Low earth orbit satellite clock error integrity monitoring method based on batch least square method

Abstract

The invention discloses a low earth orbit satellite clock error integrity monitoring method based on a batch least square method, which solves the problem of lack of integrity monitoring for low earth orbit satellite clock error calculated by an efficient batch least square method in the prior art, and comprises the following steps: determining an observation noise upper bound and an SISRE error decomposition upper bound; constructing an observation upper bound covariance matrix of each epoch according to the data and GNSS observation data; combining the data and the constraint equation to obtain a complete upper bound covariance matrix; calculating according to the complete upper bound covariance matrix and the first design matrix to obtain an upper bound covariance matrix and an upper bound standard deviation of all unknown numbers; according to the projection matrix from the observation domain to the result domain and the SISRE upper bound system deviation, the maximum deviation influence and the upper bound deviation of all unknown numbers are obtained through calculation; according to the upper bound standard deviation and the upper bound deviation, the protection level of the low earth orbit satellite clock error is calculated; and comparing the protection level with the low earth orbit satellite clock error alarm threshold to complete low earth orbit satellite clock error integrity monitoring.

Description

Technical Field

[0001] The present invention relates to the field of communication, navigation and remote sensing technology, and in particular to a method for monitoring the clock error integrity of low-orbit satellites based on a batch least squares method. Background Art

[0002] Thanks to the low altitude, high speed, and low cost of low-orbit satellites, low-orbit enhanced GNSS (Global Navigation Satellite System) positioning, navigation, and timing have garnered increasing attention in recent years due to their advantages, including strong signal strength, fast convergence time, and multipath noise reduction. To better utilize low-orbit navigation signals for high-precision, real-time positioning and timing on the ground, precise and reliable LEO satellite clock error products are a crucial prerequisite and guarantee. Their integrity is also the foundation for future LEO enhanced GNSS ground positioning, navigation, and timing integrity monitoring.

[0003] Existing general integrity monitoring methods typically perform standard single-point positioning based on the smoothed pseudoranges used in civil aviation. These include the Advanced Receiver Autonomous Integrity Monitoring Algorithm (ARAIM), which relies on broadcast ephemeris solutions, and the DFMC SBAS (Dual-Frequency Multi-Constellation Satellite-Based Augmentation System) integrity monitoring algorithm, which uses precise star clock ephemeris solutions for dual-frequency multi-system SBAS (Satellite-Based Augmentation System). The algorithm calculates the protection level of the aircraft's positioning results based on a pre-determined integrity risk and compares it with an alarm threshold. If the protection level exceeds the alarm threshold, the system is deemed unavailable, and an alert is issued to the system and users.

[0004] Integrity monitoring algorithms for ground-based precise point positioning (PGP) and RTK (Real-Time Kinematic Positioning) and PPP-RTK (Precise Point Positioning – Real-Time Kinematic) positioning using carrier phase observations have also been studied in recent years. Currently, there are no standard examples like those used in civil aviation. Multiple civil aviation integrity monitoring algorithms calculate the protection level of ground positions. Some studies are based on the characteristics of carrier phase observations that distinguish them from pseudorange observations, taking into account the risk of bias propagation and integer ambiguity fixation in filtering.

[0005] Current solutions for precise, real-time timing of low-orbit satellites based on carrier phase and pseudorange often rely on Kalman filtering, taking into account the propagation of biases within the filter. However, while Kalman filtering-based timing for low-orbit satellites fully meets real-time requirements, its accuracy is often inferior to that of batch least squares timing. The propagation of biases within the filter also often results in lower protection level performance. In applications with less stringent real-time requirements, such as those where lags of several minutes or even hours are tolerated, clock errors calculated using batch least squares are more accurate and stable.

[0006] Current technology supports LEO satellite orbit determination integrity monitoring methods based on batch least squares, but not LEO satellite clock error integrity monitoring methods. As a key step in time synchronization with the ground and other satellites in both high and low orbits, LEO satellite clock error calculations require not only accuracy but also security and reliability, which are essential steps after clock error parameter calculation. Calculating the protection level supports a series of subsequent safety-related decisions, such as the availability and health of clock error products. Therefore, a LEO satellite clock error integrity monitoring method based on batch least squares is urgently needed. Summary of the Invention

[0007] The present invention provides a method for monitoring the integrity of low-orbit satellite clock errors based on the batch least squares method, thereby solving the problem in the prior art of the lack of specialized integrity monitoring for low-orbit satellite clock errors solved by the efficient batch least squares method. The method achieves near-real-time calculation of the protection level of the low-orbit satellite clock error solution result and compares it with the alarm threshold, and issues an alarm when the alarm threshold is exceeded.

