files from multiple stations, extract elevation angle and azimuth angle data, extract signal-to-noise ratio, multipath, and frequency band data according to signal type, and perform time alignment processing on all station data. The interference detection and scoring module is used to employ a dynamic signal-to-noise ratio threshold model associated with the elevation angle, and to perform signal-to-noise ratio anomaly detection, multipath anomaly detection, frequency band number anomaly detection, and data missing detection according to signal type. It calculates the interference score based on the detection results and records at least the station, time, signal type, elevation angle, azimuth angle, and interference score for each interference event. The spatial analysis module is used to group interference events by time window, and then group the interference events within each time window by station. When there are interference events at least two stations within the same time window, the module calculates the spatial impact range of the interference corresponding to that time window, including the center location, the radius of influence, and the confidence level.

[0013] According to one aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the interference impact range analysis method based on multi-station GNSS data.

[0014] According to one aspect of the present invention, a computer-readable storage medium is provided, storing a computer program that, when executed by a processor, implements the interference impact range analysis method based on multi-station GNSS data.

[0015] This invention, through organizing multi-station observation data by signal type, implementing dynamic signal-to-noise ratio thresholds and interference detection by signal type, and grouping by time window, has the following beneficial effects: (1) A dynamic signal-to-noise ratio threshold model is adopted to dynamically adjust the threshold according to the elevation angle, and the signal-to-noise ratio and multipath data are processed separately according to the signal type, which improves the interference identification accuracy and solves the problems of insufficient identification accuracy of fixed threshold and signal type confusion. (2) By detecting and identifying abnormal situations such as sudden signal interruption during satellite ascent and descent, the spatial impact range of interference is calculated by using the multi-station weighted average method or azimuth intersection method, which improves the accuracy and reliability of spatial positioning results and solves problems such as single multi-station positioning and insufficient detection of missing data. (3) It is applicable to GNSS signal quality monitoring and interference source location, providing more reliable technical support for interference monitoring and location. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the interference impact range analysis method based on multi-station GNSS data provided in an embodiment of the present invention. Detailed Implementation

[0018] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0020] This invention provides a method for analyzing the interference impact range based on multi-station GNSS data. (See attached document.) Figure 1 It includes the following steps: Step 1: Read the observation data files from multiple CORS stations, extract the elevation angle and azimuth angle data, extract and organize the signal-to-noise ratio, multipath, and frequency band data according to the signal type, and perform time alignment processing on all station data to ensure the consistency of the time series.

[0021] The specific operation method for reading observation data files from multiple CORS stations and organizing the data according to signal type is as follows: The observation data files from each CORS station are read, and signal-to-noise ratio (SNR) data, multipath data, frequency band data, elevation angle, and azimuth angle data are extracted. Specifically, SNR data is extracted separately according to signal type (e.g., S1C, S2W, S2X, S5X, etc.), multipath data is extracted separately according to signal type (e.g., M1C, M2W, M5X, etc.), and frequency band data is extracted separately according to different observation value types (carrier phase, pseudorange) for different systems (GPS, GLONASS, Galileo, BeiDou). An independent data structure is constructed for each (system, satellite, signal) combination. The data from each station are time-aligned according to a unified time base to ensure consistency in the time series of each station, facilitating subsequent interference detection and spatial aggregation by epoch.

[0022] Step 2: Use a dynamic signal-to-noise ratio (SNR) threshold model to dynamically adjust the SNR threshold based on the elevation angle. Perform SNR anomaly detection, multipath anomaly detection, frequency band number anomaly detection, and data missing detection according to signal type. Calculate the interference score and severity of each item. Record the station, time, system, satellite, signal type, elevation angle, azimuth angle, interference score, and interference type label for each interference event.

