A Method and System for Selecting the Location of Encrypted Reference Stations Based on Ionospheric Precision Information

Abstract

This invention discloses a method and system for selecting locations of encrypted reference stations based on ionospheric accuracy information. The method includes: constructing an ionospheric delay interpolation model within the service area based on the ionospheric delay of each baseline and the positional relationship between reference stations; estimating the ionospheric accuracy information of a single epoch at the user terminal based on the ionospheric delay interpolation model; calculating the ionospheric accuracy information of multiple epochs based on historical observation data; estimating the accuracy matrix of the user terminal's undetermined parameters using a GNSS double-difference observation model; calculating the positioning error of candidate points within the area based on the undetermined parameter accuracy matrix at the user terminal; and selecting locations for the construction of encrypted reference stations that meet the required number of locations based on the positioning error and the geographical conditions of the points. This invention utilizes GNSS measured data from the reference station network within the service area to estimate the ionospheric accuracy information of any point within the service area, thereby determining the priority construction locations for encrypted reference stations and maximizing the service capability of newly built encrypted reference stations for the entire network.

Description

Technical Field

[0001] This invention belongs to the field of global navigation systems and positioning measurement technology, and particularly relates to a method and system for selecting the location of encrypted reference stations based on ionospheric accuracy information. Background Technology

[0002] A satellite navigation reference station network is a network of multiple high-precision GNSS (Global Navigation Satellite System) receivers distributed globally or in specific regions. It uses technologies such as DGNSS (Differential Global Navigation Satellite System), Real-Time Kinematic (RTK), and Precise Point Positioning-Real-Time Kinematic (PPP-RTK) to provide users with real-time, precise positioning services.

[0003] Reference stations are a core component of satellite navigation reference station networks. They receive signals from medium, high, and low Earth orbit navigation satellites, generate high-precision observation data, and transmit this data to the data center via various communication methods. The data center then uses this high-precision observation data from reference stations within its area to generate various types of navigation and positioning products. The quality and accuracy of these products are key factors affecting the service capabilities of the reference station network. After the reference station network is established, to further improve its service capabilities, especially to enhance user positioning in areas with weak service capabilities, additional encrypted reference stations can be added to the existing network. Constructing encrypted stations in suitable locations can supplement the data in weak areas, improving the overall network service capabilities; conversely, inappropriate locations will result in wasted resources and limited improvement to the network's service capabilities. Therefore, the selection of locations for encrypted stations is crucial.

[0004] Traditional methods for constructing additional stations either only consider the spatial relationship between reference stations, emphasizing the uniformity of their spatial distribution, while the actual ionospheric activity is often inconsistent across space; or they utilize large amounts of user positioning data, which is costly; or they rely on empirical formulas to identify areas where the positioning products produced by the reference station network have low accuracy, i.e., areas with weak service capabilities, and construct additional stations in these areas. However, in reality, these empirical formulas cannot accurately reflect the complex spatiotemporal changes of various error sources (such as ionospheric delay), especially during the midday hours when the atmosphere is active and in low-latitude regions. As a result, after the additional stations are built, the relevant observational data cannot effectively enhance the existing reference station network. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a method for selecting the location of encrypted reference stations based on ionospheric accuracy information. Using measured GNSS observation data, the method estimates the accuracy information of ionospheric products within the service area of ​​the reference station network, calculates the positioning error of candidate points, and finally determines the construction location of the encrypted reference station. This maximizes the improvement of the overall network service capability brought about by the newly built encrypted reference station. The method includes the following steps:

[0006] Step 1: Complete the network of reference stations within the service area, resolve the ambiguity at each frequency of the reference station network, and calculate the ionospheric delay on each baseline based on the actual GNSS observation data;

[0007] Step 2: Based on the ionospheric delay on each baseline and the positional relationship between reference stations, construct an ionospheric delay interpolation model within the service area;

[0008] Step 3: Based on the ionospheric delay interpolation model constructed in Step 2, estimate the ionospheric accuracy information of a single epoch at the user end;

[0009] Step 4: Based on historical observation data, use the calculation method in Step 3 to estimate the ionospheric accuracy information for multiple epochs, and use the GNSS double-difference observation model to estimate the accuracy matrix of the parameters to be determined at the user end.

