GNSS (Global Navigation Satellite System) multi-frequency multi-mode precise single-point positioning integer ambiguity partial fixing method

Abstract

The invention provides a GNSS (Global Navigation Satellite System) multi-frequency multi-mode precise point positioning integer ambiguity part fixing method, which comprises the following steps of: carrying out multi-frequency multi-mode PPP (Point-to-Point Protocol) floating point solution positioning to obtain an N1 ambiguity variance and an L1 phase observation value residual error; determining a reference satellite according to the signal-to-noise ratio, the obtained N1 ambiguity variance and the L1 phase observation value residual error; obtaining inter-satellite single-difference ultra-wide lane ambiguity and an inter-satellite single-difference ultra-wide lane ambiguity residual error based on the determined reference satellite; screening the inter-satellite single-difference ultra-wide lane ambiguity by using the inter-satellite single-difference ultra-wide lane ambiguity residual error; the ambiguity parameter is updated by using the screened inter-satellite single-difference ultra-wide lane ambiguity; and carrying out secondary updating on the ambiguity parameter by utilizing the screened inter-satellite single-difference wide-lane ambiguity to obtain an inter-satellite single-difference wide-lane ambiguity fixed solution, and carrying out partial fixation by utilizing the inter-satellite single-difference narrow-lane ambiguity after the inter-satellite single-difference wide-lane ambiguity is fixed to obtain the fixed solution of the fixed inter-satellite single-difference narrow-lane ambiguity.

Description

Technical Field

[0001] The present invention relates to GNSS integer ambiguity determination technology, and particularly to GNSS multi-frequency multi-mode precise point positioning (PPP) integer ambiguity fixing technology. Background Art

[0002] To achieve integer ambiguity fixing (AR) for GNSS multi-frequency multi-system (multi-mode) precise point positioning (PPP), generally according to the difficulty level, the inter-satellite single difference (SD) ultra-wide lane (EWL) ambiguity, the inter-satellite single difference wide lane (WL) ambiguity, and the inter-satellite single difference narrow lane (NL) ambiguity are gradually fixed, so as to achieve the purpose of integer ambiguity fixing in non-differential non-combination PPP positioning.

[0003] However, when performing multi-system combined PPP positioning, there are problems such as easy failure of full ambiguity fixing and low accuracy of narrow lane ambiguity fixing. Therefore, it is necessary to improve the methods of the existing technology. Summary of the Invention

[0004] The present invention is made in view of the above situation of the existing technology, to solve one or more problems existing in the existing technology, and at least provide a beneficial option.

[0005] According to one aspect of the present invention, there is provided a method for partially fixing integer ambiguities in GNSS multi-frequency multi-mode precise point positioning (PPP). The method includes the following steps: performing multi-frequency multi-mode PPP float solution positioning to obtain N1 ambiguity variance and L1 phase observation residuals; calculating satellite scores K based on the signal-to-noise ratio, the obtained N1 ambiguity variance, and the L1 phase observation residuals, so as to determine reference satellites; obtaining inter-satellite single difference ultra-wide lane ambiguities and inter-satellite single difference ultra-wide lane ambiguity residuals based on the determined reference satellites; screening the inter-satellite single difference ultra-wide lane ambiguities using the inter-satellite single difference ultra-wide lane ambiguity residuals; updating the ambiguity parameters using the screened inter-satellite single difference ultra-wide lane ambiguities; performing secondary update on the ambiguity parameters using the screened inter-satellite single difference wide lane ambiguities to obtain a fixed solution of the inter-satellite single difference wide lane ambiguities, and partially fixing the inter-satellite single difference narrow lane ambiguities using the inter-satellite single difference narrow lane ambiguities after the inter-satellite single difference wide lane ambiguities are fixed to obtain a fixed solution of the fixed inter-satellite single difference narrow lane ambiguities.

[0006] According to another aspect of the present invention, there is provided a method for partially fixing integer ambiguities in GNSS multi-frequency and multi-mode PPP. The method includes steps for fixing narrow-lane ambiguities. The steps for fixing narrow-lane ambiguities include: determining inter-satellite single-difference narrow-lane ambiguities and performing full ambiguity fixing on them; judging whether the full ambiguity fixing is successful; if it is judged that the full ambiguity fixing is successful, using the obtained fixed inter-satellite single-difference narrow-lane ambiguities to obtain an inter-satellite single-difference narrow-lane ambiguity fixed solution; and if it is judged that the full ambiguity fixing is not successful, dividing all inter-satellite single-difference narrow-lane ambiguity parameters of all satellites into two parts: ambiguities that are easy to fix and ambiguities that are difficult to fix, and performing partial ambiguity fixing based on the ambiguities that are easy to fix and the ambiguities that are difficult to fix. Among them, the ambiguities that are difficult to fix include satellites with inter-satellite single-difference ultra-wide-lane and inter-satellite single-difference wide-lane ambiguity residual tests exceeding the limit.

