CN113325443A - Dynamic visual analysis method for GNSS space signal quality - Google Patents
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Abstract
The invention relates to a dynamic visualization analysis method for GNSS space signal quality, wherein dynamic visualization software adopts mathematical statistics methods such as mean value, variance and the like to realize the functions of operation state analysis, observation data state analysis, evaluation result dynamic analysis and abnormal state association analysis of a space signal quality monitoring and evaluation subsystem. The data analysis and processing is based on the parallel real-time analysis of the signal quality, the signal data analysis module can be implemented in a distributed mode, calculation is decomposed to a plurality of servers, the data processing efficiency is improved, and time delay is reduced. Data analysis, namely visually displaying real-time updating of data, and timely grasping the change condition of each index of signal quality and the abnormal condition of the data; during the operation of the system, technicians can configure visualization on line and take effect in real time.
Description
Technical Field
The invention belongs to the technical field of GNSS observation data index change, and particularly relates to a dynamic visual analysis method for GNSS space signal quality.
Background
With the rapid development of the global Navigation Satellite system gnss (global Navigation Satellite system), the global 4-up Satellite positioning system (GPS, BDS, GLONASS, Galileo), the japanese quasi-zenith Satellite Navigation system, the indian regional Navigation Satellite system, and the like. Each in-orbit satellite outputs a large amount of signal data at any time. How to utilize the spatial signal data to carry out dynamic visual analysis on the working state and the signal quality of the satellite is a difficult problem which is troubling technical personnel. The traditional method is to store received satellite signal data, then use Matlab to calculate and analyze and output various charts and data files, then make report files for reference of the calculator, the analysis only carries out independent analysis on the signal data in a certain time period, the analysis result deviation caused by the influence of the working state parameters of the receiver equipment or the health state of the satellite on the data is not concerned, the analysis result is limited to the change of a single index and the correlation influence among several indexes, for example, the receiver works in an abnormal state or the satellite is set up improperly at a high angle, the validity of the output data is influenced, and the signal quality is easily judged by analyzing the data and neglecting peripheral information. The analysis without introducing peripheral information is easy to cause misjudgment and the technicians of off-line analysis cannot grasp the real condition of signal quality in time. Secondly, the conventional primary analysis is usually performed by analyzing data in a relatively short time period, and is lack of correlation comparison analysis with historical data, so that information obtained by analysis is easy to lose due to insufficient observation time, and a change trend of signal quality for a long time is difficult to obtain.
Disclosure of Invention
The invention aims to solve the problems and provides a dynamic visualization analysis method for GNSS space signal quality, which can visually and real-timely show the GNSS observation data index change condition and the correlation influence relationship among indexes.
In order to achieve the purpose, the invention provides the following technical scheme: a dynamic visualization analysis method for GNSS space signal quality comprises a satellite signal data received by a receiver, a data preprocessing module, a visualization data analysis and calculation module, a satellite encoding data anomaly rule visualization index configuration database and a signal quality result data anomaly alarm information database, wherein the satellite signal data received by the receiver comprises a GPS, a BDS, a GLONASS, a Galileo, working state data of the receiver and satellite health condition data, and the satellite signal data received by the receiver is sent to the data preprocessing module through a network.
Preferentially, the method comprises the following steps: the data preprocessing module completes data system, precision conversion, deletion correction, data structure standardization, UTC time standardization, data time sequence calibration, same satellite multi-source data merging and serial-to-parallel processing;
the method comprises the following steps of carrying out real-time analysis on signal data of different satellite systems, and simultaneously writing analysis results and original data into a signal quality result data abnormity warning information database:
the method comprises the following steps of completing analysis and processing of real-time data streams of Beidou system B1, B2 and B3 frequency point signals, GPS system L1, L2 and L5 frequency point signals, Galileo system E1, E5 and E6 frequency point signals, GLONASS system G1, G2 and G3 frequency point signals based on parallel calculation, wherein the analysis comprises the following steps: the method comprises the steps of parallel calculation of a ranging code and a carrier coherence evaluation item, parallel calculation of coherence between intra-frequency/inter-frequency ranging code phases, and real-time analysis and calculation of a pseudo range/carrier phase/carrier-to-noise ratio/Doppler measured value.