[0008] The present invention provides a method for monitoring the clock error integrity of low-orbit satellites based on a batch least squares method, the method comprising: Determine the upper bound of the observation noise and the upper bound of the SISRE (Signal-In-Space Range Error) error decomposition; wherein the upper bound of the observation noise includes: the upper bound standard deviation of the carrier phase noise and the upper standard deviation of pseudorange noise The upper bound of the SISRE error decomposition includes: the upper bound standard deviation of the SISRE random noise formed by the GNSS orbit clock error , the upper bound systematic bias of SISRE formed by GNSS orbit clock error ; According to the upper bound of the observation noise and the standard deviation of the upper bound of the SISRE random noise and real-time onboard GNSS observation data of low-orbit satellites to construct the upper bound covariance matrix of observations for each epoch ; Combine the observation upper bound covariance matrix of each epoch and the constraint equations of some dynamic parameters to obtain the complete upper bound covariance matrix ; Construct the first design matrix , according to the complete upper bound covariance matrix and the first design matrix Calculate the upper bound covariance matrix of all unknowns , and obtain the upper bound covariance matrix of all unknowns of low-orbit satellites in each epoch ; According to the projection matrix from the observation domain to the result domain and the SISRE upper bound systematic deviation , calculate the maximum deviation effect of all unknowns , and extract the upper bound deviation of the low-orbit satellite clock error of each epoch ; According to the upper standard deviation of the low-orbit satellite clock error of each epoch and the upper bound deviation of the clock error of each epoch Calculate the protection level of low-orbit satellite clock error ; Determine the protection level and low-orbit satellite clock error alarm threshold Complete low-orbit satellite clock error integrity monitoring.

[0009] The present invention provides conservative error quantification limits by determining the upper bound of observation noise and the upper bound of SISRE error decomposition, ensuring that the integrity calculation is within a preset safety range and enhancing the reliability of the system. The observation upper bound covariance matrix of each epoch is constructed to quantify the uncertainty of the observation data, provide an accurate statistical basis for real-time satellite data, and improve the accuracy of subsequent processing. Combining the observation upper bound covariance matrix of each epoch and the constraint equations of some dynamic parameters, a complete upper bound covariance matrix is ​​obtained to reduce the estimation bias and improve the integrity and robustness of the covariance estimation. A first design matrix is ​​constructed, and the upper bound covariance matrix of all unknowns is calculated based on the complete upper bound covariance matrix and the first design matrix, and the upper bound standard deviation of the low-orbit satellite clock error of each epoch is obtained. The error is converted to the clock error dimension to facilitate the direct evaluation of the integrity contribution, and the upper bound standard of the low-orbit satellite clock error of each epoch is extracted to provide input for calculating the protection level of the low-orbit satellite clock error. Based on the projection matrix from the observation domain to the result domain and the SISRE upper bound systematic bias, the maximum bias impact of all unknowns is calculated. The upper bound bias of the LEO satellite clock error at each epoch is extracted to capture the systematic bias effect and quantify potential risks. The upper bound bias of the LEO satellite clock error at each epoch provides a bias component for the protection level. The protection level of the LEO satellite clock error is calculated based on the upper bound standard deviation and upper bound bias of the LEO satellite clock error at each epoch, ensuring the comprehensiveness of the integrity assessment. The protection level and the LEO satellite clock error alarm threshold are determined to enable automatic fault monitoring, promptly detect clock error anomalies, and safeguard the integrity of LEO satellite navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flowchart of the steps of a method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0011] 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 them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0012] A method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method, see Figure 1 The method includes the following steps S101 to S106.

