WO2023082785A1 - 网络rtk抗电离层干扰定位方法、装置、系统、设备及存储介质 - Google Patents

网络rtk抗电离层干扰定位方法、装置、系统、设备及存储介质 Download PDF

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WO2023082785A1
WO2023082785A1 PCT/CN2022/116380 CN2022116380W WO2023082785A1 WO 2023082785 A1 WO2023082785 A1 WO 2023082785A1 CN 2022116380 W CN2022116380 W CN 2022116380W WO 2023082785 A1 WO2023082785 A1 WO 2023082785A1
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Prior art keywords
ionospheric
terminal
quality factor
rtk
filtering mode
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PCT/CN2022/116380
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English (en)
French (fr)
Inventor
陈华炎
何锡扬
战兴群
冯绍军
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千寻位置网络（浙江）有限公司
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Publication of WO2023082785A1 publication Critical patent/WO2023082785A1/zh

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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
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
    • 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
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
    • G01S19/072—Ionosphere corrections
    • 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
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/40—Correcting position, velocity or attitude
    • G01S19/41—Differential correction, e.g. DGPS [differential GPS]
    • 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
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position

Definitions

  • the application belongs to the technical field of satellite positioning, and in particular relates to a network RTK anti-ionospheric interference positioning method, device, system, equipment and storage medium.
  • the server can model the ionospheric error and tropospheric error, and broadcast the corresponding differential correction number to the terminal according to the approximate position of the terminal.
  • the terminal can eliminate the influence of ionospheric errors and tropospheric errors through differential corrections to achieve high-precision positioning.
  • the server has residual errors in the modeling of the ionosphere error, which leads to a large ionosphere error after the terminal uses the difference correction number broadcasted by the server, making the terminal unable to fix the ambiguity of the entire cycle. Degree or full-circle ambiguity is fixed and wrong, and high-precision positioning cannot be performed.
  • the embodiment of the present application provides a network RTK anti-ionospheric interference positioning method, device, system, equipment and storage medium, which can solve the technical problem that the network RTK positioning cannot achieve high-precision positioning when the ionosphere is active.
  • the embodiment of the present application provides a network RTK anti-ionospheric interference positioning method, which is applied to a terminal, and the method includes:
  • the differential correction number and quality factor are generated by the server based on the observation data and location information of each base station and the approximate location information uploaded by the terminal.
  • the quality factor is used to represent the atmospheric error used to generate the differential correction number model accuracy
  • the RTK filtering mode includes ionosphere-free combined filtering mode or non-combined filtering mode
  • the determined RTK filtering mode is used to filter and solve the observation data of the terminal and the difference correction number received by the terminal, and obtain the high-precision position information of the terminal.
  • the quality factor that characterizes the accuracy of the atmospheric error model is broadcast by the server, so that the terminal can select the RTK filter mode from the ionospheric combined filter mode or the non-combined filter mode according to the quality factor, and can choose to eliminate the ionospheric error during the active period of the ionosphere.
  • the ionosphere-free combined filter mode performs filter calculations to eliminate the influence of ionospheric errors and achieve high-precision positioning during ionospheric active periods.
  • the embodiment of the present application provides a network RTK anti-ionospheric interference positioning method, which is applied to a server, and the method includes:
  • each base station in the base station network multiple baselines of ionospheric errors and tropospheric errors are generated, and the baseline is formed by connecting two base stations;
  • the atmospheric error model is obtained;
  • model parameters of the atmospheric error model calculate the difference correction number of multiple grid point positions in the base station network and the quality factor of multiple grid point positions
  • RTK filtering mode includes ionosphere-free combined filtering mode or non-combined filtering mode.
  • the server can broadcast the difference correction number and quality factor of the target grid point to the terminal according to the approximate position sent by the terminal, so that after the terminal determines the RTK filtering mode according to the quality factor, it performs filtering calculation according to the difference correction number and the observation data of the terminal, and obtains the terminal high-precision location information.
  • the embodiment of the present application provides a network RTK anti-ionospheric interference positioning device, the device includes:
  • the receiving module is used to receive the differential correction number and quality factor broadcast by the server.
  • the differential correction number and quality factor are generated by the server based on the observation data and location information of each base station and the approximate location information uploaded by the terminal.
  • the quality factor is used to represent and generate differential corrections Atmospheric error model precision used for the calculation;
  • a determination module configured to determine the RTK filtering mode according to the received quality factor, the RTK filtering mode includes an ionosphere-free combined filtering mode or a non-combined filtering mode;
  • the positioning module is used to filter and calculate the observation data of the terminal and the differential correction number received by the terminal by using a determined RTK filtering mode, so as to obtain high-precision position information of the terminal;
  • the device includes:
  • the error module is used to generate ionospheric errors and tropospheric errors of multiple baselines according to the observation data and position information of each base station in the base station network, and the baseline is formed by connecting two base stations;
  • the modeling module is used to model the ionospheric error and tropospheric error based on multiple baselines and the position information of each base station to obtain an atmospheric error model;
  • Calculation module for calculating the differential correction number of multiple grid point positions in the base station network and the quality factor of multiple grid point positions according to the model parameters of the atmospheric error model;
  • a matching module configured to determine a target grid point closest to the terminal's approximate position from among multiple grid point positions according to the approximate position information sent by the terminal;
  • the broadcast module is used to broadcast the differential correction number and quality factor of the target grid point to the terminal, so that the terminal determines the RTK filtering mode according to the quality factor of the target grid point, and uses the differential correction number to perform filtering calculation according to the RTK filtering mode to obtain the terminal High-precision position information, RTK filter mode includes ionosphere-free combined filter mode or non-combined filter mode.
  • the embodiment of the present application provides a network RTK anti-ionospheric interference positioning system, including a server and a terminal, and the system includes:
  • the server According to the observation data and location information of each base station in the base station network, the server generates ionospheric errors and tropospheric errors of multiple baselines, and the baseline is formed by connecting two base stations;
  • the server performs modeling based on the ionospheric error and tropospheric error of multiple baselines and the location information of each base station to obtain an atmospheric error model;
  • the server calculates the difference correction number of multiple grid point positions in the base station network and the quality factor of multiple grid point positions according to the model parameters of the atmospheric error model;
  • the server determines the target grid point closest to the terminal's approximate position from among multiple grid point positions according to the approximate position information sent by the terminal;
  • the server broadcasts the differential correction number and quality factor of the target grid point to the terminal;
  • the terminal receives the differential correction number and quality factor broadcast by the server.
  • the differential correction number and quality factor are generated by the server based on the observation data and location information of each base station and the approximate location information uploaded by the terminal.
  • the quality factor is used to represent the atmosphere used to generate the differential correction number error model accuracy;
  • the terminal determines the RTK filtering mode according to the received quality factor, and the RTK filtering mode includes an ionosphere-free combined filtering mode or a non-combined filtering mode;
  • the terminal adopts the determined RTK filtering mode to filter and solve the observation data of the terminal and the difference correction number received by the terminal, and obtain the high-precision position information of the terminal.
  • the embodiment of the present application provides a network RTK anti-ionospheric interference positioning device.
  • the network RTK anti-ionospheric interference positioning device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it realizes The above network RTK anti-ionospheric interference positioning method.
  • the embodiment of the present application provides a computer storage medium, on which computer program instructions are stored.
  • the computer program instructions are executed by a processor, the above network RTK anti-ionospheric interference positioning method is realized.
  • the network RTK anti-ionospheric interference positioning method provided by the embodiment of the present application generates a quality factor representing the accuracy of the atmospheric error model when the server models the ionospheric error and tropospheric error, and compares the quality factor with the The difference correction number is broadcast to the terminal together.
  • the terminal can judge whether the current differential correction number is affected by the active ionosphere according to the quality factor, and select the appropriate RTK filter mode from the ionosphere-free combined filter mode or non-combined filter mode according to the judgment result, and the observation data of the terminal and The differential corrections received by the terminal are filtered and calculated to eliminate the influence of ionospheric errors when the ionosphere is active and achieve high-precision positioning.
  • the filter mode can be switched according to the active state of the ionosphere, avoiding the interference of ionospheric errors during the active period of the ionosphere, and improving the positioning effect during the active period of the ionosphere.
  • Fig. 1 is a schematic flow diagram of a network RTK anti-ionospheric interference positioning method provided by an embodiment of the present application
  • FIG. 2 is a schematic flow diagram of a network RTK anti-ionospheric interference positioning method provided by another embodiment of the present application;
  • FIG. 3 is a schematic flow diagram of a network RTK anti-ionospheric interference positioning method provided in another embodiment of the present application.
  • Fig. 4 is a schematic diagram of the refinement steps of S210 in the embodiment of Fig. 2;
  • FIG. 5 is a schematic flow diagram of a network RTK anti-ionospheric interference positioning method provided by an embodiment of the present application
  • FIG. 6 is a schematic flow diagram of a network RTK anti-ionospheric interference positioning method provided by another embodiment of the present application.
  • FIG. 7 is a schematic flow diagram of a network RTK anti-ionospheric interference positioning method provided by another embodiment of the present application.
  • Fig. 8 is a schematic structural diagram of a network RTK anti-ionospheric interference positioning device provided by an embodiment of the present application.
  • FIG. 9 is a schematic structural diagram of a network RTK anti-ionospheric interference positioning device provided by another embodiment of the present application.
  • FIG. 10 is a schematic diagram of a hardware structure of a network RTK anti-ionospheric interference positioning device provided by an embodiment of the present application.
  • each base station can obtain the atmospheric delay information of the ionosphere and troposphere respectively, and calculate and generate the ionosphere error and troposphere error corresponding to the base station.
  • the atmospheric error model can be modeled according to the base station network composed of each base station, and the differential correction number of the approximate position can be calculated and sent to the terminal according to the established atmospheric error model, so that the terminal can observe The data and differential corrections are filtered and calculated to obtain high-precision position information of the terminal.
  • Embodiments of the present application provide a network RTK anti-ionospheric interference positioning method, device, system, equipment, and storage medium. The following first introduces the network RTK anti-ionospheric interference positioning method provided by the embodiment of the present application.
  • Fig. 1 shows a schematic flowchart of a network RTK anti-ionospheric interference positioning method provided by an embodiment of the present application.
  • the network RTK anti-ionospheric interference positioning method is applied to the terminal, and the methods include:
  • the differential correction number and quality factor are generated by the server based on the observation data and location information of each base station and the approximate location information uploaded by the terminal.
  • the quality factor is used to represent the difference used for generating the differential correction number. Atmospheric error model accuracy;
  • the RTK filtering mode includes an ionosphere-free combined filtering mode or a non-combined filtering mode
  • the server can perform data communication with various base stations and terminals to realize data transmission.
  • the observation data of the base station may include observed carrier waves, pseudo-range observation values, etc.
  • the location information of the base station may include base station coordinates, antenna information codes, and the like.
  • the observation data of the terminal may include carrier waves, pseudorange observation values, etc. observed at the same epoch as the base station. It can be understood that the data acquired by the base station may also include ephemeris data, and the data acquired by the terminal may also include ephemeris data.
  • each base station can send its observation data and location information to the server, and the terminal can send its approximate location information to the server.
  • the server can generate the differential correction number and quality factor corresponding to the terminal according to the observation data and location information of the base station and the rough location information uploaded by the terminal.
