CN113253318B - GNSS data remote super-calculation method - Google Patents
GNSS data remote super-calculation method Download PDFInfo
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- CN113253318B CN113253318B CN202110682990.1A CN202110682990A CN113253318B CN 113253318 B CN113253318 B CN 113253318B CN 202110682990 A CN202110682990 A CN 202110682990A CN 113253318 B CN113253318 B CN 113253318B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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- G01S19/35—Constructional details or hardware or software details of the signal processing chain
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
Abstract
The invention discloses a GNSS data remote super-calculation method, which comprises the following steps: s1: acquiring GNSS original data, packaging the GNSS original data and storing the GNSS original data in a memory; s2: decrypting and analyzing the GNSS original data in the memory, and storing the GNSS data obtained after decryption and analysis are finished; s3: the GNSS data which are decrypted and analyzed are called, core operation is carried out, final resolving data are obtained, and the final resolving data are stored in a warehouse; s4: and obtaining final resolving data or GNSS original data through a computer client or a mobile phone access server, and performing single-server deployment, multi-server deployment or cloud service deployment according to the user quantity and the GNSS data quantity to complete the GNSS data remote super calculation. The hypercalculation method of the invention can be compatible with GNSS data formats of all manufacturers and Cors reference system data of all types, and supports conversion among different GNSS data formats.
Description
Technical Field
The invention belongs to the technical field of GNSS data processing, and particularly relates to a GNSS data remote super-calculation method.
Background
In the field of high-precision position service, the positioning method is mainly realized by depending on a Global Navigation Satellite System (GNSS) technology, and by establishing a satellite navigation positioning reference station system (CORS) to continuously observe GNSS satellite information in real time, the method can quickly and effectively weaken the main error influence of orbit, clock error, atmosphere and the like, thereby realizing the real-time centimeter-level and afterwards millimeter-level precision positioning. GNSS-based deformation monitoring, mapping and navigation, tracking and positioning, and the like, all have great demands for high-precision (millimeter-scale) location services. The general units do not have service conditions, and the main reasons are as follows: (1) high-precision GNSS resolving needs data such as high-precision coordinates, displacement rate and the like of a reference station, and is difficult to obtain by a general user; (2) high-precision GNSS resolving needs to rely on observation data of satellites, the data structures are complex, the data volume is large, the specialization is strong, and common users are difficult to master; (3) the high-precision (millimeter-scale) resolving service is carried out in a manual mode on the premise that a large amount of manpower and material resources are required, the time is seriously delayed, and the high-precision resolving requirement and the high-efficiency requirement of a large number of users can not be met; (4) the GNSS terminal equipment with medium and high precision (centimeter level) automatic resolving at present has the advantages of complex structure, high manufacturing cost, high power consumption and difficult popularization.
Disclosure of Invention
The invention aims to solve the problem of GNSS data calculation and provides a GNSS data remote super-calculation method.
The technical scheme of the invention is as follows: a GNSS data remote super-calculation method comprises the following steps:
s1: acquiring GNSS original data, packaging the GNSS original data and storing the GNSS original data in a memory;
s2: decrypting and analyzing the GNSS original data in the memory, and storing the GNSS data obtained after decryption and analysis are finished;
s3: the GNSS data which are decrypted and analyzed are called, core operation is carried out, final resolving data are obtained, and the final resolving data are stored in a warehouse;
s4: and acquiring final resolved data or GNSS original data through a computer client or a mobile phone access server, and flexibly performing single-server deployment, multi-server deployment or cloud service deployment according to the user quantity and the GNSS data quantity to finish the GNSS data remote super-computation.