[0013] S101, determining an upper bound on observation noise and an upper bound on SISRE error decomposition; wherein the upper bound on observation noise includes: an upper bound standard deviation on carrier phase noise and an upper bound standard deviation on pseudorange noise; and the upper bound on SISRE error decomposition includes: an upper bound standard deviation on SISRE random noise formed by GNSS orbit clock error and an upper bound systematic bias on SISRE formed by GNSS orbit clock error; Among them, the upper standard deviation of the carrier phase noise is expressed as: ; The upper standard deviation of pseudorange noise is expressed as: The upper standard deviation of the SISRE random noise formed by the GNSS orbit clock error is expressed as: The upper bound systematic deviation of SISRE formed by GNSS orbit clock error is expressed as: ; For example, the carrier phase and pseudorange observation noise, and the multipath effect of low-orbit satellites in an open environment are characterized as noise, and the upper standard deviation is the upper standard deviation of the pseudorange noise. and the upper standard deviation of the carrier phase noise , which can be defined based on empirical data. The GNSS real-time orbit clock error is qualitatively divided into noise and bias. The upper standard deviation of the random noise of SISRE formed by the GNSS orbit clock error of its combined product SISRE is determined based on empirical data using a two-step method. and the SISRE upper bound systematic bias formed by GNSS orbit clock error , the present invention only protects the above threat sources.

[0014] S102, constructing the observation upper bound covariance matrix of each epoch based on the observation noise upper bound, the standard deviation of the SISRE random noise upper bound, and the real-time onboard GNSS observation data of the low-orbit satellite; Among them, the upper bound standard deviation of SISRE random noise is expressed as: ; The upper bound covariance matrix of observations at each epoch is expressed as: ; Here, the upper bound covariance matrix of the observations at each epoch is Expressed as: (1); in, represents a block diagonal matrix; Indicates the The weight matrix related to the elevation angle of the first GNSS satellite at the moment; Represents matrix inversion operation; represents the combined expansion factor for the ionosphere-free combination; represents the upper bound standard deviation of the carrier phase noise of the first GNSS satellite; represents the upper bound standard deviation of the SISRE random noise of the first GNSS satellite; Indicates the Moment The weight matrix related to the GNSS satellites and elevation angles; No. The upper standard deviation of the carrier phase noise of each GNSS satellite; Indicates the The upper bound standard deviation of the SISRE random noise of each GNSS satellite; represents the upper standard deviation of the pseudorange noise of the first GNSS satellite, Indicates the The upper standard deviation of the pseudorange noise of GNSS satellites.

[0015] In the method provided by the present invention, in addition to observation, in order to avoid rank deficiency, some dynamic parameters (such as random acceleration) in the solution parameters need to be constrained to 0, and a certain weight is given to the constraint (the upper bound form standard deviation is set to ), and construct its covariance matrix .

[0016] For example, the divisor of random acceleration is 0, which is expressed as: (2); in, Indicates the number of dynamic parameters that need to be constrained.

[0017] S103, combining the upper bound covariance matrix of observations at each epoch and the constraint equations of some dynamical parameters to obtain a complete upper bound covariance matrix; wherein the upper bound covariance matrix of observations at each epoch is expressed as: ; The complete upper bound covariance matrix is ​​expressed as: ; Here, the upper bound covariance matrix of the constraint equations for some dynamic parameters is expressed as: (3); in, Indicates the length is The identity matrix of Indicates the number of dynamic parameters that need to be constrained; represents the upper bound constraint variance of some kinetic parameters; Represents the upper bound covariance matrix of the constraint equation.

[0018] For example, the complete upper bound covariance matrix for all observations is It can be expressed as: (4); in, For all The covariance matrix of the epoch observations is expressed as: (5); in, represents the upper bound covariance matrix of observations at each epoch; Indicates the The observation upper bound covariance matrix corresponding to the moment.

[0019] S104, construct the first design matrix, based on the complete upper bound covariance matrix and the first design matrix Calculate the upper bound covariance matrix of all unknowns , and obtain the standard deviation of the clock error form of each epoch ; Among them, all unknowns are unknowns when solving the low-orbit satellite clock error using batch least squares method; the first design matrix is ​​expressed as: ; The complete upper bound covariance matrix is ​​expressed as: ; Specifically, in step S104, a first design matrix is ​​constructed , according to the complete upper bound covariance matrix and the first design matrix Calculate the upper bound covariance matrix of all unknowns , and obtain the standard deviation of the clock error form of each epoch , including the following steps S1041 to S1043: S1041, constructing the first design matrix including the observation equation and the dynamic approximation , and combined with the complete upper bound covariance matrix, solve the upper bound covariance matrix of all unknowns ; S1042, based on the upper bound covariance matrix of all unknowns , extract the upper bound variance of the low-orbit satellite clock error parameters of each epoch; S1043, calculate the upper bound variance to obtain the upper bound standard deviation of the low-orbit satellite clock error of each epoch .