  • the terminal can select the corresponding RTK filter according to the quality factor mode, so that when the ionosphere is active, the RTK filter mode that can effectively eliminate the residual error of the ionosphere can be selected, and in the determined RTK filter mode, the filter calculation can be performed according to the difference correction number and its own observation data to fix the whole circle ambiguity degree, and obtain high-precision location information of the terminal.
  • the quality factor that characterizes the accuracy of the atmospheric error model is broadcast by the server, so that the terminal can select the RTK filter mode from the ionospheric combined filter mode or the non-combined filter mode according to the quality factor, and can choose to eliminate the ionospheric error during the active period of the ionosphere.
  • the ionosphere-free combined filter mode performs filter calculations to eliminate the influence of ionospheric errors and achieve high-precision positioning during ionospheric active periods.
  • each base station can upload observed observation data and location information, and the terminal can upload its approximate location information.
  • the server After receiving the observation data and location information of each base station and the approximate location information of the terminal, the server can generate differential correction numbers and quality factors, and broadcast the differential correction numbers and quality factors to the terminals.
  • the terminal may determine an RTK filtering mode for performing filter calculation according to the received quality factor.
  • the RTK filtering mode can be ionosphere-free combined filtering mode or non-combined filtering mode. Among them, if the RTK filtering mode adopts the ionosphere-free combined filtering mode, it can eliminate the influence of the ionospheric error when the residual error of the ionosphere is large, and realize high-precision positioning of the terminal during the active period of the ionosphere; if the RTK filtering mode adopts the non-combined filtering mode mode, it can achieve high-precision positioning of the terminal when the ionosphere is not active.
  • the above S120 may include:
  • the terminal may judge whether the ionosphere of the current epoch is active according to the received quality factor, and if it is determined that the ionosphere of the current epoch is active, then obtain the number of epochs in which the ionosphere is active in the first time period, And when the preset value is reached, it is determined that the RTK filtering mode adopted is the ionosphere-free combination mode, so that the terminal observation data and the differential correction number received by the terminal are filtered and calculated according to the ionosphere-free combination mode, so as to eliminate the active ionosphere Influenced by ionospheric errors, the high-precision position information of the terminal can be obtained.
  • the terminal may judge the quality factor according to a preset judgment rule, so as to determine whether the ionosphere of the current epoch is active.
  • a preset judgment rule is met, it is determined that the ionosphere is active in the current epoch.
  • the terminal when the terminal determines that the ionosphere is active in the current epoch, it may count the number of epochs in which the ionosphere is active in the first time period up to the current epoch, so as to obtain the number of active ionospheres in the first time period. Number of epochs.
  • the preset judgment rule may be whether the number of epochs in which the ionosphere is active within the first time period reaches a preset first epoch threshold.
  • the ionospheric activity value corresponding to the current epoch may be set to "active" or "1", and stored in the database.
  • the ionospheric activity value corresponding to the current epoch may be set to "inactive" or "0", and stored in the database.
  • the terminal When the terminal determines that the ionosphere is active in the current epoch, it can also obtain the number of "active" or "1" ionospheric activity values in the past first time period from the database, so as to determine the history of ionospheric activity in the first time period. number of elements.
  • the terminal may compare the number of epochs with active ionosphere with the preset first epoch threshold, if the number of epochs with active ionosphere reaches When the first epoch threshold is preset, the terminal may determine the adopted RTK filtering mode as the ionosphere-free combined filtering mode.
  • the terminal can calculate the ionosphere-free combination observation value according to its own observation data and the ionosphere-free combination formula.
  • the ionosphere-free combination formula is as follows:
  • P 1 and P 2 are the pseudo-range observation values of the first frequency and the second frequency respectively (unit: m)
  • ⁇ 1 and ⁇ 2 are the carrier observation values of the first frequency and the second frequency respectively (unit: week)
  • P IF , ⁇ IF are the ionospheric combined observations of pseudorange and carrier, respectively.
  • the preset judging rule may also be judging whether the number of epochs in which the ionosphere is continuously active within the first time period reaches a preset first epoch threshold.
  • the terminal may acquire ionospheric activity values in historical epochs whose quantity is a preset first epoch threshold value starting from the current epoch. For example, when the preset threshold value of the first epoch is 10, the active value of the ionosphere for 10 consecutive epochs can be obtained starting from the current epoch.
  • the terminal can determine the RTK filtering mode as the ionosphere-free combined filtering mode. If there is at least one epoch with an ionospheric activity value of "inactive" or "0", the RTK filter mode will not be adjusted.
  • Fig. 3 in order to realize high-precision positioning when the ionosphere is inactive, after the above-mentioned S230, may include:
  • the RTK filtering mode is switched to a non-combined filtering mode.
  • the terminal when the terminal determines that the ionosphere is inactive in the current epoch, it acquires the number of epochs in which the ionosphere is inactive in the second time period, and the number of epochs in which the ionosphere is inactive in the second time period reaches The corresponding preset value determines that the adopted RTK filtering mode is the non-combined filtering mode.
  • the terminal performs filter calculation on the observation data of the terminal and the differential correction number received by the terminal through the non-combined filtering mode, which can eliminate the influence of various errors on the integer ambiguity, thereby quickly fixing the integer ambiguity and calculating the height of the terminal. Accurate location information.
  • the terminal when the terminal determines that the ionosphere is inactive in the current epoch, it may count the number of epochs in which the ionosphere is active in the second time period up to the current epoch, so as to obtain the number of epochs in which the ionosphere is inactive in the second time period number of epochs. For example, when the terminal determines that the ionosphere is not active in the current epoch, the ionospheric activity value corresponding to the current epoch may be set to "inactive" or "0", and stored in the database.
  • the terminal determines that the ionosphere is not active in the current epoch, it can also obtain the number of ionospheric active values "inactive" or "0" in the second time period in the past from the database, so as to determine that the ionosphere is active in the second time period number of epochs.
  • the terminal may compare the number of epochs in which the ionosphere is inactive with a preset second epoch threshold, and if the number of epochs in which the ionosphere is inactive When the number of epochs reaches the preset second epoch threshold, the terminal may determine the adopted RTK filtering mode as a non-combined filtering mode.
  • the above preset judgment rule may also be whether the number of epochs in which the ionosphere is continuously inactive reaches a preset second epoch threshold. That is, when the terminal determines that the ionosphere of the current epoch is not active, it can acquire the ionospheric activity values of multiple consecutive epochs before the current epoch. If the layer active value is "inactive" or "0", the terminal can switch the RTK filtering mode to a non-combined filtering mode. If there is at least one ionospheric activity value "active" or "1" among the ionospheric activity values of multiple consecutive epochs, the RTK filtering mode is not adjusted.
  • the quality factor may include the ionospheric quality factor corresponding to multiple satellites and the tropospheric quality corresponding to multiple satellites Factors, above S210, may include:
  • the received ionospheric quality factors of multiple satellites and the tropospheric quality factors of multiple satellites are respectively sorted from small to large;
  • the above S210 may include:
  • the quality factors received by the terminal include ionospheric quality factors of multiple satellites and tropospheric quality factors of multiple satellites.
  • the terminal can sort the ionospheric quality factors and also sort the tropospheric quality factors. After sorting, the ionospheric quality factor of a specific quantile and the tropospheric quality factor of a specific quantile can be obtained, and the ionization of the current epoch can be determined according to the obtained ionospheric quality factor, tropospheric quality factor and the preset minimum active threshold Whether the layer is active.
  • the quality factor When calculating the quality factor, there will be other influencing factors, resulting in a certain error in the obtained quality factor.
  • the influence of public errors caused by other factors such as base station observations and base station network topology can be eliminated, thereby accurately judging the current active state of the ionosphere.
  • the terminal may sort the received ionospheric quality factors of the multiple satellites in ascending order, and sort the received tropospheric quality factors of the multiple satellites in ascending order.
  • the terminal may determine the first quantile of the ionospheric quality factors among the sorted ionospheric quality factors; and may determine the second quantile of the tropospheric quality factors of the sorted tropospheric quality factors.
  • the quantile value of the first quantile may be less than or equal to the quantile value of the second quantile.
  • the first quantile may be 75% and the second quantile may be 90%.
  • the first quantile is 75% of the ionospheric quality factor ⁇ I,75 , which means that in the sorting from small to large, the number of ionospheric quality factors smaller than this ionospheric quality factor accounts for 75% of the total number.
  • the tropospheric quality factor ⁇ T,90 whose second quantile is 90% means that in the sorting from small to large, the number of tropospheric quality factors smaller than this tropospheric quality factor accounts for 90% of the total number.
  • the terminal After obtaining the ionospheric quality factor of the first quantile and the tropospheric quality factor of the second quantile, the terminal can compare the ionospheric quality factor of the first quantile with the tropospheric quality factor of the second quantile, and determine the first Whether the ionospheric quality factor of the quantile is greater than the tropospheric quality factor of the second quantile. The terminal may also judge whether the ionospheric quality factor of the first quantile is greater than a preset minimum active threshold.
  • the terminal may determine the ionospheric quality factor of the current epoch when the ionospheric quality factor of the first quantile is greater than the tropospheric quality factor of the second quantile, and the ionospheric quality factor of the first quantile is greater than the preset minimum active threshold. layer active.
  • the preset minimum active threshold I low can be determined, And judge whether ⁇ I,75 > ⁇ T,90 and ⁇ I,75 >I low .
  • ⁇ I,75 > ⁇ T,90 and ⁇ I,75 >I low it can be determined that the ionosphere of the current epoch is active, otherwise it can be determined that the ionosphere of the current epoch is calm or inactive.
  • the factors affecting the quality factor are not only the ionospheric modeling error or the tropospheric modeling error, but also the geometric topology of the base station network and the observation noise of the base station. It is difficult to judge whether the ionosphere is in an active state at this time if only comparing the ionospheric quality factor with the preset minimum active threshold. Therefore, the ionospheric quality factor can also be compared with the tropospheric quality factor to exclude the influence of common errors caused by base station observations, base station network topology and other factors.
  • the terminal may sort the received ionospheric quality factors of the multiple satellites from large to small, and sort the received tropospheric quality factors of the multiple satellites from large to small.
  • the terminal may determine the ionospheric quality factor of the third quantile in the sorted ionospheric quality factors; and may determine the tropospheric quality factor of the fourth quantile in the sorted tropospheric quality factors. where the quantile value of the third quantile is greater than or equal to the quantile value of the fourth quantile.
  • the terminal may determine the ionospheric quality factor of the current epoch when the ionospheric quality factor of the third quantile is greater than the tropospheric quality factor of the fourth quantile, and the ionospheric quality factor of the third quantile is greater than the preset minimum active threshold. layer active.
  • the terminal may filter and calculate the observation data of the terminal and the difference correction number received by the terminal according to the determined RTK filtering mode, so as to obtain high-precision position information of the terminal. For example, according to the quality factor received, the terminal can determine that the RTK filtering mode is the non-ionospheric combined filtering mode when determining that the ionosphere is an active period; when determining that the ionosphere is not an active period, determine that the RTK filtering mode is non-combined filtering model.
  • the terminal can use the non-combined filtering mode to filter and calculate the differential correction number and the terminal observation data, so as to obtain high-precision position information of the terminal during the ionosphere inactive period.
  • the terminal can use the ionosphere-free combination filter mode to calculate the ionosphere-free combination observation value based on the carrier observation values and pseudorange observation values of the two frequencies, so that the terminal can eliminate the Due to the influence of ionospheric errors, high-precision position information of the terminal can also be obtained according to the differential correction number and the observation data of the terminal during the active period of the ionosphere.