Preferentially, the method comprises the following steps: and carrying out abnormity judgment on an analysis result according to a data abnormity rule set by a satellite coding data abnormity rule visualization index configuration database, wherein the judgment rule is combined judgment according to the health state of the satellite and the data threshold range of the receiver parameter, when the data is abnormal, outputting abnormal information and storing the abnormal information into a signal quality result data abnormity warning information database, and the abnormal information and the corresponding original data are subjected to association marking.
Preferentially, the method comprises the following steps: the input data of the visualized data analysis and calculation module comprises data output by the signal quality parallel real-time analysis module and data in the signal quality result data abnormity warning information database.
Preferentially, the method comprises the following steps: the time series data application algorithm comprises the following steps:
down-sampling and interpolation: a down-sampling algorithm, an interpolation algorithm,
and (2) polymerization calculation: logic aggregation, arithmetic aggregation, statistics,
and writing the result into a visual time sequence database after calculation for use by a visual service module.
Preferentially, the method comprises the following steps: the signal quality result data abnormity warning information database transmits historical data to a multi-index historical data correlation analysis module, the multi-index historical data correlation analysis module can achieve comparison analysis of the historical data, index correlation analysis is achieved, and analysis results are written into a visual time sequence database to be used by a visual service module.
Preferentially, the method comprises the following steps: the visual time sequence database transmits partial data to a signal quality dynamic visual service module, the signal quality dynamic visual service module comprises a visual online configuration module, a multi-index comparison analysis broken line graph, a quality summary data pie graph and a column graph, an abnormal alarm information chart visualization, a signal quality index change broken line graph, a signal quality index normal distribution graph, a signal quality index association analysis scattered line graph and a multi-index difference analysis stacking area graph, and the signal quality dynamic visual service transmits partial data to a multi-index multi-dimensional visual data instrument panel.
Preferentially, the method comprises the following steps: the multi-index multi-dimensional visual data instrument panel aims at the comprehensive information or multi-index data of a single satellite, so that the multi-index multi-dimensional visual data instrument panel can present various information on one interface; a single visual chart representation can be used for a single index or index alignment.
Preferentially, the method comprises the following steps: the visualization online configuration module can realize online configuration of a data source and visual output of a chart style, is rapid in configuration, can store the existing visualization display configuration as a template, and is convenient to recycle.
Preferentially, the method comprises the following steps: due to the fact that the analysis method is large in data size, parallel computing can be used for analysis and processing in order to improve data processing efficiency and guarantee data dynamic visualization effect, and computing can be provided by means of multi-core CPU or GPU computing power.
Compared with the prior art, the invention has the beneficial effects that:
a dynamic visualization analysis method for GNSS space signal quality is characterized in that a dynamic visualization software adopts mathematical statistics methods such as mean value and variance to realize the functions of running state analysis, observation data state analysis, evaluation result dynamic analysis and abnormal state correlation analysis of a space signal quality monitoring and evaluation subsystem. Data analysis, namely visually displaying real-time updating of data, and timely grasping the change condition of each index of signal quality and the abnormal condition of the data; during the operation of the system, technicians can configure visualization on line and take effect in real time.
The dynamic visualization software supports visualization display of single-satellite data analysis results, visualization display of multi-satellite data analysis results and visualization display of performance comparison analysis results among systems. The analysis result is more objective and accurate, the same index data can be related to data comparison analysis in a specific historical time period, and the advantages of big data are fully utilized to extract more information.
GNSS signal data all have time scales, and data storage is according to time scale subregion storage, also all is time range condition during data inquiry, and the system can be gathered according to the time is automatic, from millisecond level data summarization to second level, again to minute level, hour level etc. and the data utilization cost is reduced to aggregated data promotion performance.
