Positioning operation and maintenance platform and method

Abstract

The invention provides a positioning operation and maintenance platform and method, and relates to the technical field of satellite positioning system operation and maintenance. The positioning operation and maintenance platform comprises a basic system which is used for collecting observation station data and system operation data of a positioning service full link provided by a space-ground integrated positioning service system in real time; the monitoring system is used for performing anomaly monitoring by applying a big data analysis technology and an anomaly detection algorithm based on deep learning based on the observation station data and the system operation data acquired from the basic system, and triggering an alarm mechanism when an anomaly occurs; the analysis system is used for performing quality analysis by using a fused observation station data processing technology based on the observation station data acquired from the basic system to form a data quality analysis report; and the operation and maintenance system is connected with the space-ground integrated positioning service system and is used for carrying out iterative updating and playback of an algorithm version on the positioning algorithm of the space-ground integrated positioning service system. The air-ground integrated positioning service platform is operated and maintained, and stable operation of the air-ground integrated positioning service platform is guaranteed.

Description

Technical Field

[0001] This application relates to the technical field of satellite positioning system operation and maintenance, and particularly to a positioning operation and maintenance platform and method. Background Art

[0002] With the development of satellite technology, the concept of "space-ground integrated high-precision positioning" represented by the "satellite + ground station" technology has been technically verified in the past few years, opening up a mature path for formal commercialization. In the mass consumption field, a new model of "constellation + Internet + other industries" characterized by integration is being constructed, which will drive the transformation of people's production and living styles. In specific industries, satellite positioning technology integrates the upstream and downstream of the supply chain, provides vertical solutions, and realizes services at the sub-meter, centimeter, and even millimeter levels.

[0003] Due to its data stream characteristics, high-precision positioning services have the characteristics of low latency and no data retransmission. In order to ensure the provision of highly available services, it is necessary to build a professional operation and maintenance management system, improve business processes, standardize business operations, and ensure the security and stability of the business. Summary of the Invention

[0004] Embodiments of this application provide a positioning operation and maintenance platform and method to achieve the effect of efficiently and comprehensively operating and maintaining the space-ground integrated positioning service system.

[0005] In a first aspect, embodiments of this application provide a positioning operation and maintenance platform, including:

[0006] A basic system for real-time collecting station data and system operation data of the entire link of the positioning service provided by the space-ground integrated positioning service system;

[0007] A monitoring system for performing anomaly monitoring based on the station data and system operation data obtained from the basic system by using big data analysis technology and an anomaly detection algorithm based on deep learning, and triggering an alarm mechanism when an anomaly occurs;

[0008] An analysis system for performing quality analysis on the basis of the station data obtained from the basic system by using a fused station data processing technology to form a data quality analysis report;

[0009] An operation and maintenance system connected to the space-ground integrated positioning service system for iteratively updating and replaying the algorithm version of the positioning algorithm of the space-ground integrated positioning service system.

[0010] In a possible implementation manner, the operation and maintenance system is specifically used for:

[0011] Automatically triggering a test process for the submitted positioning algorithm, where the test process includes a data processing process test, a parameter setting test, and a deployment link test;

[0012] Use a version control system for version management;

[0013] Adopt the module division of the microservice system, create independent branches for each version of the positioning algorithm, and integrate with the continuous integration tool using the hook mechanism;

[0014] Use a version management database to record the update information of the positioning algorithm. The update information includes algorithm code, core metadata related to the version, detailed code change history of the algorithm, and code difference analysis results of different versions;

[0015] Use a batch deployment tool to perform distributed deployment and configuration of the positioning algorithm.

[0016] In a possible implementation, the version management database includes a relational database and a non-relational database. Among them, the relational database stores at least the algorithm code and core metadata related to the version; the non-relational database stores at least the detailed code change history of the algorithm and the code difference analysis results of different versions.

[0017] In a possible implementation, the data processing flow test includes: using simulated data combined with actual acquisition data obtained from the message queue to automatically write customized test cases to test the processing ability and accuracy of the positioning algorithm on each microservice node under different data scales and types;

[0018] Parameter setting test includes: using a distributed test tool to test the data interaction interface between the positioning algorithm and the external system; performing unit tests on the functional modules inside the positioning algorithm to cover various possible input situations and boundary conditions;

[0019] Deployment link test includes: setting up a multi-stage test environment, simulating the production environment to deploy a complete microservice architecture using container technology, dynamically adjusting configuration parameters to restore the real running scenario; deploying the algorithm microservice on some real server nodes, realizing service registration and invocation through the service registration and discovery mechanism, monitoring the performance of the positioning algorithm in the actual business, and collecting user feedback and system operation data.

[0020] In a possible implementation, the operation and maintenance system is also used for:

[0021] Playback multiple versions of the positioning algorithm with the same parameter settings in the same deployment environment;

[0022] And / or, based on a preset performance evaluation index system, call the microservice system to perform performance analysis on multiple versions of the positioning algorithm, and generate a performance analysis report for comparing the performance of multiple versions of the positioning algorithm.

[0023] In a possible implementation, the analysis system is specifically used for:

[0024] Based on the signal enhancement algorithm that combines wavelet transform and adaptive filtering, separate and strengthen the useful signals in the station data, and suppress the noise interference in the station data;

[0025] Based on the multipath cancellation algorithm that combines multi-base station joint solution and ray tracing technology, determine the multipath errors in the useful signals caused by multipath effects, and perform error correction on the useful signals based on the multipath errors to obtain the error correction signals corresponding to the station data;

[0026] Based on the antenna calibration model that combines electromagnetic simulation and field calibration, determine the antenna offset in the error correction signals, and perform offset correction on the error correction signals based on the antenna offset to obtain the offset correction signals corresponding to the station data;

[0027] According to the offset correction signals, determine the signal strength and signal-to-noise ratio corresponding to the station data;

[0028] According to the preset signal quality scoring mechanism, score the multipath errors, antenna offsets, signal strengths, and signal-to-noise ratios of the station data to form a data quality analysis report.

[0029] In a possible implementation, the analysis system is further used for:

[0030] According to the data quality analysis report, call the expert system to generate an optimization report for the space-ground integrated positioning service system, and the expert system is used to generate the optimization report based on the data quality analysis report.

[0031] In a possible implementation, the basic system is specifically used for:

[0032] Capture signals from different satellite constellations and each frequency point in the space-ground integrated positioning service system through the sensor matrix to obtain the station data and system operation data of the entire positioning service link;

[0033] And, based on the highly reliable transmission protocol that combines forward error correction coding and retransmission mechanism, transmit the corresponding station data or system operation data to the monitoring system and the analysis system.

[0034] In a possible implementation, the operation and maintenance system is further used for:

[0035] Automated operation and maintenance work orders, where the automated operation and maintenance work orders include automatically parsing the work order content based on natural language processing technology and a preset definition rule library, and classifying the work orders according to the work order content; based on the dynamic work order allocation algorithm, combined with the skill portraits of operation and maintenance personnel, workload balance, and geographical location, automatically match the work order operation and maintenance objects;

[0036] And / or, the full life cycle operation and maintenance management of supplier information, including qualification review, contract management, service performance evaluation function, automatically associating suppliers according to the work order content, and initiating collaboration with suppliers.

[0037] In a second aspect, the embodiments of the present application provide a positioning operation and maintenance method, which is applied to the operation and maintenance system in the positioning operation and maintenance platform in the first aspect and / or various possible implementation manners of the first aspect. The positioning operation and maintenance method includes:

[0038] In response to the submission instruction of the positioning algorithm, automatically trigger the test process for the submitted positioning algorithm. The test process includes data processing process test, parameter setting test, and deployment link test, and perform the following processing on the positioning algorithm:

[0039] Use a version control system to manage the version of the positioning algorithm;

[0040] Adopt the module division of the microservice system to create an independent branch for the positioning algorithm version;

[0041] Use a version management database to record the update information of the positioning algorithm. The update information includes algorithm code, core metadata related to the version, detailed code change history of the algorithm, and code difference analysis results of different versions;

[0042] Use a batch deployment tool to perform distributed deployment and configuration on the positioning algorithm;

[0043] Based on a preset performance evaluation index system, call the microservice system to perform performance analysis on the positioning algorithm and generate a performance analysis report corresponding to the positioning algorithm.

[0044] In a possible implementation manner, the version management database includes a relational database and a non-relational database. Using the version management database to record the update information of the positioning algorithm includes:

[0045] Store the algorithm code of the newly submitted positioning algorithm and the core metadata related to the version in the relational database;

[0046] Store the detailed code change history of the newly submitted positioning algorithm and the code difference analysis results with the previous version in the non-relational database.