  • Fig. 5 shows a schematic flowchart of a network RTK anti-ionospheric interference positioning method provided by another embodiment of the present application.
  • the network RTK anti-ionospheric interference positioning method is applied to the server, and the network RTK anti-ionospheric interference positioning method includes:
  • S510 according to the observation data and position information of each base station in the base station network, generate ionospheric errors and tropospheric errors of multiple baselines, where the baselines are formed by connecting two base stations;
  • RTK filter mode includes ionosphere-free combined filter mode or non-combined filter mode.
  • the server can generate ionospheric errors and tropospheric errors of multiple baselines according to the data sent by each base station in the base station network, and perform modeling based on the baseline errors to obtain an atmospheric error model.
  • the differential correction number and quality factor of each grid point position in the area covered by the base station network can be calculated through the atmospheric error model.
  • the nearest grid point can be determined from multiple grid points according to the approximate position, and the difference correction number and quality factor corresponding to the grid point can be broadcast to the terminal, so that the terminal
  • the filtering calculation is performed according to the difference correction number and the observation data of the terminal, and the high-precision position information of the terminal is obtained.
  • the server may receive observation data and location information respectively sent by each base station in the base station network.
  • a baseline can be formed by connecting any two base stations, and the ionospheric error and tropospheric error of the baseline can be generated according to the observation data and location information of the two base stations. After the base stations are connected in pairs, the ionospheric errors and tropospheric errors corresponding to the multiple baselines in the base station network can be generated.
  • the above S510 may include:
  • the server may obtain observation data and location information of each base station in the base station network.
  • the double-difference ambiguity of the baseline can be calculated according to the observation data and location information of the two base stations.
  • the ionospheric and tropospheric error values of the baseline can be calculated back.
  • the ionospheric error value and tropospheric error value of multiple baselines can be obtained by back-calculating each baseline in turn. It can be understood that the ionospheric error value and the tropospheric error value of the baseline are the differential correction numbers corresponding to the baseline.
  • multiple base stations can be formed by connecting two by two base stations, and multiple base lines and base stations can form a network to form a base station network. According to the observation data and location information of each base station, the double-difference ambiguity of the corresponding baseline can be solved.
  • the ionospheric error value and the tropospheric error value of the baseline can be calculated through corresponding formulas.
  • the inverse formula is as follows:
  • f 1 and f 2 are respectively the first and second frequencies (unit: MHz) of the base station observation signal, and The carrier observation values (unit: m) of the ambiguity are restored for the first frequency and the second frequency respectively, is the double-difference vacuum geometric distance value (unit: m), It can be calculated based on the satellite coordinates and the precise coordinates of the base station.
  • the server can perform atmospheric calculations for the area covered by the base station network according to the ionospheric errors and tropospheric errors of the multiple baselines and the location information of each base station. Modeling of the error model and solving the model parameters of the atmospheric error model. After the atmospheric error model is established, for a specific position in the region, the ionospheric error and tropospheric error of the specific position can be calculated according to the coordinates of the specific position and the model parameters of the atmospheric error model.
  • modeling equation for an atmospheric error model can be:
  • L is the observed value of the atmospheric error model, and the ionospheric error and tropospheric error can be modeled separately. That is, the observed value of the ionospheric error is The observed value of the tropospheric error is m is the number of baselines used to build the atmospheric error model. A is the coefficient matrix related to the coordinate position of the baseline, and X is the model parameter to be solved.
  • the above modeling equation can be solved to determine the model parameters of the atmospheric error model.
  • the above modeling equation can be solved by the least square method, and the model parameters of the atmospheric error model are obtained as:
  • the terminal can determine the positions of multiple grid points within the range according to the range of the base station network, and determine the difference correction number and quality factor.
  • the differential correction number of the grid point position is the ionospheric error and tropospheric error of the grid point position
  • the quality factor is the ionospheric modeling error quality factor of each satellite at the grid point position and the tropospheric modeling error quality factor of each satellite .
  • the differential correction number calculation formula is as follows:
  • B correction is the coefficient matrix corresponding to the coordinates of the grid point position
  • L correction is the ionospheric error value or tropospheric error value of the grid point position obtained after the solution.
  • multiple grid point positions can be generated by the interpolation algorithm, and the ionospheric error value or tropospheric error value corresponding to each grid point position can be calculated through the above-mentioned differential correction number calculation formula, namely Calculate the difference correction number corresponding to each grid point position.
  • the interpolation algorithm can be inverse distance weighting method, linear interpolation method, least squares collocation method, etc. After calculating the difference correction number of each grid point position, if the server receives the approximate position sent by the terminal, it can determine the grid point position closest to the approximate position, and broadcast the difference correction of the closest grid point position to the terminal number and quality factors.
  • the above S530 may include:
  • the ionosphere modeling error quality factor of each satellite and the troposphere modeling error quality factor of each satellite can also be calculated at each grid point position.
  • the server can also substitute the coordinate positions of each baseline into the model parameters to obtain the ionospheric error value and the tropospheric error value corresponding to the baseline position under the atmospheric error model.
  • the server can determine the actual error value under the atmospheric error model The observed residual between the value and the error value computed by the model.
  • the formula for calculating the observation residual is as follows:
  • A is the coefficient matrix related to the coordinate position of the baseline
  • L is the ionospheric error value or tropospheric error value obtained by back-calculating the baseline according to the double-difference ambiguity
  • V is the observation value residual of the atmospheric error model.
  • ⁇ 0 is the standard deviation of unit weight
  • n is the number of baselines
  • k is the number of modeling parameters in the atmospheric error model.
  • the precision factor matrix of the modeling parameters of the atmospheric error model can be calculated according to the standard deviation of the unit weight.
  • the calculation formula of precision factor matrix is as follows:
  • the server may calculate the quality factor of the grid point position according to the position information of the grid point in the base station network. After calculating the position information of each grid point, the quality factor of each grid point position can be obtained. Calculated as follows:
  • B correction is the coefficient matrix corresponding to the coordinates of the grid point position
  • D is the above precision factor matrix
  • the quality factor of each grid point position may include an ionospheric modeling error quality factor and a troposphere modeling error quality factor.
  • the final calculated quality factor is the ionospheric modeling error quality factor of each satellite.
  • the input observation value is the tropospheric error value of each baseline
  • the final calculated quality factor is the tropospheric modeling error quality factor of each satellite.
  • the server determines the differential correction number and quality factor of each grid point position in the base station network, it can determine the approximate position corresponding to the terminal according to the approximate position information sent by the terminal, and determine the corresponding approximate position of the terminal from multiple grid point positions.
  • the grid point closest to the approximate position of is used as the target grid point.
  • the server determines the target grid point according to the approximate position of the terminal, it can obtain the differential correction number and quality factor of the target grid point, and broadcast it to the terminal.
  • the terminal After combining the difference correction number and quality factor of the target grid point, the terminal can determine the RTK filtering mode according to the quality factor, and use the difference correction number and the observation data of the terminal to perform filtering calculation according to the determined RTK filtering mode, so as to obtain the terminal high-precision location information.
  • the present application also provides a specific implementation manner of a network RTK anti-ionospheric interference positioning device. See the examples below.
  • the network RTK anti-ionospheric interference positioning device 800 provided in the embodiment of the present application includes the following modules:
  • the receiving module 801 is used to receive the difference correction number and quality factor broadcast by the server.
  • the difference correction number and quality factor are generated by the server according to the observation data and location information of each base station and the approximate location information uploaded by the terminal.
  • the quality factor is used to represent the generated difference Atmospheric error model precision used for corrections;
  • a decision module 802 configured to determine an RTK filtering mode according to the received quality factor, where the RTK filtering mode includes an ionosphere-free combined filtering mode or a non-combined filtering mode;
  • the positioning module 803 is configured to use a determined RTK filtering mode to filter and calculate the observation data of the terminal and the difference correction number received by the terminal, so as to obtain high-precision position information of the terminal.
  • the error module 901 is used to generate ionospheric errors and tropospheric errors of multiple baselines according to the observation data and position information of each base station in the base station network, and the baselines are formed by connecting two base stations;
  • the modeling module 902 is used to model the ionospheric error and tropospheric error based on multiple baselines and the position information of each base station to obtain an atmospheric error model;
  • Calculation module 903 for calculating the differential correction number of multiple grid point positions in the base station network and the quality factor of multiple grid point positions according to the model parameters of the atmospheric error model;
  • a matching module 904 configured to determine the target grid point closest to the approximate position of the terminal from among multiple grid point positions according to the approximate position information sent by the terminal;
  • the dissemination module 905 is used to broadcast the differential correction number and quality factor of the target grid point to the terminal, so that the terminal determines the RTK filtering mode according to the quality factor of the target grid point, and uses the differential correction number to perform filtering calculation according to the RTK filtering mode to obtain High-precision position information of the terminal, RTK filter mode includes ionosphere-free combined filter mode or non-combined filter mode.
  • each base station can send its observation data and location information to the server, and the terminal can send its approximate location information to the server.
  • the server can generate the differential correction number and quality factor corresponding to the terminal according to the observation data and location information of the base station and the rough location information uploaded by the terminal.
  • the terminal can select the corresponding RTK filter according to the quality factor mode, so that when the ionosphere is active, the RTK filter mode that can effectively eliminate the residual error of the ionosphere can be selected, and in the determined RTK filter mode, the filter calculation can be performed according to the difference correction number and its own observation data to fix the whole circle ambiguity degree, and obtain high-precision location information of the terminal.
  • the quality factor that characterizes the accuracy of the atmospheric error model is broadcast by the server, so that the terminal can select the RTK filter mode from the ionospheric combined filter mode or the non-combined filter mode according to the quality factor, and can choose to eliminate the ionospheric error during the active period of the ionosphere.
  • the ionosphere-free combined filter mode performs filter calculations to eliminate the influence of ionospheric errors and achieve high-precision positioning during ionospheric active periods.
  • the determination module 802 may further include:
  • a judging unit configured to judge whether the ionosphere of the current epoch is active according to the received quality factor
  • the first acquisition unit is used to obtain the active epoch number of the ionosphere in the first time period when the ionosphere of the current epoch is active;
  • the first determining unit is configured to determine the RTK filtering mode as the ionosphere-free combined filtering mode when the number of epochs in which the ionosphere is active reaches a preset first epoch threshold.
  • the above-mentioned determination module 802 may also include:
  • the second acquisition unit is used to acquire the number of epochs in which the ionosphere is inactive in the second time period when the ionosphere of the current epoch is inactive;
  • the second determining unit is configured to switch the RTK filtering mode to a non-combined filtering mode when the number of epochs in which the ionosphere is inactive reaches a preset second epoch threshold.
  • the quality factor includes the ionospheric quality factor corresponding to multiple satellites and the tropospheric quality factor corresponding to multiple satellites, and the above-mentioned determination unit may also include:
  • the first sorting subunit is used to sort the received ionospheric quality factors of multiple satellites and the tropospheric quality factors of multiple satellites respectively from small to large;
  • the first comparison subunit is used to judge whether the ionospheric quality factor of the first quantile is greater than the tropospheric quality factor of the second quantile, and whether the ionospheric quality factor of the first quantile is greater than a preset minimum active threshold, wherein the first The quantile is less than or equal to the second quantile.