[0010] Step 5: Calculate the positioning error of the candidate points in the region based on the precision matrix of the parameters to be determined on the user terminal. Based on the positioning error of the candidate points and the geographical conditions of the candidate points, select the construction locations of the required number of encrypted reference stations.

[0011] Furthermore, in step 1, the ambiguity at each frequency of the reference station network is resolved. Once the ambiguity is fixed, the ionospheric delay at each baseline is calculated as follows:

[0012]

[0013] In the formula, λ1 and λ2 represent the ionospheric delay on the L1 signal between reference stations, respectively; f1 and f2 represent the frequencies of the L1 and L2 signals, respectively; λ1 and λ2 represent the wavelengths of the L1 and L2 signals, respectively; and N1 and N2 represent the ambiguity on the L1 and L2 signals between reference stations, respectively. and These represent the carrier observations of the L1 and L2 signals, respectively.

[0014] Furthermore, in step 2, an indirect adjustment method is used to construct an ionospheric delay interpolation model within the service area. The specific calculation method is as follows:

[0015] V r =B r XL r (2)

[0016]

[0017] In the formula, V r B represents the ionospheric delay residual in the indirect adjustment model; r To construct a matrix, where ΔX i and ΔY i L represents the components on the X and Y axes of the plane corresponding to the baseline, respectively; r Let I be the reference value vector. i This represents the ionospheric delay of the corresponding baseline; X is the fitting parameter vector, where a1 and a2 are the fitting parameters of the linear interpolation model, and n is the number of baselines.

[0018] The adjusted fitting parameter vector is calculated using the least squares method. Right now:

[0019]

[0020] Among them, P r The weight matrix is ​​calculated as follows:

[0021]

[0022] In the formula, d i This represents the planar distance to the corresponding baseline.

[0023] Furthermore, in step 3, the coordinate difference matrix B between the user terminal and the main reference station is used... u The ionospheric delay at the user end is calculated using the following formula:

[0024]

[0025] In the formula, I ru ΔX represents the ionospheric delay at the user terminal, ΔY represents the coordinate difference between the user terminal and the main reference station on the X-axis, and ΔY represents the coordinate difference between the user terminal and the main reference station on the Y-axis.

[0026] The ionospheric delay at the user end calculated by equation (8) has an error compared to the actual ionospheric delay, which is denoted as V. u ,but:

[0027]

[0028] In the formula, L u For the actual ionospheric delay at the user end, E u It is a unit vector.

[0029] According to the law of error propagation, the user-end ionospheric delay error V u The variance is expressed as:

[0030]

[0031] In the formula, D represents the variance of the error in the user-end ionospheric delay product. LL The ionospheric delay variance is the baseline and the user end.

[0032] In actual operation, the server calculates the ionospheric delay product for each user terminal using a separate ionospheric delay interpolation model within the region. Therefore, if the number of users in the model is considered to be 1, then D LL It is an n+1 square matrix, that is:

[0033]

[0034] In the formula, Let P be the unit weighted variance of the ionospheric delay residuals of n baselines and the user's baseline relative to the main reference station baseline. r For the weighted matrix, d u This refers to the planar distance between the user terminal and the main reference station.

[0035] Considering that the user is located within the network, and the properties of their ionospheric delay residual are similar to those of surrounding stations, their ionospheric delay residual can be approximated as the average of the ionospheric delay residuals of other reference stations. The estimate is:

[0036]

[0037] In the formula, V is the unit weighted variance of the ionospheric delay residuals on n baselines. n Let P be the ionospheric delay residual over n baselines. r Let t be the weight matrix, and t be the number of necessary observations.

[0038] The variance of the ionospheric delay error is calculated using equations (10)-(14). This refers to the user-end ionospheric accuracy information for each epoch.