[0007] The above two aspects of the present invention can both improve the accuracy of parameters and accelerate the process of fixing wide-lane and narrow-lane ambiguities. These two aspects can be used together or separately. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present invention can be better understood in conjunction with the accompanying drawings. The drawings are schematic and are not intended to limit the scope of protection of the present invention.

[0009] Figure 1 FIG. shows a schematic flowchart of a method for partially fixing integer ambiguities in GNSS multi-frequency and multi-mode precise point positioning (PPP) according to an embodiment of the present invention.

[0010] Figure 2 FIG. shows a schematic flowchart of a method for fixing narrow-lane ambiguities according to an embodiment of the present invention.

[0011] Figure 3 FIG. shows a schematic flowchart of a method for performing partial ambiguity fixing based on ambiguities that are easy to fix and ambiguities that are difficult to fix according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] The following will describe the specific embodiments of the present invention in conjunction with the accompanying drawings. These descriptions are merely exemplary and are intended to enable those skilled in the art to clearly understand the technical solutions of the present invention. In these descriptions, there is no description of components or steps that are essential for commercial use or practice of the embodiments of the present invention in reality but are not helpful for understanding the present invention, and these descriptions are not intended to limit the scope of protection of the present invention.

[0013] In the process of researching the prior art, the inventors of the present invention found that the full ambiguity fixation in GNSS multi-system combined precise point positioning (PPP) is prone to failure because as the number of ambiguities increases, the dimension of the ambiguity search space increases significantly, and the correlation between ambiguities cannot be completely eliminated by relevant algorithms. At this time, a partial ambiguity fixation method is required to use better ambiguity parameters for fixation.

[0014] Furthermore, the inventors of the present invention found the following problems in the prior art. The commonly used partial ambiguity fixation methods include the elevation angle sorting method and the ambiguity variance sorting method, both of which select ambiguities using a single factor index. However, it is difficult to obtain the optimal ambiguity parameters by selecting ambiguities using a single factor index. Under normal circumstances, the higher the satellite elevation angle, the higher the corresponding signal-to-noise ratio (SNR), the smaller the influence of the observation value on the multipath effect and the atmospheric delay term error, and the higher the accuracy of the estimated ambiguity parameters. However, in the case of relatively poor observation conditions, there is no positive correlation between the satellite elevation angle, the signal-to-noise ratio, and the quality of the observation data. The signal-to-noise ratio reflects the ratio between the signal power and the noise level and can better reflect the level of the observation quality. If a higher elevation angle satellite with poor observation quality participates in the positioning solution calculation, it is very likely to contaminate other normal observation values and reduce the positioning accuracy of the overall floating solution of the ambiguity.

[0015] In addition, the phase observation value residuals after PPP filtering can usually well reflect the quality of the phase observation values and can also be used to measure the quality of the ambiguity estimation. Therefore, in order to screen ambiguities by integrating multiple accuracy factor indicators and make full use of the ambiguity parameters of each satellite, the inventors of the present invention proposed the following partial ambiguity fixation method. It should be understood that the method of the present invention is not intended to solve all the problems existing in the discovered prior art.

[0016] Figure 1 Fig. shows a schematic flow of a method for partially fixing integer ambiguities in GNSS multi-frequency multi-mode precise point positioning (PPP) according to an embodiment of the present invention.

[0017] As Figure 1 shown, according to a method for partially fixing integer ambiguities in GNSS multi-frequency multi-mode PPP according to an embodiment of the present invention, first, in step S100, a floating solution calculation of multi-frequency multi-system (multi-mode) PPP positioning is performed to obtain N1 ambiguity variances (N1_amb_var) and L1 phase observation value residuals (L1_res). The original frequency floating ambiguities can be calculated first, and then the N1 ambiguity variances (N1_amb_var) and L1 phase observation value residuals (L1_res) can be obtained based on the original floating ambiguities.

[0018] According to an embodiment, first, the tropospheric delay dry component, antenna phase center deviation, phase wrapping, relativistic effect, tide and other error sources are corrected by using modeled error compensation. Then, the following equations (1) and (2) are used as the observation equations for pseudorange observations and carrier phase observations:

[0019]

[0020] Where: are the pseudorange observation and the carrier phase observation respectively; the superscript s is the satellite PRN number, and Q is the satellite system; the subscript r is the receiver end; the subscript j is the frequency number; is the wavelength corresponding to the specified frequency j; is the geometric distance between the satellite end s and the receiver end r; c is the speed of light in vacuum; dt s,Q are the receiver clock error and the satellite clock error respectively; is the wet mapping function of tropospheric delay related to the satellite elevation angle; ZWD r is the wet component of tropospheric delay in the zenith direction; is the amplification factor of ionospheric delay related to frequency; is the first frequency corresponding ionospheric delay; is the integer ambiguity corresponding to the carrier phase observation; are the pseudorange hardware delays corresponding to the receiver end and the satellite end respectively; are the carrier phase hardware delays corresponding to the receiver end and the satellite end respectively; are the measurement noises of the pseudorange observation and the carrier phase observation including the unmodeled residual errors respectively.

