Positioning terminal PPP-RTK real-time precise product monitoring method and device

Abstract

The application discloses a positioning end PPP-RTK real-time precision product monitoring method and device, and belongs to the technical field of satellite navigation and positioning. The method comprises the following steps: acquiring a PPP-RTK positioning result and a post-precise coordinate reference value in real time, calculating an ENU direction positioning deviation, fusing three types of parameters of satellite geometric configuration, product precision and data timeliness to generate a reliability index C, and dynamically adjusting an alarm threshold value according to the index C; establishing a positioning precision database to support rapid query and analysis; formulating a multi-level alarm rule for positioning continuity and precision overrun, and presetting a diagnosis item mapping relationship; automatically executing data recording, root cause diagnosis and information output after triggering the alarm, and realizing full-process automation from abnormal sensing to root cause diagnosis. Through the three-layer intelligent closed-loop system of "evaluation-prediction-diagnosis", the reliability, stability and operation and maintenance efficiency of the PPP-RTK positioning service are significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of satellite navigation and positioning technology, specifically relating to a PPP-RTK real-time precision product monitoring method and device for positioning terminals. Background Technology

[0002] Regional augmented precise point positioning (PPP-RTK) technology, as an important development direction in the field of Global Navigation Satellite Systems (GNSS), integrates the technical advantages of precise point positioning (PPP) and network real-time dynamic positioning (RTK). It generates and broadcasts state-space representation (SSR) correction information through a regional reference network, enabling users to achieve fast and high-precision point positioning over a wide area. This technology shows broad application prospects in fields with extremely high requirements for real-time performance and reliability, such as surveying and exploration, intelligent transportation, precision agriculture, and autonomous driving.

[0003] However, the actual positioning performance of the PPP-RTK system is constrained by a variety of factors. Besides common issues such as satellite signal propagation errors, receiver noise, and multipath effects, the quality of its core SSR (Search Engine Response) enhancement products—including the accuracy and completeness of orbit and clock corrections, and the timeliness of data transmission—has a decisive impact on the convergence speed, stability, and final accuracy of the positioning results. Especially in complex observation environments or under space weather disturbances, anomalies or interruptions in SSR products often directly lead to a decline in positioning performance or even service failure.

[0004] Currently, performance monitoring of PPP-RTK systems largely focuses on server-side product quality assessment, lacking real-time and continuous monitoring methods for user-end positioning effectiveness. Traditional methods often only focus on a single parameter (such as DOP value or data latency), failing to comprehensively reflect the overall reliability of positioning results. This leads to insufficient flexibility in alarm mechanisms, high false alarm rates, and difficulty in timely pinpointing the root cause of problems. As PPP-RTK technology gradually moves towards large-scale commercial use, building an automated monitoring system capable of real-time detection of positioning anomalies, intelligent diagnosis of fault causes, and support for operational and maintenance decisions has become a key challenge for improving system reliability and service capabilities.

[0005] Therefore, there is an urgent need to develop a real-time monitoring method that takes terminal positioning performance as the core and integrates multi-source information to achieve a closed-loop process from "anomaly detection" to "root cause diagnosis", providing technical support for the high availability and robust operation of the PPP-RTK system. Summary of the Invention

[0006] To address the aforementioned technical issues, this invention provides a method and apparatus for real-time precision product monitoring using PPP-RTK positioning. By constructing an overall monitoring and evaluation architecture centered on the terminal's PPP-RTK positioning performance, it enables real-time and continuous monitoring and maintenance of PPP-RTK positioning performance, thereby improving the reliability and stability of positioning services.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for real-time precision product monitoring using PPP-RTK positioning, the method comprising:

[0009] Step S1: Obtain the real-time positioning results and precise coordinate reference values ​​of PPP-RTK, calculate the positioning deviation of ENU direction, integrate three types of parameters: satellite geometry, product accuracy and data timeliness, generate a quantitative credibility index, and dynamically adjust the alarm threshold of ENU in each direction according to the credibility index.