[0039] Furthermore, the observation equation for the user end in step 4 is:

[0040]

[0041] In the formula, i and j represent satellite numbers, and r and u represent receiver numbers. These are the double-difference pseudorange observations between satellites i and j, and between receivers r and u. It is the double difference distance between satellites i and j and between receivers r and u. It is the ionospheric delay between i and j satellites and between r and u receivers. These are the double-difference carrier observations between satellites i and j, and between receivers r and u. It is the double-difference ambiguity between satellites i and j and between receivers r and u, where λ represents the frequency of the corresponding carrier signal.

[0042] The user-side indirect adjustment model is constructed as follows:

[0043]

[0044] In the formula, V is the residual vector of the equation. It is the double-difference unit vector on the line connecting receivers r and u with satellites i and j, Δx ru It is the coordinate change of the approximate r and u coordinates of the receiver. It is the ionospheric delay between i and j satellites and between r and u receivers. It refers to the double-difference ambiguity between satellites i and j, and between receivers r and u. These are the double-difference pseudorange observations between satellites i and j, and between receivers r and u. The distance between the receiver (r, u) and satellite (i, j) is calculated from the user's approximate coordinates. It is the a priori ionospheric delay between i and j satellites and between r and u receivers. These are the double-difference carrier observations between satellites i and j, and between receivers r and u. λ represents the a priori double-difference ambiguity between satellites i and j and between receivers r and u, where λ represents the frequency of the corresponding carrier signal.

[0045] make

[0046] Equation (17) can be simplified as follows:

[0047] V = BX * -L (18)

[0048] The observation weight matrix P is calculated using the elevation angle model or the signal-to-noise ratio random error model, and the relevant parameters to be determined are obtained by solving the least squares method:

[0049]

[0050] Let A = (B) T PB) -1 B T P, according to the error propagation law, yields the accuracy matrix of the parameter to be determined. for:

[0051]

[0052] in:

[0053]

[0054] In the formula, D L This is the observation accuracy matrix; For random errors in observations, in the GNSS double-difference observation model, it can be expressed as:

[0055]

[0056] In the formula, For the random error of the pseudorange or carrier observation value corresponding to satellite i, when the observation value is pseudorange, The value is 1 when the observed value is a carrier wave. The variance of the ionospheric delay error at multiple epochs was calculated from historical observation data, which is 0.001. Find the RMS value of the element corresponding to satellite i that is on the diagonal, and you will get...

[0057] Furthermore, in step 5, The positioning error D is obtained by adding the first three elements of the middle diagonal. XYZ Calculate D for all candidate points within the service area. XYZ According to the D of the candidate point XYZ Based on the geographical conditions of the candidate sites, select locations for constructing the required number of encrypted base stations.

[0058] The present invention also provides a system for selecting the location of an encrypted reference station based on ionospheric precision information, which is used to implement the method for selecting the location of an encrypted reference station based on ionospheric precision information as described above.

[0059] Furthermore, it includes a processor and a memory, the memory being used to store program instructions, and the processor being used to call the stored instructions in the memory to execute the encrypted reference station location selection method based on ionospheric accuracy information as described above.

[0060] Alternatively, it may include a readable storage medium storing a computer program that, when executed, implements the method for selecting the location of an encrypted reference station based on ionospheric precision information as described above.

[0061] Compared with the prior art, the present invention has the following advantages:

[0062] This invention uses GNSS measured data from a reference station network within the service area to estimate the ionospheric accuracy information of any point within the service area. Then, it identifies areas (points) within the coverage area of ​​the reference station network that are greatly affected by the ionosphere and have weak service capabilities. These areas (points) are then designated as priority areas for the construction of densified reference stations, thereby maximizing the service capabilities of newly built densified reference stations for the entire network. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0064] Figure 1 This is a flowchart of the method for selecting the location of an encrypted reference station based on ionospheric accuracy information according to an embodiment of the present invention.