[0021] Let there be variables:

[0022]

[0023] where the subscripts i and j are the i-th frequency and the j-th frequency respectively; and are the differential code biases at the satellite end and the receiver end respectively; and are the differential time-varying phase biases at the satellite end and the receiver end respectively; α ij and β ij are the ionosphere-free combination coefficients respectively; and are the pseudorange hardware delays at the satellite end and the receiver end of the ionosphere-free combination respectively; and are the time-varying parts of the carrier phase hardware delays at the satellite end and the receiver end of the ionosphere-free combination respectively.

[0024] Since precise satellite clock offset products are usually obtained based on the dual-frequency ionosphere-free combination, the precise clock offset contains the time-varying parts of the pseudorange hardware delay and phase hardware delay of the ionosphere-free combination, as shown in Equation (4):

[0025]

[0026] If we set:

[0027]

[0028] And linearize Equations (1) - (2), construct the corresponding function model, and after arrangement, we get Equations (6) and (7).

[0029]

[0030] Where: is the difference between the pseudorange observation value for correcting the differential code bias at the satellite end and the initial value of the satellite-to-ground distance ; is the difference between the carrier phase observation value and the initial value of the satellite-to-ground distance ; is the unit cosine of the direction from the satellite end to the Beidou receiver end; V X is the correction of the three-dimensional coordinates of the station.

[0031] The satellite elevation angle weight determination method can be adopted to establish the corresponding stochastic model as:

[0032]

[0033] Where, a is the additive constant, b is the multiplicative constant, a and b are not equal and independent of each other; E is the satellite elevation angle, with the unit of radian. Using the function models of Equations (6) - (7) and the stochastic model of Equation (8), the mathematical model of GNSS multi-frequency multi-mode non-differential non-combination PPP positioning can be formed. Using the extended Kalman filter (EKF) to optimally estimate the state parameters involved in this model, such as the three-dimensional coordinate parameters of the station, the GNSS receiver clock offset, the wet component of the zenith tropospheric delay (ZWD), the ionospheric slant delay in the satellite-to-station direction and the original frequency floating-point ambiguity etc., to obtain the floating-point solution of GNSS multi-frequency multi-mode PPP positioning and its corresponding variance-covariance matrix, and the variance of the N1 ambiguity is included in this variance-covariance matrix.

[0034] Alternatively, the calculation of the floating-point solution of GNSS multi-frequency multi-mode PPP positioning can be carried out by methods currently known to those skilled in the art or methods known in the future.

[0035] Then, according to the original frequency floating-point ambiguity Obtain the N1 ambiguity variance (N1_amb_var). For the L1 phase observation residual (L1_res), it is obtained by subtracting the calculated value from the observed value, that is

[0036] Next, in step S200, determine the reference satellite according to the obtained N1 ambiguity variance (N1_amb_var) and L1 phase observation residual (L1_res).

[0037] According to one embodiment, the observed satellites are sorted using the signal-to-noise ratio (SNR), the filtered N1 ambiguity variance (N1_amb_var), and the L1 phase observation residual (L1_res). The signal-to-noise ratio (SNR) is usually given in the RINEX observation file (i.e., the O file). According to one embodiment of the present invention, the SNR, N1_amb_var, and L1_res are normalized to convert them into dimensionless quantities. First, the maximum-minimum normalization can be used. Specifically, the three factors of SNR, N1_amb_var, and L1_res can be sorted from largest to smallest respectively to determine the maximum value X MAX and X MIN , and then the corresponding normalized values of each factor can be determined using the following formula, where X is the current value of SNR, N1_amb_var, and L1_res.

[0038]

[0039] After normalization, the values of each factor are between 0 and 1, where 0 is the worst and 1 is the best. The corresponding are respectively denoted as O SNR 、O var 、O res , where X is the current value of SNR, N1_var, and L1_res, and the subscripts MAX and MIN respectively represent the maximum and minimum values, are the normalized values of each factor.

[0040] Then, calculate the satellite score K of each observed satellite.

[0041] According to one embodiment, K = W1O SNR + W2O var + W3O res , where W 1、 W 2、 W3 are weighting factors. Preferably, the sum of W1, W2, and W3 is set to 1.

[0042] According to one embodiment, each weighting factor W1, W2, and W3 can be calculated as follows.

[0043] First calculate the weight ratio of each satellite factor In the formula, the superscript i represents the satellite. After obtaining the weight ratio, the information entropy of each factor is calculated (Formula 10). The normalized difference coefficient d = 1-E is used to reflect the degree of differentiation of each factor. Then, the weight of each factor is calculated. Among them, k = 1, 2, 3 are the ordinal numbers of each factor.

[0044] According to one embodiment, the satellite score K may be calculated by using empirically determined fixed values of W1, W2, and W3.

