Precise point positioning ambiguity fixing method based on phase deviation precision factor

Abstract

The invention discloses a precise point positioning ambiguity fixing method based on a phase deviation precision factor, and belongs to the technical field of a global navigation satellite system, and the method comprises the steps: calculating the decimal cycle parts of ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity based on a GNSS reference station phase observation value; sequentially selecting observation stations according to the number of observation satellites, calculating a receiver end UPD value and a satellite end UPD value through iteration by using a phase deviation whole network resolving method and decimal cycles of the ultra-wide lane ambiguity, the wide lane ambiguity and the narrow lane ambiguity, and extracting a residual vector of phase deviation; calculating a UPD precision factor according to the residual vector of the phase deviation; and updating the ambiguity variance-covariance matrix of the user side by using the UPD precision factor, and fixing the ambiguity of the user side based on an LAMBDA algorithm. According to the invention, the problem of inconsistency between the ambiguity and the precision of the ambiguity variance-covariance matrix in the prior art is solved.

Description

Technical Field

[0001] The invention relates to a single-point positioning ambiguity fixing method based on phase deviation precision factor, and belongs to the technical field of global navigation satellite systems. Background Art

[0002] As a key infrastructure for providing national positioning, navigation and timing services, GNSS (Global Navigation Satellite System) has demonstrated its extensive application value in many fields such as precision agriculture, intelligent transportation and space environment monitoring. Among them, the traditional precise point positioning (PPP) technology can theoretically achieve centimeter-level positioning accuracy by combining a single receiver with precise ephemeris and clock products. However, the convergence time of PPP technology is long, usually more than 30 minutes, which seriously limits its application in real-time high-precision positioning scenarios. In order to overcome this limitation, PPP-AR (Precise Point Positioning Ambiguity Fixation) technology came into being. PPP-AR technology can significantly shorten the convergence time and improve positioning accuracy by restoring the integer characteristics of carrier phase ambiguity. In particular, the least squares ambiguity reduction and correlation adjustment method (LAMBDA) is widely used in the GNSS ambiguity fixation process, which relies on real ambiguities and their corresponding variance-covariance matrices to search for integer ambiguities. In recent years, PPP-AR technology has been widely promoted and applied in surveying and mapping, geological disaster monitoring and other fields, and has become one of the core means of GNSS high-precision positioning.

[0003] Although PPP-AR technology has made significant progress in high-precision positioning, the existing technology still has some obvious defects. First, when using the LAMBDA method for PPP-AR, the real ambiguity is usually obtained by deducting the phase bias from the PPP floating-point solution, while the variance-covariance matrix uses the ambiguity variance-covariance information of the PPP floating-point solution. However, due to the existence of phase bias estimation errors, the real ambiguity obtained after deducting the phase bias and the variance-covariance matrix of the PPP floating-point solution may have inconsistent accuracy. This inconsistency will lead to a decrease in the success rate of ambiguity fixation, especially in complex environments such as active ionospheric periods or areas with significant multipath effects. Secondly, with the growth of real-time application needs, although the International GNSS Service (IGS) has provided real-time satellite orbit, clock and phase bias products, which has promoted the development of real-time PPP-AR, the quality and delay of real-time products have a significant impact on the performance of PPP-AR. The delay of real-time products will lead to the accumulation of satellite clock and orbit errors, further exacerbating the uncertainty of ambiguity fixation. In addition, the existing methods do not fully consider the uncertainty of UPD (uncalibrated phase delay) correction when processing on the user side, which also leads to a decrease in the success rate of ambiguity fixation, especially when the quality of real-time products is poor. In complex environments, the performance of traditional PPP-AR methods is further limited, and the convergence time is significantly extended, making it difficult to meet the needs of real-time centimeter-level positioning. Therefore, the existing technologies still have obvious bottlenecks in terms of efficiency and robustness in high-precision real-time positioning. Summary of the invention

[0004] The purpose of the present invention is to provide a single-point positioning ambiguity fixing method based on phase deviation precision factor, which solves the problem of inconsistency between the ambiguity and the ambiguity variance-covariance matrix in the prior art by introducing the phase deviation precision factor into the ambiguity variance-covariance matrix, and improves the ambiguity fixing success rate and positioning robustness in complex environments and real-time product delays.