Further, in step S1, the specific method for acquiring GNSS raw data includes: the method comprises the steps that GNSS raw data of satellites are received by utilizing GNSS data acquisition equipment or GNSS raw data of each base station are acquired by utilizing the internet;
the specific method for storing the packed GNSS original data packet into the memory comprises the following steps: utilizing a firewall to carry out interaction, and transmitting the GNSS original data packet to a cloud server in a secret file form through a wireless network or a wired network; and storing the GNSS original data packet received by the cloud server into a memory through the preposed communication, simultaneously performing CRC (cyclic redundancy check), and discarding the GNSS original data which do not pass the CRC as error data.
Further, in step S2, the specific method for performing decryption includes: converting the GNSS original data in the memory into a binary form; the specific method for carrying out the analysis is as follows: and analyzing the position information of the GNSS original data in the memory, and updating the latitude and longitude of the equipment.
Further, step S3 includes the following sub-steps:
s31: calling GNSS data, and classifying according to the source type of the GNSS data to obtain the GNSS data of the base station and the GNSS data of the mobile station;
s32: classifying according to the format of GNSS data of the base station and the mobile station to obtain GNSS data in an RTCM format and GNSS data in an RAM format;
s33: performing RTCM analysis on GNSS data in an RTCM format, analyzing GNSS data in an RAM format by a manufacturer, and generating an RINEX format of ephemeris and an RINEX format of epoch;
s34: and pairing and resolving the ephemeris and the epoch, and storing a final resolving result into a result database.
Further, in step S33, the RTCM format of the GNSS data includes rtcm2.x format and rtcm3.x format;
in step S33, the analysis includes the following substeps:
s331: distinguishing GNSS data packet headers, analyzing the packet body according to the packet headers, and generating a plurality of small packets;
s332: circularly processing a plurality of packets, transmitting one packet into an analysis dynamic library for analysis to obtain an ephemeris or an epoch, and entering step S333 if the packet is the ephemeris or entering step S334 if the packet is the epoch;
s333: encrypting the ephemeris, and transmitting the ephemeris to a disk for pairing to generate an RINEX format of the ephemeris;
s334: encrypting the epoch, transmitting the epoch to a disk, and carrying out identification naming by seconds in ttag week to generate RINEX format of the epoch;
in step S333, the ephemeris includes the project ephemeris and the wide-area ephemeris.
Further, in step S34, the pairing method includes one base station to one mobile station, one base station to several mobile stations, several base stations to one mobile station, and several base stations to several mobile stations.
Further, in step S34, the calculating includes single base station calculating and multiple base station calculating;
the solution of ephemeris and epochs comprises the following sub-steps:
s341: establishing a pairing relation table according to a pairing mode;
s342: judging whether the GNSS data of the base station in the pairing relationship table changes, if so, entering a step S343, otherwise, entering a step S344;
s343: updating the pairing relationship table, adding the changed GNSS data into a resolving process, and entering the step S344;
s344: according to the pairing relation table, circularly pairing the paired GNSS data in sequence until the circularly pairing is passed, and entering the step S345;
s345: judging whether the GNSS data is settled, if so, returning to the step S344, otherwise, entering the step S346;
s346: reading the base station data, the mobile station data and the ephemeris, and judging whether the ephemeris meets a resolving condition, if so, entering a step S347, otherwise, returning to the step S344;
s347: and performing single-base station solution or multi-base station solution on the paired GNSS data, and storing the final solution data.
Further, in step S344, the specific method for cycle pairing is as follows: the base station ttag tag file has been found, the mobile station ttag tag file has been found, and the ephemeris has been found;
in step S347, the specific method for performing solution on the single base station is as follows: performing single base station calculation on the paired GNSS data, and sequentially performing adjustment and coordinate conversion on the single base station calculation result to obtain final calculation data;
the specific method for carrying out multi-base station calculation comprises the following steps: calling single base station resolving, adjustment and coordinate conversion to obtain a plurality of single base station resolving results in the same coordinate system, eliminating results with out-of-limit coordinate mutual difference in the plurality of single base station resolving results in the same coordinate system, and averaging with the remaining coordinates to obtain a final multi-base station resolving data result;
the final resolving data comprises a base station number, a mobile station number, satellite time, earth center coordinates and mean errors, earth center coordinates and mean errors, plane rectangular coordinates and mean errors and local independent coordinates and mean errors.