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In order to more clearly illustrate the technical solution of the embodiment of the present invention, the drawings needed to be used in the description of the embodiment will be briefly introduced below, it is obvious that the drawings in the following description are only for more clearly illustrating the embodiment of the present invention or the technical solution in the prior art, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic view of the overall structural framework of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood and implemented by those skilled in the art, the present invention is further described with reference to the following specific examples, which are provided for illustration only and are not intended to limit the present invention.
The method for dynamically visualizing analysis on GNSS space signal quality as shown in fig. 1 includes a receiver receiving satellite signal data, a data preprocessing module, a visualized data analysis and calculation module, a satellite encoded data anomaly rule visualized index configuration database and a signal quality result data anomaly alarm information database, wherein the receiver receiving satellite signal data includes GPS, BDS, GLONASS, Galileo, working state data of the receiver and satellite health status data, and the receiver receiving satellite signal data is sent to the data preprocessing module through a network.
Data preprocessing: processing of data system, precision conversion, deletion correction, data structure standardization, UTC time standardization, data time sequence calibration, same satellite multi-source data merging, serial-to-parallel conversion and the like is completed, so that the requirement of a subsequent analysis algorithm is met;
and (4) carrying out real-time analysis on the signal data of different satellite systems, and simultaneously writing the analysis result and the original data into a time sequence database.
For Beidou system B1, B2 and B3 frequency point signals, GPS system L1, L2 and L5 frequency point signals, Galileo system E1, E5 and E6 frequency point signals, GLONASS system G1, G2 and G3 frequency point signals complete analysis and processing of real-time data streams based on parallel calculation, and the analysis comprises the following steps: the method comprises the steps of parallel calculation of a ranging code and a carrier coherence evaluation item, parallel calculation of coherence between intra-frequency/inter-frequency ranging code phases, and real-time analysis and calculation of measured values such as pseudo range/carrier phase/carrier-to-noise ratio/Doppler.
Because the analysis result and the original data have the characteristics of strong time sequence and large data quantity, the time sequence database is used for storing the result and the original data. Because the data volume greatly improves the data processing efficiency and guarantees the dynamic visualization effect of the data, the analysis and the processing are carried out by using the parallel computation, and the computation can be provided by means of the computing power of a multi-core CPU or a GPU.
The visualized data analysis and calculation module is used for performing calculation processing specially for visualized display of analysis result data according to the requirements of data visualization indexes, and inputting data output by the signal quality parallel real-time analysis module and data in the signal quality result data abnormity warning information database. The application algorithm for the time sequence database mainly comprises the following steps:
down-sampling and interpolation: down-sampling algorithms (max/min/mean), interpolation algorithms (zero-filling/linear/bezier curves);
and (3) polymerization calculation: logic aggregation, arithmetic aggregation, statistics.
After calculation, the calculation result is written into a visual time sequence database for a visual service module to use.
The multi-index historical data correlation analysis module finishes reading historical data from a signal quality result data abnormal alarm information database, comparison analysis of the historical data is achieved, index correlation analysis is achieved, and analysis results are also written into a visual time sequence database for a visual service module to use.
The signal quality data dynamic visualization service reads data from a visualization time sequence database, then combines configured visualization templates to render data, and finally presents the data visualization to a user through a webpage or other visualization components.
For comprehensive information or multi-index data of a single satellite, a plurality of visual components can be combined in a multi-index multi-dimensional visual data instrument panel mode, and various information is presented on one interface; a single visual chart representation can be used for a single index or index alignment.
The GNSS spatial signal quality indexes mainly comprise: the method comprises the following steps of correlation loss change, S curve zero crossing point deviation and slope, effective power ratio change, phase deviation change among signal components, waveform distortion parameter change, baseband signal waveform pattern inter-frequency, intra-frequency signal coherence, carrier and pseudo code coherence correlation visualization and power spectrum change.
Dynamic visualization based on the webpage guarantees the dynamic data refresh rate, a WebSocket technology can be used for achieving a data update pushing technology, and compared with common timing refresh, the method has the advantages of being small in server pressure and timely in visualized data update.
In order to realize dynamic, flexible and changeable visualization requirements, online configuration of a data source and configuration of a visually output chart style can be realized through a visualization online configuration module, and for convenient and rapid configuration, the existing visualization display configuration can be stored as a template so as to be reused.
