GNSS satellite clock error estimation method considering elastic power

Abstract

The application relates to the technical field of satellite navigation satellite-based augmentation, and particularly discloses a GNSS satellite clock error estimation method considering elastic power, which comprises the following steps: based on pseudo-range observation values and phase observation values, elastic code bias of GNSS and corresponding elastic factors are generated by using Kalman filtering; when GNSS is in elastic power, the pseudo-range observation values are corrected, the corrected pseudo-range observation values are aligned to a preset satellite clock error reference benchmark, and a function model is obtained; a random model is constructed according to the elevation angle of GNSS, the elastic code bias and the corresponding elastic factors; the clock error benchmark is determined by taking the atomic clock station as a reference clock or by separating the receiver clock and the satellite clock according to the satellite zero-mean benchmark; and the satellite clock error with the unified benchmark and the corresponding elastic factors are generated according to the function model, the random model and the clock error benchmark. The GNSS satellite clock error still has high stability and precision during the elastic power period.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation satellite-based augmentation technology, and more specifically to a GNSS satellite clock bias estimation method that takes into account elastic power. Background Technology

[0002] With the continuous development of the Global Navigation Satellite System (GNSS), users' requirements for GNSS service performance are increasing. GNSS services are steadily moving towards real-time performance, high accuracy, and high reliability. The service model that was previously dominated by the single-system GPS has gradually shifted to a multi-system integrated GNSS service model, and GNSS observation signals are also gradually moving from traditional dual-frequency observation to the era of multi-frequency observation. Both Precise Point Positioning (PPP) and PPP Ambiguity Search (PPPAR) technologies heavily rely on the support of precise clock bias products. As an indispensable precision product for GNSS positioning, navigation, and timing (PNT), the accuracy and stability of clock bias directly affect the PNT model establishment method. Based on different ambiguity fixing methods, satellite clock biases can be divided into three types: pseudorange clocks, integer clocks, and phase clocks.

[0003] However, satellite navigation systems are susceptible to interference and spoofing, posing potential risks to the operation and development of critical national and societal infrastructure. Resilient power technology, as an effective means, increases satellite signal transmission power, enabling receivers to relock signals in complex electromagnetic interference environments, thereby overcoming the inherent vulnerability of satellite navigation systems and ensuring the normal operation of satellite navigation equipment. However, during resilient power, satellite code bias and phase bias change significantly. Currently, several mainstream methods for satellite clock bias and phase bias are closely coupled with code bias and phase bias in their parameter estimation process or final representation. Research in this area is currently lacking; therefore, it is urgent to improve existing satellite clock bias processing strategies to optimize the performance of GNSS satellite-based service corrections. Summary of the Invention

[0004] To address the aforementioned problems, the purpose of this invention is to provide a GNSS satellite clock bias estimation method that takes into account elastic power. This method improves the existing model from the perspectives of both functional and stochastic models, ensuring high stability and accuracy of GNSS satellite clock bias even during periods of elastic power.

[0005] This invention provides a GNSS satellite clock bias estimation method that takes into account elastic power, comprising: Based on pseudorange and phase observations from the Global Navigation Satellite System (GNSS), Kalman filtering is used to generate the elastic code bias and corresponding elasticity factor of GNSS. When the GNSS is in elastic power, the pseudorange observations are corrected and aligned to a preset satellite clock bias reference, thus obtaining a function model for estimating satellite clock bias. A stochastic model for estimating satellite clock bias is constructed based on the GNSS elevation angle, the elastic code deviation, and the corresponding elastic factor. The clock bias reference can be determined by using the atomic clock station as the reference clock, or by separating the receiver clock and the satellite clock using the satellite zero-mean reference. Based on the function model, the stochastic model, and the clock bias benchmark, a unified satellite clock bias and corresponding elasticity factor are generated.

[0006] In one possible implementation, the function model is represented by the following formula: In the formula, For the first Frequency and the Frequency-point ionosphere-free combination The result of subtracting the calculated observation from the pseudorange observation. For the first Frequency and the Frequency-point non-ionospheric combination The result of subtracting the calculated observation from the phase observation. For tropospheric wet delay mapping function, Dual-frequency ionosphere-free model The parameter matrix to be estimated For the first Frequency and the Frequency-point non-ionospheric combination pseudorange observation residuals, For the first Frequency and the Frequency-point non-ionospheric combination The phase observation residuals.

[0007] In one possible implementation, the following formula represents the... Model parameter matrix to be estimated: In the formula, The receiver clock bias after parameter recombination. For satellite clock bias after parameter recombination, For tropospheric wet delay, For the parameter recombination of the first Frequency and the Frequency-point non-ionospheric combination ambiguity For time, For transpose, For receiver, For satellites.