[0010] Step S2: Establish a structured positioning accuracy database to store timestamps, coordinate deviations, accuracy indicators, and environmental parameters;

[0011] Step S3: For location continuity anomalies, formulate hierarchical alarm rules based on duration; for accuracy exceeding limits anomalies, determine alarm levels based on ENU alarm thresholds in each direction; wherein, the database has preset upstream state diagnostic items corresponding to each alarm level, forming a mapping relationship between alarm levels and potential root causes.

[0012] Step S4: After real-time comparison triggers an alarm, the system automatically performs closed-loop processing of data recording, root cause diagnosis, information association, and encrypted transmission, and outputs structured alarm information that integrates fault phenomena, environmental context, and confirmed root causes.

[0013] On the other hand, the present invention provides a positioning-end PPP-RTK real-time precision product monitoring device, comprising:

[0014] The calculation module is used to obtain the real-time positioning results and precise coordinate reference values ​​of PPP-RTK, calculate the positioning deviation of ENU direction, integrate three types of parameters: satellite geometry, product accuracy and data timeliness, generate a quantitative credibility index, and dynamically adjust the alarm threshold of ENU in each direction according to the credibility index.

[0015] The storage module is used to establish a structured positioning accuracy database, storing timestamps, coordinate deviations, accuracy indicators, and environmental parameters.

[0016] The alarm module is used to formulate hierarchical alarm rules based on duration for abnormal positioning continuity; and to determine the alarm level based on the alarm thresholds in each direction of ENU for abnormal accuracy. The database has preset upstream state diagnostic items corresponding to each alarm level, forming a mapping relationship between alarm level and potential root cause.

[0017] The output module is used to automatically perform closed-loop processing of data recording, root cause diagnosis, information association and encrypted transmission after real-time comparison and alarm triggering, and output structured alarm information that integrates fault phenomena, environmental context and confirmed root causes.

[0018] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned positioning end PPP-RTK real-time precision product monitoring method.

[0019] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned positioning end PPP-RTK real-time precision product monitoring method.

[0020] The beneficial effects of this invention are as follows:

[0021] This invention constructs a three-layer intelligent closed-loop system of "evaluation-prediction-diagnosis" to achieve real-time, continuous monitoring and intelligent operation and maintenance of PPP-RTK positioning performance. The system dynamically adjusts alarm thresholds based on a multi-dimensional reliability index C, exhibiting environmental adaptability, effectively reducing false alarm rates, and improving monitoring sensitivity. Through deep coupling of multi-level alarm rules with upstream status, it achieves trigger-based diagnosis, rapidly outputting root causes and significantly improving operation and maintenance efficiency. This system effectively enhances the reliability and stability of positioning services and can be widely applied to high-precision positioning scenarios such as precision measurement and autonomous driving, demonstrating significant practical application value. Attached Figure Description

[0022] Figure 1 This is a flowchart of a PPP-RTK real-time precision product monitoring method for positioning terminals according to the present invention. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] This invention proposes a method and device for real-time precision product monitoring using PPP-RTK positioning, primarily aimed at monitoring the quality of BeiDou augmentation information products. It constructs a comprehensive monitoring and evaluation architecture centered on the terminal's PPP-RTK positioning performance, forming a monitoring and alarm mechanism focused on the continuity and reliability of PPP-RTK positioning results. This mechanism promptly detects data anomalies and issues early warnings, enabling real-time operation and maintenance monitoring of the terminal and completing the monitoring and evaluation of the positioning performance of cloud-based products. Figure 1 As shown, the specific technical solution is as follows:

[0025] Step S1, Real-time accuracy calculation and reliability assessment: Obtain the real-time positioning results of PPP-RTK and the post-event precise coordinate reference value, calculate the ENU directional positioning deviation, integrate three types of parameters: satellite geometry, product accuracy and data timeliness, generate a quantitative reliability index C, and dynamically adjust the alarm thresholds in each direction according to the C value to achieve environmentally adaptive monitoring sensitivity control.