  • Judgment module 802 also includes:
  • the first active subunit is used to determine the current epoch when the ionospheric quality factor of the first quantile is greater than the tropospheric quality factor of the second quantile, and the ionospheric quality factor of the first quantile is greater than a preset minimum active threshold
  • the ionosphere is active.
  • the above determination unit may also include:
  • the second sorting subunit is used to sort the received ionospheric quality factors of multiple satellites and the tropospheric quality factors of multiple satellites respectively from large to small;
  • the second sorting subunit is used to judge whether the ionospheric quality factor of the third quantile is greater than the tropospheric quality factor of the fourth quantile, and whether the ionospheric quality factor of the third quantile is greater than the preset minimum active threshold, wherein the third The quantile is greater than or equal to the fourth quantile.
  • Judgment module 802 also includes:
  • the second sorting subunit is used to determine the current epoch when the ionospheric quality factor of the third quantile is greater than the tropospheric quality factor of the fourth quantile, and the ionospheric quality factor of the third quantile is greater than a preset minimum active threshold The ionosphere is active.
  • the error module 901 may further include:
  • the fixed unit is used to solve the double-difference ambiguity of multiple baselines according to the observation data and location information of each base station in the base station network;
  • the error unit is used to calculate the ionospheric error value and the tropospheric error value of the multiple baselines according to the double-difference ambiguities of the multiple baselines.
  • the calculation module 903 may also include:
  • the residual unit is used to calculate the observation value residual of each baseline in the atmospheric error model according to the model parameters of the atmospheric error model, the position information of each baseline corresponding to the base station, and the ionospheric error value and tropospheric error value of each baseline;
  • the precision unit is used to calculate the precision factor matrix of the model parameters according to the observation residuals of each baseline;
  • the calculation unit is used to calculate the quality factor of each grid point position according to the precision factor matrix and the position information of multiple grid points in the base station network.
  • the network RTK anti-ionospheric interference positioning device provided in the embodiment of the present application can implement the various processes in the method embodiments shown in FIG. 1 to FIG. 7 , and will not be repeated here to avoid repetition.
  • the network RTK anti-ionospheric interference positioning system provided by an embodiment of the present application, the network RTK anti-ionospheric interference positioning system includes a server and a terminal, and the system includes:
  • the server According to the observation data and location information of each base station in the base station network, the server generates ionospheric errors and tropospheric errors of multiple baselines, and the baseline is formed by connecting two base stations;
  • the server performs modeling based on the ionospheric error and tropospheric error of multiple baselines and the location information of each base station to obtain an atmospheric error model;
  • the server calculates the difference correction number of multiple grid point positions in the base station network and the quality factor of multiple grid point positions according to the model parameters of the atmospheric error model;
  • the server determines the target grid point closest to the terminal's approximate position from among multiple grid point positions according to the approximate position information sent by the terminal;
  • the server broadcasts the differential correction number and quality factor of the target grid point to the terminal;
  • the terminal receives the differential correction number and quality factor broadcast by the server.
  • the differential correction number and quality factor are generated by the server based on the observation data and location information of each base station and the approximate location information uploaded by the terminal.
  • the quality factor is used to represent the atmosphere used to generate the differential correction number error model accuracy;
  • the terminal determines the RTK filtering mode according to the received quality factor, and the RTK filtering mode includes an ionosphere-free combined filtering mode or a non-combined filtering mode;
  • the terminal adopts the determined RTK filtering mode to filter and solve the observation data of the terminal and the difference correction number received by the terminal, and obtain the high-precision position information of the terminal.
  • the network RTK anti-ionospheric interference positioning system provided in the embodiment of the present application can implement each process in the method embodiments shown in FIG. 1 to FIG. 7 , and will not be repeated here to avoid repetition.
  • FIG. 10 shows a schematic diagram of the hardware structure of the network RTK anti-ionospheric interference positioning device provided by the embodiment of the present application.
  • the network RTK anti-ionospheric interference positioning device may include a processor 1001 and a memory 1002 storing computer program instructions.
  • processor 1001 may include a central processing unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.
  • CPU central processing unit
  • ASIC Application Specific Integrated Circuit
  • Memory 1002 may include mass storage for data or instructions.
  • the memory 1002 may include a hard disk drive (Hard Disk Drive, HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a Universal Serial Bus (Universal Serial Bus, USB) drive or two or more Combinations of multiple of the above.
  • Storage 1002 may include removable or non-removable (or fixed) media, where appropriate.
  • the memory 1002 may be internal or external to the network RTK anti-ionospheric jamming positioning device.
  • memory 1002 is a non-volatile solid-state memory.
  • Memory may include read only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices.
  • ROM read only memory
  • RAM random access memory
  • magnetic disk storage media devices e.g., magnetic disks
  • optical storage media devices e.g., magnetic disks
  • flash memory devices e.g., electrical, optical, or other physical/tangible memory storage devices.
  • the processor 1001 reads and executes the computer program instructions stored in the memory 1002 to implement any one of the network RTK anti-ionospheric interference positioning methods in the above embodiments.
