A method for weighting observation values in navigation satellite precision data processing

Abstract

The present invention relates to the technical field of high-precision positioning and orbit determination for the Global Navigation Satellite System (GNSS), and specifically to a method for weighting observation values for precise data processing of navigation satellites. The method comprises the following steps: Step 1: constructing a GNSS precise data processing observation model; Step 2: weighting pseudorange observation values; Step 3: weighting phase observation values; and Step 4: repeating Steps 1-3 based on the weights for each satellite and epoch determined in Step 3, to calculate the final precise positioning and orbit determination result through iterative calculation. By weighting observation values on a satellite-by-satellite and epoch-by-epoch basis, satellite observation information can be fully utilized, avoiding the deletion of satellite observation values for entire arc segments due to poor observation quality during certain periods of time. The present invention creatively implements precise weighting of observation values on a satellite-by-epoch and epoch-by-epoch basis based on post-validation residuals of observation values, thereby improving the performance of precise GNSS positioning and orbit determination.

Description

Technical Field

[0001] The present invention relates to the technical field of high-precision positioning and orbit determination of a global navigation satellite system (GNSS), and in particular to an observation value weighting method for precise data processing of a navigation satellite. Background Art

[0002] Global navigation satellite systems, represented by the US GPS, China's BeiDou (BeiDou Satellite System), Russia's GLONASS, and Europe's Galileo, offer centimeter-level or higher positioning accuracy in fields such as earth science, surveying and mapping, agriculture, autonomous driving, aerospace, logistics, and disaster monitoring, significantly facilitating human life. To achieve high-precision GNSS applications, global or regional tracking stations are required to receive navigation satellite signals from tens of thousands of kilometers above the Earth. These stations then acquire pseudorange and phase observations between the Earth and the satellite. These pseudorange and phase data are then precisely processed to produce high-precision satellite orbits or tracking station coordinates.

[0003] However, navigation satellite downlink signals, transmitted from satellite antennas, propagate through the atmosphere to the receiving equipment at tracking stations. These signals are affected by atmospheric delays, observation environment errors, and observation noise. Furthermore, the propagation paths of downlink signals from different satellites vary. Consequently, the quality of pseudorange and phase observations from different systems and satellites varies in both space and time. In GNSS precision data processing, it is necessary to assign appropriate weights to pseudorange and phase observations to achieve high-precision positioning and orbit determination. Traditional observation weighting methods typically use empirical methods such as elevation angle and signal-to-noise ratio (SNR) to assign observation weights. These methods suffer from the following main issues: Empirical weighting methods are poorly applicable, especially at tracking stations with complex observing environments, where observations are subject to significant multipath influences. Using elevation angle alone cannot yield appropriate weights. Furthermore, not all observation data files from the International GNSS Service (IGS) provide SNR information, making it impossible to use empirical SNR weighting methods to set observation weights at these stations. Furthermore, post-processing of precision data over long arcs often uses satellite observation residuals to remove anomalous satellites, resulting in low observation data utilization. Finally, for multi-system precision data processing, the elevation angle-based weighting method does not take into account the differences in receiver observation noise caused by satellite signal quality between different systems.

[0004] In response to the above problems, the present invention establishes an observation weight determination method and system for GNSS precision data processing based on the posterior residuals of the observations. Summary of the Invention

[0005] The purpose of the present invention is to provide an observation value weighting method for navigation satellite precision data processing to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for determining weights of observation values for precise data processing of navigation satellites comprises the following steps:

[0008] Step 1: Construct a GNSS precision data processing observation model: Use GNSS signal tracking equipment at global tracking stations to collect GNSS observation data, remove gross error data, mark phase cycle slips, establish pseudorange observation equations and phase observation equations, and use the least squares principle to solve them to obtain estimated values of the parameters to be estimated;

[0009] Step 2: Determine the weight of pseudorange observations: Substitute the estimated values of the parameters to be estimated into the pseudorange observation equation to calculate the pseudorange residuals, and calculate the weights of the pseudorange observations by level, epoch, and satellite.