[0005] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions:

[0006] The present invention provides a method for fixing ambiguity of precise point positioning based on phase deviation precision factor, comprising:

[0007] Get the GNSS base station phase observation value on the server side;

[0008] Based on the phase observations of the GNSS reference station, the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity of the floating point ambiguity is calculated;

[0009] The stations are selected in turn according to the number of observed satellites, and the UPD values ​​of all receivers in the reference station network and the UPD values ​​of all visible satellites are iteratively calculated by using the phase deviation whole network solution method and the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity, and the residual vector of the phase deviation is extracted;

[0010] Calculate the UPD precision factor based on the residual vector of the phase deviation;

[0011] The UPD precision factor is used to update the ambiguity variance-covariance matrix of the user end, and the ambiguity of the user end is fixed based on the LAMBDA algorithm.

[0012] Furthermore, based on the phase observation values ​​of the GNSS reference station, the fractional cycle parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity of the floating point ambiguity are calculated, including:

[0013] estimating floating point ambiguities from the GNSS reference station phase observations based on a non-differenced non-combined observation model;

[0014] The floating point ambiguity includes integer ambiguity, receiver-side and satellite-side phase deviations;

[0015] Performing linear combination processing on the floating point ambiguities to transform them into ultra-wide lane ambiguities, wide lane ambiguities and narrow lane ambiguities;

[0016] The ultra-wide lane ambiguity, the wide lane ambiguity and the narrow lane ambiguity are rounded off respectively to obtain the integer parts of the ultra-wide lane ambiguity, the wide lane ambiguity and the narrow lane ambiguity;

[0017] The fractional parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity are obtained by subtracting the integer parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity from the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

[0018] Furthermore, the stations are selected in turn according to the number of observed satellites, and the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites are iteratively calculated using the phase deviation whole-network solution method and the fractional cycle parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity, including:

[0019] The UPD value at the receiver end of the station with the largest number of observed satellites is set to 0, and the UPD value at the receiver end is subtracted from the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity to obtain the initial UPD value at the satellite end;

[0020] Select the remaining stations in descending order according to the number of observed satellites, and repeat the following steps until all stations have been processed:

[0021] For each known satellite at each station:

[0022] Subtracting the satellite-side UPD value from the fractional cycle parts of the ultra-wide lane ambiguity, the wide lane ambiguity, and the narrow lane ambiguity, and then taking the average value as the receiver-side UPD value;

[0023] For each unknown satellite at each station:

[0024] The satellite-side UPD value of the unknown satellite is obtained by subtracting the UPD value at the receiver from the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

[0025] The satellite-side UPD values ​​of the same satellite obtained by each measuring station are weighted averaged to obtain the satellite-side UPD value of the satellite;

[0026] If the difference between the satellite-side UPD values ​​obtained in two adjacent iterations is less than a preset threshold, the loop is exited to obtain the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites.

[0027] Further, the UPD value at the receiver end is expressed as:

[0028] ;

[0029] In the formula, Indicates the UPD value at the receiver end, that is, The UPD value of each receiver, Indicates The total number of satellites that can be observed by a receiver, Indicates satellites, represents the floating point ambiguity, represents the integer ambiguity, Indicates the satellite UPD value, that is, The UPD value of the satellite.

[0030] Furthermore, the satellite UPD value is expressed as:

[0031] ;

[0032] In the formula, Indicates the satellite UPD value, that is, UPD value of satellites It means that the The total number of receivers for satellites, Indicates Receivers, Indicates Satellite No. The UPD value is calculated at each receiver. Indicates Satellites No. The UPD value calculated at each receiver The corresponding weight.

[0033] Furthermore, the residual vector of the phase deviation is distributed on each satellite, wherein the residual vector of the phase deviation is expressed as:

[0034] ;

[0035] In the formula, The residual vector representing the phase deviation, represents the total number of receivers in the base station network, Represents the total number of all visible satellites in the base station network, Indicates The receiver observes The phase deviation residual of each satellite is Indicates The receiver observes The floating point ambiguities for each satellite, Indicates The receiver observes The integer ambiguity of the satellites, express OK The identity matrix of the columns, represents the Kronecker product, express A column vector with 1 row and 1 column. express A column vector with 1 row and 1 column. express OK The identity matrix of the columns, represents the satellite-side UPD vector of all visible satellites in the base station network, represents the receiver-side UPD vector of all receivers in the base station network, Indicates transpose.