[0045] Then, the observed satellites are sorted according to the K value, and the satellite with the largest K value is selected as the reference satellite.

[0046]

[0047] According to an embodiment of the present invention, weights can be adaptively adjusted based on the environment. This approach eliminates the magnitude of the three factor data after normalization, allowing comparison and weighting of these factor indicators. Finally, the observed satellites are sorted according to their K values, and the satellite with the largest K value is selected as the reference satellite. By calculating the K value in this way and determining the reference satellite based on it, observation quality can be further improved.

[0048] Next, in step S300, based on the determined reference satellite, the ultra-wide lane (EWL) ambiguity of the inter-satellite single difference (SD) (ie, SD EWL ambiguity) is obtained.

[0049] According to one embodiment, to achieve PPP ambiguity fixation, first, the phase deviation product is used to eliminate the influence of satellite hardware delay. The ambiguity parameter after eliminating the satellite hardware delay is:

[0050]

[0051] Where, represents the ambiguity parameter after correcting the phase delay, and are the hardware delays of the satellite and receiver, respectively. Secondly, to eliminate the impact of hardware delays on the receiver side, a reference satellite is selected to calculate the inter-satellite single-difference (SD) ambiguity. The ambiguity parameters that eliminate the phase delays between the satellite and receiver sides theoretically have integer characteristics, allowing the ambiguity parameters to be fixed. Using the ambiguity parameters after eliminating the phase deviations between the satellite and receiver sides, a series of ultra-wide lane (EWL) ambiguities are formed for different system frequency characteristics. For example, for the GPS system, the Galileo system, and the BDS system, a series of ultra-wide lane (EWL) ambiguities are expressed as follows:

[0052]

[0053] Among them, represents the extra-wide lane (EWL) ambiguity. Then, the single-difference extra-wide lane ambiguity (SD EWL) between each non-reference satellite and the reference satellite is calculated as

[0054] Set the fractional part of the SD EWL ambiguity as the SD EWL ambiguity residual.

[0055] Then, in step S400, the SD EWL ambiguity is screened using the SD EWL ambiguity residual.

[0056] According to one implementation, the SD EWL ambiguity residual corresponding to the SD EWL ambiguity is compared with a first predetermined threshold, and the SD EWL ambiguity with an SD EWL ambiguity residual less than the first predetermined threshold is selected.

[0057] Specifically, the first predetermined threshold can be 1 / 4 = 0.25 cycle. That is, the SD EWL ambiguity is screened under the following conditions:

[0058] SD EWL ambiguity residual < 0.25 cycle. Cycle represents a week and is the unit of the ambiguity residual.

[0059] According to another implementation, the satellite elevation cut-off angle is set to 15°. The elevation cut-off angle means that satellites below this angle are excluded and do not participate in the positioning solution. Exclusion is performed during satellite selection, and the satellites participating in all subsequent steps are those with an elevation angle greater than the cut-off angle.

[0060] The above two conditions can be used simultaneously for screening the SD EWL ambiguity. That is, the ambiguity of satellites with an elevation angle greater than 15° and an SD EWL ambiguity residual < 0.25 cycle is used.

[0061] According to one implementation, for the SD EWL ambiguity, since its wavelength is long and it is less affected by observation noise, it is directly fixed as an integer using methods such as LAMBDA, and the preset value of the Ratio test is set to 1 (equivalent to not performing the Ratio test).

[0062] Then, in step S500, the state parameters (including the ambiguity parameter) are updated using the screened SD EWL ambiguity.

[0063] According to an embodiment of the present invention, parameters such as the three-dimensional position of the measuring station, clock error, troposphere, ionosphere, and ambiguity are updated. After the SD EWL ambiguity is fixed as an integer, the SD EWL ambiguity can be regarded as a true value, and this ambiguity can be used as virtual observation information to constrain the floating-point ambiguity parameter, reducing the correlation between the ambiguity parameter and other state parameters to improve the accuracy of the floating-point ambiguity parameter. Therefore, the SD EWL ambiguity parameters of all frequency combinations are jointly used as virtual observation information to constrain the floating-point ambiguity parameter, and the fixed SD EWL ambiguity constraint equation is:

[0064]

[0065] In the formula, is the fixed SD EWL ambiguity, and the subscript j represents the frequency (j = 3, 4, 5); is the residual of the SDEWL ambiguity. After constraining the floating-point ambiguity parameter with the fixed SD EWL ambiguity, the accuracy of the floating-point parameter can be further improved, accelerating the subsequent wide-lane and narrow-lane ambiguity fixing processes.

[0066] Those skilled in the art can understand that in the above process, using the fixed SD EWL ambiguity to constrain the floating-point ambiguity parameter completes the update of the ambiguity parameter.

[0067] According to the embodiment of the present invention, a more suitable reference satellite can be better selected, so that the ambiguity parameter after inter-satellite single difference is more accurate. According to the embodiment of the present invention, the filtered SD EWL ambiguity is further used for fixing, and the floating-point ambiguity parameter is constrained by the fixed SD EWL ambiguity, so that the fixed solution of the inter-satellite single difference narrow-lane ambiguity obtained later will be more accurate.