[0010] Step 3: Determine the weight of the phase observations: Substitute the estimated values of the parameters to be estimated back into the phase observation equation to calculate the phase residuals. Detect small phase cycle slips based on the phase residual sequence. Calculate the residual mean by segmenting the phase residuals according to the cycle slips and deduct it from the phase residuals to obtain the updated phase residuals. Calculate the phase observation weights hierarchically, epoch by epoch, and satellite by satellite.

[0011] Step 4: Based on the weights of each satellite and each epoch determined in step 3, repeat steps 1-3 and calculate the final precise positioning and orbit determination result through iterative calculation.

[0012] Preferably, the pseudorange observation equation and phase observation equation in step 1 are as follows:

[0013] (1);

[0014] In formula (1):

[0015] and : represent pseudorange and phase measurement values respectively;

[0016] : The geometric distance between the station and the satellite; s : satellite number; r : Receiver number; i : frequency point number;

[0017] c :Speed of light in vacuum;

[0018] : receiver clock error; : satellite clock error;

[0019] : ionospheric delay projection function; : station zenith ionospheric delay;

[0020] : tropospheric mapping function; : zenith tropospheric delay;

[0021] : carrier phase integer ambiguity parameter; :The i The wavelength of the frequency point;

[0022] , : No. i The pseudo-range observation value receiver and phase end hardware delay of each frequency point;

[0023] , : No. i The phase observation value receiver and satellite hardware delay at each frequency point;

[0024] , :Respectively i The pseudorange and phase multipath effects and noise of each frequency point.

[0025] Preferably, the pseudorange residual in step 2 is calculated as follows:

[0026] (2);

[0027] In formula (2):

[0028] : Pseudorange residual.

[0029] Preferably, the step 2 of calculating the pseudorange observation weights on a hierarchical, epoch-by-epoch, and satellite-by-satellite basis specifically includes:

[0030] The calculation method of pseudorange observation weight is:

[0031] (3);

[0032] In formula (3):

[0033] j: number of iterations;

[0034] : The weight of the pseudorange observation value of satellite s frequency point i determined by the j-th iteration calculation, the initial weight is 1;

[0035] , : empirical coefficient, set according to the number of iterations;

[0036] : The standard deviation calculated based on the residuals of all satellite pseudorange observations.

[0037] Preferably, the standard deviation calculated based on the residuals of all satellite pseudorange observations is The calculation method is:

[0038] (4);

[0039] In formula (4):

[0040] : the weighted mean of the residuals of pseudorange observations at frequency point i of satellite s;

[0041] : The weight of the pseudorange observation value of satellite s at frequency point i determined by the j-1th iteration calculation.

[0042] Preferably, the weighted mean of the residuals of the pseudorange observation values of the satellite s frequency point i is The calculation method is:

[0043] (5).

[0044] Preferably, the phase residual in step 3 is calculated as follows:

[0045] (6);

[0046] In formula (6):

[0047] : Phase residual.

[0048] Preferably, the performing of phase small cycle slip detection based on the phase residual sequence in step 3, calculating the residual mean of the phase residual according to the cycle slip segment and deducting it from the phase residual to obtain the updated phase residual specifically includes:

[0049] (7);

[0050] In formula (7):

[0051] and Represent the updated phase residual and residual segment mean respectively.

[0052] Preferably, the hierarchical and epoch-by-epoch and satellite-by-satellite calculation of the phase observation weights in step 2 specifically includes:

[0053] The calculation method of phase observation weight is:

[0054] (8);

[0055] In formula (8):

[0056] : The weight of the phase observation value of satellite s at frequency point i determined by the j-th iteration calculation, with the initial weight being 1;

[0057] : The standard deviation calculated based on the residuals of all satellite phase observations.

[0058] Preferably, the standard deviation calculated based on the residuals of all satellite phase observations is The calculation method is:

[0059] (9);

[0060] In formula (9):

[0061] : the weighted mean of the residuals of the phase observations at frequency i of satellite s;

[0062] : The phase observation weight of satellite s at frequency point i determined by the j-1th iteration calculation;

[0063] Preferably, the weighted mean of the residuals of the phase observation values of the satellite s frequency point i is The calculation method is:

[0064] (10).