  • the network RTK anti-ionospheric interference positioning device may further include a communication interface 1003 and a bus 1010 .
  • a processor 1001 a memory 1002 , and a communication interface 1003 are connected through a bus 1010 to complete mutual communication.
  • the communication interface 1003 is mainly used to realize the communication between various modules, devices, units and/or devices in the embodiments of the present application.
  • the bus 1010 includes hardware, software or both, and couples the components of the network RTK anti-ionospheric interference positioning device to each other.
  • the bus may include Accelerated Graphics Port (AGP) or other graphics bus, Enhanced Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), HyperTransport (HT) interconnect, Industry Standard Architecture (ISA) Bus, Infiniband Interconnect, Low Pin Count (LPC) Bus, Memory Bus, Micro Channel Architecture (MCA) Bus, Peripheral Component Interconnect (PCI) Bus, PCI-Express (PCI-X) Bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus or other suitable bus or a combination of two or more of these.
  • Bus 1010 may comprise one or more buses, where appropriate. Although the embodiments of this application describe and illustrate a particular bus, this application contemplates any suitable bus or interconnect.
  • the network RTK anti-ionospheric interference positioning device can be based on the above-mentioned embodiments, so as to realize the network RTK anti-ionospheric interference positioning method and device described in conjunction with FIGS. 1 to 9 .
  • the embodiments of the present application may provide a computer storage medium for implementation.
  • Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by a processor, any one of the network RTK anti-ionospheric interference positioning methods in the above embodiments is implemented.
  • the functional blocks shown in the above structural block diagrams may be implemented as hardware, software, firmware or a combination thereof.
  • it When implemented in hardware, it may be, for example, an electronic circuit, an application specific integrated circuit (ASIC), suitable firmware, a plug-in, a function card, or the like.
  • ASIC application specific integrated circuit
  • the elements of the present application are the programs or code segments employed to perform the required tasks.
  • Programs or code segments can be stored in machine-readable media, or transmitted over transmission media or communication links by data signals carried in carrier waves.
  • "Machine-readable medium" may include any medium that can store or transmit information.
  • machine-readable media examples include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, and the like.
  • Code segments may be downloaded via a computer network such as the Internet, an Intranet, or the like.
  • processors may be, but are not limited to, general purpose processors, special purpose processors, application specific processors, or field programmable logic circuits. It can also be understood that each block in the block diagrams and/or flowcharts and combinations of blocks in the block diagrams and/or flowcharts can also be realized by dedicated hardware for performing specified functions or actions, or can be implemented by dedicated hardware and Combination of computer instructions to achieve.

Abstract

一种网络RTK抗电离层干扰定位方法、装置、系统、设备及存储介质。方法包括：服务器根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，所述基线为两个所述基站相连形成；基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；根据所述大气误差模型的模型参数计算所述基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；向所述终端播发所述目标格网点的差分改正数和质量因子；终端接收服务器播发的差分改正数和质量因子，所述差分改正数和所述质量因子为服务器根据各个基站的观测数据和位置信息以及所述终端上传的概略位置信息生成；根据接收到的质量因子确定RTK滤波模式，所述RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；采用确定的所述RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到所述终端的高精度位置信息。装置包括接收模块，判定模块和定位模块；或者装置包括误差模块，建模模块，计算模块，匹配模块和播发模块。系统包括服务器和终端。设备包括处理器以及存储有计算机程序指令的存储器。计算机存储介质上存储有计算机程序指令。

Description

网络RTK抗电离层干扰定位方法、装置、系统、设备及存储介质
相关申请的交叉引用
本申请要求享有于2021年11月09日提交的名称为“网络RTK抗电离层干扰定位方法及相关设备”的中国专利申请202111322856.7的优先权，该申请的全部内容通过引用并入本文中。
技术领域
本申请属于卫星定位技术领域，尤其涉及一种网络RTK抗电离层干扰定位方法、装置、系统、设备及存储介质。
背景技术
目前，在网络RTK(Real-time kinematic，实时动态载波相位差分)定位技术中，服务器可以对电离层误差和对流层误差进行建模，并根据终端的概略位置向终端播发相应的差分改正数。终端可以通过差分改正数消除电离层误差和对流层误差的影响，实现高精度定位。
然而，在电离层活跃期，服务器在电离层误差建模时存在残余误差，从而导致终端在使用服务器所播发的差分改正数后，仍存在较大的电离层误差，使得终端无法固定整周模糊度或者整周模糊度固定错误，无法进行高精度定位。
发明内容
本申请实施例提供了一种网络RTK抗电离层干扰定位方法、装置、系统、设备及存储介质，能够解决网络RTK定位在电离层活跃期时无法实现高精度定位的技术问题。
第一方面，本申请实施例提供一种网络RTK抗电离层干扰定位方法，应用于终端，方法包括：
接收服务器播发的差分改正数和质量因子，差分改正数和质量因子为服务器根据各个基站的观测数据和位置信息以及终端上传的概略位置信息生成，质量因子用于表 征生成差分改正数所用的大气误差模型精度；
根据接收到的质量因子确定RTK滤波模式，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
采用确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到终端的高精度位置信息。
通过服务器播发表征大气误差模型精度的质量因子，能够使得终端根据该质量因子从无电离层组合滤波模式或非组合滤波模式中选择RTK滤波模式，在电离层活跃期时能够选择消除电离层误差的无电离层组合滤波模式进行滤波解算，以消除电离层误差的影响，实现电离层活跃期的高精度定位。
第二方面，本申请实施例提供一种网络RTK抗电离层干扰定位方法，应用于服务器，方法包括：
根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，基线为两个基站相连形成；
基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
根据大气误差模型的模型参数计算基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
向终端播发目标格网点的差分改正数和质量因子，以使终端根据目标格网点的质量因子确定RTK滤波模式，并根据RTK滤波模式采用差分改正数进行滤波解算以得到终端的高精度位置信息，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式。
服务器能够根据终端发送的概略位置向终端播发目标格网点的差分改正数和质量因子，以使终端根据质量因子确定RTK滤波模式后，根据差分改正数和终端的观测数据进行滤波解算，得到终端的高精度位置信息。
第三方面，本申请实施例提供一种网络RTK抗电离层干扰的定位装置，装置包括：
接收模块，用于接收服务器播发的差分改正数和质量因子，差分改正数和质量因子为服务器根据各个基站的观测数据和位置信息以及终端上传的概略位置信息生成， 质量因子用于表征生成差分改正数所用的大气误差模型精度；
判定模块，用于根据接收到的质量因子确定RTK滤波模式，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
定位模块，用于采用确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到终端的高精度位置信息；
或者，装置包括：
误差模块，用于根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，基线为两个基站相连形成；
建模模块，用于基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
计算模块，用于根据大气误差模型的模型参数计算基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
匹配模块，用于根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
播发模块，用于向终端播发目标格网点的差分改正数和质量因子，以使终端根据目标格网点的质量因子确定RTK滤波模式，并根据RTK滤波模式采用差分改正数进行滤波解算以得到终端的高精度位置信息，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式。
第四方面，本申请实施例提供了一种网络RTK抗电离层干扰定位系统，包括服务器和终端，系统包括：
服务器根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，基线为两个基站相连形成；
服务器基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
服务器根据大气误差模型的模型参数计算基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
服务器根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
服务器向终端播发目标格网点的差分改正数和质量因子；
终端接收服务器播发的差分改正数和质量因子，差分改正数和质量因子为服务器根据各个基站的观测数据和位置信息以及终端上传的概略位置信息生成，质量因子用于表征生成差分改正数所用的大气误差模型精度；
终端根据接收到的质量因子确定RTK滤波模式，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
终端采用确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到终端的高精度位置信息。
第五方面，本申请实施例提供了一种网络RTK抗电离层干扰定位设备，网络RTK抗电离层干扰定位设备包括：处理器以及存储有计算机程序指令的存储器；处理器执行计算机程序指令时实现如上的网络RTK抗电离层干扰定位方法。
第六方面，本申请实施例提供了一种计算机存储介质，计算机存储介质上存储有计算机程序指令，计算机程序指令被处理器执行时实现如上的网络RTK抗电离层干扰定位方法。