The invention has the beneficial effects that:
(1) compatibility: can be compatible with GNSS data formats of all manufacturers and Cors reference system data of all types, and supports conversion among different GNSS data formats.
(2) Flexibility: the method can effectively solve the problem of data association between the mobile station and the multiple base stations, improve the observation precision and greatly shorten the observation time under the same precision. Meanwhile, pairing service of Cors reference data and mobile station data in various modes is supported, automatic pairing setting with distance priority or data quality priority is supported, and therefore the association data relation between the reference station and the mobile station in the area is flexibly and comprehensively established and optimal calculation service is provided.
(3) The commonality is as follows: the GNSS data remote super-calculation method can improve the utilization rate of the reference station, thereby effectively solving the problem of the commonality of the reference station.
(4) Ease of use: by adopting the remote super-computation technology, the remote GNSS data receiving station and the server only need to be paired for the first time, so that the GNSS data receiving station and the server can be used all the time without manual data guiding, a hardware system and an operating system which are used for supporting resolving software in the GNSS user terminal are omitted, and the hardware cost and the operating system cost of GNSS equipment and the cost of solidifying resolving software are saved.
(5) High stability and high timeliness: GNSS data processing is completed by the background server or the cloud, so that the system is more stable, the functions are more complete, and the system is not limited by hardware, thereby improving the stability, timeliness and precision of the whole position service.
Drawings
FIG. 1 is a flow chart of a GNSS data remote super calculation method;
FIG. 2 is a schematic flow chart of a GNSS remote supercomputing technique;
FIG. 3(a) is a flow chart of GNSS data remote super-computation technique-core computation;
FIG. 3(b) is a flow chart of multi-base station solution;
FIG. 3(c) is a pairing solution flow diagram;
FIG. 3(d) is a flow chart of various solution models;
FIG. 4 is a main flow chart of data parsing;
FIG. 5 is a schematic diagram of resolving ephemeris and epoch data;
FIG. 6 is a schematic diagram of data pairing setup;
figure 7 is a single base station solver logic diagram.
Detailed Description
The embodiments of the present invention will be further described with reference to the accompanying drawings.
Before describing specific embodiments of the present invention, in order to make the solution of the present invention more clear and complete, the definitions of the abbreviations and key terms appearing in the present invention will be explained first:
CRC checking: a cyclic redundancy check code, referred to as a cyclic code for short, is a commonly used check code with error detection and correction capabilities.
ttag: tag denotes a label and ttag denotes the time stamp in seconds of the week, which is common knowledge of the person skilled in the art.
As shown in fig. 1, the present invention provides a GNSS data remote supercomputing method, which includes the following steps:
s1: acquiring GNSS original data, packaging the GNSS original data and storing the GNSS original data in a memory;
s2: decrypting and analyzing the GNSS original data in the memory, and storing the GNSS data obtained after decryption and analysis are finished;
s3: the GNSS data which are decrypted and analyzed are called, core operation is carried out, final resolving data are obtained, and the final resolving data are stored in a warehouse;
s4: and acquiring final resolved data or GNSS original data through a computer client or a mobile phone access server, and flexibly performing single-server deployment, multi-server deployment or cloud service deployment according to the user quantity and the GNSS data quantity to finish the GNSS data remote super-computation.
In the embodiment of the present invention, as shown in fig. 2, in step S1, the specific method for acquiring GNSS raw data includes: the method comprises the steps that GNSS raw data of satellites are received by utilizing GNSS data acquisition equipment or GNSS raw data of each base station are acquired by utilizing the internet;
the specific method for storing the packed GNSS original data packet into the memory comprises the following steps: utilizing a firewall to carry out interaction, and transmitting the GNSS original data packet to a cloud server in a secret file form through a wireless network or a wired network; storing the GNSS original data packet received by the cloud server into an internal memory through front-end communication, simultaneously performing CRC (cyclic redundancy check), and discarding GNSS original data which do not pass the CRC as error data;
the wireless network can adopt any one of a data radio station, GPRS, 3G, 4G and 5G; the wired network may employ any one of a cable and an optical fiber.