[0023] The specific operation method of using the dynamic signal-to-noise ratio threshold model to dynamically adjust the signal-to-noise ratio threshold according to the elevation angle, and to perform interference detection and calculate interference scores according to signal type is as follows: (1) Calculation of dynamic signal-to-noise ratio threshold: For each signal type, based on the elevation angle of the current epoch. (Unit: degrees) Calculate the dynamic signal-to-noise ratio threshold The formula used is: (1), in, Elevation angle The corresponding signal-to-noise ratio threshold (unit: dB-Hz). The signal-to-noise ratio threshold (in dB-Hz) at a high elevation angle of 90°. The signal-to-noise ratio threshold (in dB-Hz) at a low elevation angle of 0°. Elevation angle (unit: degrees). If the signal-to-noise ratio of a signal at a certain epoch is lower than the corresponding... If the signal-to-noise ratio is abnormal at that epoch, it is determined that the signal has an abnormal signal-to-noise ratio.

[0024] (2) Interference score and severity calculation: The interference score is equal to the sum of the severity of each anomaly type and the missing data score, that is: (2), in, To interfere with the scoring, The severity of the signal-to-noise ratio. This represents the severity of multipath propagation (with a maximum value of 1). The severity depends on the number of frequency bands. Scoring is assigned to areas of missing data. The formulas for calculating each severity level are as follows: (3), (4), (5), in, Signal-to-noise ratio threshold (unit: dB-Hz). Signal-to-noise ratio (SNR) observations (unit: dB-Hz); Multipath threshold (unit: cm). These are multipath observations (unit: cm). Minimum number of frequency points This represents the actual number of frequency points. Multipath anomaly detection: If... Higher than This is then identified as a multipath anomaly. Calculated according to formula (4) and not exceeding 1.0. Frequency band number anomaly judgment: If the number of available frequency bands for a satellite at a certain epoch is lower than... If so, it is determined that the number of frequency bands is abnormal. Calculate according to formula (5).

[0025] (3) Data Missing Detection and Scoring: Construct a complete time series for each (system, satellite, signal) combination; search backwards from the current epoch for the nearest available data epoch that matches the current combination; if the current epoch has no observations but the nearest available data epoch has a value, it is preliminarily determined to be data missing. Verification is performed if the elevation angles of the time points before and after verification are both within the range of 5° to 85°, and the time interval is greater than 0.5 minutes and does not exceed 30 minutes; if these conditions are met, it is confirmed as data missing. Data Missing Scoring With time interval (Unit: minutes) Related issues mainly include missing signal-to-noise ratio (SNR) data and missing multipath data. The formula for calculating the SNR data missing score is as follows: (6), Multipath data missing: If the event has been judged as interference for other reasons, then (7), otherwise (8), in, The time interval (in minutes) between the current epoch and the most recent epoch with data.

[0026] (4) Interference scoring and recording: Interference scoring and recording of the same station and combination at the same epoch. , , and The interference score of the event is obtained by adding them together. Record the station, time, system, satellite, signal type, elevation angle, azimuth angle, interference score, and interference type label for each interference event, for use in step 3 to calculate the spatial impact range.

[0027] Step 3: Group the interference events by time window, and group the interference events within each time window by station; use the weighted average method or azimuth intersection method to calculate the center location, radius of influence, and confidence level of the spatial influence range of the interference.

[0028] The specific operation method for grouping interference events by time window, calculating the center location, influence radius, and confidence level is as follows: (1) Group the interference events according to a preset time window (e.g., 30 minutes); group the interference events in each time window according to the station, and calculate the spatial influence range of the interference for the window only when there are interference events in at least two stations within the window.

[0029] (2) Calculation of center position: Method A is a weighted average method based on the station position, which is the sum of the interference scores of each station within the time window. The central longitude is obtained by weighting the longitude and latitude of the stations respectively. Central latitude The calculation formula is: (9), (10) in, , These are the longitude and latitude of the center of the area affected by the interference (unit: degrees). , For the first Longitude and latitude (in degrees) of each affected station. For the first The sum of interference scores for each station within this time window, with the summation range covering all affected stations within this time window. , (Number of affected stations). Method B is a positioning method based on azimuth intersection. When the number of affected stations is ≥3, select up to 4 stations with the highest interference scores, calculate the azimuth ray based on the position and azimuth of each station, find the intersection point of the rays, and take the average to obtain the center position. Method A or Method B can be used alone, or the results of the two methods can be averaged.