[0047] In a possible implementation manner, the positioning operation and maintenance method further includes:

[0048] In the same deployment environment, with the same parameter settings, replay multiple versions of the positioning algorithm, and the multiple versions of the positioning algorithm include the newly submitted positioning algorithm.

[0049] In a possible implementation manner, the positioning operation and maintenance method further includes:

[0050] Based on natural language processing technology and a preset definition rule library, automatically parse the work order content and classify the work orders according to the work order content; based on a dynamic work order allocation algorithm, combined with the skill portraits of operation and maintenance personnel, workload balance, and geographical location, automatically match the operation and maintenance objects of the work orders;

[0051] And / or, perform operation and maintenance management of the entire life cycle of supplier information, including qualification review, contract management, service performance evaluation functions, automatically associate suppliers according to the work order content, and initiate collaboration with suppliers.

[0052] Thirdly, the embodiment of the present application provides a positioning operation and maintenance method, which is applied to the analysis system in the first aspect and / or various possible implementation manners of the first aspect. The positioning operation and maintenance method includes:

[0053] Receive the station data sent by the basic system in the positioning operation and maintenance platform. The station data includes the station data of the entire positioning service link provided by the space-earth integrated positioning service system;

[0054] Use the integrated station data processing technology to perform quality analysis and form a data quality analysis report.

[0055] In a possible implementation manner, using the integrated station data processing technology to perform quality analysis and form a data quality analysis report includes:

[0056] Based on the signal enhancement algorithm that combines wavelet transform and adaptive filtering, separate and strengthen the useful signals in the station data and suppress the noise interference in the station data;

[0057] Based on the multipath elimination algorithm of multi-base station joint solution and ray tracing technology, determine the multipath error caused by the multipath effect in the useful signals, and perform error correction on the useful signals based on the multipath error to obtain the error correction signal corresponding to the station data;

[0058] Based on the antenna calibration model of electromagnetic simulation and field calibration, determine the antenna offset in the error correction signal, and perform offset correction on the error correction signal based on the antenna offset to obtain the offset correction signal corresponding to the station data;

[0059] According to the offset correction signal, determine the signal strength and signal-to-noise ratio corresponding to the station data;

[0060] According to the preset signal quality scoring mechanism, score the multipath error, antenna offset, signal strength, and signal-to-noise ratio of the station data to form a data quality analysis report.

[0061] In a possible implementation manner, the positioning operation and maintenance method further includes:

[0062] According to the data quality analysis report, an expert system is invoked to generate an optimization report for the space-ground integrated positioning service system. The expert system is used to generate the optimization report based on the data quality analysis report.

[0063] The positioning operation and maintenance platform and method provided by the embodiments of the present application set up a basic system to collect the station data and system operation data in the space-ground integrated positioning service system. The monitoring system uses an anomaly monitoring algorithm based on deep learning and big data technology to perform anomaly monitoring on the positioning data and system operation data. Through the integration of multi-level monitoring and alarm systems, real-time monitoring and alarm of the entire positioning service network are realized from end to end. The efficiency of anomaly handling is improved. The analysis system widely integrates station data processing technologies and can automatically generate a station data quality analysis report for the entire constellation and all frequency points, analyze the quality of the positioning data, and provide a reliable basis for the optimization of the positioning service. The operation and maintenance system performs iterative update and playback management on the algorithms in the space-ground integrated positioning service system to ensure the stable operation of the algorithms in the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0065] Figure 1 It is a schematic diagram of the usage scenario of the positioning operation and maintenance platform provided by the embodiments of the present application;

[0066] Figure 2 It is a schematic diagram of the structure of the positioning operation and maintenance platform provided by the embodiments of the present application;

[0067] Figure 3 It is a schematic diagram of the flow of the positioning operation and maintenance method provided by the embodiments of the present application;

[0068] Figure 4 It is a schematic diagram of the software architecture of the positioning operation and maintenance platform provided by the embodiments of the present application;

[0069] Figure 5 It is a schematic diagram of the functional architecture of the positioning operation and maintenance platform provided by the embodiments of the present application.

[0070] Through the above-mentioned accompanying drawings, the clear embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and text descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0072] With the development of commerce and technology and the outbreak of new demands in material civilization, the traditional relationship between people has gradually expanded to the relationship between people and things, and between things and things. Technologies that were originally in high-end industrial chains or large enterprises, such as satellite positioning technology, have increasingly entered people's lives and daily work. With the continuous enrichment of application scenarios and the diversified development of technology applications, satellite positioning technology has spread throughout all aspects of life. Different from traditional pure satellite positioning or pure ground base station positioning, with the development of satellite technology, the concept of "space-ground integrated high-precision positioning" represented by the "satellite + ground station" technology has been technically verified and opened the mature path of formal commercialization. Efficiently and comprehensively operating and maintaining the increasingly popular space-ground integrated high-precision positioning service system and ensuring its stable operation have become technical problems to be solved urgently.

[0073] The present application provides a positioning operation and maintenance platform, which includes a basic system, a monitoring system, an analysis system, and an operation and maintenance system. The basic system obtains the station data and system operation data of the entire positioning service link provided by the space-ground integrated positioning service system. The monitoring system uses big data analysis technology and anomaly monitoring algorithms based on deep learning to monitor anomalies in the positioning data and system operation data obtained by the basic module. The analysis system performs data quality analysis on the positioning data obtained by the basic module. The operation and maintenance system is used to manage the positioning algorithms of the space-ground integrated positioning service. Through the above technical means, anomaly monitoring, data quality analysis, and positioning algorithm operation and maintenance management of the space-ground integrated positioning system are realized, ensuring the stable operation of the space-ground integrated positioning system.

[0074] In some embodiments, the application scenarios of the positioning operation and maintenance platform provided by the embodiments of the present application are as Figure 1 shown. The space-ground integrated positioning service system 11 includes software and hardware devices such as satellites 111, ground base stations 112, and a positioning service platform 113. The positioning operation and maintenance platform 12 is connected to each device in the space-ground integrated positioning service system 11 in a wired or wireless manner, can collect data of each device in the space-ground integrated positioning service system 11, and can also transmit data to each device. The positioning operation and maintenance platform 12 can generate display information and display it on the display device 13. Exemplarily, the display device 13 may include a mobile device, a personal computer terminal, or a monitoring large screen.

[0075] In one embodiment, asFigure 2 As shown in the figure, the positioning operation and maintenance platform 20 includes: a basic system 21, a monitoring system 22, an analysis system 23, and an operation and maintenance system 24.

[0076] Among them, the basic system 21 is used to collect in real time the station data and system operation data of the entire positioning service link provided by the space-ground integrated positioning service system.

[0077] The monitoring system 22 is used to monitor the anomalies in the positioning data and system operation data based on the station data and system operation data obtained from the basic system 21, using big data analysis technology and anomaly detection algorithms based on deep learning, and trigger an alarm mechanism when an anomaly occurs.

[0078] The analysis system 23 is used to perform quality analysis on the basis of the station data obtained from the basic system 21 by using the integrated station data processing technology to form a data quality analysis report.

[0079] The operation and maintenance system 24 is used to manage the positioning algorithms of the space-ground integrated positioning service system, and the management includes iterative updates and playback of algorithm versions.

[0080] Specifically, the basic system 21 includes various collectors installed at key nodes of satellite receiving devices, data transmission lines (such as routers, switches, etc.), and algorithm processing servers. The collectors can collect the station data and system operation data of the entire positioning service link provided by the space-ground integrated positioning service system. Exemplarily, the system operation data can be parameters such as the packet loss rate of data transmission, the CPU usage rate of algorithm processing, and the memory occupancy, serving as the basic data source of the monitoring system. In addition to collecting the station data and system operation data, the basic module will also sort and package the above data, and use the optimized User Datagram Protocol (UDP) to transmit the data to the monitoring system 22 and the analysis system 23. The optimized UDP protocol refers to optimizing the UDP protocol on the basis of the UDP protocol by using the integrated error correction coding technology and retransmission mechanism to reduce the bit error rate and packet loss rate.

[0081] The monitoring system 22 is built-in with an anomaly monitoring algorithm module based on deep learning, which is trained by a large amount of historical data and can automatically identify anomalies in satellite positioning data and system operation data. At the same time, big data analysis technology is used to analyze and predict massive positioning data and system data to assist in identifying anomalies and risks in the data. When an anomaly or risk is identified, the monitoring module triggers an alarm mechanism, generates a warning message, and sends the warning message to the display device to push the monitoring results and warning message to the operation and maintenance personnel in the form of charts and alarm indicators. At the same time, the positioning operation and maintenance platform 20 will record detailed monitoring data and alarm logs, which is convenient for the operation and maintenance personnel to conduct subsequent analysis and troubleshooting. Through this close cooperation from the infrastructure layer to the presentation layer, real-time full-link monitoring of all links from the data source to the application layer is achieved, effectively ensuring the stability and reliability of the high-precision positioning service. Optionally, as Figure 2 shown, the positioning operation and maintenance platform 20 may further include a resource management system 25, which is used to store alarm information, abnormal positioning data, and / or system operation data, and can also store the information of each software and hardware in the space-earth integrated positioning service system, facilitating the management of the space-earth integrated positioning service system.