与相关技术相比，本申请实施例提供的网络RTK抗电离层干扰定位方法，在服务器对电离层误差和对流层误差进行建模时，生成表征大气误差模型精度的质量因子，并将质量因子与差分改正数一同播发给终端。终端可以根据该质量因子判断当前的差分改正数是否受到电离层活跃的影响，并根据判断结果从无电离层组合滤波模式或非组合滤波模式中选择合适的RTK滤波模式，对终端的观测数据和终端接收的差分改正数进行滤波解算，以在电离层活跃时消除电离层误差的影响，实现高精度定位。通过服务器所播发的质量因子，可以根据电离层的活跃状态进行滤波模式的切换，避免电离层活跃期时电离层误差的干扰，改善电离层活跃期的定位效果。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，显而易见地，下面所描述的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请一实施例提供的网络RTK抗电离层干扰定位方法的流程示意图；
图2是本申请另一实施例提供的网络RTK抗电离层干扰定位方法的流程示意图；
图3是本申请又一实施例提供的网络RTK抗电离层干扰定位方法的流程示意图；
图4是图2实施例中S210的细化步骤示意图；
图5是本申请一实施例提供的网络RTK抗电离层干扰定位方法的流程示意图；
图6是本申请另一实施例提供的网络RTK抗电离层干扰定位方法的流程示意图；
图7是本申请又一实施例提供的网络RTK抗电离层干扰定位方法的流程示意图；
图8是本申请一实施例提供的网络RTK抗电离层干扰定位装置的结构示意图；
图9是本申请另一实施例提供的网络RTK抗电离层干扰定位装置的结构示意图；
图10是本申请一实施例提供的网络RTK抗电离层干扰定位装置设备的硬件结构示意图。
具体实施方式
下面将详细描述本申请的各个方面的特征和示例性实施例，为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及具体实施例，对本申请进行进一步详细描述。应理解，此处所描述的具体实施例仅意在解释本申请，而不是限定本申请。对于本领域技术人员来说，本申请可以在不需要这些具体细节中的一些细节的情况下实施。下面对实施例的描述仅仅是为了通过示出本申请的示例来提供对本申请的更好的理解。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。下面将结合附图对实施例进行详细描述。
在现代GNSS(Global navigation satellite system，全球卫星导航系统)高精度实时定位中，网络RTK定位技术已经成为目前的主流应用。在网络RTK定位技术中，各 个基站可以分别获取电离层和对流层的大气延迟信息，并计算生成该基站所对应的电离层误差和对流层误差。根据终端所发送的概略位置，能够根据各个基站所组成的基站网络进行大气误差模型的建模，并根据建立的大气误差模型计算得到概略位置的差分改正数后发送至终端，以使终端对观测数据和差分改正数进行滤波解算，得到终端的高精度位置信息。
然而，在电离层活跃期，对电离层的误差进行建模时，存在较大的观测值误差。当终端接收到差分改正数后，由于仍存在较大的电离层误差，使得终端无法固定整周模糊度或者错误固定整周模糊度，从而导致无法得到高精度的定位结果。
本申请实施例提供了一种网络RTK抗电离层干扰定位方法、装置、系统、设备及存储介质。下面首先对本申请实施例所提供的网络RTK抗电离层干扰定位方法进行介绍。
图1示出了本申请一个实施例提供的网络RTK抗电离层干扰定位方法的流程示意图。网络RTK抗电离层干扰定位方法应用于终端，方法包括：
S110，接收服务器播发的差分改正数和质量因子，差分改正数和质量因子为服务器根据各个基站的观测数据和位置信息以及终端上传的概略位置信息生成，质量因子用于表征生成差分改正数所用的大气误差模型精度；
S120，根据接收到的质量因子确定RTK滤波模式，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
S130，采用确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到终端的高精度位置信息。
服务器可以和各个基站以及终端进行数据通信，以实现数据传输。其中，基站的观测数据可以包括观测到的载波、伪距观测值等，基站的位置信息可以包括基站坐标、天线信息编码等。终端的观测数据可以包括与基站相同历元观测到的载波、伪距观测值等。可以理解的是，基站所获取到的数据还可以包括星历数据，终端所获取到的数据同样可以包括星历数据。
在本实施例中，各个基站能够将其观测数据和位置信息发送至服务器，终端则可以将其概略位置信息发送至服务器。服务器根据基站观测数据和位置信息以及终端上传的概略位置信息，能够生成该终端对应的差分改正数和质量因子，终端在接收到差分改正数和质量因子后，能够根据质量因子选择相应的RTK滤波模式，从而在电离层 活跃时选择能够有效消除电离层残余误差的RTK滤波模式，还能够在确定的RTK滤波模式下，根据差分改正数与自身的观测数据进行滤波解算，以固定整周模糊度，并得到终端的高精度位置信息。通过服务器播发表征大气误差模型精度的质量因子，能够使得终端根据该质量因子从无电离层组合滤波模式或非组合滤波模式中选择RTK滤波模式，在电离层活跃期时能够选择消除电离层误差的无电离层组合滤波模式进行滤波解算，以消除电离层误差的影响，实现电离层活跃期的高精度定位。
在S110中，各个基站可以上传观测到的观测数据和位置信息，终端可以上传其概略位置信息。服务器在接收到各个基站的观测数据和位置信息以及终端的概略位置信息后，可以生成差分改正数和质量因子，并向终端播发差分改正数和质量因子。
在S120中，终端在接收到差分改正数和质量因子后，可以根据接收到的质量因子确定进行滤波解算的RTK滤波模式。RTK滤波模式可以为无电离层组合滤波模式或非组合滤波模式。其中，若RTK滤波模式采用无电离层组合滤波模式，能够在电离层的残余误差较大时消除电离层误差的影响，实现电离层活跃期的终端高精度定位；若RTK滤波模式采用非组合滤波模式，则能够在电离层不活跃时实现终端的高精度定位。
作为一个可选实施例，请参照图2，为了在电离层活跃时消除电离层误差的影响，上述S120，可以包括：
S210，根据接收到的质量因子判断当前历元的电离层是否活跃；
S220，在当前历元的电离层活跃时，获取第一时间段内电离层活跃的历元数量；
S230，在电离层活跃的历元数量达到预设第一历元阈值时，将RTK滤波模式确定为无电离层组合滤波模式。
在本实施例中，终端可以根据接收到的质量因子来判断当前历元的电离层是否活跃，若确定当前历元的电离层活跃，则获取第一时间段内电离层活跃的历元数量，并在达到预设值时确定采用的RTK滤波模式为无电离层组合模式，从而根据无电离层组合模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，以消除电离层活跃时电离层误差的影响，从而得到终端的高精度位置信息。
在S210中，终端可以在接收到质量因子后，根据预设的判断规则对质量因子进行判断，以确定当前历元的电离层是否活跃。在满足预设的判断规则时，即确定当前历元的电离层活跃。
在S220中，在终端确定当前历元的电离层活跃时，可以对当前历元为止的第一时 间段内，电离层活跃的历元数量进行计数，以获取第一时间段内电离层活跃的历元数量。预设的判断规则可以是第一时间段内电离层活跃的历元数量是否达到预设第一历元阈值。
例如，在终端确定当前历元电离层活跃时，可以将当前历元对应的电离层活跃值设置为“活跃”或者“1”，并存储在数据库中。同样地，在终端确定当前历元电离层为不活跃时，可以将当前历元对应的电离层活跃值设置为“不活跃”或者“0”，并存储在数据库中。在终端确定当前历元电离层活跃时，还可以从数据库中获取过去第一时间段内电离层活跃值为“活跃”或者“1”的数量，从而确定第一时间段内电离层活跃的历元数量。
在S230中，终端在获取第一时间段内电离层活跃的历元数量后，可以将电离层活跃的历元数量与预设第一历元阈值进行比较，若电离层活跃的历元数量达到预设第一历元阈值时，则终端可以将采用的RTK滤波模式确定为无电离层组合滤波模式。
无电离层组合滤波模式中，终端可以根据自身的观测数据以及无电离层组合公式计算得到无电离层组合观测值。无电离层组合公式如下：
Figure PCTCN2022116380-appb-000001
Figure PCTCN2022116380-appb-000002
其中，P 1,P 2分别为第一频、第二频的伪距观测值(单位：m)，φ 1,φ 2分别为第一频、第二频的载波观测值(单位：周)，P IF,φ IF分别为伪距和载波的无电离层组合观测值。通过获取无电离层组合观测值，并用无电离层组合观测值代替伪距观测值和载波观测值进行滤波解算，能够在电离层活跃时消除电离层的残余误差，得到高精度的终端位置信息。
可以理解的是，在上述实施例中，预设的判断规则还可以是判断第一时间段内电离层连续活跃的历元数量是否达到预设第一历元阈值。在该判断规则中，每当终端确定当前历元的电离层活跃时，可以从当前历元开始，获取数量为预设第一历元阈值的历史历元电离层活跃值。例如，在预设第一历元阈值为10时，可以从当前历元开始往前，获取连续10个历元的电离层活跃值，若该10个历元的电离层活跃值均为“活跃”或者“1”，则终端可以将RTK滤波模式确定为无电离层组合滤波模式。若存在至少一个历元的电离层活跃值为“不活跃”或者“0”，则不对RTK滤波模式进行调整。
作为一个可选实施例，请参照图3，为了在电离层不活跃时实现高精度定位，上述 S230之后，可以包括：
S310，在当前历元的电离层不活跃时，获取第二时间段内电离层不活跃的历元数量；
S320，在电离层不活跃的历元数量达到预设第二历元阈值时，RTK滤波模式切换为非组合滤波模式。
在本实施例中，终端在确定当前历元的电离层不活跃时，获取第二时间段内电离层不活跃的历元数量，并在第二时间段内电离层不活跃的历元数量达到相应的预设值时确定采用的RTK滤波模式为非组合滤波模式。终端通过非组合滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，能够消除各种误差对整周模糊度的影响，从而快速固定整周模糊度，计算出终端的高精度位置信息。
在S310中，终端确定当前历元的电离层不活跃时，可以对当前历元为止的第二时间段内，电离层活跃的历元数量进行计数，以获取第二时间段内电离层不活跃的历元数量。例如，在终端确定当前历元电离层不活跃时，可以将当前历元对应的电离层活跃值设置为“不活跃”或者“0”，并存储在数据库中。在终端确定当前历元电离层不活跃时，还可以从数据库中获取过去第二时间段内电离层活跃值为“不活跃”或者“0”的数量，从而确定第二时间段内电离层活跃的历元数量。
在S320中，终端在获取第二时间段内电离层不活跃的历元数量后，可以将电离层不活跃的历元数量与预设第二历元阈值进行比较，若电离层不活跃的历元数量达到预设第二历元阈值时，则终端可以将采用的RTK滤波模式确定为非组合滤波模式。
同样地，上述预设的判断规则还可以是电离层连续不活跃的历元数量是否达到预设第二历元阈值。即，在终端确定当前历元的电离层不活跃时，可以获取当前历元之前的连续多个历元的电离层活跃值，若存在预设第二历元阈值个连续的历元，其电离层活跃值为“不活跃”或者“0”，则终端可以将RTK滤波模式切换为非组合滤波模式。若在连续多个历元的电离层活跃值中，存在至少一个电离层活跃值为“活跃”或者“1”，则不对RTK滤波模式进行调整。
作为一个可选实施例，请参照图4，为了在根据质量因子判断电离层是否活跃时消除公共误差的影响，质量因子可以包括对应多个卫星的电离层质量因子和对应多个卫星的对流层质量因子，上述S210，可以包括：
S410，将接收到的多个卫星的电离层质量因子和多个卫星的对流层质量因子分别 进行从小到大排序；
S420，判断第一分位的电离层质量因子是否大于第二分位的对流层质量因子，以及第一分位的电离层质量因子是否大于预设最小活跃阈值，其中第一分位小于或等于第二分位。
S210之后，还包括：
S430，在第一分位的电离层质量因子大于第二分位的对流层质量因子，且第一分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
作为另一个可选实施例，上述S210，可以包括：
S440，将接收到的多个卫星的电离层质量因子和多个卫星的对流层质量因子分别进行从大到小排序；
S450，判断第三分位的电离层质量因子是否大于第四分位的对流层质量因子，以及第三分位的电离层质量因子是否大于预设最小活跃阈值，其中第三分位大于或等于第四分位。
S210之后，还包括：
S460，在第三分位的电离层质量因子大于第四分位的对流层质量因子，且第三分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
在本实施例中，终端所接收到的质量因子，包括多个卫星的电离层质量因子和多个卫星的对流层质量因子。终端在接收到多个卫星的电离层质量因子和多个卫星的对流层质量因子后，可以将电离层质量因子进行排序，将对流层质量因子也进行排序。在排序后可以获取特定分位的电离层质量因子以及特定分位的对流层质量因子，并根据获取到的电离层质量因子、对流层质量因子以及预设最小活跃阈值的大小来确定当前历元的电离层是否活跃。在计算质量因子时，还会存在其他影响因素，导致得到的质量因子存在一定误差。通过将电离层质量因子与对流层质量因子进行对比，能够排除基站观测、基站网络拓扑结构等其他因素造成的公共误差的影响，从而准确地判断当前电离层的活跃状态。
在S410中，终端可以将接收到的多个卫星的电离层质量因子按照从小到大进行排序，并将接收到的多个卫星的对流层质量因子按照从小到大进行排序。
在S420中，终端在排序后的电离层质量因子中，可以确定第一分位的电离层质量因子；在排序后的对流层质量因子中，则可以确定第二分位的对流层质量因子。其中 第一分位的分位值可以为小于或等于第二分位的分位值。例如，第一分位可以为75％，第二分位可以为90％。其中，第一分位为75％的电离层质量因子σ I,75，是指由小到大的排序中，小于该电离层质量因子的电离层质量因子数量占总数量的75％。同样地，第二分位为90％的对流层质量因子σ T,90，是指由小到大的排序中，小于该对流层质量因子的对流层质量因子数量占总数量的90％。
在获取到第一分位的电离层质量因子和第二分位的对流层质量因子后，终端可以对第一分位的电离层质量因子和第二分位的对流层质量因子进行比较，判断第一分位的电离层质量因子是否大于第二分位的对流层质量因子。终端还可以对第一分位的电离层质量因子是否大于预设最小活跃阈值进行判断。
在S430中，终端可以在第一分位的电离层质量因子大于第二分位的对流层质量因子，并且第一分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
例如，在获取到第一分位为75％的电离层质量因子σ I,75以及第二分位为90％的对流层质量因子σ T,90后，可以确定预先设置的最小活跃阈值I low，并判断是否σ I,75>σ T,90且σ I,75>I low。在σ I,75>σ T,90且σ I,75>I low时，可以确定当前历元的电离层活跃，否则可以确定当前历元的电离层平静或不活跃。
可以理解的是，影响质量因子的因素不仅仅是电离层建模误差或者对流层建模误差，还包括基站网络的几何拓扑结构以及基站的观测噪声。若仅仅只是将电离层质量因子与预设的最小活跃阈值进行大小比较，难以判断此时电离层是否为活跃状态。因此，还可以将电离层质量因子与对流层质量因子进行对比，以排除基站观测、基站网络拓扑结构等其他因素造成的公共误差的影响。
在S440中，终端可以将接收到的多个卫星的电离层质量因子按照从大到小进行排序，并将接收到的多个卫星的对流层质量因子按照从大到小进行排序。
在S450中，终端在排序后的电离层质量因子中，可以确定第三分位的电离层质量因子；在排序后的对流层质量因子中，则可以确定第四分位的对流层质量因子。其中第三分位的分位值大于或等于第四分位的分位值。
在S460中，终端可以在第三分位的电离层质量因子大于第四分位的对流层质量因子，并且第三分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