[0036] Furthermore, the UPD precision factor is calculated based on the residual vector of the phase deviation, including:

[0037] Calculate the RMS of all elements in the residual vector of the phase deviation to obtain the UPD precision factor;

[0038] Wherein, the UPD precision factor is expressed as:

[0039] ;

[0040] In the formula, Indicates The UPD precision of the satellites is It means that the The total number of receivers for satellites, Indicates Receivers, Indicates The receiver observes The phase deviation residuals of the satellites.

[0041] Further, the UPD precision factor is used to update the ambiguity variance-covariance matrix of the user end, wherein the updated ambiguity variance-covariance matrix is ​​expressed as:

[0042] ;

[0043] In the formula, represents the updated user-side ambiguity variance-covariance matrix, represents the ambiguity variance-covariance matrix of the user side, where represents the ambiguity of the user side, represents a diagonal matrix consisting of UPD diffs of precision, Indicates the total number of satellites that the receiver can observe.

[0044] Furthermore, the UPD precision factor is used to update the ambiguity variance-covariance matrix of the user end, and the ambiguity of the user end is fixed based on the LAMBDA algorithm, including:

[0045] Using the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity as ambiguities at the user end;

[0046] De-correlating the ambiguity of the user terminal and the updated ambiguity variance-covariance matrix through a reversible integer transformation matrix to obtain an ambiguity vector and a transformed ambiguity variance-covariance matrix;

[0047] Performing ambiguity integer search and verification on the ambiguity vector and the converted ambiguity variance-covariance matrix to obtain integer ambiguity solutions;

[0048] The ambiguity at the user end is fixed according to the integer ambiguity solution.

[0049] Furthermore, the ambiguity vector and the converted ambiguity variance-covariance matrix are respectively expressed as:

[0050] ;

[0051] In the formula, represents the ambiguity vector, represents the ambiguity of the user side, represents a reversible integer transformation matrix, represents the transformed ambiguity variance-covariance matrix, represents the ambiguity variance-covariance matrix of the user side, represents the transposed matrix of the reversible integer transformation matrix, Indicates transpose.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. The present invention introduces the phase deviation precision factor and combines the phase observation value of the GNSS reference station to perform precise single-point positioning ambiguity fixation, which can accurately calculate and update the ambiguity variance-covariance matrix of the user end, which not only improves the accuracy of ambiguity fixation, but also enhances the robustness in complex environments and real-time data delays, thereby significantly improving the overall performance and reliability of precise single-point positioning.

[0054] 2. The present invention selects measuring stations in sequence according to the number of observed satellites, and uses the phase deviation whole-network solution method combined with the fractional cycle part of the wide-lane and narrow-lane ambiguities for iterative calculation. It can accurately solve the receiver-side UPD values ​​of all receivers and the satellite-side UPD values ​​of all visible satellites. It not only takes into account the influence of the number of observed satellites and gives priority to measuring stations with rich observation data, but also continuously updates the receiver-side UPD values ​​and the satellite-side UPD values ​​in a step-by-step approximation manner until the convergence conditions are reached, which significantly improves the accuracy and reliability of the estimation of the receiver-side UPD values ​​and the satellite-side UPD values, provides a solid foundation for subsequent ambiguity fixation, and thus improves the accuracy and efficiency of precise point positioning.

[0055] 3. The present invention updates the ambiguity variance-covariance matrix of the user end by combining the UPD precision factor, so that the search efficiency and success rate of the LAMBDA algorithm in the ambiguity fixing process are greatly improved, thereby accelerating the convergence speed while ensuring the positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flow chart of a method for fixing ambiguity of precise point positioning based on phase deviation precision factor provided by an embodiment of the present invention;

[0057] Figure 2 It is a schematic diagram of a convergence speed calculation example of a precise single-point positioning ambiguity fixing method based on phase deviation precision factor provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0059] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0060] Example 1

[0061] like Figure 1 As shown, this embodiment introduces a method for fixing ambiguity of precise single-point positioning based on phase deviation precision factor, which is characterized by comprising:

[0062] Step 1: Get the GNSS base station phase observation value on the server side.

[0063] The GNSS (Global Navigation Satellite System) base station provides high-precision satellite observation data, including pseudorange and phase observation values. The present invention calculates the floating point ambiguity by obtaining the phase observation value.

[0064] Step 2: Based on the phase observations of the GNSS reference station, calculate the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity of the floating point ambiguity.