[0030] (3) Radius of influence: Based on the center position calculated above, calculate the distance from the center to each affected station, and take the maximum value as the radius of influence of the interference space.

[0031] (4) Confidence level: based on the number of affected stations within the time window Total number of stations participating in the analysis and the average interference score within that time window Calculate confidence level The calculation formula is: (11), in, The confidence level is defined as follows, and its value range is: , This represents the number of affected stations. This represents the total number of stations. The average interference score.

[0032] Preferably, the method described in this embodiment of the invention further includes: Step 4: Output the spatial impact range of the interference (center latitude and longitude, radius of influence, list of affected stations, azimuth range, elevation range, confidence level), statistical results of interference events, and analysis report.

[0033] The specific operation methods for the output interference spatial influence range, statistical results, and analysis report are as follows: Output the spatial impact range of interference for each time window, including center longitude, center latitude, radius of influence, list of affected stations, azimuth range, elevation range, confidence level, etc.; output statistical results of interference events, such as statistics by station, by signal type, and by time distribution; output analysis report, which is convenient for GNSS signal quality monitoring and interference source location applications.

[0034] Based on the same inventive concept as the aforementioned method embodiments, this invention also provides an interference impact range analysis system based on multi-station GNSS data. The system includes: a data reading and processing module, an interference detection and scoring module, a spatial analysis module, and an output module.

[0035] The data reading and processing module is used to read observation data files from multiple stations (such as CORS stations), extract elevation angle and azimuth angle data, and extract signal-to-noise ratio, multipath, and frequency band data according to signal type, and perform time alignment processing on all station data.

[0036] Specifically, the data reading and processing module first traverses the observation files (e.g., RINEX format) of each station, parsing the signal-to-noise ratio (SNR) observations, multipath error values, number of available frequency bands, and elevation and azimuth angles calculated from ephemeris for each satellite from each epoch. This module groups and stores the SNR by signal type (e.g., S1C, S2W, S2X, S5X, etc.) and the multipath by signal type (e.g., M1C, M2W, M5X, etc.), constructing an independent data structure for each (system, satellite, signal) combination. Simultaneously, this module interpolates or aligns the data from all stations according to a unified time base to ensure temporal consistency in subsequent analysis.

[0037] The interference detection and scoring module is used to employ a dynamic signal-to-noise ratio threshold model associated with the elevation angle, and to perform signal-to-noise ratio anomaly detection, multipath anomaly detection, frequency band number anomaly detection, and data missing detection according to signal type. It calculates the interference score based on the detection results and records at least the station, time, signal type, elevation angle, azimuth angle, and interference score for each interference event.

[0038] In this embodiment, the interference detection and scoring module first calculates the dynamic signal-to-noise ratio threshold for each signal type based on the elevation angle E of the current epoch. If the actual signal-to-noise ratio is lower than this threshold, it is judged as an abnormal signal-to-noise ratio, and the severity is calculated. Multipath anomaly detection: If multipath observations Above the threshold If so, it is judged as abnormal, and the severity is determined accordingly. Frequency band anomaly detection: If the actual number of frequency points of a satellite at a certain epoch... Below the minimum frequency The severity Data missing detection: For each signal type combination, a complete time series is constructed. If there is no observation at the current epoch, but the most recent epoch with data in the same combination contains an observation, and the corresponding elevation angle is within the range of 5° to 85° and the time interval is between 0.5 minutes and 30 minutes, then it is confirmed as data missing, and a missing value score is calculated based on the time interval. Finally, , , and The interference score is obtained by adding them together. This module records at least the station, time, signal type, elevation angle, azimuth angle, and interference score for each interference event.

[0039] The spatial analysis module is used to group interference events by time window, and then group the interference events within each time window by station. When there are interference events at least two stations within the same time window, the module calculates the spatial impact range of the interference corresponding to that time window, including the center location, the radius of influence, and the confidence level.