[0068] According to an embodiment, as Figure 1 shown, the method of the present invention may further include step S600 of performing a secondary update on the state parameters (including the ambiguity parameter) using the inter-satellite single difference wide-lane ambiguity (SD WL).

[0069] According to an embodiment, first, the floating-point ambiguity parameters constrained by the SD EWL ambiguity are combined into the WL ambiguity:

[0070]

[0071] In the formula, represents the wide-lane ambiguity. Then, the SDWL floating-point ambiguity is calculated by taking the difference between each non-reference satellite and the reference satellite. The fractional part of the SD WL floating-point ambiguity is regarded as the SD WL ambiguity residual.

[0072] Then, the SD WL ambiguity residual corresponding to the SD WL ambiguity is compared with a second predetermined threshold, and the SD WL ambiguity whose SD WL ambiguity residual is smaller than the second predetermined threshold is selected.

[0073] According to one embodiment, the second predetermined threshold may be 0.15 cycles. That is, the SD WL ambiguity is screened according to the following conditions:

[0074] SD WL ambiguity residual <0.15cycle.

[0075] According to one embodiment, the first predetermined threshold is generally greater than the second predetermined threshold. Setting the threshold in this way can better avoid the influence of ambiguity of poor observation quality on the fixed solution.

[0076] According to another embodiment, the satellite cutoff elevation angle is set to 15°. Satellites below this elevation angle are excluded from participating in the positioning solution. This exclusion occurs during satellite selection, and satellites participating in all subsequent steps are those with elevation angles greater than the cutoff elevation angle.

[0077] The above two conditions can be used simultaneously to filter the SD WL ambiguities, that is, the ambiguities of satellites with elevation angles greater than 15° and SD WL ambiguity residuals less than 0.15cycle are used.

[0078] According to one embodiment, for the SD WL ambiguity, since its wavelength is long and is less affected by observation noise, it is directly fixed to an integer using methods such as LAMBDA, and the preset value of the Ratio test is set to 1 (equivalent to not performing a Ratio test).

[0079] Finally, the state parameters (including ambiguity parameters) are updated and calculated using the filtered fixed SD WL ambiguity.

[0080] According to one embodiment of the present invention, the three-dimensional position, clock error, troposphere, ionosphere and ambiguity parameters of the measuring station are updated and calculated.

[0081] According to one embodiment, the fixed SD WL ambiguity constraint equation is:

[0082]

[0083] Where, is the fixed SD WL ambiguity; is the residual of the SD WL ambiguity.

[0084] After constraining the floating-point ambiguity parameters with fixed SD WL ambiguities, the accuracy of the floating-point parameters can be further improved, and the subsequent wide-lane and narrow-lane ambiguity fixing process can be accelerated.

[0085] Those skilled in the art can understand that in the above process, by using fixed SD WL ambiguity to constrain the floating-point ambiguity parameter, the update of the ambiguity parameter is completed.

[0086] By using the above method, since the ambiguity parameter is well updated, the accuracy of fixing the narrow-lane ambiguity can be improved.

[0087] After updating the ambiguity parameter by using the screened inter-satellite single-difference ultra-wide-lane ambiguity and inter-satellite single-difference wide-lane ambiguity, the fixed solution of the inter-satellite single-difference wide-lane ambiguity is obtained, and partial fixing is performed by using the inter-satellite single-difference narrow-lane ambiguity after fixing the inter-satellite single-difference wide-lane ambiguity to obtain the fixed solution of the fixed inter-satellite single-difference narrow-lane ambiguity. It can be carried out by using various methods known currently and in the future.

[0088] In addition, the inventor also found a method that can be used alone or together with the above method to improve the accuracy of fixing the narrow-lane ambiguity.

[0089] Figure 2 The schematic flowchart of a method for fixing the narrow-lane ambiguity according to an embodiment of the present invention is shown.

[0090] As Figure 2 shown, according to another embodiment of the present invention, first in step S700, the inter-satellite single-difference narrow-lane ambiguity (SD NL) is determined and fully fixed for it.

[0091] This step can be carried out after step S600 of Figure 1 , that is, by using the updated ambiguity parameter, the SD NL ambiguity is determined and fully fixed for it. However, those skilled in the art should understand that this step can be carried out by using any existing and future-known technologies. Those skilled in the art can use any existing and future-known technologies to meet various physical examinations required for determining the SD NL ambiguity and fully fixing it. For example, various required parameters and pre-calculations, etc.

[0092] According to one embodiment, after using the fixed SD WL ambiguity constraint parameter, the inter-satellite single-difference (SD) first frequency (N1) and SD second frequency (N2) ambiguities are combined to form the inter-satellite single-difference ionosphere-free (SD IF) ambiguity, and then the inter-satellite single-difference narrow-lane (SD NL) ambiguity is derived. The combined SD IF ambiguity and the derived SD NL ambiguity are:

[0093]

[0094] For the exported SD NL ambiguities, all the SD NL ambiguities are used for full ambiguity fixing, i.e., determining the integer solution.