[0026] Calculate the accuracy of PPP-RTK real-time positioning results and evaluate the overall reliability of the current positioning solution in real time. Obtain the PPP-RTK real-time positioning results of the station and calculate the real-time positioning accuracy in the XYZ directions. Obtain the PPP-RTK real-time positioning results of the station based on PPP-RTK real-time corrections. Use the millimeter-level station coordinates obtained through high-precision post-processing software as reference coordinates to calculate the real-time accuracy of the station in the XYZ directions, and convert the real-time accuracy in the XYZ directions to the ENU directions in the Northeast-Northeast coordinate system. Perform dynamic reliability evaluation and adaptive alarm threshold generation. Existing technologies typically view DOP, product accuracy, or data latency in isolation. This invention innovatively integrates these three into a unified, quantified reliability index. The formula for the reliability index C is:

[0027] ,

[0028] ,

[0029] Among them, C [0,1]. C=1 represents the ideal situation, and C=0 represents completely unreliable. This value provides a quantitative basis for subsequent intelligent decision-making. The alarm thresholds in each direction are dynamically adjusted based on the C value to achieve environmentally adaptive monitoring sensitivity control. It is the normalized value of the geometrical accuracy attenuation factor (DOP), reflecting the impact of satellite geometry on positioning accuracy. It has a poor (minimum) geometric distribution with a value of 1. The optimal (maximum) geometric distribution has a value of 5. The standard deviation of the accuracy of corrections such as satellite orbit and clock bias provided for the product. This is the delay time for SSR data.

[0030] ,

[0031] in, It is a dynamic threshold. This is a static threshold (for example, setting the E direction to 0.2m and the U direction to 0.5m). The sensitivity coefficient is typically set to 0.4. This coefficient is used to calculate the dynamic alarm thresholds for each direction, effectively reducing the false alarm rate.

[0032] When the environment is reliable (C→1): (1-C)→0, The system uses strict raw thresholds for monitoring, because any exceeding of the limit at this time is likely a real fault, thus ensuring high monitoring sensitivity.

[0033] When the environment is unreliable (C→0): (1-C)→1, The system automatically relaxes the threshold. This is because the increased positioning error at this point is expected (e.g., due to ionospheric disturbances), thus greatly suppressing false alarms.

[0034] Sensitivity coefficient k: This is a configurable parameter that determines the extent to which the threshold is relaxed. The larger the k value, the more "tolerant" the system is in harsh environments. This design allows the invention to flexibly adapt to the needs of different users and different scenarios. For example, aviation users with extremely high safety requirements can choose a smaller k value, typically 0.4 for PPP-RTK real-time precision product positioning accuracy.

[0035] Step S2: Establish a positioning accuracy database to store real-time positioning accuracy data; create a new database on the server, and create a new table in the database to store real-time positioning accuracy data, recording the timestamp, coordinate deviation, accuracy indicators, and environmental parameters of each positioning; and optimize the design of the data index to support millisecond-level query response, providing data support for multi-dimensional historical data analysis and system performance evaluation.

[0036] Step S3: Formulate multi-level alarm rules for positioning continuity and accuracy exceeding limits based on the interruption time and the degree of accuracy deviation; including:

[0037] Establish a 5-level alarm rule for positioning continuity. When positioning is interrupted, determine the alarm level and perform a database interface query. Under the premise of no network interruption, there are two possible causes for positioning interruption: one is the interruption of the PPP-RTK real-time positioning program, and the other is the interruption of the observation data stream. Obtain the interruption information of the PPP-RTK real-time positioning program and the interruption information of the station data stream to determine the cause of the positioning interruption and send an email alarm.

[0038] When the real-time positioning result is interrupted for ≤5 minutes, the L1 alarm level will automatically query the status of the upper-level data stream information, including the interruption information of the PPP-RTK positioning program and the interruption information of the SSR product data stream. The alarm information will be uploaded to the database and sent via email.