Visualization adopts componentization and self-defined template technology, thereby realizing flexible and changeable combination and meeting different data analysis requirements.
The data analysis and processing is based on parallelization signal data analysis, the signal quality parallel real-time analysis module can be implemented in a distributed mode, calculation is decomposed into a plurality of servers, the data processing efficiency is improved, and time delay is reduced; the GNSS signal data have time marks, the data storage is stored in a partition mode according to the time marks, time range conditions are also provided during data query, the system automatically collects the data according to the time, millisecond-level data are collected to second level, then minute level, hour level and the like, the performance is improved by aggregating the data, and the data utilization cost is reduced;
the dynamic features of the dynamic visualization are embodied in two aspects:
(1) data analysis, namely visually displaying real-time updating of data, and timely grasping the change condition of each index of signal quality and the abnormal condition of the data;
(2) during the operation period of the system, technicians can configure visualization on line and take effect in real time.
The data association visualization analysis not only reflects the association influence among all indexes in the same time period, but also can associate the satellite health state and the working parameter factors of the receiver, and the analysis result has higher objectivity and accuracy. The same index data can also be related to data comparison analysis of historical specific time periods, and the advantages of big data are fully utilized to extract more information.
The dynamic visual analysis of the spatial signal quality requires collecting data and information such as monitoring duration, monitoring times, monitoring data files, monitoring evaluation parameters and the like of a specified satellite, wherein the monitoring evaluation parameters comprise: the method comprises the following steps of signal emission bandwidth, out-of-band redundant radiation power spectrum density, out-of-band rejection, correlation loss, phase deviation among signal components, inter-frequency and intra-frequency signal coherence, ground minimum received power, effective signal power ratio deviation among signal components, synthesized power spectrum deviation, S-curve zero crossing point deviation and slope, time domain signal waveform distortion and carrier and pseudo code coherence.
The dynamic visualization software adopts mathematical statistics methods such as mean value, variance and the like to realize the functions of running state analysis, observation data state analysis, evaluation result dynamic analysis and abnormal state correlation analysis of the space signal quality monitoring and evaluation subsystem. The dynamic visualization software supports visualization display of single-star data analysis results, visualization display of multi-star data analysis results and visualization display of performance comparison and analysis results among systems. The data association visualization analysis realized by the method is not limited to the association relation among all indexes at the same time point, and also comprises the following steps: and the correlation of the analysis result index and the health state of the satellite and the working state parameter of the receiver are correlated.
A dynamic visualization analysis method for GNSS space signal quality is characterized in that a receiver receives satellite signal data of Beidou, GPS, GALILEO, GLONASS and other GNSS systems, the system dynamic analysis function of a space signal quality monitoring and evaluating subsystem is achieved, the system running state and trend of the space signal quality monitoring and evaluating subsystem are analyzed through monitoring and processing system state data, signal monitoring data and evaluation results, and performance index states and trends of monitoring and evaluating objects, namely GNSS signals are analyzed. And carrying out abnormity judgment on the analysis result according to the data in the set visual index configuration database of the satellite coding data abnormity rule, wherein the judgment rule is combined with the combination judgment of the satellite health state and the data threshold range of the receiver parameter, if the data is abnormal, outputting abnormity information and storing the abnormity information into a signal quality result data abnormity warning information database, and the abnormity information and the corresponding original data are subjected to association marking to support subsequent association visual analysis.
The details of the present invention not described in detail are prior art.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A dynamic visualization analysis method for GNSS spatial signal quality is characterized in that: the satellite signal data received by the receiver comprises GPS, BDS, GLONASS, Galileo, working state data of the receiver and satellite health condition data, and the satellite signal data received by the receiver is sent to the data preprocessing module through a network.