在S130中，终端可以根据确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，以得到终端的高精度位置信息。例如，终端根据接收到的质量因子，可以在确定电离层为活跃期时，确定RTK滤波模式为无电离层组合滤波模式；在确定电离层不为活跃期时，确定RTK滤波模式为非组合滤波模式。
在电离层不为活跃期时，终端能够通过非组合滤波模式对差分改正数和终端的观测数据进行滤波解算，从而在在电离层不活跃时期得到终端的高精度位置信息。
在电离层为活跃期时，终端能够通过无电离层组合滤波模式，根据两个频率的载波观测值和伪距观测值计算出无电离层组合观测值，从而使得终端在滤波解算时能够消除电离层误差的影响，在电离层活跃期也能够根据差分改正数和终端的观测数据得到终端的高精度位置信息。
图5示出了本申请另一个实施例提供的网络RTK抗电离层干扰定位方法的流程示意图。网络RTK抗电离层干扰定位方法应用于服务器，网络RTK抗电离层干扰定位方法包括：
S510，根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，基线为两个基站相连形成；
S520，基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
S530，根据大气误差模型的模型参数计算基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
S540，根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
S550，向终端播发目标格网点的差分改正数和质量因子，以使终端根据目标格网点的质量因子确定RTK滤波模式，并根据RTK滤波模式采用差分改正数进行滤波解算以得到终端的高精度位置信息，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式。
在本实施例中，服务器能够根据基站网络中各个基站发送的数据生成多条基线的电离层误差和对流层误差，并根据基线的误差进行建模，得到大气误差模型。通过大气误差模型可以计算出基站网络覆盖的区域内各个格网点位置的差分改正数和质量因子。在接收到终端发送的概略位置后，可以根据概略位置从多个格网点中确定距离最 近的格网点，并将该格网点对应的差分改正数和质量因子播发至终端，以使终端根据质量因子确定RTK滤波模式后，根据差分改正数和终端的观测数据进行滤波解算，得到终端的高精度位置信息。
在S510中，服务器可以接收基站网络中各个基站分别发送的观测数据和位置信息。在基站网络的各个基站中，将任意两个基站相连即可形成一条基线，根据该两个基站的观测数据和位置信息即可生成该条基线的电离层误差和对流层误差。在将各个基站进行两两相连后，即可生成基站网络中多条基线分别对应的电离层误差和对流层误差。
作为一个可选实施例，请参照图6，为了生成基线的电离层误差和对流层误差，上述S510，可以包括：
S610，根据基站网络中各个基站的观测数据和位置信息，解算多条基线的双差模糊度；
S620，根据多条基线的双差模糊度计算多条基线的电离层误差值和对流层误差值。
在本实施例中，服务器可以获取基站网络中各个基站的观测数据和位置信息。在选择两个基站相连形成一条基线时，根据这两个基站的观测数据和位置信息即可计算得到该条基线的双差模糊度。在将基线的双差模糊度进行固定后，可以反算出该基线的电离层误差值和对流层误差值。通过对每条基线依次进行反算，即可得到多条基线的电离层误差值和对流层误差值。可以理解的是，基线的电离层误差值和对流层误差值即为基线对应的差分改正数。
在S610中，通过多个基站两两相连，即可形成多条基线，多条基线以及基站可以构成网形，从而形成基站网络。根据各个基站的观测数据和位置信息，即可解算出对应的基线的双差模糊度。
在S620中，根据基线固定的双差模糊度，可以通过相应的公式计算得到基线的电离层误差值和对流层误差值。反算公式如下：
Figure PCTCN2022116380-appb-000003
Figure PCTCN2022116380-appb-000004
其中，
Figure PCTCN2022116380-appb-000005
为电离层误差值，
Figure PCTCN2022116380-appb-000006
为对流层误差值。f 1和f 2分别为基站观测信号的第一和第二频率(单位：MHz)，
Figure PCTCN2022116380-appb-000007
和
Figure PCTCN2022116380-appb-000008
分别为第一频率和第二频率恢复了模糊度的载波观测值(单位：m)，
Figure PCTCN2022116380-appb-000009
为双差真空几何距离值(单位：m)，
Figure PCTCN2022116380-appb-000010
可以根据卫星坐标和基站精确坐标计算得到。
在S520中，服务器在分别计算得到多条基线的电离层误差和对流层误差后，可以根据多条基线的电离层误差和对流层误差以及各个基站的位置信息，对该基站网络所覆盖的区域进行大气误差模型的建模，并解出大气误差模型的模型参数。在建立大气误差模型后，对于该区域内的特定位置，可以根据特定位置的坐标以及大气误差模型的模型参数计算得出该特定位置的电离层误差和对流层误差。
例如，大气误差模型的建模方程可以为：
L＝AX；
其中，L为大气误差模型的观测值，对于电离层误差和对流层误差，可以分别进行建模。即，电离层误差的观测值为
Figure PCTCN2022116380-appb-000011
对流层误差的观测值为
Figure PCTCN2022116380-appb-000012
m为用于建立大气误差模型的基线数量。A为与基线的坐标位置相关的系数矩阵，X为待求解的模型参数。
在确定系数矩阵A以及观测值L后，可以对上述建模方程进行求解，以确定大气误差模型的模型参数。例如，可以采用最小二乘法对上述建模方程进行求解，得到大气误差模型的模型参数为：
Figure PCTCN2022116380-appb-000013
在S530中，终端可以根据基站网络的范围确定范围内的多个格网点位置，并根据上述大气误差模型的模型参数以及每个格网点的位置坐标确定每个格网点位置对应的差分改正数和质量因子。其中，格网点位置的差分改正数即该格网点位置的电离层误差和对流层误差，质量因子为该格网点位置下各个卫星的电离层建模误差质量因子和各个卫星的对流层建模误差质量因子。
在根据上述建模方程得到大气误差模型的模型参数后，若想要对某个特定位置的电离层误差和对流层误差进行计算，可以通过差分改正数计算公式得到，差分改正数计算公式如下：
Figure PCTCN2022116380-appb-000014
其中，B correction为格网点位置的坐标对应的系数矩阵，L correction则为解算后得到的格网点位置的电离层误差值或对流层误差值。
可以理解的是，在基站网络的范围内，可以通过内插值算法生成多个格网点位置，并通过上述差分改正数计算公式计算每个格网点位置对应的电离层误差值或对流层误差值，即计算得到每个格网点位置对应的差分改正数。内插值算法可以是反距离加权 法、线性内插法、最小二乘配置法等。在计算出各个格网点位置的差分改正数后，若服务器接收到终端发送的概略位置，即可确定与概略位置最接近的格网点位置，并向终端播发该最接近的格网点位置的差分改正数和质量因子。
作为一个可选实施例，请参照图7，为了生成格网点位置的质量因子，上述S530，可以包括：
S710，根据大气误差模型的模型参数、各条基线对应基站的位置信息以及各条基线的电离层误差值和对流层误差值计算得到大气误差模型中各条基线的观测值残差；
S720，根据各条基线的观测值残差计算模型参数的精度因子矩阵；
S730，根据精度因子矩阵和基站网络中多个格网点的位置信息，分别计算得到每个格网点位置的质量因子。
在本实施例中，在确定基站网络范围内的各个格网点位置，并计算得到每个格网点位置分别对应的电离层误差和对流层误差，即每个格网点位置分别对应的差分改正数后，还可以计算得到每个格网点位置下，各个卫星的电离层建模误差质量因子和各个卫星的对流层建模误差质量因子。
在S710中，服务器在解算出大气误差模型的模型参数后，还可以将各个基线的坐标位置代入模型参数中，得到大气误差模型下基线位置对应的电离层误差值和对流层误差值。服务器根据大气误差模型下基线的电离层误差值和对流层误差值以及上述根据基线的双差模糊度反算得到的电离层误差值和对流层误差值，即可确定在大气误差模型下，实际的误差值与模型计算得到的误差值之间的观测值残差。观测值残差的计算公式如下：
Figure PCTCN2022116380-appb-000015
上述公式中，A为与基线的坐标位置相关的系数矩阵，L为该基线根据双差模糊度反算得到的电离层误差值或者对流层误差值，V为大气误差模型的观测值残差。
在S720中，根据上述各条基线的观测值残差，可以计算得到相应的单位权标准差，单位权标准差的计算公式为：
Figure PCTCN2022116380-appb-000016
其中，σ 0为单位权标准差，n为基线个数，k为大气误差模型中建模参数的个数。
在计算得到单位权标准差后，可以根据单位权标准差计算大气误差模型建模参数的精度因子矩阵。精度因子矩阵的计算公式如下：
Figure PCTCN2022116380-appb-000017
在S730中，在计算得到精度因子矩阵后，服务器可以根据基站网络中格网点的位置信息，计算得到该格网点位置的质量因子。对每个格网点的位置信息进行计算后即可得到每个格网点位置的质量因子。计算公式如下：
Figure PCTCN2022116380-appb-000018
其中，B correction为格网点位置位置的坐标对应的系数矩阵，D为上述精度因子矩阵。
可以理解的是，每个格网点位置的质量因子可以包括电离层建模误差质量因子和对流层建模误差质量因子。在计算大气误差模型的观测值残差时，若输入的观测值为各条基线的电离层误差值，则最终计算得到的质量因子为各个卫星的电离层建模误差质量因子。同样地，若输入的观测值为各条基线的对流层误差值，则最终计算得到的质量因子为各个卫星的对流层建模误差质量因子。
在S540中，服务器在确定基站网络中每个格网点位置的差分改正数和质量因子后，可以根据终端发送的概略位置信息确定终端对应的概略位置，并从多个格网点位置中确定与终端的概略位置最接近的格网点，作为目标格网点。
在S550中，服务器在根据终端的概略位置确定目标格网点后，可以获取目标格网点的差分改正数和质量因子，并播发给终端。终端在结合搜到目标格网点的差分改正数和质量因子后，可以根据质量因子确定RTK滤波模式，并根据确定的RTK滤波模式采用差分改正数以及终端的观测数据进行滤波解算，从而得到终端的高精度位置信息。
基于上述实施例提供的网络RTK抗电离层干扰定位方法，相应地，本申请还提供了网络RTK抗电离层干扰定位装置的具体实现方式。请参见以下实施例。
首先参见图8，本申请实施例提供的网络RTK抗电离层干扰定位装置800包括以下模块：
接收模块801，用于接收服务器播发的差分改正数和质量因子，差分改正数和质量因子为服务器根据各个基站的观测数据和位置信息以及终端上传的概略位置信息生成，质量因子用于表征生成差分改正数所用的大气误差模型精度；
判定模块802，用于根据接收到的质量因子确定RTK滤波模式，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
定位模块803，用于采用确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到终端的高精度位置信息。
或者，请参见图9，装置包括：
误差模块901，用于根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，基线为两个基站相连形成；
建模模块902，用于基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
计算模块903，用于根据大气误差模型的模型参数计算基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
匹配模块904，用于根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
播发模块905，用于向终端播发目标格网点的差分改正数和质量因子，以使终端根据目标格网点的质量因子确定RTK滤波模式，并根据RTK滤波模式采用差分改正数进行滤波解算以得到终端的高精度位置信息，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式。
在本实施例中，各个基站能够将其观测数据和位置信息发送至服务器，终端则可以将其概略位置信息发送至服务器。服务器根据基站观测数据和位置信息以及终端上传的概略位置信息，能够生成该终端对应的差分改正数和质量因子，终端在接收到差分改正数和质量因子后，能够根据质量因子选择相应的RTK滤波模式，从而在电离层活跃时选择能够有效消除电离层残余误差的RTK滤波模式，还能够在确定的RTK滤波模式下，根据差分改正数与自身的观测数据进行滤波解算，以固定整周模糊度，并得到终端的高精度位置信息。通过服务器播发表征大气误差模型精度的质量因子，能够使得终端根据该质量因子从无电离层组合滤波模式或非组合滤波模式中选择RTK滤波模式，在电离层活跃期时能够选择消除电离层误差的无电离层组合滤波模式进行滤波解算，以消除电离层误差的影响，实现电离层活跃期的高精度定位。
作为本申请的一种实现方式，为了在电离层活跃时消除电离层误差的影响，上述判定模块802还可以包括：
判定单元，用于根据接收到的质量因子判断当前历元的电离层是否活跃；
第一获取单元，用于在当前历元的电离层活跃时，获取第一时间段内电离层活跃 的历元数量；
第一确定单元，用于在电离层活跃的历元数量达到预设第一历元阈值时，将RTK滤波模式确定为无电离层组合滤波模式。
作为本申请的一种实现方式，为了在电离层不活跃时实现高精度定位，上述判定模块802还可以包括：
第二获取单元，用于在当前历元的电离层不活跃时，获取第二时间段内电离层不活跃的历元数量；
第二确定单元，用于在电离层不活跃的历元数量达到预设第二历元阈值时，RTK滤波模式切换为非组合滤波模式。
作为本申请的一种实现方式，为了根据质量因子判断电离层是否活跃，质量因子包括对应多个卫星的电离层质量因子和对应多个卫星的对流层质量因子，上述判定单元还可以包括：
第一排序子单元，用于将接收到的多个卫星的电离层质量因子和多个卫星的对流层质量因子分别进行从小到大排序；
第一比较子单元，用于判断第一分位的电离层质量因子是否大于第二分位的对流层质量因子，以及第一分位的电离层质量因子是否大于预设最小活跃阈值，其中第一分位小于或等于第二分位。
判定模块802还包括：
第一活跃子单元，用于在第一分位的电离层质量因子大于第二分位的对流层质量因子，且第一分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
或者，上述判定单元还可以包括：
第二排序子单元，用于将接收到的多个卫星的电离层质量因子和多个卫星的对流层质量因子分别进行从大到小排序；
第二排序子单元，用于判断第三分位的电离层质量因子是否大于第四分位的对流层质量因子，以及第三分位的电离层质量因子是否大于预设最小活跃阈值，其中第三分位大于或等于第四分位。
判定模块802还包括：
第二排序子单元，用于在第三分位的电离层质量因子大于第四分位的对流层质量 因子，且第三分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
作为本申请的一种实现方式，为了生成基线的电离层误差和对流层误差，上述误差模块901还可以包括：
固定单元，用于根据基站网络中各个基站的观测数据和位置信息，解算多条基线的双差模糊度；
误差单元，用于根据多条基线的双差模糊度计算多条基线的电离层误差值和对流层误差值。
作为本申请的一种实现方式，为了生成格网点位置的质量因子，上述计算模块903还可以包括：
残差单元，用于根据大气误差模型的模型参数、各条基线对应基站的位置信息以及各条基线的电离层误差值和对流层误差值计算得到大气误差模型中各条基线的观测值残差；
精度单元，用于根据各条基线的观测值残差计算模型参数的精度因子矩阵；
