A pseudorange robustness method for inertial navigation-assisted BeiDou heterogeneous constellations

Abstract

The present invention provides an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method, constructs a noise matrix R, distinguishes satellites according to satellite observation signals and constructs a heterogeneous constellation model, calculates the standard deviation of the heterogeneous constellation model, calculates the standard deviation of pseudo-range observation values ​​by error propagation law and standard deviation, and constructs the noise matrix R based on the standard deviation; constructs an anti-error factor, obtains Beidou pseudo-range observation values ​​and inertial navigation position observation values, obtains Beidou pseudo-range observation value residuals by inertial navigation position observation values, and constructs an anti-error factor based on the pseudo-range observation value residuals; combines filtering, constructs an equivalent covariance matrix according to the noise matrix R and the anti-error factor, performs combined filtering and solving based on the equivalent covariance matrix, and obtains a combined navigation result. The present invention can improve the positioning reliability and stability of the BDS / IMU tight group positioning system.

Description

Technical Field

[0001] The present invention relates to the field of Beidou positioning technology, and in particular to an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method. Background Art

[0002] With the widespread application of navigation and location services in modern industries, strict requirements are also placed on the all-weather high stability and high reliability of positioning services. The Beidou satellite system is widely used in my country's economic construction and residents' lives, and plays an important role in national production. When the satellite signal is disturbed by the environment, the quality of satellite observation values ​​decreases, and the availability of satellites cannot be effectively guaranteed. The positioning information of inertial navigation is not affected by the environment, but the error accumulates over time, so the inertial navigation system cannot maintain high-precision result output for a long time. Satellite navigation systems and inertial navigation systems can complement each other to a certain extent, which is currently the best combined navigation solution.

[0003] The BeiDou satellite navigation system consists of a hybrid constellation of GEO (geosynchronous orbit satellite), IGSO (inclined geosynchronous orbit satellite) and MEO (medium earth orbit satellite). There are differences in the degree of correlation between the observation values ​​of different constellations and the random model of altitude angle.

[0004] In the BDS / IMU tight combination process, if the hybrid constellation uses the same altitude angle random model parameters, it cannot truly reflect the accuracy of the observation value, which will affect the convergence speed and positioning accuracy of the tight combination filter.

[0005] At the same time, due to the interference of the external observation environment, multipath errors will affect the accuracy of pseudorange observations. In the process of tight combination filtering, if abnormal pseudorange observations are not detected and participate in the filter measurement update, it may cause the combined positioning accuracy to decrease or even cause combined filtering anomalies. Therefore, abnormal pseudorange observations participating in the BDS / IMU tight combination filtering solution will have a great impact on the system reliability and stability. Summary of the invention

[0006] In view of this, the problem to be solved by the present invention is to provide an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method, which can improve the positioning reliability and stability of the BDS / IMU tight-group positioning system.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is: an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method, including constructing a noise matrix R, distinguishing satellites according to satellite observation signals and constructing a heterogeneous constellation model, and calculating the standard deviation of the heterogeneous constellation model. , through the error propagation law and the standard deviation Calculate the standard deviation of pseudorange observations , based on the standard deviation Construct the noise matrix R;

[0008] Building a robustness factor , obtain Beidou pseudorange observation values ​​and inertial navigation position observation values, and use the inertial navigation position observation values ​​to assist in obtaining Beidou pseudorange observation value residuals , based on the pseudorange observation residual Building a robustness factor ;

[0009] Combined filtering, based on the noise matrix R and the robustness factor Constructing the equivalent covariance matrix , based on the equivalent covariance matrix Perform combined filtering and solving to obtain the combined navigation results.

[0010] Furthermore, the standard deviation formula:

[0011] ,

[0012] ,

[0013] in, represents the heterogeneous constellation factor, E represents the satellite altitude angle, , , , represents the noise factor, represents the carrier-to-noise ratio, represents the GEO satellite factor, represents the IGEO satellite factor, represents the MEO satellite factor, Indicates the constellation logo.

[0014] Furthermore, the noise matrix R formula is:

[0015] ,

[0016] ,

[0017] in, represents the standard deviation of the ionospheric correction model, represents the standard deviation of the tropospheric correction model, Indicates the code deviation corrected standard deviation, represents the standard deviation of the ephemeris.