[0039] When the real-time positioning result interruption time is ≤15min, the L2 alarm level will automatically query the status of the upper-level data stream information, including the interruption information of the PPP-RTK positioning program and the interruption information of the SSR product data stream. The alarm information will be uploaded to the database and sent via email.

[0040] When the real-time positioning result interruption time is ≤30min, the L3 alarm level will be activated, and the status of the upper-level data stream information will be automatically queried, including the interruption information of the PPP-RTK positioning program and the interruption information of the SSR product data stream. The alarm information will be uploaded to the database and sent via email.

[0041] When the real-time positioning result interruption time is ≤60min, the L4 alarm level will automatically query the status of the upper-level data stream information, including the interruption information of the PPP-RTK positioning program and the interruption information of the SSR product data stream. The alarm information will be uploaded to the database and sent via email.

[0042] When the real-time positioning result interruption time is ≤120min, the L5 alarm level will be activated, and the status of the upper-level data stream information will be automatically queried, including the interruption information of the PPP-RTK positioning program and the interruption information of the SSR product data stream. The alarm information will be uploaded to the database and sent via email.

[0043] Establish a 5-level alarm rule for accuracy exceeding limits, for example, the positioning accuracy requirements are: E<0.2m, N<0.2m, U<0.5m. Combined with the dynamic alarm threshold in step S1, when positioning accuracy exceeds limits, determine the alarm level, and then query the database to determine the cause of the exceedance. Assuming the positioning model is correct, there are generally two situations that lead to real-time positioning accuracy exceeding limits: SSR product data stream interruption and SSR product accuracy exceeding limits. Determine the cause of the accuracy exceedance and send an email alarm.

[0044] First, obtain the real-time accuracy. From step S1, obtain the deviations ΔE, ΔN, and ΔU in the E, N, and U directions calculated by PPP-RTK in real time. Then, obtain the corresponding dynamic thresholds T_dynamic(E), T_dynamic(N), and T_dynamic(U).

[0045] Unidirectional over-limit: If ΔX > T_dynamic(X) in any direction, trigger G1 alarm;

[0046] Bidirectional over-limit: If ΔX1>T_dynamic(X1) and ΔX2>T_dynamic(X2) in any two directions, trigger the G2 alarm;

[0047] Three-way over-limit: ΔX > T_dynamic(X) in all three directions E, N, and U, triggering the G3 alarm;

[0048] Significantly exceeding limits:

[0049] If ΔX > 1m in any direction, trigger alarm G4.

[0050] When ΔE, ΔN, and ΔU in all three directions are greater than 1m, the G5 alarm is triggered.

[0051] Query the database and the status of the parent SSR product: whether the SSR data stream is interrupted, whether the SSR product accuracy exceeds the limit, and determine the cause.

[0052] Step S4, Real-time Monitoring and Intelligent Alarm Output: The system continuously compares the location results with dynamic thresholds through the real-time monitoring module. When any level of alarm triggering condition is met, the following steps are automatically executed:

[0053] (1) Data recording steps: The alarm timestamp, real-time positioning deviation, credibility index C, dynamic threshold T_dynamic and satellite geometric configuration parameters are synchronously stored in the monitoring database;

[0054] (2) Root cause diagnosis steps: Automatically obtain the PPP-RTK solution process status, SSR data stream transmission status and precision product accuracy identifier by calling the system application interface;

[0055] (3) Alarm generation steps: The root cause information obtained from diagnosis is correlated with the location anomaly data to generate structured alarm information containing fault level, location deviation value, environmental confidence, dynamic threshold and confirmed root cause;

[0056] (4) Information output steps: The structured alarm information is transmitted to the operation and maintenance management terminal through an encrypted communication protocol to complete the fully automated processing from fault detection to root cause diagnosis.