[0065] The floating point ambiguity includes the integer cycle ambiguity, the UPD value at the receiver end and the UPD value at the satellite end. The wide lane and narrow lane ambiguity are obtained by linearly combining the floating point ambiguities of different frequencies. They have different sensitivities to ionospheric delays, so they can be used to separate and estimate phase deviations. The present invention estimates the UPD value at the receiver end and the UPD value at the satellite end by calculating the fractional cycle part of the wide lane and narrow lane ambiguities.

[0066] Step 3: Select the measuring stations in turn according to the number of observed satellites, and use the whole-network solution method of phase deviation and the fractional cycle part of ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity to iteratively calculate the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites and extract the residual vector of phase deviation.

[0067] The phase deviation whole network solution method uses the observation data of multiple stations and satellites to estimate the UPD value at the receiver and the UPD value at the satellite through iterative calculation. Stations with more observation satellites usually provide more observation information and are therefore processed first. The present invention reduces the uncertainty of the ambiguity parameters by iteratively calculating the UPD value, and the extracted phase deviation residual vector is used to evaluate the estimation accuracy of the UPD value.

[0068] Step 4: Calculate the UPD precision factor based on the residual vector of the phase deviation.

[0069] The UPD precision factor reflects the uncertainty or accuracy of the UPD value estimation. The UPD precision factor is calculated based on the statistical characteristics of the phase deviation residual vector, such as the root mean square error. The present invention uses the UPD precision factor to update the ambiguity variance-covariance matrix of the user end, thereby improving the reliability and accuracy of ambiguity fixation.

[0070] Step 5: Use the UPD precision factor to update the user-side ambiguity variance-covariance matrix, and fix the user-side ambiguity based on the LAMBDA algorithm.

[0071] The LAMBDA (Least-squares AMBiguity Decorrelation Adjustment) algorithm is an efficient method for integer ambiguity search. It reduces the correlation between ambiguity parameters through de-correlation processing, thereby improving search efficiency and success rate. The updated ambiguity variance-covariance matrix provided by the present invention provides more accurate statistical information for the LAMBDA algorithm, making the ambiguity fixing process more stable and reliable. Finally, the present invention fixes the ambiguity of the user end through the LAMBDA algorithm and realizes high-precision positioning.

[0072] Example 2

[0073] Based on the same inventive concept as Example 1, this embodiment introduces the implementation steps of a method for fixing ambiguity of precise point positioning based on phase deviation precision factor, including:

[0074] Step 1: Get the GNSS base station phase observation value on the server side.

[0075] Step 2: Based on the phase observations of the GNSS reference station, calculate the fractional cycle parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity of the floating point ambiguity.

[0076] In some embodiments, calculating fractional cycle parts of ultra-wide lane ambiguities, wide lane ambiguities, and narrow lane ambiguities of floating point ambiguities based on GNSS reference station phase observations includes:

[0077] Step 2.1: estimating floating point ambiguities from the phase observation values ​​of the GNSS reference station based on the non-differenced non-combined observation model;

[0078] In this embodiment, the floating point ambiguity includes integer ambiguity, receiver-side and satellite-side phase deviation. The floating point ambiguity of each satellite is expressed as:

[0079] ;

[0080] In the formula, Indicates The floating point ambiguities for each satellite, represents the integer ambiguity, Indicates the UPD value at the receiver end, that is, The UPD value of each receiver, Indicates the satellite UPD value, that is, Satellite-side UPD value of each satellite.

[0081] Step 2.2: Perform linear combination processing on the floating point ambiguity and transform it into ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

[0082] In this embodiment, the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity are expressed as:

[0083] ;

[0084] In the formula, , and They represent the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity respectively, , and Respectively, at frequencies , and Previous The receiver observes The floating point ambiguity solution is satellite-times, where , and Respectively represent the first signal frequency, the second signal frequency, and the third signal frequency transmitted by the corresponding satellite system:

[0085] The corresponding satellite system may be a GPS system, a GLONASS system, a Galileo system, a BDS system, etc., wherein the specific values ​​of the first signal frequency, the second signal frequency, and the third signal frequency in these satellite systems are as follows:

[0086] GPS system: The first signal frequency is L1: 1575.42MHz, the second signal frequency is L2: 1227.60MHz, and the third signal frequency is L5: 1176.45MHz;

[0087] GLONASS system: The first signal frequency is L1: ~1602MHz, the second signal frequency is L2: ~1246MHz, and the third signal frequency is L3: 1202.025MHz;

[0088] Galileo system: the first signal frequency is E1: 1575.42MHz, the second signal frequency is E5a: 1176.45MHz, and the third signal frequency is E5b: 1207.14MHz;

[0089] BDS system: The first signal frequency is B1: 1561.098 MHz, the second signal frequency is B2: 1207.14 MHz, and the third signal frequency is B3: 1268.52 MHz.