[0018] Furthermore, the robustness factor formula:

[0019] ,

[0020] in, and represents the robustness coefficient, represents the standardized residual.

[0021] Furthermore, the standardized residual formula:

[0022] ,

[0023] in: , Design matrix for position, , is the identity matrix, , , is the covariance matrix of pseudorange observations, is the inertial navigation position covariance matrix, represents the residual of pseudorange observation;

[0024] The pseudorange observation residual formula:

[0025] ,

[0026] in, It is composed of position correction, receiver clock error correction and receiver clock drift correction. , It indicates the distance from the receiver antenna position predicted by the inertial navigation to the Beidou available observation satellite. It represents the estimated distance from the BeiDou receiver antenna position to the BeiDou available observation satellites.

[0027] Furthermore, the equivalent covariance matrix formula:

[0028] .

[0029] Furthermore, the filtering solution formula is:

[0030] ,

[0031] ,

[0032] ,

[0033] in, represents the filter gain matrix, represents the state variance prediction value, represents the observation coefficient matrix, represents the state variance estimate, represents the state prediction value, represents the state valuation, represents the observation vector matrix, Represents the identity matrix.

[0034] Furthermore, the observation vector matrix formula:

[0035] ,

[0036] ,

[0037] in, represents the receiver pseudorange observation value, represents the distance from the inertial navigation predicted receiver antenna position to the i-th Beidou satellite, represents the ionospheric correction parameter, represents the tropospheric correction parameter, is the speed of light in vacuum, Represents the satellite clock error.

[0038] The advantages and positive effects of the present invention are:

[0039] The BDS / IMU tight-fitting positioning system uses the gyro-addition data collected by the inertial navigation system and the pseudo-range observations collected by the Beidou receiver for combined calculation. Based on the characteristics of the Beidou system satellite constellation, a Beidou heterogeneous constellation random model is established. It can more accurately feedback the accuracy of satellite observation values ​​and improve the accuracy and reliability of the integrated navigation system.

[0040] Due to external environmental interference, satellite observations are affected by multipath errors, etc., and pseudorange observations in actual tests inevitably contain gross errors. If abnormal pseudorange observations are not detected and participate in the filter measurement update, it may cause a decrease in the combined positioning accuracy or even cause combined filter anomalies. The noise matrix R of the constellation is calculated based on the heterogeneous constellation model, and the residuals of the pseudorange observations of the satellite navigation are calculated with the assistance of inertial navigation data. . Based on the pseudorange observation residual Building a robustness factor , noise matrix R and robustness factor Constructing the equivalent covariance matrix , the equivalent covariance matrix Substituting the filtering formula into the filter solution can effectively reduce the impact of gross error observations on the combined system and improve the positioning reliability and stability of the BDS / IMU tight-fitting positioning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 It is an overall flow chart of an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method of the present invention;

[0043] Figure 2 It is a flow chart of constructing a heterogeneous constellation model in an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method of the present invention;

[0044] Figure 3 This is a comparison chart before and after using the robust algorithm;

[0045] Figure 4 yes Figure 3 A local enlargement of the . DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0048] The present invention provides an inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method, including a BDS / IMU tightly combined positioning system, using a state update equation to predict the state parameters of the next moment, and the state update equation is:

[0049] ,

[0050] in, represents the predicted value of the state at time k, represents the state valuation at time k-1, Represents the state transfer matrix between time k-1 and time k.

[0051] State parameters in the state update equation for:

[0052] ,

[0053] in, Represents the position error in 3 directions, Indicates the speed error in 3 directions, Indicates the misalignment angle error in three directions, Indicates the acceleration zero bias error in three directions, Indicates the gyro bias error in three directions, represents the clock bias error of the satellite receiver, Indicates the satellite receiver's clock drift error.

[0054] Based on state parameter , construct the combined measurement equation:

[0055] ,

[0056] in, represents the observation vector matrix, represents the observation coefficient matrix, Indicates the measurement noise, usually The mean of is zero.