[0020] For example, to solve the formal standard deviation of the clock error parameter used for integrity calculation, it is necessary to calculate the upper bound covariance matrix of all unknowns of the unknown vector to be solved , specifically expressed as: (6); in, represents the upper bound covariance matrix of all unknowns; represents the first design matrix; Represents the transpose of a matrix; Represents the inverse of the full upper bound covariance matrix.

[0021] Here, the first design matrix , expressed as: (7); in, represents the second design matrix corresponding to the observation equation; represents the third design matrix corresponding to some kinetic parameter constraints; represents the first design matrix.

[0022] Afterwards, The epoch clock error parameters at the moment are used to determine the upper bound covariance matrix of all unknowns of the low-orbit satellite integrity. The upper bound covariance matrix of all unknowns can be obtained The square root of the element corresponding to the epoch clock error parameter is obtained.

[0023] S105, according to the projection matrix from the observation domain to the result domain and SISRE upper bound systematic deviation , calculate the maximum deviation effect of all unknowns , and extract the upper bound deviation of the low-orbit satellite clock error of each epoch ; Specifically, in step S105, based on the projection matrix from the observation domain to the result domain and the SISRE upper bound systematic deviation, the maximum deviation impact of all unknowns is calculated, and the upper bound deviation of the low-orbit satellite clock error of each epoch is extracted, including the following steps S1051 to S1053. The projection matrix is ​​expressed as: ; The upper bound systematic deviation of SISRE is expressed as: ; The maximum deviation effect of all unknowns is expressed as: The upper bound of the low-orbit satellite clock error at each epoch is expressed as: .

[0024] S1051, based on the complete upper bound covariance matrix , the first design matrix and the upper bound covariance matrix , calculate the projection matrix ; Here, the projection matrix Expressed as: (8); S1052, according to the SISRE upper bound system deviation and the projection matrix Calculate the maximum deviation effect of all unknowns ; Here, the maximum deviation of all unknowns affects Expressed as: (9); in, represents the upper bound covariance matrix of all unknowns; represents the first design matrix; Represents the transpose of a matrix; represents the inverse matrix of the complete upper bound covariance matrix; It represents the upper bound systematic deviation of SISRE formed by GNSS orbit clock error.

[0025] S1053, based on the maximum deviation effect of all unknowns Calculate the upper bound deviation of the low-orbit satellite clock error at each epoch .

[0026] For example, as mentioned in S101, the deviation protection of the present invention is caused by the deviation of the real-time GNSS orbit star clock combination error, and its deviation vector is (including the upper bound deviation vector of each system SISRE , the deviation acts on all IF carrier phases and pseudorange observations, forming an impact on the estimated parameters, and the maximum deviation of all unknowns affects , specifically expressed as: .

[0027] Considering that the actual deviation may be positive or negative, the SISRE upper bound system deviation Maximum bias effect on all unknowns It is expressed as formula (9).

[0028] get After that, the deviation is transferred to The influence of the epoch clock error parameter is The upper bound deviation of the low-orbit satellite clock error at each epoch in .

[0029] S106: Calculate the protection level based on the upper bound standard deviation of the LEO satellite clock error at each epoch and the upper bound deviation of the LEO satellite clock error at each epoch. The upper bound standard deviation of the LEO satellite clock error at each epoch is expressed as: The upper bound of the low-orbit satellite clock error at each epoch is expressed as: The upper limit deviation is calculated to obtain the protection level as follows: .

[0030] Specifically, in step S106, the upper limit standard deviation of the clock error of each epoch is calculated. and the upper bound deviation of the low-orbit satellite clock error at each epoch Calculated protection level , including the following steps S1061 to S1062.

[0031] S1061, based on the pre-set integrity risk , calculate the expansion factor ; S1062, according to the expansion factor , the upper bound standard deviation of the low-orbit satellite clock error at each epoch and the upper bound deviation of the low-orbit satellite clock error at each epoch , calculate the protection level .

[0032] Here, the protection level Expressed as: (10); in, represents the expansion factor; Indicates the The upper bound covariance matrix of all unknowns of the low-orbit satellite at the moment; Indicates the The upper bound deviation of the low-orbit satellite clock error at the moment; Indicates the protection level.

[0033] Here, the expansion factor The inverse cumulative distribution function of the integrity risk and the standard normal distribution can be used to The specific calculation formula is expressed as: (11); in, Represents the inverse cumulative distribution function of the standard normal distribution; Indicates the pre-set integrity risk.