[0057] On the other hand, the present invention provides a positioning-end PPP-RTK real-time precision product monitoring device, which includes various modules capable of implementing the various steps of the aforementioned method, specifically including:

[0058] The calculation module is used to obtain the real-time positioning results and precise coordinate reference values ​​of PPP-RTK, calculate the positioning deviation of ENU direction, integrate three types of parameters: satellite geometry, product accuracy and data timeliness, generate a quantitative credibility index, and dynamically adjust the alarm threshold of ENU in each direction according to the credibility index.

[0059] The storage module is used to establish a structured positioning accuracy database, storing timestamps, coordinate deviations, accuracy indicators, and environmental parameters.

[0060] The alarm module is used to formulate hierarchical alarm rules based on duration for abnormal positioning continuity; and to determine the alarm level based on the alarm thresholds in each direction of ENU for abnormal accuracy. The database has preset upstream state diagnostic items corresponding to each alarm level, forming a mapping relationship between alarm level and potential root cause.

[0061] The output module is used to automatically perform closed-loop processing of data recording, root cause diagnosis, information association and encrypted transmission after real-time comparison and alarm triggering, and output structured alarm information that integrates fault phenomena, environmental context and confirmed root causes.

[0062] Example:

[0063] An operator of a BeiDou ground-based augmentation system uses the method described in this invention to monitor the real-time performance of its PPP-RTK service. The system is deployed on a cloud server and continuously receives real-time PPP-RTK positioning results and post-event precise coordinate reference values ​​from multiple stations.

[0064] First, the system calculates the positioning deviation in the ENU direction for each station in real time, and generates a weighted reliability index C based on the current satellite geometry (DOP value), SSR product accuracy, and data latency (Δt). For example, if C = 0.7 at a certain moment, the system automatically increases the dynamic alarm thresholds in the E, N, and U directions to adapt to the current mild ionospheric disturbance environment.

[0065] Subsequently, the system stores the timestamp, coordinate deviation, C-value, and raw observation data into the indexed and optimized monitoring database. When a station experiences a positioning interruption for 10 minutes, the system triggers an L2-level continuity alarm, automatically queries the upstream service status, discovers an SSR data stream interruption, and then generates a structured alarm message, which is sent to the maintenance personnel via encrypted email, indicating "SSR data stream anomaly caused service interruption".

[0066] On another occasion, the system detected that the deviation in direction E at a certain station exceeded the dynamic threshold, triggering a G1-level accuracy alarm. The diagnostic module determined that the SSR product itself had exceeded its accuracy limits, and then recorded the event and issued an alarm. Throughout the entire process, the system achieved fully automated processing from anomaly detection, adaptive threshold adjustment, root cause diagnosis to information output, significantly improving the efficiency of operation and maintenance response and the reliability of positioning services.

[0067] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned positioning end PPP-RTK real-time precision product monitoring method.

[0068] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned positioning end PPP-RTK real-time precision product monitoring method.

[0069] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for real-time precision product monitoring using PPP-RTK positioning, characterized in that, The method includes: Step S1: Obtain the PPP-RTK real-time positioning results and precise coordinate reference values, calculate the positioning deviations in the three directions of ENU under the northeast-northeast coordinate system, integrate three types of parameters—satellite geometry, product accuracy, and data timeliness—to generate a quantified reliability index, and dynamically adjust the alarm thresholds in the three directions of ENU based on the reliability index. Step S2: Establish a structured positioning accuracy database, which includes storage timestamps, coordinate deviations, accuracy indicators, and environmental parameters. Step S3: For positioning continuity anomalies, formulate hierarchical alarm rules based on duration; for accuracy exceeding limits anomalies, determine the alarm level based on alarm thresholds in the three directions of ENU; wherein, the structured positioning accuracy database has preset upstream state diagnostic items corresponding to each alarm level, forming a mapping relationship between alarm level and potential root cause. Step S4: After real-time comparison triggers the alarm, the system automatically performs closed-loop processing of data recording, root cause diagnosis, information association and encrypted transmission, and outputs structured alarm information that integrates fault phenomena, environmental context and confirmed root causes. In step S1, the reliability index C is calculated by weighting the normalized satellite geometric accuracy attenuation factor, the standard deviation of SSR product accuracy, and the exponential attenuation term of SSR data delay time. ， ， Among them, C [0,1], It is the normalized satellite geometric accuracy attenuation factor. For the maximum geometric distribution, It is the minimum geometric distribution. For product accuracy standard deviation, SSR data delay time; The dynamic adjustment of the ENU alarm thresholds in three directions includes calculating the dynamic alarm thresholds in the three directions of the ENU according to the following formula: ， in, It is a dynamic threshold. This is a static threshold. The sensitivity coefficient is denoted as .