The CRC check ensures that the analyzed data are valid data. And storing the decrypted and verified original data and the analyzed longitude and latitude into an original data database, and calling the original data and the analyzed longitude and latitude for a core calculation process.
In this embodiment of the present invention, in step S2, the specific method for performing decryption is as follows: converting the GNSS original data in the memory into a binary form; the specific method for carrying out the analysis is as follows: and analyzing the position information of the GNSS original data in the memory, and updating the latitude and longitude of the equipment.
In the embodiment of the present invention, as shown in fig. 3(a), step S3 includes the following sub-steps:
s31: calling GNSS data, and classifying according to the source type of the GNSS data to obtain the GNSS data of the base station and the GNSS data of the mobile station;
s32: classifying according to the format of GNSS data of the base station and the mobile station to obtain GNSS data in an RTCM format and GNSS data in an RAM format;
s33: performing RTCM analysis on GNSS data in an RTCM format, analyzing GNSS data in an RAM format by a manufacturer, and generating an RINEX format of ephemeris and an RINEX format of epoch;
the invention supports data of different manufacturers. Before analysis, data classification pretreatment is carried out, data source manufacturers are distinguished according to data packet header files, and corresponding analysis methods are designed according to different equipment data protocols of the manufacturers. Finally, the data of different manufacturers are analyzed into a uniform and standard RINEX format for subsequent uniform solution,
s34: and pairing and resolving the ephemeris and the epoch, and storing a final resolving result into a result database.
The GNSS equipment flexibly constructs a regional type Cors reference station, which can be used as a reference station and a mobile station, and provides great flexibility for selecting pairing of the Cors station and the mobile station. A pairing service of Cors reference data and mobile station data in various modes is supported, such as a plurality of Cors to one mobile station, one Cors to a plurality of mobile stations, a mobile station for manually assigning a Cors station pair, and the like, and automatic pairing setting of distance priority or data quality (satellite number, signal-to-noise ratio) priority is supported.
As shown in fig. 4, the present invention supports data from different vendors. Before analysis, data classification pretreatment is carried out, data source manufacturers are distinguished according to data packet header files, and corresponding analysis methods are designed according to different equipment data protocols of the manufacturers. And finally, analyzing the data of different manufacturers into a uniform and standard RINEX format so as to be convenient for subsequent uniform resolution. The method mainly analyzes the position information data, the epoch data and the ephemeris data of the equipment. The ephemeris may be synthesized as single-item ephemeris and wide-area ephemeris. Project ephemeris and wide-area ephemeris files are required to be synthesized after ephemeris data are analyzed, the project ephemeris refers to ephemeris data received by GNSS equipment in a single project, the wide-area ephemeris is accumulation of the ephemeris data received by all the GNSS equipment in the system, and the wide-area ephemeris is more comprehensive and complete. When ephemeris is used, if project ephemeris is found to be absent, wide-area ephemeris may be used in place of the project ephemeris, which may be stored in different locations for separate use.
The invention can be compatible with GNSS data formats of all manufacturers, if the RTCM format carries out RTCM analysis according to versions, if the RAW format carries out analysis by different manufacturers, and supports the conversion among different GNSS data formats, such as RTCM2.X to RTCM3X, RTCM3X to Rinex, RTCM3X to ephemeris, Ublox RAW to Rinex and the like. Compatibility also manifests itself in the compatibility of all types of Cors reference system data.