2. The method of claim 1, wherein the method comprises: the data preprocessing module completes data system, precision conversion, deletion correction, data structure standardization, UTC time standardization, data time sequence calibration, same satellite multi-source data merging and serial-to-parallel processing;
the method comprises the following steps of carrying out real-time analysis on signal data of different satellite systems, and simultaneously writing analysis results and original data into a signal quality result data abnormity warning information database:
the method comprises the following steps of completing analysis and processing of real-time data streams of Beidou system B1, B2 and B3 frequency point signals, GPS system L1, L2 and L5 frequency point signals, Galileo system E1, E5 and E6 frequency point signals, GLONASS system G1, G2 and G3 frequency point signals based on parallel calculation, wherein the analysis comprises the following steps: the method comprises the steps of parallel calculation of a ranging code and a carrier coherence evaluation item, parallel calculation of coherence between intra-frequency/inter-frequency ranging code phases, and real-time analysis and calculation of a pseudo range/carrier phase/carrier-to-noise ratio/Doppler measured value.
3. The method of claim 1, wherein the method comprises: and carrying out abnormity judgment on an analysis result according to a data abnormity rule set by a satellite coding data abnormity rule visualization index configuration database, wherein the judgment rule is combined judgment according to the health state of the satellite and the data threshold range of the receiver parameter, when the data is abnormal, outputting abnormal information and storing the abnormal information into a signal quality result data abnormity warning information database, and the abnormal information and the corresponding original data are subjected to association marking.
4. The method of claim 1, wherein the method comprises: the input data of the visualized data analysis and calculation module comprises data output by the signal quality parallel real-time analysis module and data in the signal quality result data abnormity warning information database.
5. The method of claim 1, wherein the method comprises: the time series data application algorithm comprises the following steps:
down-sampling and interpolation: a down-sampling algorithm, an interpolation algorithm,
and (2) polymerization calculation: logic aggregation, arithmetic aggregation, statistics,
and writing the result into a visual time sequence database after calculation for use by a visual service module.
6. The method of claim 4, wherein the GNSS spatial signal quality is analyzed by dynamic visualization, and the method further comprises: the signal quality result data abnormity warning information database transmits historical data to a multi-index historical data correlation analysis module, the multi-index historical data correlation analysis module can achieve comparison analysis of the historical data, index correlation analysis is achieved, and analysis results are written into a visual time sequence database to be used by a visual service module.
7. The method of claim 7, wherein the method comprises: the visual time sequence database transmits partial data to a signal quality dynamic visual service module, the signal quality dynamic visual service module comprises a visual online configuration module, a multi-index comparison analysis broken line graph, a quality summary data pie graph and a column graph, an abnormal alarm information chart visualization, a signal quality index change broken line graph, a signal quality index normal distribution graph, a signal quality index association analysis scattered line graph and a multi-index difference analysis stacking area graph, and the signal quality dynamic visual service transmits partial data to a multi-index multi-dimensional visual data instrument panel.
8. The method of claim 7, wherein the method comprises: the multi-index multi-dimensional visual data instrument panel aims at the comprehensive information or multi-index data of a single satellite, so that the multi-index multi-dimensional visual data instrument panel can present various information on one interface; a single visual chart representation can be used for a single index or index alignment.
9. The method of claim 7, wherein the method comprises: the visualization online configuration module can realize online configuration of a data source and visual output of a chart style, is rapid in configuration, can store the existing visualization display configuration as a template, and is convenient to recycle.
10. The method for dynamic visualization analysis of GNSS spatial signal quality as claimed in any of claims 1 to 10, wherein: due to the fact that the analysis method is large in data size, parallel computing can be used for analysis and processing in order to improve data processing efficiency and guarantee data dynamic visualization effect, and computing can be provided by means of multi-core CPU or GPU computing power.
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| CN114296109A (en) * | 2021-12-28 | 2022-04-08 | 汇鲲化鹏(海南)科技有限公司 | Baseband processing method and system for GNSS signal slice navigation data |
| CN114296109B (en) * | 2021-12-28 | 2023-03-24 | 汇鲲化鹏(海南)科技有限公司 | Baseband processing method and system for GNSS signal slice navigation data |
| CN114384558A (en) * | 2022-01-12 | 2022-04-22 | 中国人民解放军国防科技大学 | GPU-based online signal quality monitoring and analyzing method and system |
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