[0008] In one possible implementation, the stochastic model is represented by the following formula. : In the formula, , and Indicates the noise ratio of the observed values. Indicates satellite elevation angle, Elasticity factor representing satellite clock bias For time.

[0009] In one possible implementation, a Kalman filter is used to generate the phase bias and the corresponding elasticity factor based on the satellite clock bias, the pseudorange observation, and the phase observation.

[0010] In one possible implementation, the corresponding ultra-wide lane ambiguity, wide lane ambiguity, and narrow lane ambiguity are generated based on the satellite clock bias and the multi-frequency non-differential non-combined PPP model, and the uncalibrated phase deviation (UPD) is generated based on the ultra-wide lane ambiguity, wide lane ambiguity, and narrow lane ambiguity.

[0011] In one possible implementation, the uncalibrated phase deviation UPD is converted into the target phase deviation OSB using a benchmark unification method.

[0012] In one possible implementation, the satellite clock error is corrected based on the narrow alley ambiguity, the uncalibrated phase deviation (UPD), and the double-difference ambiguity fixing method to obtain the corrected satellite clock error and the UPD correction number of the wide alley ambiguity.

[0013] In one possible implementation, the method of using the atomic clock station as a reference clock includes: The reference clock of the station is expressed by the following formula. : In the formula, For time.

[0014] In one possible implementation, the method for separating the receiver clock and the satellite clock using a satellite zero-mean reference includes: The zero-mean baseline for satellites is expressed by the following formula: In the formula, For satellite clock bias, For time, For the number of satellites, For satellite indexing, For satellites.

[0015] The GNSS satellite clock bias estimation method considering elastic power provided by this invention improves the functional and stochastic models of satellite clock bias estimation by constructing elastic code bias, enabling satellite clock bias products to fully consider the influence of factors such as elastic power, thus overcoming the shortcomings of traditional solutions. This method possesses high integrity and high availability, and can flexibly respond to the needs of different scenarios, providing strong technical support for GNSS satellite-based augmentation services. Attached Figure Description

[0016] Figure 1 A flowchart illustrating the GNSS satellite clock bias estimation method provided in an embodiment of the present invention. Detailed Implementation

[0017] The embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are used to illustrate the principles of the present invention by way of example, but should not be used to limit the scope of the present invention. That is, the present invention is not limited to the described preferred embodiments, and the scope of the present invention is defined by the claims.

[0018] In the description of this invention, it should be noted that, unless otherwise stated, "a plurality of" means two or more; the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance; those skilled in the art can understand the specific meaning of the above terms in this invention as appropriate.

[0019] Satellite clock bias and phase deviation satellite-based corrections are crucial for recovering the integer characteristics of PPP ambiguity and achieving PPPAR. Common estimation methods include pseudorange clock / UPD, integer clock (IRC), and phase clock. The applicant's testing and analysis revealed that during periods of satellite elastic power, the performance of satellite clock bias and phase deviation products is significantly worse than during normal satellite operation. Taking satellite clock bias products as an example, the final expressions of satellite clock bias using the three methods are as follows: in, Indicates the actual satellite clock bias. This represents the satellite code bias in the ionospherically non-spherically linear combination form. This represents the phase deviation in the form of a linear combination without an ionosphere. This indicates the phase deviation in the narrow alleyway.

[0020] Among them, the satellite clock difference in the pseudo-range clock absorbs the code deviation constant part and the phase deviation time-varying part. The satellite clock difference in IRC also includes the phase deviation constant part. The phase clock difference solution adopts the non-difference ambiguity fixed method. In order to be compatible with the pseudo-range clock, the pseudo-range observation value is usually retained in the second iteration of clock difference solution, but the pseudo-range observation value is further deweighted and the reference is aligned to the pseudo-range clock difference reference.

[0021] In precise satellite clock bias estimation, ambiguity parameters are usually treated as constants during the filtering process. This means that the satellite code bias absorbed by ambiguity is also treated as a time-invariant parameter. All three types of clock bias estimation methods are coupled with code bias in their final expression or parameter estimation process. Code bias changes during satellite elastic power periods destroy the benchmark of the three types of clock bias products, thereby affecting the performance of satellite clock bias and further affecting the accuracy of phase bias.

[0022] To address this, this invention optimizes the satellite clock bias and phase bias estimation processing strategy during satellite elastic power periods, based on existing satellite clock bias and phase bias estimation methods, to achieve a satellite clock bias / phase bias estimation method that takes into account elastic power, thereby improving the integrity of GNSS satellite-based service correction data products.