[0065] Figure 2 This is a diagram showing the positioning error results of the candidate points calculated according to an embodiment of the present invention. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be further described below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0067] Example 1

[0068] like Figure 1 As shown, this embodiment of the invention provides a method for selecting the location of an encrypted reference station based on ionospheric precision information, comprising the following steps:

[0069] Step 1: Complete the network of reference stations within the service area, resolve the ambiguity at each frequency of the reference station network, and calculate the ionospheric delay on each baseline based on actual GNSS observation data.

[0070] The ambiguity at each frequency can be solved using multi-epoch filtering algorithms, single-epoch algorithms, or inter-station ambiguity fixing algorithms such as TCAR. This embodiment uses a multi-epoch filtering algorithm to solve the ambiguity at each frequency. Once the ambiguity is fixed, the ionospheric delay at each baseline is calculated as follows:

[0071]

[0072] In the formula, I f1 λ1 and λ2 represent the ionospheric delay on the L1 signal between reference stations, respectively; f1 and f2 represent the frequencies of the L1 and L2 signals, respectively; λ1 and λ2 represent the wavelengths of the L1 and L2 signals, respectively; and N1 and N2 represent the ambiguity on the L1 and L2 signals between reference stations, respectively. and These represent the carrier observations of the L1 and L2 signals, respectively.

[0073] Step 2: Based on the ionospheric delay on each baseline and the positional relationship between reference stations, construct an ionospheric delay interpolation model within the service area.

[0074] An ionospheric delay interpolation model within the service area is constructed using an indirect adjustment method. The specific calculation method is as follows:

[0075] V r =B r XL r (2)

[0076]

[0077] In the formula, V r B represents the ionospheric delay residual in the indirect adjustment model; r To construct a matrix, where ΔX i and ΔY i L represents the components on the X and Y axes of the plane corresponding to the baseline, respectively; r Let I be the reference value vector. i This represents the ionospheric delay of the corresponding baseline; X is the fitting parameter vector, where a1 and a2 are the fitting parameters of the linear interpolation model, and n is the number of baselines.

[0078] The adjusted fitting parameter vector is calculated using the least squares method. Right now:

[0079]

[0080] Among them, P r The weight matrix is ​​calculated as follows:

[0081]

[0082] In the formula, d i This represents the planar distance to the corresponding baseline.

[0083] Step 3: Based on the ionospheric delay interpolation model constructed in Step 2, estimate the ionospheric accuracy information of a single epoch at the user end.

[0084] Based on the coordinate difference matrix B between the user terminal and the main reference station u The ionospheric delay at the user end is calculated using the following formula:

[0085]

[0086] In the formula, I ru ΔX represents the ionospheric delay at the user terminal, ΔY represents the coordinate difference between the user terminal and the main reference station on the X-axis, and ΔY represents the coordinate difference between the user terminal and the main reference station on the Y-axis.

[0087] The ionospheric delay at the user end calculated by equation (8) has an error compared to the actual ionospheric delay, which is denoted as V. u ,but:

[0088]

[0089] In the formula, L u For the actual ionospheric delay at the user end, E u It is a unit vector.

[0090] According to the law of error propagation, the user-end ionospheric delay error V u The variance can be expressed as:

[0091]

[0092] In the formula, D represents the variance of the error in the user-end ionospheric delay product. LL The ionospheric delay variance is the baseline and the user end.

[0093] In practice, the server calculates the ionospheric delay product for each user terminal using a separate regional ionospheric delay interpolation model. Therefore, the number of users in the model can be considered as 1, and D... LL It is an n+1 square matrix, that is:

[0094]

[0095] In the formula, Let P be the unit weighted variance of the ionospheric delay residuals of n baselines and the user's baseline relative to the main reference station baseline. r The weight matrix is ​​calculated using formula (7); d u This refers to the planar distance between the user terminal and the main reference station.