[0090] This embodiment can effectively separate the ambiguity information of different frequencies by performing linear combination processing on the floating-point ambiguity, thereby laying a foundation for subsequent phase deviation estimation.

[0091] Step 2.3: Perform rounding operations on the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity respectively to obtain the integer parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

[0092] Step 2.4: Subtract the integer parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity from the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity to obtain the fractional parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

[0093] Step 3: Select the measuring stations in turn according to the number of observed satellites, and use the whole-network solution method of phase deviation and the fractional cycle part of ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity to iteratively calculate the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites and extract the residual vector of phase deviation.

[0094] In this embodiment, when the first The receiver observes When the data of a satellite is collected, the receiver-side UPD values ​​and satellite-side UPD values ​​of all satellites in all measurement stations are combined. The combined receiver-side UPD values ​​and satellite-side UPD values ​​are expressed as:

[0095] ;

[0096] In the formula, Indicates The receiver observes The floating point ambiguity of the satellites, Indicates The receiver observes The integer ambiguity of satellites is obtained. express The identity matrix of express The vector of express The identity matrix of express vector, ⊗ represents the Kronecker product, represents the phase deviation vector at the receiver end, represents the satellite phase deviation vector, Indicates transpose.

[0097] In this embodiment, since the UPD value at the receiver end and the UPD value at the satellite end are linearly correlated, resulting in a rank deficiency between the UPD value at the receiver end and the UPD value at the satellite end, this embodiment introduces an additional reference condition for constraint, and the reference condition is expressed as:

[0098] ;

[0099] In some embodiments, the measuring stations are selected in sequence according to the number of observed satellites, and the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites are calculated by iterative calculation using the phase deviation whole-network solution method and the fractional cycle parts of the ultra-wide lane ambiguity, wide lane ambiguity, and narrow lane ambiguity, including:

[0100] In some embodiments, since the solution of phase deviation depends on the rounding of ambiguity, and the ambiguity needs to eliminate the influence of phase deviation to have integer characteristics, the above-mentioned phase deviation processing requires multiple iterations to complete the phase deviation separation between the receiver and the satellite.

[0101] Step 3.1: Set the UPD value at the receiver end of the station with the largest number of observed satellites to 0, and subtract the UPD value at the receiver end from the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity, and narrow lane ambiguity to obtain the initial UPD value at the satellite end;

[0102] Step 3.2: Select the remaining stations in descending order according to the number of observed satellites, and repeat the following steps until all stations are processed:

[0103] Step 3.2.1: For each known satellite at each station:

[0104] Subtracting the satellite-side UPD value from the fractional cycle parts of the ultra-wide lane ambiguity, the wide lane ambiguity, and the narrow lane ambiguity, and then taking the average value as the receiver-side UPD value;

[0105] In this embodiment, the UPD value at the receiver end is expressed as:

[0106] ;

[0107] In the formula, Indicates the UPD value at the receiver end, that is, The UPD value of each receiver, Indicates The total number of satellites that can be observed by a receiver, Indicates satellites, represents the floating point ambiguity, represents the integer ambiguity, Indicates the satellite UPD value, that is, The UPD value of the satellite.

[0108] Step 3.2.2: For each unknown satellite in each station:

[0109] The satellite-side UPD value of the unknown satellite is obtained by subtracting the UPD value at the receiver from the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

[0110] Step 3.3: performing weighted averaging on the satellite-side UPD values ​​of the same satellite obtained by each measuring station to obtain the satellite-side UPD value of the satellite;

[0111] In this embodiment, the satellite UPD value is expressed as:

[0112] ;

[0113] In the formula, Indicates the satellite UPD value, that is, UPD value of satellites It means that the The total number of receivers for satellites, Indicates Receivers, Indicates Satellite No. The UPD value is calculated at each receiver. Indicates Satellites No. The UPD value calculated at each receiver The corresponding weight.