[0034] S107: Determine the protection level and the low-orbit satellite clock error alarm threshold to complete the low-orbit satellite clock error integrity monitoring. The protection level is expressed as: ; The low-orbit satellite clock error alarm threshold is expressed as: .

[0035] Specifically, in step S107, the protection level is determined and low-orbit satellite clock error alarm threshold Completing low-orbit satellite clock error integrity monitoring includes the following steps S1071 to S1072.

[0036] S1071, determine the protection level and low-orbit satellite clock error alarm threshold If the protection level Greater than or equal to the low-orbit satellite clock error alarm threshold , then corresponding alarms will be issued for the low-orbit satellite clock error and orbit parameters; S1072, if the protection level Less than the low-orbit satellite clock error alarm threshold , no corresponding alarm will be issued for the low-orbit satellite clock error and orbit parameters.

[0037] The present invention provides conservative error quantification limits by determining the upper bound of observation noise and the upper bound of SISRE error decomposition, ensuring that the integrity calculation is within a preset safety range and enhancing the reliability of the system. The observation upper bound covariance matrix of each epoch is constructed to quantify the uncertainty of the observation data, provide an accurate statistical basis for real-time satellite data, and improve the accuracy of subsequent processing. Combining the observation upper bound covariance matrix of each epoch and the constraint equations of some dynamic parameters, a complete upper bound covariance matrix is ​​obtained to reduce the estimation bias and improve the integrity and robustness of the covariance estimation. A first design matrix is ​​constructed, and the upper bound covariance matrix of all unknowns is calculated based on the complete upper bound covariance matrix and the first design matrix, and the upper bound standard deviation of the low-orbit satellite clock error of each epoch is obtained. The error is converted to the clock error dimension to facilitate the direct evaluation of the integrity contribution, and the upper bound standard of the low-orbit satellite clock error of each epoch is extracted to provide input for calculating the protection level of the low-orbit satellite clock error. Based on the projection matrix from the observation domain to the result domain and the SISRE upper bound systematic bias, the maximum bias impact of all unknowns is calculated. The upper bound bias of the LEO satellite clock error at each epoch is extracted to capture the systematic bias effect and quantify potential risks. The upper bound bias of the LEO satellite clock error at each epoch provides a bias component for the protection level. The protection level of the LEO satellite clock error is calculated based on the upper bound standard deviation and upper bound bias of the LEO satellite clock error at each epoch, ensuring the comprehensiveness of the integrity assessment. The protection level and the LEO satellite clock error alarm threshold are determined to enable automatic fault monitoring, promptly detect clock error anomalies, and safeguard the integrity of LEO satellite navigation.

[0038] The various embodiments in this specification are described in a progressive manner. References to the same or similar parts between the various embodiments are sufficient. Each embodiment focuses on the differences from other embodiments. All or part of the present invention can be used in a variety of general or specialized computer system environments or configurations. For example, personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

[0039] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the present invention.

Claims

1. A method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method, characterized in that: include: Determine the upper bound of observation noise and the upper bound of SISRE error decomposition; wherein the upper bound of observation noise includes: the upper bound standard deviation of carrier phase noise and the upper standard deviation of pseudorange noise The upper bound of the SISRE error decomposition includes: the upper bound standard deviation of the SISRE random noise formed by the GNSS orbit clock error and the SISRE upper bound systematic bias formed by the GNSS orbit clock error ; According to the upper bound of the observation noise and the standard deviation of the upper bound of the SISRE random noise and real-time onboard GNSS observation data of low-orbit satellites to construct the upper bound covariance matrix of observations for each epoch ; express time; Combine the observation upper bound covariance matrix of each epoch and the constraint equations of some dynamic parameters to obtain the complete upper bound covariance matrix ; Construct the first design matrix , according to the complete upper bound covariance matrix and the first design matrix Calculate the upper bound covariance matrix of all unknowns , and obtain the upper bound standard deviation of the low-orbit satellite clock error of each epoch ; Wherein, all the unknowns are the unknowns when solving the low-orbit satellite clock error using batch least squares method; According to the projection matrix from the observation domain to the result domain and the SISRE upper bound systematic deviation , calculate the maximum deviation effect of all unknowns , and extract the upper bound deviation of the low-orbit satellite clock error of each epoch ; According to the upper standard deviation of the low-orbit satellite clock error at each epoch and the upper bound deviation of the low-orbit satellite clock error at each epoch Calculate the protection level of low-orbit satellite clock error ; By comparing the protection level and low-orbit satellite clock error alarm threshold Complete low-orbit satellite clock error integrity monitoring.

2. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 1, characterized in that: The upper bound covariance matrix of the observations for each epoch is Expressed as: ； in, represents a block diagonal matrix; Indicates the The weight matrix related to the elevation angle of the first GNSS satellite at the moment; Represents matrix inversion operation; represents the combined expansion factor for the ionosphere-free combination; represents the upper bound standard deviation of the carrier phase noise of the first GNSS satellite; represents the upper bound standard deviation of the SISRE random noise of the first GNSS satellite; Indicates the Moment The weight matrix related to the GNSS satellites and elevation angles; Indicates the The upper standard deviation of the carrier phase noise of each GNSS satellite; Indicates the The upper bound standard deviation of the SISRE random noise of each GNSS satellite; represents the upper standard deviation of the pseudorange noise of the first GNSS satellite; Indicates the The upper standard deviation of the pseudorange noise of GNSS satellites.

3. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 1, characterized in that: The upper bound covariance matrix of the constraint equation is expressed as: ； in, Indicates the length is The identity matrix of Indicates the number of dynamic parameters that need to be constrained; represents the upper bound constraint variance of some kinetic parameters; Represents the upper bound covariance matrix of the constraint equation.

4. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 1, characterized in that: Constructing the first design matrix , according to the complete upper bound covariance matrix and the first design matrix Calculate the upper bound covariance matrix of all unknowns , and obtain the upper bound standard deviation of the low-orbit satellite clock error of each epoch ,include: Construct the first design matrix including observation equations and dynamic constraint equations , and combined with the complete upper bound covariance matrix , solve the upper bound covariance matrix of all unknowns ; According to the upper bound covariance matrix of all unknowns , extract the upper bound variance of the low-orbit satellite clock error parameters of each epoch; The upper bound variance is calculated to obtain the upper bound standard deviation of the low-orbit satellite clock error of each epoch .

5. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 4, characterized in that: The first design matrix , expressed as: ； in, represents the second design matrix corresponding to the observation equation; represents the third design matrix corresponding to some kinetic parameter constraints; represents the first design matrix.

6. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 1, characterized in that: The projection matrix from the observation domain to the result domain and the SISRE upper bound systematic deviation , calculate the maximum deviation effect of all unknowns , and extract the upper bound deviation of the low-orbit satellite clock error of each epoch ,include: According to the complete upper bound covariance matrix , the first design matrix and the upper bound covariance matrix , calculate the projection matrix ; According to the SISRE upper bound systematic deviation and the projection matrix Calculate the maximum deviation effect of all unknowns ; According to the maximum deviation effect of all unknowns Calculate the upper bound deviation of the low-orbit satellite clock error at each epoch .

7. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 6, characterized in that: The projection matrix Expressed as: ； The maximum deviation effect of all unknowns mentioned Expressed as: ； in, represents the upper bound covariance matrix of all unknowns; represents the first design matrix; Represents the transpose of a matrix; represents the inverse matrix of the complete upper bound covariance matrix; represents the projection matrix; represents the upper bound systematic deviation of SISRE; Represents the maximum bias effect of all unknowns.

8. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 6, characterized in that: The upper standard deviation of the low-orbit satellite clock error of each epoch and the upper bound deviation of the low-orbit satellite clock error at each epoch Calculate the protection level of low-orbit satellite clock error ,include: According to the pre-set integrity risk , calculate the expansion factor ; According to the expansion factor , the upper bound standard deviation of the low-orbit satellite clock error at each epoch and the upper bound deviation of the low-orbit satellite clock error at each epoch , calculate the protection level .

9. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 8, characterized in that: The protection level Expressed as: 。 10. The method for monitoring the clock error integrity of low-orbit satellites based on batch least squares method according to claim 1, characterized in that: The protection level is compared with the and low-orbit satellite clock error alarm threshold Complete low-orbit satellite clock integrity monitoring, including: If the protection level Greater than or equal to the low-orbit satellite clock error alarm threshold , then the low-orbit satellite clock error parameters will be warned accordingly; If the protection level Less than the low-orbit satellite clock error alarm threshold , then no corresponding alarm will be issued for the low-orbit satellite clock error parameters.

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