In the embodiment of the present invention, as shown in fig. 5, in step S33, the RTCM format of the GNSS data includes rtcm2.x format and rtcm3.x format;
in step S33, the analysis includes the following substeps:
s331: distinguishing GNSS data packet headers, analyzing the packet body according to the packet headers, and generating a plurality of small packets;
s332: circularly processing a plurality of packets, transmitting one packet into an analysis dynamic library for analysis to obtain an ephemeris or an epoch, and entering step S333 if the packet is the ephemeris or entering step S334 if the packet is the epoch;
s333: encrypting the ephemeris, and transmitting the ephemeris to a disk for pairing to generate an RINEX format of the ephemeris;
s334: encrypting the epoch, transmitting the epoch to a disk, and carrying out identification naming by seconds in ttag week to generate RINEX format of the epoch;
in step S333, the ephemeris includes the project ephemeris and the wide-area ephemeris.
Project ephemeris and wide-area ephemeris files are required to be synthesized after ephemeris data are analyzed, the project ephemeris refers to ephemeris data received by GNSS equipment in a single project, the wide-area ephemeris is accumulation of the ephemeris data received by all the GNSS equipment in the system, and the wide-area ephemeris is more comprehensive and complete. When ephemeris is used, if project ephemeris is found to be absent, wide-area ephemeris may be used in place of the project ephemeris, which may be stored in different locations for separate use.
As shown in fig. 6, the data pairing setting is a precondition of resolving, existing resolving pairings are unidirectional pairings, and the invention can realize one-to-many pairing service, many-to-one pairing service, and many-to-many cross pairing service. The pairing relationship may be set in the system database as needed. During calculation, the system automatically generates a directory corresponding to the server for matching management after reading the matching set relationship from the database, and adopts multi-thread service, and each matching pair is divided into one thread for calculation, so that the uniqueness of matching is ensured, and the overall processing efficiency of the system is improved. As shown in fig. 7, specifically:
(1) before calculation, a calculation relation table is created, and the relation table is obtained through pairing setting. Firstly, acquiring base station data into a memory, and making a strategy for updating. And if the base station pairing data change exists after the program is started, updating a base station memory table, and then adding the new pairing into a new calculation process to calculate.
(2) The calculation process of the system is always paired, the base station, the monitoring station and the ephemeris are required to be matched at the same time, and then whether calculation is carried out or not is judged, so that repeated calculation is avoided.
Resolving by the single base station: and resolving the paired GNSS data, wherein the system provides a plurality of resolving models for selection, such as: differential iterative filtering real-time static high-precision (millimeter-scale) solution, post-static high-precision (millimeter-scale) solution, RTK dynamic medium-high-precision (centimeter-scale) solution and the like.
In the embodiment of the present invention, in step S34, the pairing mode includes one base station to one mobile station, one base station to several mobile stations, several base stations to one mobile station, and several base stations to several mobile stations.
The database has generated raw data for real-time solution, so multiple tasks can be formulated to complete post-hoc static solutions. The static calculation provided by the invention is firstly to automatically complete the static calculation according to the period, and is also carried out by manually operating pairing and time period on a front-end interface. And finally, the static resolving result is converged to a result database. The convergence solution result steps are as follows: the numbers of the base station and the monitoring station are determined, and then the starting date to be resolved is determined. Because the calculated data needs to be put in storage and leveled, the medium error value, the period and the like of the leveling are also determined, and whether the data is put in a real-time calculation base is determined when the data is put in storage. Since the real-time solver is separate from the static solver.
The data of the monitoring station, the data of the base station and the ephemeris data are read firstly, and each kind of satellite data is processed, and the data are in a standard RINEX data format of Rtcm 32. Judging whether the satellites in the ephemeris data meet resolving conditions, such as: the GPS is more than 3, the Beidou is more than 3, and the like. And finally, after the data are completely prepared, simultaneously transmitting all the data into a calculation to obtain a calculation result, and storing the calculation result data into a database after arranging.