[0096] Considering that the user is located within the reference station network, and the properties of their ionospheric delay residual are similar to those of surrounding stations, their ionospheric delay residual can be approximated as the average of the ionospheric delay residuals of other reference stations. The estimate is:

[0097]

[0098] In the formula, V is the unit weighted variance of the ionospheric delay residuals on n baselines. n Let P be the ionospheric delay residual over n baselines. r Let t be the weight matrix, and t be the number of necessary observations;

[0099] The variance of the ionospheric delay error is calculated using equations (10)-(14). This refers to the user-end ionospheric accuracy information for each epoch.

[0100] Step 4: Based on historical observation data, use the calculation method in Step 3 to estimate the ionospheric accuracy information for multiple epochs, and use the GNSS double-difference observation model to estimate the accuracy matrix of the parameters to be determined at the user end.

[0101] The observation equation at the user end can be expressed as:

[0102]

[0103]

[0104] In the formula, i and j represent satellite numbers, and r and u represent receiver numbers. These are the double-difference pseudorange observations between satellites i and j, and between receivers r and u. It is the double difference distance between satellites i and j and between receivers r and u. It is the ionospheric delay between i and j satellites and between r and u receivers. These are the double-difference carrier observations between satellites i and j, and between receivers r and u. It is the double-difference ambiguity between satellites i and j and between receivers r and u, where λ represents the frequency of the corresponding carrier signal.

[0105] The user-side indirect adjustment model is constructed as follows:

[0106]

[0107] In the formula, V is the residual vector of the equation. It is the double-difference unit vector on the line connecting receivers r and u with satellites i and j, Δx ru It is the coordinate change of the approximate r and u coordinates of the receiver. It is the ionospheric delay between i and j satellites and between r and u receivers. It refers to the double-difference ambiguity between satellites i and j, and between receivers r and u. These are the double-difference pseudorange observations between satellites i and j, and between receivers r and u. The distance between the receiver (r, u) and satellite (i, j) is calculated from the user's approximate coordinates. It is the a priori ionospheric delay between i and j satellites and between r and u receivers. These are the double-difference carrier observations between satellites i and j, and between receivers r and u. λ represents the a priori double-difference ambiguity between satellites i and j and between receivers r and u, where λ represents the frequency of the corresponding carrier signal.

[0108] make

[0109] Equation (17) can be simplified as:

[0110] V = BX * -L (18)

[0111] The observation weight matrix P is calculated using the elevation angle model or the signal-to-noise ratio random error model, and the relevant parameters can be solved using the least squares method.

[0112]

[0113] Let A = (B) T PB) -1 B T P, according to the error propagation law, yields the accuracy matrix of the parameter to be determined. for:

[0114]

[0115] in:

[0116]

[0117] In the formula, D L This is the observation accuracy matrix; For the random error of the observations, in the GNSS double-difference observation model (equations (15)-(16)), It can be represented as:

[0118]

[0119] In the formula, For the random error of the pseudorange or carrier observation value corresponding to satellite i, when the observation value is pseudorange, The value is 1 when the observed value is a carrier wave. The variance of the ionospheric delay error at multiple epochs was calculated from historical observation data, which is 0.001. Find the RMS value of the element corresponding to satellite i that is on the diagonal, and you will get...

[0120] Step 5: Calculate the positioning error of the candidate points in the region based on the precision matrix of the parameters to be determined on the user terminal. Based on the positioning error of the candidate points and the geographical conditions of the candidate points, select the construction locations of the required number of encrypted reference stations.

[0121] The specific locations of the candidate sites can be obtained by evenly dividing the area according to latitude and longitude, or the candidate sites can be conditionally specified according to the relevant requirements of the builders. The sum of the first three elements on the diagonal is the positioning error D of the candidate point. XYZIn this embodiment, the service area is divided into latitude and longitude grids at 10-second intervals to obtain all candidate points. The positioning error D of all candidate points is calculated. XYZ The error results are as follows: Figure 2 As shown. Figure 2 In the middle, the black inverted triangle represents the established benchmark station, D. XYZ The higher the value, the redder the color, indicating that the location is more likely to be used as a cryptographic base station. Based on the D value of the candidate locations... XYZ Based on the geographical conditions of the location (preferably a plain with no obstructions), select a location to build a sufficient number of encrypted base stations.