[0082] For the space-earth integrated positioning service system, the signal quality of the measurement station has a great impact on the positioning service. Therefore, the positioning operation and maintenance platform 20 provided in this application deploys a sensor matrix with high sensitivity and wide frequency band characteristics in the infrastructure of the space-earth integrated positioning service system. This matrix can accurately capture weak signals, that is, positioning data, from different satellite constellations and each frequency point, and uses the optimized UDP protocol to transmit the positioning data to the analysis system 23 of the operation and maintenance platform for quality analysis of the positioning data, thereby providing a theoretical basis for optimizing the system and improving the positioning service quality.

[0083] In addition, a large number of positioning-related algorithms are involved in the space-earth integrated positioning service system, and the system is implemented using a microservices framework. With the continuous optimization of the system, the update of algorithms is inevitable. Therefore, how to ensure the stable operation of the updated algorithms in the microservices framework system has become the key to the operation and maintenance of the space-earth integrated positioning service system. This application sets up an operation and maintenance system 24, which is used to manage the positioning algorithms of the space-earth integrated positioning service system. The management includes the iterative update and playback of algorithm versions, ensuring that the algorithms in the system continuously run with the optimal performance.

[0084] The positioning and operation and maintenance platform provided by the embodiments of the present application sets up a basic system to collect positioning data and system operation data in the space-ground integrated positioning service system. The monitoring system uses an anomaly monitoring algorithm based on deep learning and big data technology to perform anomaly monitoring on the positioning data and system operation data. By integrating multi-level monitoring and alarm systems, real-time monitoring and alarm of the entire positioning service network are realized from end to end. The analysis system widely integrates station data processing technology, can automatically generate station data quality analysis reports for the entire constellation and all frequency points, and provides a reliable basis for the optimization of positioning services. The operation and maintenance system iteratively updates and replays the management of the algorithms in the space-ground integrated positioning service system to ensure the stable operation of the algorithms in the system.

[0085] In a possible implementation manner, the operation and maintenance system is specifically used for: automatically triggering the test process of the submitted positioning algorithm, where the test process includes data processing process test, parameter setting test, and deployment link test; performing version management using a version control system; adopting the module division of a microservice system to create independent branches for each positioning algorithm version, and integrating with a continuous integration tool using a hook mechanism; using a version management database to record the update information of the positioning algorithm, where the update information includes algorithm code, core metadata related to the version, detailed code change history of the algorithm, and code difference analysis results of different versions; and using a batch deployment tool to perform distributed deployment and configuration on the positioning algorithm.

[0086] During the development process of the positioning algorithm, developers often only focus on the principle and processing logic of the positioning algorithm, and rarely consider the deployment process in the system after the algorithm development is completed. The space-ground integrated positioning service system adopts a microservice architecture and presents a distributed characteristic. In order to ensure the stable operation of the positioning algorithm in the system, after receiving the submission instruction of the algorithm, the present application will first test the algorithm. The test process includes data processing process test, parameter setting test, and deployment link test. Through the data processing process test, parameter setting test, and deployment link test, it can be verified that the positioning algorithm can be normally deployed and stably operated in the space-ground integrated positioning service system. Before the formal deployment, it is also necessary to manage and record the update information of the algorithm.

[0087] The algorithm implementation version control and management strategy adopts the Git version control system and combines with the module division of Spring Cloud microservices to create independent branches for each algorithm version. At the same time, the hook mechanism of Git is used to integrate with the Jenkins continuous integration tool. When submitting code each time, the build and test processes are automatically triggered, and the update content, modification reason, person in charge, and timestamp of each submission are detailedly recorded. Through branch management, it is convenient to compare the differences between different versions and trace the evolution process of the algorithm. In addition, a version management database is used to manage and record the algorithm update information.

[0088] After completing the update information management and recording of the algorithm, the algorithm is distributedly deployed and configured. A strict version release specification is formulated. During the release process, Ansible and Spring Cloud Deployer are combined to uniformly deploy and configure the algorithm on different microservice nodes, ensuring that the installation and configuration of the algorithm on different nodes are consistent and reducing human operation errors.

[0089] For the positioning operation and maintenance platform provided by the embodiments of this application, the operation and maintenance system conducts comprehensive data processing process testing, parameter setting testing, and deployment link testing on the updated algorithm to ensure that the algorithm can stably operate under the microservice architecture of the space-ground integrated positioning service system. The version control system, microservice system, and version management database are used to manage the algorithm update, making the algorithm update information clearer and improving the management efficiency. The batch deployment tool is used to batch deploy the algorithm to ensure the consistency of algorithm installation and configuration.

[0090] In a possible implementation manner, the version management database includes a relational database and a non-relational database. Among them, the relational database stores at least the algorithm code and core metadata related to the version; the non-relational database stores at least the detailed code change history of the algorithm and the code difference analysis results of different versions.

[0091] A version management database based on the combination of the relational database MariaDB and the non-relational database Elasticsearch is established. The algorithm code and core metadata related to the version are stored in MariaDB; by using the full-text search and efficient storage capabilities of Elasticsearch, information such as the detailed code change history of the algorithm and the code difference analysis results of different versions is stored, facilitating quick retrieval and comparison.

[0092] For the positioning operation and maintenance platform provided by the embodiments of this application, when the operation and maintenance center manages the algorithm update, the relational database and the non-relational database are used to manage the algorithm update information, making it more convenient and fast to retrieve algorithm information and compare algorithm update information.

[0093] In a possible implementation manner, the data processing process testing includes: using simulated data combined with the actual collected data obtained from the message queue to automatically write customized test cases to test the processing ability and accuracy of the positioning algorithm on each microservice node under different data scales and types;

[0094] The parameter setting testing includes: using a distributed testing tool to test the data interaction interface between the positioning algorithm and the external system; conducting unit testing on the functional modules inside the positioning algorithm to cover various possible input situations and boundary conditions.

[0095] Deployment phase testing includes: setting up a multi-stage test environment, simulating the production environment to deploy a complete microservice architecture using container technology, dynamically adjusting configuration parameters to restore the real operating scenario; deploying the algorithm microservice on some real server nodes, implementing service registration and invocation through the service registration and discovery mechanism, monitoring and locating the performance of the algorithm in actual business, and collecting user feedback and system operation data.

[0096] Specifically, for the data processing flow, use simulated data combined with actual acquisition data obtained from message queues such as Kafka. By writing customized test cases, test the processing ability and accuracy of the algorithm on each microservice node under different data scales and types to ensure that the conversion and calculation of data in each processing link in the distributed environment are correct.

[0097] For parameter setting, use Spring Cloud Contract and Selenium in coordination to test the data interaction interface between the algorithm and external systems to ensure the stability of data transmission when the algorithm is integrated with other microservice components; combine Pytest to conduct unit tests on the internal functional modules of the algorithm, covering all possible input situations and boundary conditions comprehensively, and promptly discover potential logical errors.

[0098] For the deployment phase, set up a multi-stage test environment, simulate the production environment to deploy a complete microservice architecture using Docker container technology, combine with the configuration center to dynamically adjust configuration parameters, and restore the real operating scenario as much as possible to comprehensively evaluate the performance and stability of the algorithm; the small-scale actual production environment pilot test deploys the algorithm microservice on some real server nodes, implements service registration and invocation through the service registration and discovery mechanism, observes the performance of the algorithm in actual business, and collects user feedback and system operation data to provide a basis for large-scale deployment.

[0099] The positioning operation and maintenance platform provided by the embodiment of this application fully verifies the stability of the positioning algorithm through data processing flow testing, parameter setting testing, and deployment phase testing, and ensures that the positioning algorithm is normally deployed and stably operates in the space-ground integrated positioning service system.

[0100] In a possible implementation manner, the operation and maintenance system is further used for:

[0101] In the same deployment environment, replay multiple versions of the positioning algorithm with the same parameter settings;

[0102] And / or, based on a preset performance evaluation index system, call the microservice system to perform performance analysis on the positioning algorithm and generate a performance analysis report corresponding to the positioning algorithm.