[0023] Figure 1 A flowchart illustrating the GNSS satellite clock bias estimation method provided in an embodiment of the present invention is shown below. Figure 1 As shown, this invention provides a GNSS satellite clock bias estimation method that takes into account elastic power, including: Step S1: Based on the pseudorange and phase observations of the Global Navigation Satellite System (GNSS), Kalman filtering is used to generate the elastic code bias and corresponding elasticity factor of the GNSS. Step S2: When the GNSS is in elastic power, correct the pseudorange observations and align the corrected pseudorange observations to the preset satellite clock bias reference, to obtain the function model for estimating the satellite clock bias; In one possible implementation, The preset satellite clock bias reference standard is an existing satellite clock bias reference standard with ionospheric pseudorange bias, which can be expressed as follows: In the formula, Indicates the actual satellite clock bias. This represents the satellite code bias in the form of a linear combination without ionosphere, which can eliminate the influence of elastic power on pseudorange observations.

[0024] The most commonly used function model currently is the dual-frequency, ionosphere-free combined model. This invention, after error correction and parameter rearrangement, expresses the function model according to the following formula: In the formula, For the first Frequency and the Frequency-point non-ionospheric combination The result of subtracting the calculated observation from the pseudorange observation. For the first Frequency and the Frequency-point non-ionospheric combination The result of subtracting the calculated observation from the phase observation. For tropospheric wet delay mapping function, Dual-frequency ionosphere-free model The parameter matrix to be estimated For the first Frequency and the Frequency-point non-ionospheric combination pseudorange observation residuals, For the first Frequency and the Frequency-point non-ionospheric combination The phase observation residuals.

[0025] In one possible implementation, it is expressed by the following formula: Model parameter matrix to be estimated: In the formula, The receiver clock bias after parameter recombination. For satellite clock bias after parameter recombination, For tropospheric wet delay, For the parameter recombination of the first Frequency and the Frequency-point non-ionospheric combination ambiguity For time, For transpose, For receiver, For satellites.

[0026] Step S3: Construct a stochastic model for estimating satellite clock bias based on the GNSS elevation angle, elastic code deviation, and corresponding elasticity factor; In one possible implementation, the existing stochastic model is expressed as follows: In the formula, , The noise ratio factor of observations in satellite clock error estimation.

[0027] This invention mitigates the effects of parameter reconvergence and baseline disorder by rationally adjusting model parameters; the stochastic model is expressed by the following formula. : In the formula, , and Indicates the noise ratio of the observed values. Indicates satellite elevation angle, Elasticity factor representing satellite clock bias For time.

[0028] Similarly, after generating precise satellite clock bias and its elasticity factor, the stochastic model for phase deviation estimation can be expressed according to the following formula. : In the formula, , , and This represents the measurement noise ratio of the observed values ​​in the phase deviation estimation model. Indicates satellite elevation angle, Elasticity factor representing satellite clock bias For time.

[0029] Step S4: Determine the clock difference reference by using the atomic clock station as the reference clock, or by separating the receiver clock and the satellite clock using the satellite zero-mean reference. One possible implementation method that uses the atomic clock station as a reference clock includes: The reference clock of the station is expressed by the following formula. : In the formula, For time.

[0030] In one possible implementation, methods for separating the receiver clock and the satellite clock using a satellite zero-mean reference include: The zero-mean baseline for satellites is expressed by the following formula: In the formula, For satellite clock bias, For time, For the number of satellites, For satellite indexing, For satellites.

[0031] Step S5: Based on the function model, stochastic model, and clock bias benchmark, generate a benchmark-unified satellite clock bias and corresponding elasticity factor.

[0032] In one possible implementation, a Kalman filter is used to generate the phase bias and the corresponding elasticity factor based on satellite clock bias, pseudorange observations, and phase observations.

[0033] In one possible implementation, the corresponding ultra-wide lane ambiguity, wide lane ambiguity, and narrow lane ambiguity are generated based on the satellite clock bias and the multi-frequency non-differential non-combined PPP model. An uncalibrated phase deviation (UPD) is then generated based on the ultra-wide lane ambiguity, wide lane ambiguity, and narrow lane ambiguity. The model rank deficiency problem is eliminated by using the UPD at the satellite or receiver end as a reference.

[0034] In one possible implementation, the uncalibrated phase deviation UPD is converted into the target phase deviation OSB through a benchmark unification method.

[0035] In one possible implementation, the NL UPD in the pseudo-range clock / UPD method is derived from the floating-point ambiguity net solution, and the estimation methods for WL and NL UPD are similar; the IRC method estimates NL UPD and satellite clock bias simultaneously, obtains satellite clock bias based on phase, and provides WL UPD correction; the satellite clock bias is corrected according to the narrow-lane ambiguity, uncalibrated phase bias UPD, and double-difference ambiguity fixing method, to obtain the corrected satellite clock bias and wide-lane ambiguity UPD correction.

[0036] Its clock error reference is consistent with that of the pseudo-distance clock.