[0057] Observation vector matrix The expression is:

[0058] ,

[0059] ,

[0060] in, It represents the distance from the receiver antenna position predicted by the inertial navigation to the i-th Beidou available observation satellite. represents the receiver pseudorange observation value, represents the ionospheric correction parameter, represents the tropospheric correction parameter, is the speed of light in vacuum, Represents the satellite clock error.

[0061] Measurement equation observation coefficient matrix The expression is:

[0062] ,

[0063] ,

[0064] in, The direction cosine matrix from the navigation coordinate system to the Earth-centered Earth-fixed coordinate system, the matrix , the receiver antenna position predicted by the inertial navigation is , Beidou satellite position is .

[0065] like Figure 1 to Figure 2As shown, due to the heterogeneous constellation characteristics of the BeiDou satellite system, the noise matrix R of the heterogeneous constellation is constructed: satellites are distinguished based on satellite observation signals and a heterogeneous constellation model is constructed, and the standard deviation of the heterogeneous constellation model is calculated. , through the standard deviation Calculate the standard deviation of pseudorange observations , based on the standard deviation Construct the noise matrix R.

[0066] Through Beidou satellite observation information, determine the Beidou satellite number, identify the constellation the satellite is located in, and set the Beidou satellite constellation identifier.

[0067] A heterogeneous constellation model is constructed using a mixed random model of the altitude angle signal-to-noise ratio. The formula of the heterogeneous constellation model is:

[0068] ,

[0069] ,

[0070] in, represents the standard deviation of the heterogeneous constellation model, represents the heterogeneous constellation factor, E represents the satellite altitude angle, , , , Represents the noise factor of the satellite receiver, which can be fitted and set according to the noise level of the satellite receiver. represents the carrier-to-noise ratio, represents the GEO satellite factor, represents the IGEO satellite factor, represents the MEO satellite factor, Indicates the constellation logo.

[0071] An embodiment of the present application is: The value usually ranges from 1.1 to 1.3. The value usually ranges from 1.0 to 1.1. The value usually ranges from 0.8 to 1.0.

[0072] Beidou heterogeneous constellation random model fully considers the characteristics of different constellations, satellite altitude angle, satellite signal-to-noise ratio and other factors to make the standard deviation of pseudo-range observations It can more accurately reflect the accuracy of satellite observations. Based on this, the measurement noise matrix R can effectively improve the convergence speed and positioning accuracy of the compact combination filter.

[0073] The construction formula of the measurement noise matrix R is:

[0074] ,

[0075] ,

[0076] in, represents the standard deviation of the heterogeneous constellation model, is the standard deviation of the ionospheric correction model, is the tropospheric correction model standard deviation, is the code deviation corrected standard deviation, is the standard deviation of the ephemeris.

[0077] Due to external environmental interference, satellite observations are affected by multipath errors and other factors. In order to reduce the impact of pseudo-range observations containing gross errors on navigation accuracy, a robustness factor is constructed. .

[0078] Building a robustness factor : Get Beidou pseudo-range observations and inertial navigation position observations, and use inertial navigation position observations to assist in getting Beidou pseudo-range observation residuals , based on the pseudorange observation residual Building a robustness factor .

[0079] The observation equation is constructed through Beidou pseudorange observations and inertial navigation positions. The coordinate value estimation and receiver clock error parameters are calculated according to the least squares criterion, and then the observation residual is constructed. The formula is:

[0080] ,

[0081] ,

[0082] in: It is composed of position correction, receiver clock error correction and receiver clock drift correction. , Design matrix for position, , is the identity matrix, , , It indicates the distance from the receiver antenna position predicted by the inertial navigation to the Beidou available observation satellite. It represents the estimated distance from the BeiDou receiver antenna position to the BeiDou available observation satellites.

[0083] Based on the pseudorange observation residual Calculate the robustness factor The formula is:

[0084] ,

[0085] ,

[0086] in, represents the standardized residual, , is the covariance matrix of pseudorange observations, is the inertial navigation position covariance matrix, and Represents the robustness coefficient.

[0087] Filter solution, based on the noise matrix R and the robustness factor Constructing the equivalent covariance matrix , based on the equivalent covariance matrix Perform combined filtering and solving to obtain the combined navigation results.

[0088] Equivalent covariance matrix The formula is:

[0089] .

[0090] Based on the equivalent covariance matrix Filter and solve the BDS / IMU tight combination to obtain the combined positioning result.