[0114] Step 3.4: If the difference between the satellite-side UPD values ​​obtained in two consecutive iterations is less than a preset threshold, the loop is exited to obtain the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites.

[0115] In this embodiment, the difference between the satellite UPD values ​​obtained in two adjacent iterations is less than the preset threshold value, which is expressed as:

[0116] ;

[0117] In the formula, and Respectively represent Second and The difference in the satellite UPD values ​​obtained in the iterations is Indicates the preset threshold.

[0118] In some embodiments, the residual vector of the phase deviation is distributed on each satellite, wherein the residual vector of the phase deviation is expressed as:

[0119] ;

[0120] In the formula, The residual vector representing the phase deviation, Indicates the total number of receivers in the base station network (station and receiver have the same meaning, so I think this is a better way to express it). Represents the total number of all visible satellites in the base station network, Indicates The receiver observes The phase deviation residual of each satellite is Indicates The receiver observes The floating point ambiguities for each satellite, Indicates The receiver observes The integer ambiguity of the satellites, express OK The identity matrix of the columns, represents the Kronecker product, express A column vector with 1 row and 1 column. express A column vector with 1 row and 1 column. express OK The identity matrix of the columns, represents the satellite-side UPD vector of all visible satellites in the base station network, represents the receiver-side UPD vector of all receivers in the base station network, Indicates transpose.

[0121] Step 4: Calculate the UPD precision factor based on the residual vector of the phase deviation.

[0122] In some embodiments, calculating the UPD precision factor according to the residual vector of the phase deviation includes:

[0123] Calculate the RMS of all elements in the residual vector of the phase deviation to obtain the UPD precision factor;

[0124] In this embodiment, the UPD precision factor is expressed as:

[0125] ;

[0126] In the formula, Indicates The UPD precision of the satellites is It means that the The total number of receivers for satellites, Indicates Receivers, Indicates The receiver observes The phase deviation residuals of the satellites.

[0127] Step 5: Use the UPD precision factor to update the user-side ambiguity variance-covariance matrix and fix the user-side ambiguity based on the LAMBDA algorithm.

[0128] In this embodiment, the ambiguity variance-covariance matrix of the user terminal is updated by using the UPD precision factor, wherein the updated ambiguity variance-covariance matrix is ​​expressed as:

[0129] ;

[0130] In the formula, represents the updated user-side ambiguity variance-covariance matrix, represents the ambiguity variance-covariance matrix of the user side, where represents the ambiguity of the user side, represents a diagonal matrix consisting of UPD diffs of precision, Indicates the total number of satellites that the receiver can observe.

[0131] In some embodiments, the ambiguity variance-covariance matrix of the user terminal is updated using the UPD precision factor, and the ambiguity of the user terminal is fixed based on the LAMBDA algorithm, including:

[0132] Step 5.1: Using the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity as ambiguities at the user end;

[0133] Step 5.2: De-correlate the ambiguity of the user terminal and the updated ambiguity variance-covariance matrix through a reversible integer transformation matrix to obtain an ambiguity vector and a transformed ambiguity variance-covariance matrix;

[0134] Step 5.3: performing ambiguity integer search and verification on the ambiguity vector and the converted ambiguity variance-covariance matrix to obtain an integer ambiguity solution;

[0135] Step 5.4: Fix the ambiguity at the user end according to the integer ambiguity solution.

[0136] In this embodiment, the ambiguity vector and the converted ambiguity variance-covariance matrix are respectively expressed as:

[0137] ;

[0138] In the formula, represents the ambiguity vector, represents the ambiguity of the user side, represents a reversible integer transformation matrix, represents the transformed ambiguity variance-covariance matrix, represents the ambiguity variance-covariance matrix of the user side, represents the transposed matrix of the reversible integer transformation matrix, Indicates transpose.

[0139] like Figure 2 The convergence speed calculation example shown in the figure shows the influence of whether to introduce the phase deviation precision factor on the convergence time of the PPP-AR fixed solution under different delay conditions, and compares the convergence time in the active and inactive periods of the ionosphere. Figure 2 It can be seen that the present invention accelerates the convergence speed under different environments and different product delays.

[0140] Example 3

[0141] Based on the same inventive concept as other embodiments, this embodiment introduces a computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed by a processor, the steps of the method in the above-mentioned embodiment 1 or 2 are implemented.