In the embodiment of the present invention, in step S34, the calculating includes single base station calculating and multiple base station calculating;
the solution of ephemeris and epochs comprises the following sub-steps:
s341: establishing a pairing relation table according to a pairing mode;
s342: judging whether the GNSS data of the base station in the pairing relationship table changes, if so, entering a step S343, otherwise, entering a step S344; firstly, acquiring base station data into a memory, and making a strategy for updating. As shown in fig. 3(c), if there is a base station pairing data change after the program is started, it is necessary to update the base station memory table, and then add the new pairing to a new calculation process to calculate.
S343: updating the pairing relationship table, adding the changed GNSS data into a resolving process, and entering the step S344;
s344: according to the pairing relation table, circularly pairing the paired GNSS data in sequence until the circularly pairing is passed, and entering the step S345;
s345: judging whether the GNSS data is settled, if so, returning to the step S344, otherwise, entering the step S346; repeated solution is avoided;
s346: reading the base station data, the mobile station data and the ephemeris, and judging whether the ephemeris meets a resolving condition, if so, entering a step S347, otherwise, returning to the step S344;
s347: and performing single-base station solution or multi-base station solution on the paired GNSS data, and storing the final solution data.
The static solution provided by the system is firstly to automatically complete the static solution according to a period, and is also to manually operate pairing and time period to perform the static solution on a front-end interface. And finally, aggregating the static resolving result to a result database. The convergence solution result steps are as follows: the numbers of the base station and the monitoring station are determined, and then the starting date to be resolved is determined. Because the calculated data needs to be put in storage and leveled, the medium error value, the period and the like of the leveling are also determined, and whether the data is put in a real-time calculation base is determined when the data is put in storage. Since the real-time solver is separate from the static solver.
Firstly, reading monitoring station data, base station data and ephemeris data, and processing each satellite data, wherein the data are in a standard Rtcm32 RINEX data format. Judging whether the satellites in the ephemeris data meet resolving conditions, such as: the GPS is more than 3, the Beidou is more than 3, and the like. And finally, after the data are completely prepared, simultaneously transmitting all the data into a calculation to obtain a calculation result, and storing the calculation result data into a database after arranging.
As shown in fig. 3(d), the system provides a variety of solution models for selection, such as: differential iterative filtering real-time static high-precision (millimeter level) solution, post-event static high-precision (millimeter level) solution, RTK dynamic medium-high-precision (centimeter level) solution and the like;
the adjustment comprises three-dimensional unconstrained adjustment and two-dimensional constrained adjustment; and (4) performing coordinate transformation on the result data obtained after calculation according to the requirement so as to facilitate application. The invention designs a plurality of coordinate conversion modes: firstly, converting the geocentric coordinates into geodetic coordinates to obtain high-precision longitude and latitude data; converting the geodetic coordinates into station center coordinates; or converting geodetic coordinates into planar rectangular coordinates; the plane rectangular coordinate can also be converted into a local independent coordinate by a four-parameter method. And finally, storing all the result data into a database.
In this embodiment of the present invention, in step S344, a specific method for cycle pairing is: the base station ttag tag file has been found, the mobile station ttag tag file has been found, and the ephemeris has been found;
in step S347, the specific method for performing solution on the single base station is as follows: performing single base station calculation on the paired GNSS data, and sequentially performing adjustment and coordinate conversion on the single base station calculation result to obtain final calculation data;
as shown in fig. 3(b), the specific method for performing multi-base-station solution is as follows: calling single base station resolving, adjustment and coordinate conversion to obtain a plurality of single base station resolving results in the same coordinate system, eliminating results with out-of-limit coordinate mutual difference in the plurality of single base station resolving results in the same coordinate system, and averaging with the remaining coordinates to obtain a final multi-base station resolving data result;
the final resolving data comprises a base station number, a mobile station number, satellite time, earth center coordinates and mean errors, earth center coordinates and mean errors, plane rectangular coordinates and mean errors and local independent coordinates and mean errors.