[0103] To provide a basis for subsequent system optimization, it is necessary to evaluate the performance of the algorithms that have been deployed in the system. In the positioning operation and maintenance platform, historical data and actual business cases can be used to replay and verify algorithms of different versions. Specifically, a scientific and reasonable performance evaluation index system that meets the requirements of high-precision positioning services is defined, including key indicators such as positioning accuracy, calculation speed, memory occupancy, and stability, and corresponding weights are assigned to each indicator to comprehensively evaluate the performance of the algorithm. Historical data and actual business cases are used to replay and verify algorithms of different versions. During the replay process, the same input data and operating environment settings are strictly followed to ensure the fairness of the comparison. By transmitting the algorithm processing result data to a dedicated data analysis microservice, intuitive comparative analysis is carried out.

[0104] A performance monitoring and analysis platform based on the Spring Cloud microservice architecture is established. On each microservice node where the algorithm runs, Spring Boot Actuator is used to expose performance metric endpoints, data collection is performed through Prometheus, and then data visualization is displayed through Grafana. At the same time, performance reports are generated regularly and stored in Elasticsearch for quick query and analysis, providing data support for the optimization and version selection of the algorithm, and ensuring that the algorithm version with the best performance and stability is always selected for application in high-precision positioning services.

[0105] For the positioning operation and maintenance platform provided in the embodiments of this application, the operation and maintenance system can replay the algorithm with the same deployment environment and parameter settings to compare the performance of algorithms of different versions, provide guidance for the selection of algorithms, perform performance analysis on the algorithms that have been deployed in the space-ground integrated positioning service platform, determine the algorithm version with the best performance, and form a performance analysis report to provide an intuitive basis for system optimization.

[0106] In a possible implementation manner, the analysis system is specifically used for:

[0107] Based on a signal enhancement algorithm that combines wavelet transform and adaptive filtering, separate and strengthen the useful signals in the station data and suppress the noise interference in the station data; based on a multipath cancellation algorithm that combines multi-base station joint solution and ray tracing technology, determine the multipath errors caused by multipath effects in the useful signals, and perform error correction on the useful signals based on the multipath errors to obtain the error correction signal corresponding to the station data; based on an antenna calibration model that combines electromagnetic simulation and on-site calibration, determine the antenna offset in the error correction signal, and perform offset correction on the error correction signal based on the antenna offset to obtain the offset correction signal corresponding to the station data; according to the offset correction signal, determine the signal strength and signal-to-noise ratio corresponding to the station data.

[0108] In a possible implementation manner, the analysis system specifically:

[0109] A signal enhancement algorithm based on the cooperation of wavelet transform and adaptive filtering separates and strengthens the useful signals in the station data and suppresses the noise interference in the station data.

[0110] Among them, wavelet transform (WT) is a new transform analysis method. It inherits and develops the idea of localizing the short-time Fourier transform, and at the same time overcomes the shortcomings such as the window size not changing with frequency. It can provide a "time-frequency" window that changes with frequency and is an ideal tool for signal time-frequency analysis and processing. Its main feature is that through the transform, it can fully highlight the characteristics of certain aspects of the problem, can perform local analysis of time (space) frequency, gradually refine the signal (function) through dilation and translation operations at multiple scales, and finally achieve fine time division at high frequencies and fine frequency division at low frequencies. It can automatically adapt to the requirements of time-frequency signal analysis, so it can focus on any details of the signal.

[0111] Adaptive filtering is under the condition that some signal characteristics are unknown. According to a certain optimal criterion, starting from the initial conditions determined by the known partial signal characteristics, it is recursively calculated according to a certain adaptive algorithm. After a certain number of recursions, it converges to the optimal solution in a statistical approximation manner. When the statistical characteristics of the input signal are unknown or the statistical characteristics of the input signal change. The adaptive filter can automatically iteratively adjust its own filter parameters to meet the requirements of a certain criterion, so as to achieve optimal filtering. Therefore, the adaptive filter has self-adjusting and tracking capabilities. In a non-stationary environment, the adaptive filter can also track the changes of the signal to a certain extent.

[0112] A multipath cancellation algorithm based on multi-base station joint solution and ray tracing technology determines the multipath error caused by the multipath effect in the useful signal, and corrects the error of the useful signal based on the multipath error to obtain the error correction signal corresponding to the station data.

[0113] Multipath propagation refers to the phenomenon that radio waves reach the receiver antenna through two or more paths during the transmission process. This phenomenon is caused by the reflection, refraction and scattering of electromagnetic waves when encountering various obstacles (such as buildings, mountains, etc.) during the propagation process. Multipath propagation will cause the multipath effect at the receiving end of the signal, and this effect will cause the signal to be distorted and even produce errors. Specifically, it is manifested as the amplitude change and fading of the signal, which will affect the quality and stability of communication. The multipath effect will cause interference and phase shift when the signal is received through multiple paths, and may cause the signal to become very weak in some areas and unable to be fully received.

[0114] Multi - base - station joint solution refers to jointly solving the position - relationship equations between multiple base stations and a target to calculate the position of the target, so as to determine the true target position from multiple false target positions generated by multipath effects.

[0115] Ray tracing is a technology widely used to predict the propagation characteristics of radio waves in mobile communication and personal communication environments. It can be used to identify all possible ray paths between the transmitter and the receiver in a multipath channel. Once all possible rays are identified, the amplitude, phase, delay, and polarization of each ray can be calculated according to the radio - wave propagation theory. Then, by combining the antenna pattern and the system bandwidth, the coherent - synthesis result of all rays at the receiving point can be obtained.

[0116] Based on the antenna calibration model of electromagnetic simulation and field calibration, determine the antenna offset in the error - correction signal, and perform offset correction on the error - correction signal based on the antenna offset to obtain the offset - corrected signal corresponding to the station data.

[0117] Antenna offset refers to the offset between the antenna phase center and the centroid of the object. This offset will bring centimeter - level errors to satellite positioning. In general positioning, this error can be ignored, but in precise positioning, the influence of this error needs to be eliminated. Using the antenna calibration model based on electromagnetic simulation and field calibration, the antenna offset in the error - correction signal can be identified, and further correction can be performed according to the antenna offset.

[0118] According to the offset - corrected signal, determine the signal strength and signal - to - noise ratio corresponding to the station data.

[0119] According to the preset signal - quality scoring mechanism, score the multipath error, antenna offset, signal strength, and signal - to - noise ratio of the station data to form a data - quality analysis report.

[0120] Optionally, a set of quality - scoring mechanisms is constructed. This mechanism covers multiple dimensions such as signal - strength scoring, signal - to - noise - ratio scoring, multipath - error scoring, data - integrity scoring, and time - synchronization - accuracy scoring. And for each dimension, reasonable weights and threshold ranges are determined based on strict industry standards and a large amount of historical - data statistical analysis. Through a complex weighted - calculation and logical - judgment process, accurate quality scores are generated for each set of station data.

[0121] Furthermore, after scoring the positioning data in multiple dimensions, an automated data - quality analysis report is generated according to the scoring information. Relying on the intelligent - template engine and data - visualization technology, a report with rich content and intuitive presentation form is created. The starting part of the report clearly lists the basic information of the station, covering key elements such as geographical location, equipment number, start and end times of data collection, etc. Intuitively present the specific values of various quality - scoring indicators, grade - assessment results, and the comparative - analysis situation with historical data.

[0122] The positioning and operation and maintenance platform provided by the embodiment of the present application, the analysis system uses a variety of signal processing methods to process the positioning signals, and finally obtains information such as multipath error, antenna offset, signal strength, and signal-to-noise ratio, provides information for subsequent signal quality analysis, and performs multi-dimensional quality scoring on the positioning data based on a quality scoring mechanism. According to the quality scoring results, a data quality analysis report with rich content and intuitive presentation form is automatically generated, providing a basis for system optimization. In a possible implementation manner, the analysis system is further configured to: according to the data quality analysis report, call an expert system to generate an optimization report for the space-ground integrated positioning service system, and the expert system is used to generate an optimization report based on the data quality analysis report.

[0123] Among them, the expert system is an intelligent computer program system, which contains a large amount of knowledge and experience at the expert level in the field of satellite positioning. It can apply artificial intelligence technology and computer technology, reason and judge according to the knowledge and experience in the system, and simulate the decision-making process of human experts to solve those complex problems that require human experts to handle.

[0124] Exemplarily, the expert system provides highly targeted and practical adjustment and optimization suggestions, such as adjusting the angle of the antenna, changing the parameters of the signal filter, checking the connection status of the data transmission line, etc., so as to timely adjust and optimize the station data and ensure the stable operation of the high-precision positioning service.

[0125] The positioning and operation and maintenance platform provided by the embodiment of the present application, according to the data quality analysis report, uses the expert system to intelligently generate an optimization report, providing a guiding basis for the stable operation and optimization of the space-ground integrated positioning service system.

[0126] In a possible implementation manner, the basic system is specifically configured to: capture signals from different satellite constellations and each frequency point through a sensor matrix to obtain station data and system operation data of the entire link of the positioning service; based on a highly reliable transmission protocol integrating error correction coding and retransmission mechanism, transmit the corresponding station data or system operation data to the monitoring system and the analysis system.