[0122] Example 2

[0123] Based on the same inventive concept, the present invention also provides an encrypted reference station location selection system based on ionospheric precision information, including a processor and a memory. The memory is used to store program instructions, and the processor is used to call the program instructions in the memory to execute the encrypted reference station location selection method based on ionospheric precision information as described above.

[0124] Example 3

[0125] Based on the same inventive concept, the present invention also provides an encrypted reference station location selection system based on ionospheric precision information, including a readable storage medium on which a computer program is stored. When the computer program is executed, it implements the encrypted reference station location selection method based on ionospheric precision information as described above.

[0126] In specific implementation, the method proposed in the technical solution of this invention can be automatically executed by those skilled in the art using computer software technology. System devices for implementing the method, such as computer-readable storage media storing the corresponding computer program of the technical solution of this invention and computer equipment including the computer program running the corresponding computer program, should also be within the protection scope of this invention.

[0127] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to replace them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A method for selecting an encrypted reference station position based on ionospheric accuracy information, characterized in that, The method comprises the following steps: Step 1, complete the network of reference stations in the service area, solve the ambiguity of each frequency of the network of reference stations, and calculate the ionospheric delay on each baseline according to the actual observation data of GNSS; Solve the ambiguity of each frequency of the network of reference stations, and calculate the ionospheric delay on each baseline after the ambiguity is fixed as follows: （1） wherein, denotes the ionospheric delay on the L1 signal between the reference stations, and denote the frequencies of the L1 and L2 signals, respectively, and denote the wavelengths of the L1 and L2 signals, respectively, and denote the ambiguities of the L1 and L2 signals between the reference stations, respectively, and denote the carrier observations of the L1 and L2 signals, respectively; Step 2, according to the ionospheric delay on each baseline and the position relationship between the reference stations, construct an ionospheric delay interpolation model in the service area; The ionospheric delay interpolation model in the service area is constructed by using indirect adjustment, and the specific calculation method is as follows: （2） （3） （4） （5） wherein represents ionospheric delay residual error in indirect adjustment model; is a constructed matrix, wherein and respectively represent the components on the plane X axis and Y axis of the corresponding baseline; is a reference value vector, wherein represents the ionospheric delay of the corresponding baseline; is a fitting parameter vector, wherein , is a fitting parameter of linear interpolation model, n is the number of baselines; The least square method is used to calculate the fitting parameter vector after adjustment That is: （6） wherein is a unitary matrix, calculated as follows: （7） In the formula, represents the planar distance from the baseline; Step 3, estimate the ionospheric accuracy information of a single epoch at the user end based on the ionospheric delay interpolation model constructed in step 2; Based on the coordinate difference matrix between the user terminal and the main reference station The ionospheric delay at the user end is calculated using the following formula: （8） wherein is the ionospheric delay at the user end, is the coordinate difference of the user end and the main reference station in the X axis, is the coordinate difference of the user end and the main reference station in the Y axis; The ionospheric delay of the user terminal calculated from the equation (8) and the real ionospheric delay have an error, which is denoted as Then: （9） wherein is the real ionospheric delay for the user end, is a unit vector; Step 4, estimate the ionospheric accuracy information of multiple epochs by using the calculation method in step 3 based on historical observation data, and estimate the accuracy matrix of the to-be-solved parameters at the user end by using a GNSS double-difference observation model; Step 5, calculate the positioning error of the to-be-selected point in the region based on the accuracy matrix of the to-be-solved parameters at the user end, and select the construction position of the encryption reference station that meets the demand quantity according to the positioning error of the to-be-selected point and the geographical situation of the to-be-selected point.