Firstly, a plurality of coordinate achievements in the same coordinate system are obtained by calling a single base station flow, a balancing flow and a coordinate conversion flow for a plurality of times; and then, judging coordinate mutual difference, eliminating the result of mutual difference overrun, and taking the average value of qualified results as the final three-dimensional coordinate result. The finally resolved result data mainly comprises a base station number, a monitoring station number, satellite time, geocentric coordinates and medium errors, geodetic coordinates and medium errors, station center coordinates and medium errors, plane rectangular coordinates and medium errors and local independent coordinates and medium errors.
The working principle and the process of the invention are as follows: the method is based on a GNSS remote super-computation technology, a base station and a mobile station send satellite raw data to a remote server through an internet protocol, the data format types are analyzed to obtain ephemeris and observed quantity, various modes of pairing service are adopted, high-dynamic real-time calculation and static calculation of a single base station and multiple base stations are supported, so that a high-precision (accurate to millimeter level) coordinate position result is obtained, the coordinate data result is stored in a database, and an API (application program interface) is provided for a client to call to obtain a relevant coordinate position result.
The invention has the beneficial effects that:
(1) compatibility: can be compatible with GNSS data formats of all manufacturers and Cors reference system data of all types, and supports conversion among different GNSS data formats.
(2) Flexibility: the method can effectively solve the problem of data association between the mobile station and the multiple base stations, improve the observation precision and greatly shorten the observation time under the same precision. Meanwhile, pairing service of Cors reference data and mobile station data in various modes is supported, automatic pairing setting with distance priority or data quality priority is supported, and therefore the association data relation between the reference station and the mobile station in the area is flexibly and comprehensively established and optimal calculation service is provided.
(3) The commonality is as follows: the GNSS data remote super-calculation method can improve the utilization rate of the reference station, thereby effectively solving the problem of the commonality of the reference station.
(4) Ease of use: by adopting the remote super-computation technology, the remote GNSS data receiving station and the server only need to be paired for the first time, so that the GNSS data receiving station and the server can be used all the time without manual data guiding, a hardware system and an operating system which are used for supporting resolving software in the GNSS user terminal are omitted, and the hardware cost and the operating system cost of GNSS equipment and the cost of solidifying resolving software are saved.
(5) High stability and high timeliness: GNSS data processing is completed by the background server or the cloud, so that the system is more stable, the functions are more complete, and the system is not limited by hardware, thereby improving the stability, timeliness and precision of the whole position service.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (6)
1. A GNSS data remote super-calculation method is characterized by comprising the following steps:
s1: acquiring GNSS original data, packaging the GNSS original data and storing the GNSS original data in a memory;
s2: decrypting and analyzing the GNSS original data in the memory, and storing the GNSS data obtained after decryption and analysis are finished;
s3: the GNSS data which are decrypted and analyzed are called, core operation is carried out, final resolving data are obtained, and the final resolving data are stored in a warehouse;
s4: acquiring final resolved data or GNSS original data through a computer client or a mobile phone access server, and performing single-server deployment, multi-server deployment or cloud service deployment according to the user quantity and the GNSS data quantity to complete remote super calculation of the GNSS data;
the step S3 includes the following sub-steps:
s31: calling GNSS data, and classifying according to the source type of the GNSS data to obtain the GNSS data of the base station and the GNSS data of the mobile station;
s32: classifying according to the format of GNSS data of the base station and the mobile station to obtain GNSS data in an RTCM format and GNSS data in an RAM format;
s33: performing RTCM analysis on GNSS data in an RTCM format, analyzing GNSS data in an RAM format by a manufacturer, and generating an RINEX format of ephemeris and an RINEX format of epoch;
s34: pairing and resolving ephemeris and epoch, and storing a final resolving result into a result database;
in the step S34, the calculating includes single base station calculating and multiple base station calculating;
the solution of ephemeris and epochs comprises the following sub-steps:
s341: establishing a pairing relation table according to a pairing mode;
s342: judging whether the GNSS data of the base station in the pairing relationship table changes, if so, entering a step S343, otherwise, entering a step S344;
s343: updating the pairing relationship table, adding the changed GNSS data into a resolving process, and entering the step S344;
s344: according to the pairing relation table, circularly pairing the paired GNSS data in sequence until the circularly pairing is passed, and entering the step S345;
s345: judging whether the GNSS data is settled, if so, returning to the step S344, otherwise, entering the step S346;
s346: reading the base station data, the mobile station data and the ephemeris, and judging whether the ephemeris meets a resolving condition, if so, entering a step S347, otherwise, returning to the step S344;
s347: and performing single-base station solution or multi-base station solution on the paired GNSS data, and storing the final solution data.