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The present invention provides a method for weighting observation values for precise navigation satellite data processing. This method can achieve weighting of observation values using the post-validation residuals of GNSS observation values without requiring additional signal-to-noise ratio auxiliary information. By weighting observation values on a satellite-by-satellite, epoch-by-epoch basis, full utilization of satellite observation information is achieved, avoiding the deletion of satellite observation values for entire arc segments due to poor observation quality during certain periods. Weighting using post-validation residuals of observation values fully accounts for signal differences between different satellite systems, rationally determining the weight distribution of satellite observation values from different systems. This invention creatively achieves precise weighting of observation values on a satellite-by-epoch, epoch-by-epoch basis based on post-validation residuals of observation values, improving the performance of GNSS precise positioning and orbit determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 The present invention provides a flowchart of a method for weighting observation values for precise data processing of navigation satellites. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0069] Figure 1 This is a flow chart of a method for weighting observation values in navigation satellite precision data processing provided by the present invention. Figure 1 As shown, an embodiment of the present invention provides an observation value weighting method for navigation satellite precision data processing, comprising the following steps:

[0070] Step 1: Construct a GNSS precision data processing observation model: Use GNSS signal tracking equipment at global tracking stations to collect GNSS observation data, remove gross error data, mark phase cycle slips, establish pseudorange observation equations and phase observation equations, and use the least squares principle to solve them to obtain estimated values of the parameters to be estimated;

[0071] Step 2: Determine the weight of pseudorange observations: Substitute the estimated values of the parameters to be estimated into the pseudorange observation equation to calculate the pseudorange residuals, and calculate the weights of the pseudorange observations by level, epoch, and satellite.

[0072] Step 3: Determine the weight of the phase observations: Substitute the estimated values of the parameters to be estimated back into the phase observation equation to calculate the phase residuals. Detect small phase cycle slips based on the phase residual sequence. Calculate the residual mean by segmenting the phase residuals according to the cycle slips and deduct it from the phase residuals to obtain the updated phase residuals. Calculate the phase observation weights hierarchically, epoch by epoch, and satellite by satellite.

[0073] Step 4: Based on the weights of each satellite and each epoch determined in step 3, repeat steps 1-3 and calculate the final precise positioning and orbit determination result through iterative calculation.

[0074] It should be noted that the observation value weighting method for navigation satellite precision data processing provided by this invention assumes that the tracking station receiving equipment can track GNSS satellite signals and that the observations contain at least pseudoranges and phases. Only in this way can the observation equations for positioning and orbit determination be effectively established and the observation value residuals calculated. In practice, this condition is very easy to meet, as the receiving equipment at IGS global tracking stations all use measurement-type receivers, support signal tracking of at least a single satellite system, and the observation files contain pseudorange and phase observations.

[0075] In one embodiment of the present invention, the pseudorange observation equation and the phase observation equation in step 1 are as follows:

[0076] (1);

[0077] In formula (1):

[0078] and : represent pseudorange and phase measurement values respectively;

[0079] : The geometric distance between the station and the satellite; s : satellite number; r : Receiver number; i : frequency point number;

[0080] c :Speed of light in vacuum;

[0081] : receiver clock error; : satellite clock error;

[0082] : ionospheric delay projection function; : station zenith ionospheric delay;

[0083] : tropospheric mapping function; : zenith tropospheric delay;

[0084] : carrier phase integer ambiguity parameter; :The i The wavelength of the frequency point;

[0085] , : No. i The pseudo-range observation value receiver and phase end hardware delay of each frequency point;

[0086] , : No. i The phase observation value receiver and satellite hardware delay at each frequency point;

[0087] , :Respectively i The pseudorange and phase multipath effects and noise of each frequency point.

[0088] In specific precision data processing, the corresponding parameters to be estimated are set according to the requirements of precise orbit determination or positioning. At the same time, the dual-frequency ionosphere-free layer combination or non-differential non-combination mode can be selected according to user preferences.

[0089] Furthermore, in one embodiment of the present invention, the estimated value of the parameter to be estimated is substituted back into the pseudorange observation equation to calculate the pseudorange residual. The pseudorange residual in step 2 is calculated as follows:

[0090] (2);

[0091] In formula (2):

[0092] : Pseudorange residual.