[0037] To reflect the flexibility of the correction values, satellite clock bias and phase deviation are also assigned corresponding RI values.

[0038] The satellite clock bias estimation method of this invention can effectively cope with complex external environments such as elastic power, and solve the problems of fault prevention and system recovery. Even in complex scenarios, it can still meet users' stringent requirements for the accuracy, integrity, and continuity of PNT service satellite clock bias.

[0039] The GNSS satellite clock bias estimation method considering elastic power provided by this invention generates corresponding code bias values ​​and RIs by constructing elastic code biases. When the code bias value changes significantly, the improved satellite clock bias estimation function model can fully consider its impact. Furthermore, by combining factors such as elevation angle, observation noise, and elastic code bias, a stochastic model for satellite clock bias estimation is constructed, ensuring that the satellite clock bias product fully considers the influence of factors such as elastic power, thus overcoming the shortcomings of traditional solutions. This method possesses high integrity and high availability, and can flexibly respond to the needs of different scenarios, providing strong technical support for GNSS satellite-based augmentation services.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A GNSS satellite clock bias estimation method considering elastic power, characterized in that, include: Based on pseudorange and phase observations from the Global Navigation Satellite System (GNSS), Kalman filtering is used to generate the elastic code bias and corresponding elasticity factor of GNSS. When the GNSS is in elastic power, the pseudorange observations are corrected and aligned to a preset satellite clock bias reference, thus obtaining a function model for estimating satellite clock bias. A stochastic model for estimating satellite clock bias is constructed based on the GNSS elevation angle, the elastic code deviation, and the corresponding elastic factor. The clock bias reference can be determined by using the atomic clock station as the reference clock, or by separating the receiver clock and the satellite clock using the satellite zero-mean reference. Based on the function model, the stochastic model, and the clock bias benchmark, a unified satellite clock bias and corresponding elasticity factor are generated.

2. The GNSS satellite clock bias estimation method according to claim 1, characterized in that, Also includes: The function model is represented by the following formula: In the formula, For the first Frequency and the Frequency-point non-ionospheric combination The result of subtracting the calculated observation from the pseudorange observation. For the first Frequency and the Frequency-point non-ionospheric combination The result of subtracting the calculated observation from the phase observation. For tropospheric wet delay mapping function, Dual-frequency ionosphere-free model The parameter matrix to be estimated For the first Frequency and the Frequency-point non-ionospheric combination pseudorange observation residuals, For the first Frequency and the Frequency-point non-ionospheric combination Phase observation residuals, For time.

3. The GNSS satellite clock bias estimation method according to claim 2, characterized in that, Also includes: The following formula represents the... Model parameter matrix to be estimated: In the formula, The receiver clock bias after parameter recombination. For the satellite clock bias after parameter recombination, For tropospheric wet delay, For the parameter recombination of the first Frequency and the Frequency-point non-ionospheric combination ambiguity, For time, For transpose, For receiver, For satellites.

4. The GNSS satellite clock bias estimation method according to claim 1, characterized in that, Also includes: The stochastic model is expressed by the following formula. : In the formula, , and Indicates the noise ratio of the observed values. Indicates satellite elevation angle, Elasticity factor representing satellite clock bias For time.

5. The GNSS satellite clock bias estimation method according to claim 1, characterized in that, Also includes: Based on the satellite clock error, the pseudorange observation, and the phase observation, a Kalman filter is used to generate the phase deviation and the corresponding elasticity factor.

6. The GNSS satellite clock bias estimation method according to claim 1, characterized in that, Also includes: Based on the satellite clock bias and the multi-frequency non-differential non-combined PPP model, the corresponding ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity are generated, and the uncalibrated phase deviation (UPD) is generated based on the ultra-wide lane ambiguity, wide lane ambiguity and narrow lane ambiguity.

7. The GNSS satellite clock bias estimation method according to claim 6, characterized in that, Also includes: The uncalibrated phase deviation UPD is converted into the target phase deviation OSB using a benchmark unification method.

8. The GNSS satellite clock bias estimation method according to claim 6, characterized in that, Also includes: The satellite clock bias is corrected based on the narrow alley ambiguity, the uncalibrated phase deviation (UPD), and the double-difference ambiguity fixing method to obtain the corrected satellite clock bias and the UPD correction number of the wide alley ambiguity.

9. The GNSS satellite clock bias estimation method according to claim 1, characterized in that, The method of using the atomic clock station as a reference clock includes: The reference clock of the station is expressed by the following formula. : In the formula, For time.

10. The GNSS satellite clock bias estimation method according to claim 1, characterized in that, The method for separating the receiver clock and the satellite clock using a satellite zero-mean reference includes: The zero-mean baseline for satellites is expressed by the following formula: In the formula, For satellite clock bias, For time, For the number of satellites, For satellite indexing, For satellites.

Images