[0095] According to one embodiment, all the SD NL ambiguities are input into the LAMBDA algorithm to search for the integer solution.

[0096] Then, in step S800, it is judged whether the full ambiguity fixing is successful. According to one embodiment, the Ratio test threshold can be set to 2.0. If Ratio ≥ 2.0, it is considered that the full ambiguity fixing is successful. The Ratio value is a ratio obtained by calculating the residuals of all candidate ambiguity combinations in the LAMBDA algorithm for ambiguity fixing and comparing the residuals of the sub-optimal and optimal ambiguity combinations.

[0097] If it is judged in step S800 that the full ambiguity fixing is successful, then in step S900, using the obtained fixed SD NL ambiguities, the fixed solution of the SD NL ambiguities is obtained. According to one embodiment, the fixed SD NL ambiguities are taken as virtual observations and brought into the Extended Kalman Filter (EKF) to update the SD NL ambiguity fixing parameters, so as to update the three-dimensional position of the station, clock error, troposphere, ionosphere, and ambiguity parameters, and finally obtain the fixed solution of the SD NL ambiguities.

[0098] If it is judged in step S800 that the full ambiguity fixing is not successful (i.e., Ratio < 2.0), then in step S1000, all the SD NL ambiguity parameters of all satellites are divided into two parts: ambiguities that are easy to fix and ambiguities that are difficult to fix, for screening the SD NL ambiguities. That is, N = [N easy N hard , where N easy is the subset of ambiguities that are easy to fix, and N hard is the subset of ambiguities that are difficult to fix. Among them, N hard includes satellites with SD WL and SD NL ambiguity residual tests exceeding the limit.

[0099] According to one embodiment, an ambiguity residual threshold is used to determine these two ambiguity subsets. Satellites with SD WL ambiguity residuals > 0.15 cycle and satellites with SD NL ambiguity residuals > 0.15 cycle are classified into the subset of ambiguities that are difficult to fix N hard , and the remaining satellites are classified into the subset of ambiguities that are easy to fix N easy .

[0100] According to one embodiment, satellites with SD WL ambiguity residuals > 0.15 cycle, satellites with SD NL ambiguity residuals > 0.15 cycle, and satellites with K < 0.4 are determined as satellites with SD WL and SD NL ambiguity residual tests exceeding the limit and are classified into the N hard ambiguity subset, and the ambiguities of the remaining satellites are classified into the N easy ambiguity subset. The SD NL ambiguity residual is the difference between the fixed SD NL ambiguity and the unfixed SD NL ambiguity. Setting the coefficient 0.15 can avoid the influence of ambiguity parameters with poor accuracy on the fixing performance. Setting K < 0.4 is to select satellites with relatively good observation quality and relatively easy ambiguity fixing.

[0101] Then, in step S1100, partial ambiguity fixing is performed according to the easily fixed ambiguities and the difficult-to-fix ambiguities.

[0102] Figure 3 FIG. shows a schematic flowchart of a method for partial ambiguity fixing according to easily fixed ambiguities and difficult-to-fix ambiguities according to an embodiment of the present invention.

[0103] As Figure 3 shown, according to one embodiment, first, if it is determined in step S1010 that N easy > 4 (that is, the SD NL ambiguities of more than four satellites are included in the Neasy subset), then in step S1020, ambiguity fixing is performed on N easy . This can be done, for example, by inputting the ambiguity into the LAMBDA algorithm mentioned above. If the fixing fails (S1030, no), then in step S1040, according to the K value, the number of N easy is reduced. According to one embodiment, the satellites are excluded in ascending order of the K value, and the excluded satellites are added to the N hard ambiguity subset. That is, after excluding the satellite with the smallest K value, then return to step S1010. When N[[ID=2s]] easy is still greater than 4, in S1020, ambiguity fixing is performed on N easy again. Excluding means deleting the last data in the N easy set, and one is excluded each time.

[0104] According to one embodiment, satellites with K < 0.4 in the N easy subset are classified into N hard , so that satellites with relatively good observation quality and relatively easy ambiguity fixing can be selected. If the fixing in step S1020 fails, then from N easyIn the subset, the ambiguities are eliminated in ascending order according to the K value (where K ≥ 0.4 at this time) and the ambiguities are fixed. Each time, one satellite is eliminated, and the eliminated satellite is included in N hard subset until N easy the number of satellites is less than 4.

[0105] If N easy ≤ 4, that is, if the judgment in step S1010 is negative, then in step S1050, the K value limit is reduced, and N easy and N hard (for example, each time it is reduced by 0.2),

[0106] and it is judged in step S1060 whether N easy is greater than 4. If it is greater than 4, then return to step S1020. If it is not greater than 4, then the fixed solution corresponding to the SD WL ambiguity is output in step S1070.