[0127] Based on the UDP protocol, the use of combined error correction coding technology and retransmission mechanism optimizes the UDP protocol to reduce the bit error rate and packet loss rate. The retransmission mechanism refers to implementing the retransmission logic in the application program, which usually involves the following steps: assigning a unique sequence number to each sent data packet; after receiving the data packet, the receiver sends an acknowledgment (ACK) message; timeout and retransmission, if the sender does not receive the acknowledgment message within a certain time, it will retransmit the data packet. In some specific application scenarios, the retransmission policy can be customized according to the specific network conditions, such as dynamically adjusting the timeout time according to the network status; dynamically adjusting the window size according to network feedback to optimize performance; using technologies such as cyclic redundancy check to detect data errors, and designing a simple error correction mechanism; in order to avoid network congestion, traffic control and congestion control mechanisms can be introduced.

[0128] Error correction coding, also known as channel coding, is a coding technology that can automatically detect or correct errors during data transmission. Its main purpose is to enable the receiver to automatically detect or correct errors that occur during transmission, thereby improving the reliability and stability of data transmission. In the communication between satellites and the earth, due to the long distance and complex environment, error correction coding can effectively reduce transmission errors.

[0129] The positioning and operation and maintenance platform provided by the embodiments of this application can comprehensively analyze the signal quality of the space-ground integrated positioning service system by comprehensively collecting the signals of each satellite constellation and each frequency point, and then obtain the basis for maintaining and optimizing the system. By using the combined error correction coding technology and retransmission mechanism, the UDP protocol is optimized to reduce the bit error rate and packet loss rate, and improve the reliability of the system.

[0130] In a possible implementation manner, the operation and maintenance system is also used for:

[0131] Automated operation and maintenance work orders, where the automated operation and maintenance work orders include automatically parsing the work order content based on natural language processing technology and a preset definition rule library, and classifying the work orders according to the work order content; based on a dynamic work order allocation algorithm, combining the skill portraits of operation and maintenance personnel, workload balance, and geographical location, automatically matching the work order operation and maintenance objects; and / or, the whole life cycle operation and maintenance management of supplier information, including qualification review, contract management, service performance evaluation functions, automatically associating suppliers according to the work order content, and initiating cooperation with suppliers.

[0132] Among them, the work order operation and maintenance object is an operation and maintenance personnel or an operation and maintenance team composed of multiple operation and maintenance personnel.

[0133] Optionally, the location operation and maintenance platform includes a resource management system. In the resource management system, an operation and maintenance personnel database is stored, which stores information such as operation and maintenance personnel skill portraits, workload balance, and geographical locations. Using natural language processing technology and a preset definition rule library, key information of the work order is obtained, and the key information is used to match the personnel in the operation and maintenance personnel database to determine relevant operation and maintenance personnel or operation and maintenance teams.

[0134] During the work order processing, it may not only involve human resources but also require material support. During the work order processing, suppliers can be automatically associated according to the problem type, and a collaboration request can be quickly initiated through the built-in communication channels of the system to track the processing progress.

[0135] Furthermore, the operation and maintenance system also has a function of work order statistics and download, providing multi-dimensional reports, such as work order processing efficiency reports statistically calculated by time, fault type, and supplier, to assist in operation and maintenance management decision-making, comprehensively improve operation and maintenance efficiency and quality, and shorten the fault response time.

[0136] The location operation and maintenance platform provided by the embodiment of the present application, with the intelligent allocation mechanism and the supplier collaboration function, ensures the efficient utilization of resources and the timely solution of problems, significantly enhances operation and maintenance efficiency and service continuity, and effectively improves the overall operation and maintenance effectiveness.

[0137] In one implementation manner, the embodiment of the present application provides a location operation and maintenance method, which applies the operation and maintenance system in the location operation and maintenance platform in various possible implementation manners of the above embodiment. The location operation and maintenance method includes: in response to the submission instruction of the location algorithm, automatically triggering a test process for the submitted location algorithm. The test process includes a data processing process test, a parameter setting test, and a deployment link test, and the following processing is performed on the location algorithm: using a version control system to perform version management on the location algorithm; using the module division of the microservice system to create an independent branch for the location algorithm version; using a version management database to record the update information of the location algorithm, where the update information includes algorithm code, core metadata related to the version, detailed code change history of the algorithm, and code difference analysis results of different versions; using a batch deployment tool to perform distributed deployment and configuration on the location algorithm; based on a preset performance evaluation index system, calling the microservice system to perform performance analysis on the location algorithm to generate a performance analysis report corresponding to the location algorithm.

[0138] During the development of positioning algorithms, developers often only focus on the principles and processing logics of the positioning algorithms, and seldom consider the process of deploying the algorithms in the system after development. The space-ground integrated positioning service system adopts a microservices architecture and exhibits distributed characteristics. To ensure that the positioning algorithm can operate stably in the system, after receiving the submission instruction of the algorithm, this application will first test the algorithm. The test process includes testing the data processing process, parameter setting testing, and deployment link testing. By testing the data processing process, parameter setting testing, and deployment link testing, it can be verified that the positioning algorithm can be normally deployed and stably operate in the space-ground integrated positioning service system. Before formal deployment, it is also necessary to manage and record the update information of the algorithm.

[0139] Parameter setting testing includes: using a distributed testing tool to test the data interaction interface between the positioning algorithm and external systems; performing unit tests on the functional modules inside the positioning algorithm to cover various possible input situations and boundary conditions.

[0140] Deployment link testing includes: setting up a multi-stage test environment, simulating the production environment to deploy a complete microservices architecture using container technology, dynamically adjusting configuration parameters to restore the real running scenario; deploying the algorithm microservices on some real server nodes, realizing service registration and invocation through the service registration and discovery mechanism, monitoring the performance of the positioning algorithm in actual business, and collecting user feedback and system operation data.

[0141] Specifically, for the data processing process, by combining simulated data with actual collected data obtained from message queues such as Kafka, and by writing customized test cases, test the processing capabilities and accuracies of the algorithm on each microservice node under different data scales and types to ensure that the conversion and calculation of data in each processing link in the distributed environment are correct.

[0142] For parameter setting, use Spring Cloud Contract and Selenium in coordination to test the data interaction interface between the algorithm and external systems to ensure the stability of data transmission when the algorithm is integrated with other microservice components; combine Pytest to perform unit tests on the functional modules inside the algorithm to comprehensively cover various possible input situations and boundary conditions and timely discover potential logical errors.

[0143] For the deployment phase, a multi-stage test environment is set up to simulate the production environment and deploy a complete microservice architecture using Docker container technology. Combine the configuration center to dynamically adjust configuration parameters, and try to restore the real running scenario as much as possible to comprehensively evaluate the performance and stability of the algorithm. For the pilot test in a small-scale actual production environment, the algorithm microservice is deployed on some real server nodes, and the service registration and discovery mechanism is used to realize the registration and invocation of the service. Observe the performance of the algorithm in the actual business, collect user feedback and system operation data, and provide a basis for large-scale deployment.

[0144] The version control and management strategy of the algorithm implementation adopts the Git version control system, and combines with the module division of Spring Cloud microservices to create independent branches for each algorithm version. At the same time, it is integrated with the Jenkins continuous integration tool using the Git hook mechanism. When the code is submitted each time, the build and test processes are automatically triggered, and the updated content, modification reason, person in charge, and timestamp of each submission are recorded in detail. Through branch management, it is convenient to compare the differences between different versions and trace the evolution process of the algorithm. In addition, a version management database is used to manage and record the algorithm update information.

[0145] After completing the management and recording of the algorithm update information, the algorithm is deployed and configured in a distributed manner. A strict version release specification is formulated. During the release process, Ansible and Spring Cloud Deployer are combined to uniformly deploy and configure the algorithm on different microservice nodes, ensuring that the installation and configuration of the algorithm on different nodes are consistent and reducing human operation errors.

[0146] The positioning operation and maintenance method provided by the embodiment of this application conducts comprehensive data processing process tests, parameter setting tests, and deployment phase tests on the updated algorithm to ensure that the algorithm can run stably under the microservice architecture of the space-ground integrated positioning service system. The version control system, microservice system, and version management database are used to record and manage the algorithm update information, improving the efficiency of algorithm update management. The batch deployment tool is used to deploy the algorithm in batches to ensure the consistency of algorithm deployment and configuration.

[0147] In a possible implementation manner, the version management database includes a relational database and a non-relational database. The version management database is used to record the update information of the positioning algorithm, including:

[0148] The algorithm code of the newly submitted positioning algorithm and the core metadata related to the version are stored in the relational database; the detailed code change history of the newly submitted positioning algorithm and the result of the code difference analysis with the previous version are stored in the non-relational database.