[0091] The gain matrix formula is: ,in, represents the filter gain matrix, represents the state variance prediction value, represents the observation coefficient matrix.

[0092] The state estimation formula is: ,in, represents the state prediction value, represents the state valuation, Represents the observation vector matrix.

[0093] The state variance formula is: ,in, represents the identity matrix, is the predicted value of state variance, is the state variance estimate.

[0094] like Figure 3 and Figure 4 As shown in the figure, through actual testing, it is found that after the anti-error algorithm, the overall trajectory is smoother. Figure 3 In the semi-shaded area, due to the interference of some satellites, there are gross errors in the observation values. The satellite observation values ​​with gross errors participate in the tight combination solution, causing the trajectory positioning accuracy to decrease. The anti-error method proposed in this application effectively reduces the impact of gross error observation values ​​on tight combination positioning, and improves the accuracy and reliability of tight combination positioning in semi-shaded environments. Figure 4 .

[0095] The embodiments of the present invention are described in detail above, but the contents described are only preferred embodiments of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of this patent.

Claims

1. An inertial navigation-assisted Beidou heterogeneous constellation pseudo-range anti-error method, characterized in that: include, Construct the noise matrix R, distinguish satellites based on satellite observation signals and construct a heterogeneous constellation model, and calculate the standard deviation of the heterogeneous constellation model , through the error propagation law and the standard deviation Calculate the standard deviation of pseudorange observations , based on the standard deviation Construct the noise matrix R; Building a robustness factor , obtain Beidou pseudorange observation values ​​and inertial navigation position observation values, and use the inertial navigation position observation values ​​to assist in obtaining Beidou pseudorange observation value residuals , based on the pseudorange observation residual Building a robustness factor , i represents the i-th satellite; Combined filtering, based on the noise matrix R and the robustness factor Constructing the equivalent covariance matrix , based on the equivalent covariance matrix Perform combined filtering and solving to obtain combined navigation results; The standard deviation formula: ， ， in, represents the heterogeneous constellation factor, E represents the satellite altitude angle, , , , represents the noise factor, represents the carrier-to-noise ratio, represents the GEO satellite factor, represents the IGEO satellite factor, represents the MEO satellite factor, Indicates the constellation logo; The noise matrix R formula is: ， ， in, represents the standard deviation of the ionospheric correction model, represents the standard deviation of the tropospheric correction model, Indicates the code deviation corrected standard deviation, represents the standard deviation of the ephemeris; The equivalent covariance matrix formula: 。 2. According to the inertial navigation-aided Beidou heterogeneous constellation pseudo-range robustness method of claim 1, it is characterized in that: The robustness factor formula: ， in, and represents the robustness coefficient, represents the standardized residual.

3. The method for pseudo-range robustness of Beidou heterogeneous constellation assisted by inertial navigation according to claim 2 is characterized in that: The standardized residual formula: ， in: , Design matrix for position, , is the identity matrix, , , is the covariance matrix of pseudorange observations, is the inertial navigation position covariance matrix, represents the residual of pseudorange observation; The pseudorange observation residual formula: ， in, It is composed of position correction, receiver clock error correction and receiver clock drift correction. , It indicates the distance from the receiver antenna position predicted by the inertial navigation to the Beidou available observation satellite. It represents the estimated distance from the BeiDou receiver antenna position to the BeiDou available observation satellites.

4. The method for pseudo-range robustness of Beidou heterogeneous constellation assisted by inertial navigation according to claim 1 is characterized in that: The filtering solution formula is: ， ， ， in, represents the filter gain matrix, represents the state variance prediction value, represents the observation coefficient matrix, represents the state variance estimate, represents the state prediction value, represents the state valuation, represents the observation vector matrix, Represents the identity matrix.

5. The method for pseudo-range robustness of Beidou heterogeneous constellation assisted by inertial navigation according to claim 4 is characterized in that: The observation vector matrix formula: ， ， in, represents the receiver pseudorange observation value, represents the distance from the inertial navigation predicted receiver antenna position to the i-th Beidou satellite, represents the ionospheric correction parameter, represents the tropospheric correction parameter, is the speed of light in vacuum, Represents the satellite clock error.

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