[0040] The spatial analysis module first groups the interference events according to a preset time window (e.g., 30 minutes), and then aggregates the interference events by station within each window. If at least two stations in the window have interference events, the influence range is calculated. The center location can be determined in three ways: (1) weighted average method: the latitude and longitude are weighted by the sum of the interference scores of each station; (2) azimuth intersection method: select up to 4 stations with the highest interference scores, calculate the rays according to the azimuth of each station's location and the interference event record, and take the average of the intersection points; (3) combined average: average the results of the first two methods again. The influence radius is the distance from the center to the farthest affected station. The confidence level is based on the number of affected stations n, the total number of stations N, and the average interference score. calculate: .

[0041] The output module is used to output the spatial influence range of the interference. The spatial influence range of the interference includes the center latitude and longitude, the radius of influence, a list of affected stations, the azimuth range, the elevation range, and the confidence level.

[0042] This invention also provides an electronic device, which may be a computer, server, tablet computer, embedded industrial control computer, etc. The electronic device includes: a memory, a processor, an input / output interface, a communication interface, and a bus.

[0043] Memory is used to store computer programs and various data. Memory can be read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). Memory can store the operating system, application programs, and other program modules.

[0044] The processor, electrically connected to the memory, executes the computer program stored in the memory to implement the interference impact range analysis method based on multi-station GNSS data as described in any of the above method embodiments. The processor can be a general-purpose central processing unit (CPU), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits.

[0045] Input / output interfaces are used to enable information input and output, and can be connected to peripherals such as keyboards, mice, and monitors.

[0046] The communication interface is used to enable communication and interaction between this device and other devices (such as GNSS receivers and data centers). Communication can be achieved through wired means (such as USB and network cable) or wireless means (such as mobile network, WiFi, and Bluetooth).

[0047] A bus is used to transmit information between the various components of a device.

[0048] During operation, the processor acquires GNSS observation data files from multiple stations via the communication interface and calls the program in memory to perform the following operations: read the observation data, extract the elevation angle and azimuth angle, and extract the signal-to-noise ratio, multipath, and number of frequency bands according to the signal type; perform dynamic threshold anomaly detection and data missing detection; calculate interference scores and record interference events; group by time window, and calculate the spatial influence range of interference (center location, radius of influence, confidence level) when at least two stations have interference events within the window; finally, the results can be output through the input / output interface or the communication interface.

[0049] Those skilled in the art will understand that the hardware structure of the electronic device can be modified by adding or removing components as needed, and is not limited to the above-listed components.

[0050] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program can implement the interference impact range analysis method based on multi-station GNSS data described in any of the above method embodiments.

[0051] The computer-readable storage medium can be any medium capable of storing program code, including but not limited to: USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, optical disk, register, solid-state drive (SSD), etc. The storage medium can be non-transitory, that is, it does not contain transient propagation signals.

[0052] When the computer program runs on the processor, it performs the following steps: reads observation data files from multiple stations, extracts elevation angle and azimuth angle data, and extracts signal-to-noise ratio, multipath, and frequency band data according to signal type, and performs time alignment; adopts a dynamic signal-to-noise ratio threshold model to detect signal-to-noise ratio anomalies, multipath anomalies, frequency band anomalies, and data missingness according to signal type, calculates interference scores, and records interference events; groups interference events by time window and by station, and when at least two stations have interference events within the same window, calculates the spatial influence range of the interference corresponding to that time window, including the center location, influence radius, and confidence level.

[0053] By pre-storing the aforementioned computer program in a storage medium, it can be conveniently distributed, installed, or updated to different electronic devices, thereby realizing the technical solution of the present invention.

[0054] In summary, this invention improves the accuracy of interference identification and spatial positioning by organizing observation data from multiple stations according to signal type, employing a dynamic signal-to-noise ratio threshold model and interference detection based on individual signals, and calculating the spatial impact range of interference by grouping data into time windows and using weighted averages or azimuth angles, and then outputting the results. This enhances the interference detection capability and is suitable for GNSS signal quality monitoring and interference source location, providing reliable technical support for interference monitoring and positioning.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing the interference impact range based on multi-station GNSS data, characterized in that, include: Read observation data files from multiple stations, extract elevation angle and azimuth angle data, extract signal-to-noise ratio, multipath, and frequency band data according to signal type, and perform time alignment processing on all station data; A dynamic signal-to-noise ratio (SNR) threshold model associated with elevation angle is adopted, and SNR anomaly detection, multipath anomaly detection, frequency band number anomaly detection, and data missing detection are performed according to signal type. Interference score is calculated based on each detection result, and at least the station, time, signal type, elevation angle, azimuth angle, and interference score of each interference event are recorded. Interference events are grouped by time window, and interference events within each time window are grouped by station. When interference events exist at least at two stations within the same time window, the spatial influence range of the interference corresponding to that time window is calculated, including the center location, influence radius, and confidence level.