2. The PPP-RTK real-time precision product monitoring method for positioning terminals according to claim 1, characterized in that, In step S3, the hierarchical alarm rules for location continuity include five levels, from L1 to L5, which are divided according to the duration of the interruption of the PPP-RTK real-time location result: an interruption time of no more than 5 minutes is an L1 level alarm, an interruption time of more than 5 minutes but no more than 15 minutes is an L2 level alarm, an interruption time of more than 15 minutes but no more than 30 minutes is an L3 level alarm, an interruption time of more than 30 minutes but no more than 60 minutes is an L4 level alarm, and an interruption time of more than 60 minutes but no more than 120 minutes is an L5 level alarm.

3. The PPP-RTK real-time precision product monitoring method for positioning terminals according to claim 1, characterized in that, In step S3, the graded alarm rules for accuracy exceeding limits include five levels, from G1 to G5, which are divided according to the number of directions exceeding the limit and the magnitude of the exceedance: a G1 level alarm is triggered when the positioning deviation in a single direction exceeds the dynamic threshold of that direction; a G2 level alarm is triggered when the positioning deviations in any two directions exceed their corresponding dynamic thresholds; a G3 level alarm is triggered when the positioning deviations in all three directions (ENU) exceed their corresponding dynamic thresholds; a G4 level alarm is triggered when the positioning deviation in a single direction exceeds 1 meter; and a G5 level alarm is triggered when the positioning deviations in all three directions (ENU) exceed 1 meter.

4. The PPP-RTK real-time precision product monitoring method for positioning terminals according to claim 1, characterized in that, In step S4, after an alarm is triggered, an email notification containing the alarm event and the cause of the anomaly is automatically generated and sent according to the alarm level.

5. A positioning-end PPP-RTK real-time precision product monitoring device, applied to the positioning-end PPP-RTK real-time precision product monitoring method according to any one of claims 1-4, characterized in that, include: The calculation module is used to obtain the real-time positioning results and precise coordinate reference values ​​of PPP-RTK, calculate the positioning deviation of the three directions of ENU under the northeast-northeast coordinate system, integrate three types of parameters such as satellite geometry, product accuracy and data timeliness, generate a quantitative credibility index, and dynamically adjust the alarm threshold of the three directions of ENU according to the credibility index. A storage module is used to establish a structured positioning accuracy database, which includes storage timestamps, coordinate deviations, accuracy indicators, and environmental parameters. The alarm module is used to formulate hierarchical alarm rules based on duration for abnormal positioning continuity; and to determine the alarm level based on the alarm thresholds in the three directions of ENU for abnormal accuracy. The structured positioning accuracy database has preset upstream state diagnostic items corresponding to each alarm level, forming a mapping relationship between alarm level and potential root cause. The output module is used to automatically perform closed-loop processing of data recording, root cause diagnosis, information association and encrypted transmission after real-time comparison and alarm triggering, and output structured alarm information that integrates fault phenomena, environmental context and confirmed root causes.

6. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement the positioning terminal PPP-RTK real-time precision product monitoring method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, It stores executable instructions, which, when executed by a processor, enable the processor to implement the positioning end PPP-RTK real-time precision product monitoring method as described in any one of claims 1-4.

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