计算单元，用于根据精度因子矩阵和基站网络中多个格网点的位置信息，分别计算得到每个格网点位置的质量因子。
本申请实施例提供的网络RTK抗电离层干扰的定位装置能够实现图1至图7的方法实施例中的各个过程，为避免重复，这里不再赘述。
本申请一个实施例提供的网络RTK抗电离层干扰定位系统，网络RTK抗电离层干扰定位系统包括服务器和终端，系统包括：
服务器根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，基线为两个基站相连形成；
服务器基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
服务器根据大气误差模型的模型参数计算基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
服务器根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
服务器向终端播发目标格网点的差分改正数和质量因子；
终端接收服务器播发的差分改正数和质量因子，差分改正数和质量因子为服务器根据各个基站的观测数据和位置信息以及终端上传的概略位置信息生成，质量因子用于表征生成差分改正数所用的大气误差模型精度；
终端根据接收到的质量因子确定RTK滤波模式，RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
终端采用确定的RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到终端的高精度位置信息。
本申请实施例提供的网络RTK抗电离层干扰的定位系统能够实现图1至图7的方法实施例中的各个过程，为避免重复，这里不再赘述。
图10示出了本申请实施例提供的网络RTK抗电离层干扰定位设备的硬件结构示意图。
在网络RTK抗电离层干扰定位设备可以包括处理器1001以及存储有计算机程序指令的存储器1002。
具体地，上述处理器1001可以包括中央处理器(CPU)，或者特定集成电路(Application Specific Integrated Circuit，ASIC)，或者可以被配置成实施本申请实施例的一个或多个集成电路。
存储器1002可以包括用于数据或指令的大容量存储器。举例来说而非限制，存储器1002可包括硬盘驱动器(Hard Disk Drive，HDD)、软盘驱动器、闪存、光盘、磁光盘、磁带或通用串行总线(Universal Serial Bus，USB)驱动器或者两个或更多个以上这些的组合。在合适的情况下，存储器1002可包括可移除或不可移除(或固定)的介质。在合适的情况下，存储器1002可在网络RTK抗电离层干扰定位设备的内部或外部。在特定实施例中，存储器1002是非易失性固态存储器。
存储器可包括只读存储器(ROM)，随机存取存储器(RAM)，磁盘存储介质设备，光存储介质设备，闪存设备，电气、光学或其他物理/有形的存储器存储设备。因此，通常，存储器包括一个或多个编码有包括计算机可执行指令的软件的有形(非暂态)可读存储介质(例如，存储器设备)，并且当该软件被执行(例如，由一个或多个处理器)时，其可操作来执行参考根据本申请的一方面的方法所描述的操作。
处理器1001通过读取并执行存储器1002中存储的计算机程序指令，以实现上述实施例中的任意一种网络RTK抗电离层干扰定位方法。
在一个示例中，网络RTK抗电离层干扰定位设备还可包括通信接口1003和总线1010。其中，如图10所示，处理器1001、存储器1002、通信接口1003通过总线1010连接并完成相互间的通信。
通信接口1003，主要用于实现本申请实施例中各模块、装置、单元和/或设备之间的通信。
总线1010包括硬件、软件或两者，将网络RTK抗电离层干扰定位设备的部件彼此耦接在一起。举例来说而非限制，总线可包括加速图形端口(AGP)或其他图形总线、增强工业标准架构(EISA)总线、前端总线(FSB)、超传输(HT)互连、工业标准架构(ISA)总线、无限带宽互连、低引脚数(LPC)总线、存储器总线、微信道架构(MCA)总线、外围组件互连(PCI)总线、PCI-Express(PCI-X)总线、串行高级技术附件(SATA)总线、视频电子标准协会局部(VLB)总线或其他合适的总线或者两个或更多个以上这些的组合。在合适的情况下，总线1010可包括一个或多个总线。尽管本申请实施例描述和示出了特定的总线，但本申请考虑任何合适的总线或互连。
该网络RTK抗电离层干扰定位设备可以基于上述实施例，从而实现结合图1至图9描述的网络RTK抗电离层干扰定位方法和装置。
另外，结合上述实施例中的网络RTK抗电离层干扰定位方法，本申请实施例可提供一种计算机存储介质来实现。该计算机存储介质上存储有计算机程序指令；该计算机程序指令被处理器执行时实现上述实施例中的任意一种网络RTK抗电离层干扰定位方法。
需要明确的是，本申请并不局限于上文所描述并在图中示出的特定配置和处理。为了简明起见，这里省略了对已知方法的详细描述。在上述实施例中，描述和示出了若干具体的步骤作为示例。但是，本申请的方法过程并不限于所描述和示出的具体步骤，本领域的技术人员可以在领会本申请的精神后，作出各种改变、修改和添加，或者改变步骤之间的顺序。
以上的结构框图中所示的功能块可以实现为硬件、软件、固件或者它们的组合。当以硬件方式实现时，其可以例如是电子电路、专用集成电路(ASIC)、适当的固件、插件、功能卡等等。当以软件方式实现时，本申请的元素是被用于执行所需任务的程序或者代码段。程序或者代码段可以存储在机器可读介质中，或者通过载波中携带的数据信号在传输介质或者通信链路上传送。“机器可读介质”可以包括能够存储或传 输信息的任何介质。机器可读介质的例子包括电子电路、半导体存储器设备、ROM、闪存、可擦除ROM(EROM)、软盘、CD-ROM、光盘、硬盘、光纤介质、射频(RF)链路，等等。代码段可以经由诸如因特网、内联网等的计算机网络被下载。
还需要说明的是，本申请中提及的示例性实施例，基于一系列的步骤或者装置描述一些方法或系统。但是，本申请不局限于上述步骤的顺序，也就是说，可以按照实施例中提及的顺序执行步骤，也可以不同于实施例中的顺序，或者若干步骤同时执行。
上面参考根据本申请的实施例的方法、装置和计算机程序产品的流程图和/或框图描述了本申请的各方面。应当理解，流程图和/或框图中的每个方框以及流程图和/或框图中各方框的组合可以由计算机程序指令实现。这些计算机程序指令可被提供给通用计算机、专用计算机、或其它可编程数据处理装置的处理器，以产生一种机器，使得经由计算机或其它可编程数据处理装置的处理器执行的这些指令使能对流程图和/或框图的一个或多个方框中指定的功能/动作的实现。这种处理器可以是但不限于是通用处理器、专用处理器、特殊应用处理器或者现场可编程逻辑电路。还可理解，框图和/或流程图中的每个方框以及框图和/或流程图中的方框的组合，也可以由执行指定的功能或动作的专用硬件来实现，或可由专用硬件和计算机指令的组合来实现。
以上，仅为本申请的具体实施方式，所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的系统、模块和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。应理解，本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。

Claims (11)

  1. 一种网络RTK抗电离层干扰定位方法，应用于终端，所述方法包括：
    接收服务器播发的差分改正数和质量因子，所述差分改正数和所述质量因子为服务器根据各个基站的观测数据和位置信息以及所述终端上传的概略位置信息生成，所述质量因子用于表征生成所述差分改正数所用的大气误差模型精度；
    根据接收到的质量因子确定RTK滤波模式，所述RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
    采用确定的所述RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到所述终端的高精度位置信息。
  2. 根据权利要求1所述的网络RTK抗电离层干扰定位方法，其中，所述根据接收到的质量因子确定RTK滤波模式，包括：
    根据接收到的质量因子判断当前历元的电离层是否活跃；
    在当前历元的电离层活跃时，获取第一时间段内电离层活跃的历元数量；
    在电离层活跃的历元数量达到预设第一历元阈值时，将所述RTK滤波模式确定为无电离层组合滤波模式。
  3. 根据权利要求2所述的网络RTK抗电离层干扰定位方法，其中，所述将所述RTK滤波模式确定为无电离层组合滤波模式之后，还包括：
    在当前历元的电离层不活跃时，获取第二时间段内电离层不活跃的历元数量；
    在电离层不活跃的历元数量达到预设第二历元阈值时，所述RTK滤波模式切换为非组合滤波模式。
  4. 根据权利要求2所述的网络RTK抗电离层干扰定位方法，其中，所述质量因子包括对应多个卫星的电离层质量因子和对应多个卫星的对流层质量因子；所述根据接收到的质量因子判断当前历元的电离层是否活跃，包括：
    将接收到的多个卫星的电离层质量因子和多个卫星的对流层质量因子分别进行从小到大排序；
    判断第一分位的电离层质量因子是否大于第二分位的对流层质量因子，以及所述第一分位的电离层质量因子是否大于预设最小活跃阈值，其中第一分位小于或等于第二分位；
    所述根据接收到的质量因子判断当前历元的电离层是否活跃之后，还包括：
    在所述第一分位的电离层质量因子大于所述第二分位的对流层质量因子，且所述第一分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃；或者
    将接收到的多个卫星的电离层质量因子和多个卫星的对流层质量因子分别进行从大到小排序；
    判断第三分位的电离层质量因子是否大于第四分位的对流层质量因子，以及所述第三分位的电离层质量因子是否大于预设最小活跃阈值，其中第三分位大于或等于第四分位；
    所述根据接收到的质量因子判断当前历元的电离层是否活跃之后，还包括：
    在所述第三分位的电离层质量因子大于所述第四分位的对流层质量因子，且所述第三分位的电离层质量因子大于预设最小活跃阈值时，确定当前历元的电离层活跃。
  5. 一种网络RTK抗电离层干扰定位方法，应用于服务器，所述方法包括：
    根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，所述基线为两个所述基站相连形成；
    基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
    根据所述大气误差模型的模型参数计算所述基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
    根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
    向所述终端播发所述目标格网点的差分改正数和质量因子，以使所述终端根据所述目标格网点的质量因子确定RTK滤波模式，并根据所述RTK滤波模式采用差分改正数进行滤波解算以得到所述终端的高精度位置信息，所述RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式。
  6. 根据权利要求5所述的网络RTK抗电离层干扰定位方法，其中，所述根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，包括：
    根据基站网络中各个基站的观测数据和位置信息，解算多条基线的双差模糊度；
    根据多条基线的双差模糊度计算多条基线的电离层误差值和对流层误差值。
  7. 根据权利要求5所述的网络RTK抗电离层干扰定位方法，其中，所述根据所述大气误差模型的模型参数计算所述基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子，包括：
    根据所述大气误差模型的模型参数、各条基线对应基站的位置信息以及各条基线的电离层误差值和对流层误差值计算得到所述大气误差模型中各条基线的观测值残差；
    根据所述各条基线的观测值残差计算所述模型参数的精度因子矩阵；
    根据所述精度因子矩阵和所述基站网络中多个格网点的位置信息，分别计算得到每个格网点位置的质量因子。
  8. 一种网络RTK抗电离层干扰的定位装置，所述装置包括：
    接收模块，用于接收服务器播发的差分改正数和质量因子，所述差分改正数和所述质量因子为服务器根据各个基站的观测数据和位置信息以及所述终端上传的概略位置信息生成，所述质量因子用于表征生成所述差分改正数所用的大气误差模型精度；
    判定模块，用于根据接收到的质量因子确定RTK滤波模式，所述RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
    定位模块，用于采用确定的所述RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到所述终端的高精度位置信息；
    或者，所述装置包括：
    误差模块，用于根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，所述基线为两个所述基站相连形成；
    建模模块，用于基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
    计算模块，用于根据所述大气误差模型的模型参数计算所述基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
    匹配模块，用于根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
    播发模块，用于向所述终端播发所述目标格网点的差分改正数和质量因子，以使所述终端根据所述目标格网点的质量因子确定RTK滤波模式，并根据所述RTK滤波模式采用差分改正数进行滤波解算以得到所述终端的高精度位置信息，所述RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式。
  9. 一种网络RTK抗电离层干扰定位系统，包括服务器和终端，所述系统包括：
    所述服务器根据基站网络中各个基站的观测数据和位置信息，生成多条基线的电离层误差和对流层误差，所述基线为两个所述基站相连形成；
    所述服务器基于多条基线的电离层误差和对流层误差以及各个基站的位置信息进行建模，得到大气误差模型；
    所述服务器根据所述大气误差模型的模型参数计算所述基站网络中多个格网点位置的差分改正数以及多个格网点位置的质量因子；
    所述服务器根据终端发送的概略位置信息从多个格网点位置中确定距离终端概略位置最近的目标格网点；
    所述服务器向所述终端播发所述目标格网点的差分改正数和质量因子；
    所述终端接收服务器播发的差分改正数和质量因子，所述差分改正数和所述质量因子为服务器根据各个基站的观测数据和位置信息以及所述终端上传的概略位置信息生成，所述质量因子用于表征生成所述差分改正数所用的大气误差模型精度；
    所述终端根据接收到的质量因子确定RTK滤波模式，所述RTK滤波模式包括无电离层组合滤波模式或非组合滤波模式；
    所述终端采用确定的所述RTK滤波模式对终端的观测数据和终端接收到的差分改正数进行滤波解算，得到所述终端的高精度位置信息。
  10. 一种网络RTK抗电离层干扰定位设备，所述网络RTK抗电离层干扰定位设备包括：处理器以及存储有计算机程序指令的存储器；
    所述处理器执行所述计算机程序指令时实现如权利要求1-7中任一项所述的网络RTK抗电离层干扰定位方法。
  11. 一种计算机存储介质，所述计算机存储介质上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现如权利要求1-7中任一项所述的网络RTK抗电离层干扰定位方法。
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