2. The method for analyzing the interference impact range based on multi-station GNSS data according to claim 1, characterized in that, In the dynamic signal-to-noise ratio threshold model, the dynamic signal-to-noise ratio threshold is calculated based on the elevation angle of the current epoch, and the dynamic signal-to-noise ratio threshold changes linearly with the sine value of the elevation angle.

3. The method for analyzing the interference impact range based on multi-station GNSS data according to claim 1, characterized in that, The data missing detection includes: constructing a complete time series for each signal type combination; if there is no observation value in the current epoch, but the most recent epoch with data in the epoch consistent with the current combination has an observation value, it is initially determined to be data missing; if the corresponding elevation angle is within a preset effective range and the time interval meets the preset requirements, it is confirmed to be data missing, and a data missing score is calculated based on the time interval.

4. The method for analyzing the interference impact range based on multi-station GNSS data according to claim 1, characterized in that, The interference score calculation includes: adding the severity of signal-to-noise ratio (SNR) anomalies, the severity of multipath anomalies, the severity of frequency band anomalies, and the data missing score for the same epoch, station, and combination to obtain the interference score; wherein, the severity of SNR anomalies is determined based on the difference between the SNR threshold and the observed SNR value, the severity of multipath anomalies is determined based on the difference between the observed multipath values ​​and the multipath threshold and has an upper limit, and the severity of frequency band anomalies is determined based on the difference between the minimum number of frequency points and the actual number of frequency points.

5. The method for analyzing the interference impact range based on multi-station GNSS data according to claim 1, characterized in that, The calculation of the center location of the spatial influence range of interference includes: taking the sum of the interference scores of each station within the time window as the weight, and then performing a weighted average of the longitude and latitude of the stations to obtain the center longitude and center latitude.

6. The method for analyzing the interference impact range based on multi-station GNSS data according to claim 1, characterized in that, The calculation of the center location of the interference spatial influence range also includes: when the number of affected stations reaches a preset threshold, selecting several stations with the highest interference scores, calculating the azimuth ray based on the position and azimuth of each station, finding the intersection point of the ray and taking the average to obtain the center location, or averaging the center location with the weighted average to obtain the final center location.

7. The method for analyzing the interference impact range based on multi-station GNSS data according to claim 1, characterized in that, The confidence level is calculated based on the number of affected stations in the current time window, the total number of stations participating in the analysis, and the average interference score in the time window.

8. A system for analyzing the interference impact range based on multi-station GNSS data, characterized in that, include: The data reading and processing module is used to read observation data files from multiple stations, extract elevation angle and azimuth angle data, extract signal-to-noise ratio, multipath, and frequency band data according to signal type, and perform time alignment processing on all station data. The interference detection and scoring module is used to employ a dynamic signal-to-noise ratio threshold model associated with the elevation angle, and to perform signal-to-noise ratio anomaly detection, multipath anomaly detection, frequency band number anomaly detection, and data missing detection according to signal type. It calculates the interference score based on the detection results and records at least the station, time, signal type, elevation angle, azimuth angle, and interference score for each interference event. The spatial analysis module is used to group interference events by time window, and then group the interference events within each time window by station. When there are interference events at least two stations within the same time window, the module calculates the spatial impact range of the interference corresponding to that time window, including the center location, the radius of influence, and the confidence level.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the interference impact range analysis method based on multi-station GNSS data as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the interference impact range analysis method based on multi-station GNSS data as described in any one of claims 1 to 7.

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