[0107] If in step S1030, N easy is fixed successfully, then in step S1080, the fixed solution corresponding to the inter-satellite single-difference narrow lane (SD NL) is obtained. This can be completed, for example, by updating the parameters. Such a technical solution can improve the accuracy of the SD NL ambiguity again. N easy Fixing successfully means that the SD NL ambiguity is considered fixed successfully.

[0108] In steps S1070 and S1080, the satellites included in N hard do not participate in the parameter update process temporarily.

[0109] According to another embodiment, it may further include the step of updating the ambiguity parameters by using N hard

[0110] According to one embodiment, after updating the ambiguity parameters by using N easy N hard. is updated and the N hard ambiguity subset is fixed. Among them, satellites with SD L1_res < 0.15 cycle and elevation angle > 15° are selected. If N hard > 4, then partial ambiguity fixing is performed on N hard If N hard is fixed successfully, then the state parameters (including position parameters) are updated again.

[0111] Updating N hard is to use the fixed N easy as virtual observations and bring them into the extended Kalman (EKF) filter for parameter update as described above.

[0112] ​Using this method for partial ambiguity ensures both the ambiguity fixation rate and the number of fixed ambiguities.

[0113] Those skilled in the art can easily understand that the method of the present invention may also include other steps. These steps described above can also be streamlined and combined.

[0114] The labels of the units and steps in the present invention are only for convenience of description and do not represent the order of execution unless otherwise stated in the context.

[0115] Those skilled in the art should understand that the above steps can be implemented by software or dedicated hardware, such as field-programmable gate arrays, single-chip microcontrollers, or microchips, etc., or can also be implemented by a combination of software and hardware.

[0116] The present invention also provides an electronic device, including: a processor; a memory for storing executable instructions of the processor; wherein, the processor is configured to execute the instructions to implement the method of the present invention.

[0117] The present invention also relates to a computer software, which can implement the method of the present invention when executed by a computing device (such as a single-chip microcontroller, a computer, a CPU, etc.).

[0118] The present invention also relates to a computer software storage device, such as a hard disk, a floppy disk, a flash memory, etc., which stores the above computer software.

[0119] The description of the method or steps of the present invention can be used to understand the description of the units or devices, and the description of the units or devices can also be used to understand the method or steps of the present invention.

[0120] The above description is only illustrative and not a limitation on the protection scope of the present invention. Any changes and substitutions within the concept of the present invention are within the protection scope of the present invention.

Claims

1. A method for partially fixing integer ambiguities in GNSS multi-frequency and multi-mode precise point positioning, characterized in that, Including the following steps: Performing multi-frequency and multi-mode PPP floating-point solution positioning to obtain the N1 ambiguity variance and the L1 phase observation residual; Calculating the satellite score K based on the signal-to-noise ratio, the obtained N1 ambiguity variance, and the L1 phase observation residual, thereby determining the reference satellite; Based on the determined reference satellite, obtaining the inter-satellite single-difference ultra-wide lane ambiguity and the inter-satellite single-difference ultra-wide lane ambiguity residual; Using the inter-satellite single-difference ultra-wide lane ambiguity residual to screen the inter-satellite single-difference ultra-wide lane ambiguity; Updating the ambiguity parameters using the screened inter-satellite single-difference ultra-wide lane ambiguity and the inter-satellite single-difference wide lane ambiguity to obtain the fixed solution of the inter-satellite single-difference wide lane ambiguity, and Partially fixing the inter-satellite single-difference narrow lane ambiguity using the fixed inter-satellite single-difference narrow lane ambiguity after fixing the inter-satellite single-difference wide lane ambiguity to obtain the fixed solution of the fixed inter-satellite single-difference narrow lane ambiguity.

2. The method according to claim 1, wherein The steps for determining the reference satellite include: Sort the three factors of signal-to-noise ratio SNR, the obtained N1 ambiguity variance N1_amb_var, and the L1 phase observation residual L1_res from largest to smallest, and determine the maximum value X of each factor MAX and X MIN , and then use the following formula to determine the corresponding normalized value of each factor Where X is the current value of the signal-to-noise ratio SNR, the obtained N1 ambiguity variance N1_amb_var, and the L1 phase observation residual L1_res, Then, calculate the satellite score of each observation according to the following formula: K = W1O SNR + W2O var + W3O res Among them, W1, W2, and W3 are weight factors, and the sum of W1, W2, and W3 is 1; O SNR 、O var 、O res are the normalized values corresponding to the signal-to-noise ratio SNR, the obtained N1 ambiguity variance N1_amb_var, and the L1 phase observation residual L1_res, respectively Finally, sort each satellite according to the magnitude of the satellite score K value, and select the satellite with the largest K value as the reference satellite.