2. The method for remotely super calculating GNSS data according to claim 1, wherein in step S1, the specific method for collecting GNSS raw data is as follows: the method comprises the steps that GNSS raw data of satellites are received by utilizing GNSS data acquisition equipment or GNSS raw data of each base station are acquired by utilizing the internet;
the specific method for storing the packed GNSS original data packet into the memory comprises the following steps: utilizing a firewall to carry out interaction, and transmitting the GNSS original data packet to a cloud server in a secret file form through a wireless network or a wired network; and storing the GNSS original data packet received by the cloud server into a memory through the preposed communication, simultaneously performing CRC (cyclic redundancy check), and discarding the GNSS original data which do not pass the CRC as error data.
3. The GNSS data remote supercomputing method of claim 1, wherein in the step S2, the specific method for performing decryption is as follows: converting the GNSS original data in the memory into a binary form; the specific method for carrying out the analysis is as follows: and analyzing the position information of the GNSS original data in the memory, and updating the latitude and longitude of the equipment.
4. The method for remote GNSS data super calculation according to claim 1, wherein in step S33, the RTCM format of the GNSS data includes rtcm2.x format and rtcm3.x format;
in step S33, the analyzing includes the following substeps:
s331: distinguishing GNSS data packet headers, analyzing the packet body according to the packet headers, and generating a plurality of small packets;
s332: circularly processing a plurality of packets, transmitting one packet into an analysis dynamic library for analysis to obtain an ephemeris or an epoch, and entering step S333 if the packet is the ephemeris or entering step S334 if the packet is the epoch;
s333: encrypting the ephemeris, and transmitting the ephemeris to a disk for pairing to generate an RINEX format of the ephemeris;
s334: encrypting the epoch, transmitting the epoch to a disk, and carrying out identification naming by seconds in ttag week to generate RINEX format of the epoch;
in step S333, the ephemeris includes the project ephemeris and the wide-area ephemeris.
5. The method for remote GNSS data super calculation of claim 1, wherein in step S34, the pairing is performed by a base station to a mobile station, a base station to a plurality of mobile stations, a plurality of base stations to a mobile station, and a plurality of base stations to a plurality of mobile stations.
6. The method for GNSS data remote super calculation according to claim 1, wherein in step S344, the specific method for cycle pairing is as follows: the base station ttag tag file has been found, the mobile station ttag tag file has been found, and the ephemeris has been found;
in step S347, the specific method for performing solution on the single base station is as follows: performing single base station calculation on the paired GNSS data, and sequentially performing adjustment and coordinate conversion on the single base station calculation result to obtain final calculation data;
the specific method for carrying out multi-base station calculation comprises the following steps: calling single base station resolving, adjustment and coordinate conversion to obtain a plurality of single base station resolving results in the same coordinate system, eliminating results with out-of-limit coordinate mutual difference in the plurality of single base station resolving results in the same coordinate system, and averaging with the remaining coordinates to obtain a final multi-base station resolving data result;
the final resolving data comprises a base station number, a mobile station number, satellite time, a geocentric coordinate and a median error, a geodetic coordinate and a median error, a geocentric coordinate and a median error, a plane rectangular coordinate and a median error, and a local independent coordinate and a median error.
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