[0149] Specifically, a version management database is established by combining the relational database MariaDB and the non-relational database Elasticsearch. The algorithm code and core metadata related to versions are stored in MariaDB; by utilizing the full-text search and efficient storage capabilities of Elasticsearch, information such as the detailed code change history of the algorithm and the code difference analysis results of different versions is stored, facilitating quick retrieval and comparison.

[0150] The positioning and operation and maintenance method provided by the embodiments of the present application manages the algorithm update information by using a relational database and a non-relational database when performing algorithm update management, making it more convenient and faster to retrieve algorithm information and compare algorithm update information.

[0151] In a possible implementation manner, the positioning and operation and maintenance method further includes:

[0152] In the same deployment environment, with the same parameter settings, replay multiple versions of the positioning algorithm, where the multiple versions of the positioning algorithm include the newly submitted positioning algorithm.

[0153] In order to provide a basis for subsequent system optimization, it is necessary to perform performance evaluation on the algorithms that have been deployed in the system. In the positioning and operation and maintenance platform, the algorithms of different versions can be replayed and verified by using historical data and actual business cases. Specifically, define a scientific and reasonable performance evaluation index system that meets the requirements of high-precision positioning services, including key indicators such as positioning accuracy, calculation speed, memory occupancy, and stability, and assign corresponding weights to each indicator to comprehensively evaluate the performance of the algorithm. Use historical data and actual business cases to replay and verify the algorithms of different versions. During the replay process, strictly follow the same input data and operating environment settings to ensure the fairness of the comparison. By transmitting the algorithm processing result data to a dedicated data analysis microservice, intuitive comparative analysis is carried out.

[0154] The positioning and operation and maintenance method provided by the embodiments of the present application replays the algorithm with the same deployment environment and parameter settings to compare the performance of different versions of the algorithm, provides guidance for the selection of the algorithm, performs performance analysis on the algorithms that have been deployed in the space-ground integrated positioning service platform, determines the algorithm version with the best performance, and forms a performance analysis report to provide an intuitive basis for system optimization.

[0155] In a possible implementation manner, the positioning and operation and maintenance method further includes:

[0156] Based on natural language processing technology and a preset definition rule library, automatically parse the work order content and classify the work orders according to the work order content; based on a dynamic work order allocation algorithm, combine the skill portraits of operation and maintenance personnel, workload balance, and geographical location to automatically match the work order operation and maintenance objects;

[0157] And / or, perform operation and maintenance management on the entire life cycle of supplier information, including qualification review, contract management, service performance evaluation functions, automatically associate suppliers according to the work order content, and initiate collaboration with suppliers.

[0158] Among them, the operation and maintenance object of the work order is the operation and maintenance personnel or an operation and maintenance team composed of multiple operation and maintenance personnel.

[0159] Optionally, the location operation and maintenance platform includes a resource management system. In the resource management system, an operation and maintenance personnel library is stored, which stores information such as the skill portraits of operation and maintenance personnel, workload balance, and geographical locations. Use natural language processing technology and a preset definition rule library to obtain the key information of the work order, and match the key information with the personnel in the operation and maintenance personnel library to determine the relevant operation and maintenance personnel or operation and maintenance team.

[0160] During the process of work order processing, it may not only involve manpower but also require material support. During work order processing, suppliers can be automatically associated according to the problem type, and a collaboration request can be quickly initiated through the built-in communication channels of the system to track the processing progress.

[0161] Furthermore, the location operation and maintenance method also includes obtaining multi-dimensional reports, such as work order processing efficiency reports statistically by time, fault type, and supplier, to assist in operation and maintenance management decision-making, comprehensively improve operation and maintenance efficiency and quality, and shorten the fault response time.

[0162] The location operation and maintenance method provided by the embodiments of the present application, the intelligent allocation mechanism and the supplier collaboration function ensure the efficient use of resources and the timely solution of problems, significantly enhance operation and maintenance efficiency and service continuity, and effectively improve the overall operation and maintenance effectiveness.

[0163] In a possible implementation manner, the embodiments of the present application provide a location operation and maintenance method, which is applied to the analysis system in various possible implementation manners in the above embodiments. The location operation and maintenance method includes:

[0164] Receive the station data sent by the basic system in the location operation and maintenance platform. The station data includes the station data of the entire link of the positioning service provided by the space-ground integrated positioning service system;

[0165] Perform quality analysis using the integrated station data processing technology to form a data quality analysis report.

[0166] Among them, the quality analysis includes the analysis of multipath error, antenna offset signal strength, and signal-to-noise ratio of the station data. In addition, a quality scoring mechanism is constructed, which covers multiple dimensions such as signal strength scoring, signal-to-noise ratio scoring, multipath error scoring, data integrity scoring, and time synchronization accuracy scoring. For each dimension, reasonable weights and threshold ranges are determined based on strict industry standards and a large amount of historical data statistical analysis. Through a complex weighted calculation and logical judgment process, an accurate quality score is generated for each set of station data.

[0167] Furthermore, after scoring the positioning data in multiple dimensions, a data quality analysis report is automatically generated according to the scoring information. Relying on the intelligent template engine and data visualization technology, a report with rich content and intuitive presentation form is created. The starting part of the report clearly lists the basic information of the station, covering key elements such as geographical location, equipment number, start and end times of data collection, etc. The specific values, rating results of various quality scoring indicators, and the comparative analysis with historical data are presented intuitively.

[0168] The positioning operation and maintenance method provided by the embodiment of the present application processes the station data, performs multi-dimensional quality scoring on the positioning data based on the quality scoring mechanism, and automatically generates a data quality analysis report with rich content and intuitive presentation form according to the quality scoring results, providing a basis for system optimization.

[0169] In a possible implementation manner, a fused station data processing technology is used for quality analysis to form a data quality analysis report. Figure 3 The following is a schematic flow chart of the positioning operation and maintenance method provided by the embodiment of the present application. The method includes the following steps:

[0170] S301: Based on a signal enhancement algorithm that combines wavelet transform and adaptive filtering, separate and strengthen the useful signals in the station data and suppress the noise interference in the station data.

[0171] Among them, wavelet transform (WT) is a new transform analysis method. It inherits and develops the idea of localizing the short-time Fourier transform, and at the same time overcomes the disadvantages such as the window size not changing with frequency. It can provide a "time-frequency" window that changes with frequency and is an ideal tool for signal time-frequency analysis and processing. Its main feature is that through the transform, it can fully highlight the characteristics of certain aspects of the problem, and can perform local analysis of time (space) frequency. Through stretching and translation operations, the signal (function) is gradually refined at multiple scales. Finally, it achieves fine time division at high frequencies and fine frequency division at low frequencies, and can automatically adapt to the requirements of time-frequency signal analysis, so as to focus on any details of the signal.

[0172] Adaptive filtering is to start from the initial conditions determined by some known partial signal characteristics according to a certain optimal criterion under the condition that some signal characteristics are unknown, and perform recursion according to a certain adaptive algorithm. After a certain number of recursions, it converges to the optimal solution in a statistical approximation manner. When the statistical characteristics of the input signal are unknown or the statistical characteristics of the input signal change, the adaptive filter can automatically iteratively adjust its own filter parameters to meet the requirements of a certain criterion, so as to achieve optimal filtering. Therefore, the adaptive filter has the ability of self-adjustment and tracking. In a non-stationary environment, adaptive filtering can also track the changes of signals to a certain extent.

[0173] S302. The multipath cancellation algorithm based on multi-base station joint solution and ray tracing technology determines the multipath error caused by multipath effect in the useful signal, and corrects the error of the useful signal based on the multipath error to obtain the error correction signal corresponding to the station data.

[0174] Multipath propagation refers to the phenomenon that the signal transmitted from the transmitter antenna reaches the receiver antenna through two or more paths during the transmission process. This phenomenon is caused by the reflection, refraction and scattering of electromagnetic waves when they encounter various obstacles (such as buildings, mountains, etc.) during the propagation process. Multipath propagation will cause multipath effect at the receiving end, which will distort the signal and even cause errors. The specific manifestations are the amplitude change and fading of the signal, which will affect the quality and stability of communication. The multipath effect will cause interference and phase shift when the signal is received through multiple paths, and may cause the signal to become very weak in some areas and cannot be fully received.

[0175] Multi-base station joint solution refers to jointly solving the position relationship equations between multiple base stations and the target to calculate the position of the target, so as to determine the true target position from the multiple false target positions generated by the multipath effect.

[0176] Ray tracing is a technology widely used to predict the propagation characteristics of radio waves in mobile communication and personal communication environments, and can be used to identify all possible ray paths between the transmitter and receiver in the multipath channel. Once all possible rays are identified, the amplitude, phase, delay and polarization of each ray can be calculated according to the radio wave propagation theory, and then the coherent synthesis result of all rays at the receiving point can be obtained by combining the antenna pattern and the system bandwidth.