[0142] Example 4

[0143] Based on the same inventive concept as other embodiments, this embodiment introduces a computer program product, including computer instructions, which implement the steps of the method in the above-mentioned embodiment 1 or 2 when executed by a processor.

[0144] In summary, the present invention introduces the phase deviation precision factor and combines the phase observation value of the GNSS reference station to fix the ambiguity of precise single-point positioning, so as to accurately calculate and update the ambiguity variance-covariance matrix of the user side, which not only improves the accuracy of ambiguity fixation, but also enhances the robustness in complex environments and real-time data delays, thereby significantly improving the overall performance and reliability of precise single-point positioning.

[0145] The present invention selects measuring stations in sequence according to the number of observed satellites, and uses the phase deviation whole-network solution method in combination with the fractional cycle part of wide-lane and narrow-lane ambiguities for iterative calculation, so as to accurately solve the receiver-side UPD values ​​of all receivers and the satellite-side UPD values ​​of all visible satellites. It not only takes into account the influence of the number of observed satellites and gives priority to measuring stations with rich observation data, but also continuously updates the receiver-side UPD values ​​and the satellite-side UPD values ​​in a step-by-step approximation manner until the convergence condition is reached, thereby significantly improving the accuracy and reliability of the estimation of the receiver-side UPD values ​​and the satellite-side UPD values, providing a solid foundation for subsequent ambiguity fixation, thereby improving the accuracy and efficiency of precise point positioning.

[0146] The present invention updates the ambiguity variance-covariance matrix of the user end in combination with the UPD precision factor, so that the search efficiency and success rate of the LAMBDA algorithm in the ambiguity fixing process are greatly improved, thereby accelerating the convergence speed while ensuring the positioning accuracy.

[0147] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0148] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0149] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0151] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A method for fixing ambiguity of precise point positioning based on phase deviation precision factor, characterized in that: include: Get the GNSS base station phase observation value on the server side; Based on the phase observations of the GNSS reference station, the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity of the floating point ambiguity is calculated; The stations are selected in turn according to the number of observed satellites, and the UPD values ​​of all receivers in the reference station network and the UPD values ​​of all visible satellites are iteratively calculated by using the phase deviation whole network solution method and the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity, and the residual vector of the phase deviation is extracted; Calculate the UPD precision factor based on the residual vector of the phase deviation; The UPD precision factor is used to update the ambiguity variance-covariance matrix of the user end, and the ambiguity of the user end is fixed based on the LAMBDA algorithm.

2. The single point positioning ambiguity fixing method based on phase deviation precision factor according to claim 1 is characterized in that: Based on the phase observations of the GNSS reference station, the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity of the floating point ambiguity is calculated, including: estimating floating point ambiguities from the GNSS reference station phase observations based on a non-differenced non-combined observation model; The floating point ambiguity includes integer ambiguity, receiver-side and satellite-side phase deviations; Performing linear combination processing on the floating point ambiguities to transform them into ultra-wide lane ambiguities, wide lane ambiguities and narrow lane ambiguities; The ultra-wide lane ambiguity, the wide lane ambiguity and the narrow lane ambiguity are rounded off respectively to obtain the integer parts of the ultra-wide lane ambiguity, the wide lane ambiguity and the narrow lane ambiguity; The fractional parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity are obtained by subtracting the integer parts of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity from the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

3. The single point positioning ambiguity fixing method based on phase deviation precision factor according to claim 2 is characterized in that: The stations are selected in turn according to the number of observed satellites, and the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites are calculated iteratively using the phase deviation whole-network solution method and the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity, including: The UPD value at the receiver end of the station with the largest number of observed satellites is set to 0, and the UPD value at the receiver end is subtracted from the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity to obtain the initial UPD value at the satellite end; Select the remaining stations in descending order according to the number of observed satellites, and repeat the following steps until all stations have been processed: For each known satellite at each station: Subtracting the satellite-side UPD value from the fractional cycle parts of the ultra-wide lane ambiguity, the wide lane ambiguity, and the narrow lane ambiguity, and then taking the average value as the receiver-side UPD value; For each unknown satellite at each station: The satellite-side UPD value of the unknown satellite is obtained by subtracting the UPD value at the receiver from the fractional cycle part of the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity. The satellite-side UPD values ​​of the same satellite obtained by each measuring station are weighted averaged to obtain the satellite-side UPD value of the satellite; If the difference between the satellite-side UPD values ​​obtained in two adjacent iterations is less than a preset threshold, the loop is exited to obtain the receiver-side UPD values ​​of all receivers in the reference station network and the satellite-side UPD values ​​of all visible satellites.