3. The method according to claim 2, characterized in that, The weight factors W1, W2, and W3 can be calculated as follows: First, calculate the weight ratio of each factor of the observed satellite: In the formula, the superscript i represents the observed satellite; Secondly, calculate the information entropy of each factor after obtaining the weight ratio as above: Finally, calculate the weight of each factor: Where the normalization difference coefficient is d = 1 - E; k = 1, 2, 3 are the ordinals of each factor.

4. The method according to claim 1, characterized in that Using the inter-satellite single-difference ultra-wide lane ambiguity residual to screen the inter-satellite single-difference ultra-wide lane ambiguity includes: Comparing the inter-satellite single-difference ultra-wide lane ambiguity residual corresponding to the inter-satellite single-difference ultra-wide lane ambiguity with the first predetermined threshold, and selecting the inter-satellite single-difference ultra-wide lane ambiguity with the inter-satellite single-difference ultra-wide lane ambiguity residual less than the first predetermined threshold. At the same time Set the satellite cut-off elevation angle to 15°, and exclude the satellites with the satellite elevation angle lower than this cut-off elevation angle.

5. The method according to claim 4, characterized in that, The steps for secondary updating of the ambiguity parameters using the fixed solution of the inter-satellite single-difference ultra-wide lane ambiguity include: Forming the inter-satellite single-difference wide lane ambiguity with the floating-point ambiguity parameters constrained by the inter-satellite single-difference ultra-wide lane ambiguity; Comparing the inter-satellite single-difference wide lane ambiguity residual corresponding to the inter-satellite single-difference wide lane ambiguity with the second predetermined threshold, and selecting the inter-satellite single-difference wide lane ambiguity with the inter-satellite single-difference wide lane ambiguity residual less than the second predetermined threshold; and Updating the ambiguity parameters using the screened inter-satellite single-difference wide lane ambiguity.

6. The method according to claim 5, characterized in that, The second predetermined threshold is less than the first predetermined threshold.

7. The method according to claim 1, characterized in that, The method further includes the step of fixing the narrow lane ambiguity, and the step of fixing the narrow lane ambiguity includes: Determining the inter-satellite single-difference narrow lane ambiguity and performing full ambiguity fixing on it; Judging whether the full ambiguity fixing is successful; If it is judged that the full ambiguity fixing is successful, then using the obtained fixed inter-satellite single-difference narrow lane ambiguity to obtain the fixed solution of the inter-satellite single-difference narrow lane ambiguity; If it is determined that the full ambiguity fixation is not successful, all the inter-satellite single-difference narrow-lane ambiguities of all satellites are divided into two parts: ambiguities that are easy to fix and ambiguities that are difficult to fix. Among them, the ambiguities that are difficult to fix include satellites with inter-satellite single-difference ultra-wide-lane and inter-satellite single-difference wide-lane ambiguity residual test exceeding the limit; and Partial ambiguity fixation is performed based on the ambiguities that are easy to fix and the ambiguities that are difficult to fix.

8. The method according to claim 7, wherein The two parts of the ambiguities that are easy to fix and the ambiguities that are difficult to fix are determined by comparing the satellite score K with the K value threshold; or Satellites with SD WL ambiguity residuals > 0.25 cycles and inter-satellite single-difference narrow-lane ambiguities corresponding to satellites with SD NL ambiguity residuals > 0.15 cycles are classified into the difficult-to-fix ambiguity subset N hard , and the remaining satellites are classified into the easy-to-fix ambiguity subset N easy .

9. The method according to claim 8, wherein Partial ambiguity fixation is performed as follows based on the ambiguities that are easy to fix and the ambiguities that are difficult to fix: A: Determine whether the ambiguity subset N that is easy to fix includes SD NL ambiguities of more than four satellites easy in it; B: If the easy-to-fix ambiguity subset N is determined in step A easy contains more than four SD NL ambiguities of satellites, then for the easy-to-fix ambiguity subset N easy perform ambiguity fixing; C: If the fixation in step B fails, according to the satellite score K value, reduce the subset Neasy of the ambiguities that are easy to fix, and return to step A; D: If it is determined in step A that the SD NL ambiguity in the easily-fixed ambiguity subset N easy does not include more than four satellite SD NL ambiguities, then reduce the threshold of the satellite score K value and re-partition the difficult-to-fix ambiguity subset N hard and the easily-fixed ambiguity subset N easy ; E: Determine whether the newly partitioned ambiguity subset N that is easy to fix easy includes inter-satellite single-difference narrow-lane ambiguities of more than four satellites. If so, return to step B. If not, output the inter-satellite single-difference wide-lane fixed solution; and F: If the fixation in step B is successful, obtain the fixed solution corresponding to the inter-satellite single-difference narrow-lane ambiguity.

10. The method according to claim 9, wherein In step C, according to the K value, reduce the ambiguity subset N that is easy to fix easy To exclude satellites in ascending order of the K value, exclude one satellite at a time, and add the excluded satellite to N hard Ambiguity subset In step B, it is determined whether the fixation is successful by judging whether the Ratio value is greater than 2.0; In step D, the threshold of the K value is reduced by 0.2 each time.

Images