[0177] S303. The antenna calibration model based on electromagnetic simulation and field calibration determines the antenna offset in the error correction signal, and corrects the offset of the error correction signal based on the antenna offset to obtain the offset correction signal corresponding to the station data.

[0178] Antenna offset refers to the offset between the antenna phase center and the centroid of the object. This offset can introduce centimeter-level errors in satellite positioning. In general positioning, this error can be ignored, but in precise positioning, it is necessary to eliminate the influence of this error. By using an antenna calibration model based on electromagnetic simulation and field calibration, the antenna offset in the error correction signal can be identified, and further correction can be made according to the antenna offset.

[0179] S304. Determine the signal strength and signal-to-noise ratio corresponding to the station data according to the offset correction signal.

[0180] S305. Score the multipath error, antenna offset, signal strength, and signal-to-noise ratio of the station data according to a preset signal quality scoring mechanism to form a data quality analysis report.

[0181] The positioning operation and maintenance method provided by the embodiments of the present application uses a variety of signal processing methods to process positioning signals, and finally obtains information such as multipath error, antenna offset, signal strength, and signal-to-noise ratio, providing information for subsequent signal quality analysis. And based on the quality scoring mechanism, multi-dimensional quality scoring is performed on the positioning data, and a content-rich and intuitively presented data quality analysis report is automatically generated according to the quality scoring results, providing a basis for the optimization of the system.

[0182] In a possible implementation manner, the positioning operation and maintenance method further includes:

[0183] According to the data quality analysis report, call an expert system to generate an optimization report for the space-ground integrated positioning service system. The expert system is used to generate an optimization report based on the data quality analysis report.

[0184] Among them, the expert system is an intelligent computer program system that contains a large amount of knowledge and experience at the level of experts in the field of satellite positioning. It can apply artificial intelligence technology and computer technology to reason and judge according to the knowledge and experience in the system, and simulate the decision-making process of human experts to solve those complex problems that require human experts to handle.

[0185] Exemplarily, the expert system provides highly targeted and practically operable adjustment and optimization suggestions, such as adjusting the angle of the antenna, changing the parameters of the signal filter, checking the connection status of the data transmission line, etc., so as to adjust and optimize the station data in a timely manner and ensure the stable operation of the high-precision positioning service.

[0186] The positioning operation and maintenance method provided by the embodiments of the present application uses the expert system to intelligently generate an optimization report according to the data quality analysis report, providing a guiding basis for the stable operation and optimization of the space-ground integrated positioning service system.

[0187] In addition, from the perspective of the software system structure, the system architecture of the present application is asFigure 4 As shown. The system is implemented using the mainstream SpringCloud microservices framework. It can be divided into: presentation layer, access layer, gateway layer, service layer, basic service layer, and infrastructure layer from top to bottom.

[0188] Presentation layer: Provides the operation and maintenance guarantee platform for user access and the visualization entrance of the monitoring dashboard.

[0189] Access layer: Implements load balancing and reverse proxy using Nginx, and uses floating IP to achieve web high availability (HighAvailability).

[0190] Gateway layer: Uses Gateway as the gateway service, and all clients and consumers access the microservices through a unified gateway. The gateway is responsible for authentication, monitoring, load balancing, caching, request sharding and management, and static response processing.

[0191] Service layer: Consists of multiple microservices, providing the business services of this system, including user service, authentication service, analysis service, work order service, operation and maintenance management, RTCM and other microservices.

[0192] Basic service layer: Has common basic services such as message service, process service, monitoring service, log service, file service, and collection service.

[0193] Infrastructure layer: Uses MariaDB as the main database, Redis for high-speed caching, and Elasticsearch for non-relational databases. The microservices support multiple deployment methods: on hardware servers, virtual machines, and docker containers.

[0194] This framework combines cutting-edge development tools and cross-platform capabilities, thus improving the flexibility, performance, and maintainability of the system. This comprehensive technology selection helps the system achieve excellent performance and user experience in different aspects.

[0195] In some embodiments, the functional architecture of the positioning operation and maintenance platform is as Figure 5 shown. The basic module in the figure is equivalent to the basic system in the above text, responsible for functions such as data collection and interface management. The resource center is equivalent to the resource management system in the above text, used to manage various software and hardware resources in the space-ground integrated positioning service system. The monitoring center is equivalent to the monitoring system in the above text, used to monitor abnormalities in the space-ground integrated positioning service system. The operation and maintenance center is equivalent to the operation and maintenance system in the above text, used for automatic processing of work orders and algorithm update management. The analysis center is equivalent to the analysis system in the above text, used for positioning data quality analysis.

[0196] In some embodiments, the monitoring center specifically monitors the following items:

[0197] The time delay between the access time of station data and the current GPST time, supports setting thresholds and triggering alarm notifications.

[0198] The time delay between the arrival time of broadcast ephemeris and the current GPST time, supports setting thresholds and triggering alarm notifications.

[0199] The time delay between the input time of ultra-fast orbit files and DCB files and the current GPST time, supports setting thresholds and triggering alarm notifications.

[0200] The time delays of 4 products of SSR1 - 4 respectively from the current GPST time, support setting thresholds and triggering alarm notifications; count the number of satellites in the satellite systems (GPS, BDS, GALILEO, GLONASS) of these 4 SSR products. For the SSR4 product, regional conditions are also required to count its satellite number.

[0201] Real-time orbit difference sequence, supports setting thresholds and triggering alarm notifications.

[0202] Real-time sequence of UPD product data, supports setting thresholds and triggering alarm notifications.

[0203] Real-time sequence of PPP-RTK positioning data of monitoring stations, supports setting thresholds and triggering alarm notifications.

[0204] Real-time sequence diagram of atmosphere (monitoring stations, ionosphere and troposphere) data, supports setting thresholds and triggering alarm notifications.

[0205] Display the single-difference situation between ionospheric stations, updated once per minute.

[0206] Weekly statistical report on the evaluation of orbit and clock products (post-precision products).

[0207] Weekly statistical report on DCB products (STD).

[0208] Daily statistical report on UPD product STD.

[0209] Daily statistical report on the accuracy of atmosphere products (out-of-station compliance) for each area.

[0210] Statistical report on the atmospheric estimation results of external monitoring stations.

[0211] Daily statistical report on the PPP-RTK results of monitoring stations for each area. Receiver port monitoring: Monitor 2 ports of the receiver to detect port connectivity.

[0212] Station link monitoring: 2 wired and wireless lines, packet loss rate (by the number of epochs).

[0213] Monitoring of the station coordinates: The precise coordinates when going to the station - the coordinate difference of the product ppprtk. An alarm is required if the error exceeds the expected value.

[0214] Monitoring of the number of satellites at the station: Statistical count of the number of satellites searched by the monitoring station, by subsystem. An alarm is required if the number of satellites is less than a certain number.

[0215] Monitoring large screen at the station: Epoch packet loss rate, satellite search situation, coordinate offset monitoring, power situation of the station, 4G signal strength, dedicated line packet loss rate.

[0216] In one implementation, the signal quality analysis report may include the following content:

[0217] Statistical count of the MP12, MP21, MP15, MP51, MP17, and MP71 values of the GNSS constellation over a one-day period.

[0218] Statistical count of the cycle slip ratio of the GNSS constellation over a one-day period.

[0219] Statistical count of the cycle slip ratio of the four-system data over a one-day period.

[0220] Statistical count of the data availability rate of the GNSS constellation over a one-day period.

[0221] Statistical count of the data availability rate of the four-system data over a one-day period.

[0222] Statistical count of the satellite numbers and cycle slips of the GNSS constellation with cycle slips over a one-day period.

[0223] Statistical count of the number of satellites with cycle slips in the GNSS constellation over a one-day period.

[0224] Output the quality inspection report of the GNSS constellation over a one-day period, and present it by linking pictures.

[0225] Statistical report on the basic situation of the constellation.

[0226] Statistical report on the working status of satellites.

[0227] Statistical report on the availability of national PDOP.

[0228] Statistical report on signal-to-noise ratio.

[0229] Statistical report on multipath effects.

[0230] Statistical report on real-time cycle slip detection.

[0231] Statistical report on the number of instantaneously visible satellites and PDOP values.