4. The single point positioning ambiguity fixing method based on phase deviation precision factor according to claim 3 is characterized in that: The UPD value at the receiver end is expressed as: ； In the formula, Indicates the UPD value at the receiver end, that is, The UPD value of each receiver, Indicates The total number of satellites that can be observed by a receiver, Indicates satellites, represents the floating point ambiguity, represents the integer ambiguity, Indicates the satellite UPD value, that is, The UPD value of the satellite.

5. The single point positioning ambiguity fixing method based on phase deviation precision factor according to claim 3 is characterized in that: The satellite UPD value is expressed as: ； In the formula, Indicates the satellite UPD value, that is, UPD value of satellites It means that the The total number of receivers for satellites, Indicates Receivers, Indicates Satellite No. The UPD value is calculated at each receiver. Indicates Satellites No. The UPD value calculated at each receiver The corresponding weight.

6. The method for fixing the ambiguity of single-point positioning based on phase deviation precision factor according to claim 1, characterized in that: The residual vector of the phase deviation is distributed on each satellite, wherein the residual vector of the phase deviation is expressed as: ； In the formula, The residual vector representing the phase deviation, represents the total number of receivers in the base station network, Represents the total number of all visible satellites in the base station network, Indicates The receiver observes The phase deviation residual of each satellite is Indicates The receiver observes The floating point ambiguities of the satellites, Indicates The receiver observes The integer ambiguity of the satellites, express OK The identity matrix of the columns, represents the Kronecker product, express A column vector with 1 row and 1 column. express A column vector with 1 row and 1 column. express OK The identity matrix of the columns, represents the satellite-side UPD vector of all visible satellites in the base station network, represents the receiver-side UPD vector of all receivers in the base station network, Indicates transpose.

7. The single point positioning ambiguity fixing method based on phase deviation precision factor according to claim 1 is characterized in that: The UPD precision factor is calculated based on the residual vector of the phase deviation, including: Calculate the RMS of all elements in the residual vector of the phase deviation to obtain the UPD precision factor; Wherein, the UPD precision factor is expressed as: ； In the formula, Indicates The UPD precision of the satellites is It means that the The total number of receivers for satellites, Indicates Receivers, Indicates The receiver observes The phase deviation residuals of the satellites.

8. The method for fixing the ambiguity of single-point positioning based on phase deviation precision factor according to claim 2, characterized in that: The UPD precision factor is used to update the ambiguity variance-covariance matrix of the user end, wherein the updated ambiguity variance-covariance matrix is ​​expressed as: ； In the formula, represents the updated user-side ambiguity variance-covariance matrix, represents the ambiguity variance-covariance matrix of the user side, where represents the ambiguity of the user side, represents a diagonal matrix consisting of UPD diffs of precision, Indicates the total number of satellites that the receiver can observe.

9. The method for fixing the ambiguity of single-point positioning based on phase deviation precision factor according to claim 8, characterized in that: The UPD precision factor is used to update the user-side ambiguity variance-covariance matrix, and the ambiguity of the user-side is fixed based on the LAMBDA algorithm, including: Using the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity as ambiguities at the user end; De-correlating the ambiguity of the user terminal and the updated ambiguity variance-covariance matrix through a reversible integer transformation matrix to obtain an ambiguity vector and a transformed ambiguity variance-covariance matrix; Performing ambiguity integer search and verification on the ambiguity vector and the converted ambiguity variance-covariance matrix to obtain integer ambiguity solutions; The ambiguity at the user end is fixed according to the integer ambiguity solution.

10. The method for fixing the ambiguity of single-point positioning based on phase deviation precision factor according to claim 9, characterized in that: The ambiguity vector and the converted ambiguity variance-covariance matrix are respectively expressed as: ； In the formula, represents the ambiguity vector, represents the ambiguity of the user side, represents a reversible integer transformation matrix, represents the transformed ambiguity variance-covariance matrix, represents the ambiguity variance-covariance matrix of the user side, represents the transposed matrix of the reversible integer transformation matrix, Indicates transpose.

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