[0093] Furthermore, in one embodiment of the present invention, the step 2 of calculating the pseudorange observation weights on a hierarchical, epoch-by-epoch, and satellite-by-satellite basis specifically includes:

[0094] The calculation method of pseudorange observation weight is:

[0095] (3);

[0096] In formula (3):

[0097] j: number of iterations;

[0098] : The weight of the pseudorange observation value of satellite s frequency point i determined by the j-th iteration calculation, the initial weight is 1;

[0099] , : empirical coefficient, set according to the number of iterations; generally, m is 10 and n is 5 in the first calculation, and 5 and 3 respectively in subsequent iterative calculations; k is the coefficient value, generally 2 in the first calculation and 1 in subsequent iterative calculations;

[0100] : The standard deviation calculated based on the residuals of all satellite pseudorange observations.

[0101] Specifically, in one embodiment of the present invention, the standard deviation calculated based on the residuals of all satellite pseudorange observations is The calculation method is:

[0102] (4);

[0103] In formula (4):

[0104] : the weighted mean of the residuals of pseudorange observations at frequency point i of satellite s;

[0105] : The weight of the pseudorange observation value of satellite s at frequency point i determined by the j-1th iteration calculation.

[0106] Specifically, in one embodiment of the present invention, the weighted mean of the residuals of the pseudo-range observation values of the satellite s frequency point i is The calculation method is:

[0107] (5).

[0108] In one embodiment of the present invention, the phase residual in step 3 is calculated as follows:

[0109] (6);

[0110] In formula (6):

[0111] : Phase residual.

[0112] In one embodiment of the present invention, performing phase small cycle slip detection based on the phase residual sequence in step 3, calculating the residual mean of the phase residual according to the cycle slip segment and deducting it from the phase residual to obtain the updated phase residual specifically includes:

[0113] (7);

[0114] In formula (7):

[0115] and Represent the updated phase residual and residual segment mean respectively.

[0116] In one embodiment of the present invention, the hierarchical calculation of the phase observation weights on an epoch-by-epoch and satellite-by-satellite basis in step 2 specifically includes:

[0117] The calculation method of phase observation weight is:

[0118] (8);

[0119] In formula (8):

[0120] : The weight of the phase observation value of satellite s at frequency point i determined by the j-th iteration calculation, with the initial weight being 1;

[0121] : The standard deviation calculated based on the residuals of all satellite phase observations.

[0122] Specifically, the standard deviation calculated based on the residuals of all satellite phase observations is The calculation method is:

[0123] (9);

[0124] In formula (9):

[0125] : the weighted mean of the residuals of the phase observations at frequency i of satellite s;

[0126] : The phase observation weight of satellite s at frequency point i determined by the j-1th iteration calculation.

[0127] Specifically, the weighted mean of the residuals of the phase observation values of the satellite s frequency point i is The calculation method is:

[0128] (10).

[0129] The present invention provides a method for weighting observation values for precise navigation satellite data processing. This method can achieve weighting of observation values using the post-validation residuals of GNSS observation values without requiring additional signal-to-noise ratio auxiliary information. By weighting observation values on a satellite-by-satellite, epoch-by-epoch basis, full utilization of satellite observation information is achieved, avoiding the deletion of satellite observation values for entire arc segments due to poor observation quality during certain periods. Weighting using post-validation residuals of observation values fully accounts for signal differences between different satellite systems, rationally determining the weight distribution of satellite observation values from different systems. This invention creatively achieves precise weighting of observation values on a satellite-by-epoch, epoch-by-epoch basis based on post-validation residuals of observation values, improving the performance of GNSS precise positioning and orbit determination.