2. The method for selecting the position of an encrypted reference station based on ionospheric precision information according to claim 1, characterized in that: The variance of the ionospheric delay error at the user end in step 3 is expressed according to the law of error propagation as: where σ2is the variance of the ionospheric delay error at the user end. （10） wherein is the variance of the ionospheric delay product error at the user end, is the variance of the ionospheric delay at the baseline and the user end; In actual operation, the server will separately use the ionospheric delay interpolation model in the region to calculate the ionospheric delay product for each user terminal, so the number of user terminals in the model is considered as 1, that is, is an n+1 square matrix, that is: （11） （12） wherein is n the unit weight variance of the baseline and the ionospheric delay residual of the user with the master reference station baseline, is the weight matrix, is the plane distance between the user end and the master reference station. Considering that the user is located inside the network, the ionospheric delay residual of the user is approximately the same as that of the surrounding stations, the ionospheric delay residual of the user can be approximated as the average of the ionospheric delay residuals of other reference stations, and then is estimated as: （13） （14） wherein is n the unit weight variance of ionospheric delay residuals on the baseline, is n ionospheric delay residuals on the baseline, is a weight matrix, t is the number of necessary observations; The variance of ionospheric delay error is calculated according to formula (10)-(14) That is, the ionospheric precision information of the user terminal at each epoch.

3. The method for selecting the location of an encrypted reference station based on ionospheric precision information as described in claim 1, characterized in that: The observation equation of the user end in step 4 is: （15） （16） wherein i , j denotes a satellite number, r , u denotes a receiver number, is i, j a double-difference pseudo-range observation between r , u receivers, is i, j a double-difference range between r , u receivers, is i, j an ionospheric delay between r , u receivers, is i, j a double-difference carrier-phase observation between r , u receivers, is i, j a double-difference ambiguity between r , u receivers, denotes a frequency of a corresponding carrier signal; The indirect adjustment model of the user end is constructed as follows: （17） where V is the equation residual vector, is the receiver r , u is the unit vector of the double difference between the satellite i , j and the receiver , r is the coordinate variation of the approximate coordinate of the receiver u , is the ionospheric delay between the satellites i, j , r and the receivers u , is the double difference ambiguity between the satellites i, j , r and the receivers u , is the double difference pseudo-range observation between the satellites i, j , r and the receivers u , is the double difference geometric distance between the satellites r , u and the receivers i , j calculated from the approximate coordinate of the user , i, j is the prior ionospheric delay between the satellites r , u and the receivers , i, j is the double difference carrier observation between the satellites r , u and the receivers , i, j is the prior double difference ambiguity between the satellites r , u and the receivers denotes the frequency of the corresponding carrier signal.

4. The method of claim 3, wherein the ionospheric precision information is obtained from a global positioning system (GPS) receiver. In step 4, let , , then equation (17) is simply written as: （18） The observation value weight matrix P is calculated according to the elevation angle model or the signal-to-noise ratio random error model, and the related to-be-solved parameters are solved by using the least square method as follows: （19） Let The precision matrix of the parameters to be solved is obtained according to the error propagation law : （20） Wherein: （21） wherein is the observation precision matrix; is the observation random error, which in the GNSS double difference observation model can be expressed as: （22） where is the pseudorange or carrier phase observation of satellite i , and is the random error of the pseudorange or carrier phase observation of satellite , and is the variance of ionospheric delay error of satellite i at epoch i, which is calculated from historical observation data, and is the RMS value of the elements in the diagonal of R, i.e., 5. The method for selecting the location of an encrypted reference station based on ionospheric precision information as described in claim 4, characterized in that: In step 5 The positioning error is obtained by adding the first three elements of the diagonal in step 4 The positioning error of all candidate sites in the service area is calculated The positioning error of all candidate sites in the service area is calculated The construction locations of the encrypted reference stations satisfying the demand quantity are selected according to the positioning error of the candidate sites and the geographical conditions of the candidate sites.

6. An ionospheric precision information based encrypted reference station position selection system, characterized by, The device comprises a processor and a memory, the memory is used to store program instructions, and the processor is used to call the program instructions in the memory to execute the method for selecting the position of the encryption reference station based on the ionospheric accuracy information according to any one of claims 1-5.

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