[0232] Finally, it should be noted that: those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not disclosed in the present invention. It is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A positioning operation and maintenance platform, characterized in that Including: A basic system for real-time collection of station data and system operation data of the entire link of the positioning service provided by the space-ground integrated positioning service system; A monitoring system for anomaly monitoring based on the station data and system operation data obtained from the basic system, using big data analysis technology and anomaly detection algorithms based on deep learning, and triggering an alarm mechanism when an anomaly occurs; An analysis system for quality analysis using integrated station data processing technology based on the station data obtained from the basic system to form a data quality analysis report; An operation and maintenance system connected to the space-ground integrated positioning service system for iterative update and playback of the algorithm version of the positioning algorithm of the space-ground integrated positioning service system.

2. The positioning and operation and maintenance platform according to claim 1, characterized in that The operation and maintenance system is specifically used for: Automatically triggering a test process for the submitted positioning algorithm, and the test process includes a data processing process test, a parameter setting test, and a deployment link test; Using a version control system for version management; Adopting the module division of the microservice system to create independent branches for each positioning algorithm version, and integrating with the continuous integration tool using a hook mechanism; Using a version management database to record the update information of the positioning algorithm, and the update information includes algorithm code, core metadata related to the version, detailed code change history of the algorithm, and code difference analysis results of different versions; Using a batch deployment tool to perform distributed deployment and configuration of the positioning algorithm.

3. The positioning and operation and maintenance platform according to claim 2, wherein The version management database includes a relational database and a non-relational database. Among them, the relational database stores at least the algorithm code and core metadata related to the version; the non-relational database stores at least the detailed code change history of the algorithm and the code difference analysis results of different versions.

4. The positioning and operation and maintenance platform according to claim 2, characterized in that, The data processing process test includes: using simulated data combined with the actual collected data obtained from the message queue to automatically write customized test cases to test the processing ability and accuracy of the positioning algorithm on each microservice node under different data scales and types; The parameter setting test includes: using a distributed test tool to test the data interaction interface between the positioning algorithm and the external system; performing unit tests on the functional modules inside the positioning algorithm to cover various possible input situations and boundary conditions; The deployment link test includes: setting up a multi-stage test environment, simulating the production environment to deploy a complete microservice architecture using container technology, dynamically adjusting configuration parameters to restore the real operation scenario; deploying the algorithm microservice on some real server nodes, realizing service registration and invocation through the service registration and discovery mechanism, monitoring the performance of the positioning algorithm in the actual business, and collecting user feedback and system operation data.

5. The positioning and operation and maintenance platform according to claim 2, wherein The operation and maintenance system is also used for: Playing back multiple versions of the positioning algorithm with the same parameter settings in the same deployment environment; And / or, based on a preset performance evaluation index system, calling the microservice system to perform performance analysis on multiple versions of the positioning algorithm to generate a performance analysis report for comparing the performance of multiple versions of the positioning algorithm.

6. The positioning and operation and maintenance platform according to any one of claims 1 to 5, characterized in that The analysis system is specifically used for: A signal enhancement algorithm based on the collaboration of wavelet transform and adaptive filtering separates and strengthens the useful signals in the station data and suppresses the noise interference in the station data; A multipath cancellation algorithm based on multi-base station joint solution and ray tracing technology determines the multipath errors caused by multipath effects in the useful signals, and corrects the errors of the useful signals based on the multipath errors to obtain the error correction signals corresponding to the station data; An antenna calibration model based on electromagnetic simulation and field calibration determines the antenna offset in the error correction signals, and corrects the offset of the error correction signals based on the antenna offset to obtain the offset correction signals corresponding to the station data; Based on the offset correction signals, determine the signal strength and signal-to-noise ratio corresponding to the station data; According to a preset signal quality scoring mechanism, score the multipath errors, antenna offsets, signal strengths, and signal-to-noise ratios of the station data to form the data quality analysis report.

7. The positioning and operation and maintenance platform according to any one of claims 1 to 5, characterized in that The analysis system is further configured to: According to the data quality analysis report, call an expert system to generate an optimization report for the space-ground integrated positioning service system, and the expert system is used to generate an optimization report based on the data quality analysis report.

8. The positioning and operation and maintenance platform according to any one of claims 1 to 5, characterized in that, The basic system is specifically configured to: Capture signals from different satellite constellations and each frequency point in the space-ground integrated positioning service system through a sensor matrix to obtain the station data and system operation data of the entire positioning service link; And, based on a highly reliable transmission protocol that combines error correction coding and retransmission mechanism, transmit the corresponding station data or system operation data to the monitoring system and the analysis system.

9. The positioning and operation and maintenance platform according to any one of claims 1 to 5, characterized in that, The operation and maintenance system is further configured to: Automated operation and maintenance work orders, where the automated operation and maintenance work orders include automatically parsing the work order content based on natural language processing technology and a preset definition rule library, classifying the work orders according to the work order content; based on a dynamic work order allocation algorithm, automatically matching the work order operation and maintenance objects in combination with the skill portraits of operation and maintenance personnel, workload balance, and geographical location; And / or, the full life cycle operation and maintenance management of supplier information, including functions such as qualification review, contract management, service performance evaluation, automatically associating suppliers according to the work order content, and initiating collaboration with suppliers.

10. A positioning and operation and maintenance method, characterized in that, Applied to the operation and maintenance system in the positioning operation and maintenance platform according to any one of claims 1 to 9, the positioning operation and maintenance method includes: In response to the submission instruction of the positioning algorithm, automatically trigger the test process of the submitted positioning algorithm. The test process includes data processing process test, parameter setting test, and deployment link test, and perform the following processing on the positioning algorithm: Use a version control system to manage the version of the positioning algorithm; Adopt the module division of the microservice system to create an independent branch for the version of the positioning algorithm; Use a version management database to record the update information of the positioning algorithm, and the update information includes algorithm code, core metadata related to the version, detailed code change history of the algorithm, and code difference analysis results of different versions; Use a batch deployment tool to perform distributed deployment and configuration on the positioning algorithm; Based on a preset performance evaluation index system, call the microservice system to perform performance analysis on the positioning algorithm, and generate a performance analysis report corresponding to the positioning algorithm.

11. The positioning and operation and maintenance method according to claim 10, characterized in that The version management database includes a relational database and a non-relational database. The version management database is used to record the update information of the positioning algorithm, including: Store the algorithm code of the newly submitted positioning algorithm and the core metadata related to the version in the relational database; Store the detailed code change history of the newly submitted positioning algorithm and the result of the code difference analysis with the previous version in the non-relational database.

12. The positioning and operation and maintenance method according to claim 10 or 11, characterized in that The positioning operation and maintenance method further includes: In the same deployment environment, replay multiple versions of the positioning algorithm with the same parameter settings, and the multiple versions of the positioning algorithm include the newly submitted positioning algorithm.

13. The positioning and operation and maintenance method according to claim 10 or 11, characterized in that, The positioning operation and maintenance method further includes: Based on natural language processing technology and a preset definition rule library, automatically parse the work order content, and classify the work order according to the work order content; based on a dynamic work order allocation algorithm, combine the skill portraits of operation and maintenance personnel, workload balance, and geographical location to automatically match the work order operation and maintenance object; And / or, perform operation and maintenance management on the entire life cycle of the supplier information, including qualification review, contract management, service performance evaluation functions, automatically associate the supplier according to the work order content, and initiate collaboration with the supplier.

14. A positioning and operation and maintenance method, characterized in that, Applied to the analysis system in the positioning operation and maintenance platform according to any one of claims 1 to 9, the positioning operation and maintenance method includes: Receive the station data sent by the basic system in the positioning operation and maintenance platform, and the station data includes the station data of the entire positioning service link provided by the space-ground integrated positioning service system; Use the integrated station data processing technology to perform quality analysis and form a data quality analysis report.

15. The positioning and operation and maintenance method according to claim 14, wherein The use of the integrated station data processing technology to perform quality analysis and form a data quality analysis report includes: Based on a signal enhancement algorithm that combines wavelet transform and adaptive filtering, separate and strengthen the useful signals in the station data, and suppress the noise interference in the station data; Based on a multipath cancellation algorithm that combines multi-base station joint solution and ray tracing technology, determine the multipath error caused by the multipath effect in the useful signal, and perform error correction on the useful signal based on the multipath error to obtain the error correction signal corresponding to the station data; Based on an antenna calibration model that combines electromagnetic simulation and on-site calibration, determine the antenna offset in the error correction signal, and perform offset correction on the error correction signal based on the antenna offset to obtain the offset correction signal corresponding to the station data; According to the offset correction signal, determine the signal strength and signal-to-noise ratio corresponding to the station data; According to a preset signal quality scoring mechanism, score the multipath error, antenna offset, signal strength, and signal-to-noise ratio of the station data to form the data quality analysis report.

16. The positioning and operation and maintenance method according to claim 14 or 15, characterized in that, The positioning operation and maintenance method further includes: According to the data quality analysis report, call the expert system to generate an optimization report for the space-ground integrated positioning service system, and the expert system is used to generate an optimization report based on the data quality analysis report.

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