[0130] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for weighting observation values for precise navigation satellite data processing, characterized in that: The following steps are involved: Step 1: Construct a GNSS precision data processing observation model: Use GNSS signal tracking equipment at global tracking stations to collect GNSS observation data, remove gross error data, mark phase cycle slips, establish pseudorange observation equations and phase observation equations, and use the least squares principle to solve them to obtain estimated values of the parameters to be estimated; Step 2: Determine the weight of pseudorange observations: Substitute the estimated values of the parameters to be estimated into the pseudorange observation equation to calculate the pseudorange residuals, and calculate the weights of the pseudorange observations by level, epoch, and satellite. Step 3: Determine the weight of the phase observations: Substitute the estimated values of the parameters to be estimated back into the phase observation equation to calculate the phase residuals. Detect small phase cycle slips based on the phase residual sequence. Calculate the residual mean by segmenting the phase residuals according to the cycle slips and deduct it from the phase residuals to obtain the updated phase residuals. Calculate the phase observation weights hierarchically, epoch by epoch, and satellite by satellite. Step 4: Based on the weights of each satellite and each epoch determined in step 3, repeat steps 1-3 and calculate the final precise positioning and orbit determination result through iterative calculation.

2. The method for determining weights of observation values for precise navigation satellite data processing according to claim 1, wherein: The pseudorange observation equation and phase observation equation described in step 1 are as follows: (1)； In formula (1): and : represent pseudorange and phase measurement values respectively; : The geometric distance between the station and the satellite; s : satellite number; r : Receiver number; i : frequency point number; c : speed of light in vacuum; : receiver clock error; : satellite clock error; : ionospheric delay projection function; : station zenith ionospheric delay; : tropospheric mapping function; : zenith tropospheric delay; : carrier phase integer ambiguity parameter; :The i The wavelength of the frequency point; , : No. i The pseudo-range observation value receiver and phase end hardware delay of each frequency point; , : No. i The phase observation value of each frequency point is delayed by the hardware of the receiver and the satellite end; , :Respectively i The pseudorange and phase multipath effects and noise of each frequency point.

3. The method for determining weights of observation values for precise navigation satellite data processing according to claim 2, wherein: The calculation method of the pseudorange residual in step 2 is: (2)； In formula (2): : Pseudorange residual.

4. The method for determining weights of observation values for navigation satellite precision data processing according to claim 3, wherein: The calculation of pseudorange observation weights by epoch and satellite at each level in step 2 specifically includes: The calculation method of pseudorange observation weight is: (3)； In formula (3): j: number of iterations; : The weight of the pseudorange observation value of satellite s at frequency point i determined by the j-th iteration calculation, with the initial weight being 1; , : empirical coefficient, set according to the number of iterations; : The standard deviation calculated based on the residuals of all satellite pseudorange observations.

5. The method for determining weights of observation values for precise navigation satellite data processing according to claim 4, wherein: The standard deviation calculated based on the residuals of all satellite pseudorange observations The calculation method is: (4)； In formula (4): : the weighted mean of the residuals of pseudorange observations at frequency point i of satellite s; : The weight of the pseudorange observation value of satellite s at frequency point i determined by the j-1th iteration calculation; The weighted mean of the residuals of the pseudorange observation values of the satellite s frequency point i The calculation method is: (5)。 6. The method for determining weights of observation values for navigation satellite precision data processing according to claim 5, wherein: The calculation method of the phase residual in step 3 is: （6）； In formula (6): : Phase residual.

7. The method for determining weights of observation values for precise navigation satellite data processing according to claim 6, wherein: The phase residual sequence is used to detect small phase cycle slips in step 3, and the residual mean is calculated by segmenting the phase residual according to the cycle slip and then deducted from the phase residual to obtain the updated phase residual. Specifically, the following steps are performed: （7）； In formula (7): and Represent the updated phase residual and residual segment mean respectively.

8. The method for determining weights of observation values for precise navigation satellite data processing according to claim 7, wherein: The calculation of the phase observation weights at each level, epoch and satellite in step 2 specifically includes: The calculation method of phase observation weight is: （8）； In formula (8): : The weight of the phase observation value of satellite s at frequency point i determined by the j-th iteration calculation, with the initial weight being 1; : The standard deviation calculated based on the residuals of all satellite phase observations.

9. The method for determining weights of observation values for precise navigation satellite data processing according to claim 8, wherein: The standard deviation calculated based on the residuals of all satellite phase observations The calculation method is: （9）； In formula (9): : the weighted mean of the residuals of the phase observations at frequency i of satellite s; : The phase observation weight of satellite s at frequency point i determined by the j-1th iteration calculation; The weighted mean of the residuals of the phase observations at frequency point i of the satellite s is The calculation method is: （10）。

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