Autonomous monitoring method and device for GNSS receiver

Abstract

The invention discloses an autonomous monitoring method for a GNSS receiver, relates to the technical field of monitoring, aims at fault detection and elimination in a multi-constellation GNSS system and testing of simulation data, and compared with an existing snapshot weighted least squares (WLS) algorithm, the method has the advantages that a position solution generated by ARAIM is smaller in error and better in performance, and the accuracy of the position solution generated by ARAIM is improved. And the capability of the fault detection and elimination method is also good. In addition, the invention also discusses the horizontal and vertical protection levels of the ARAIM algorithm and the position information difference between the ARAIM algorithm and a simulation true value, and analyzes the influence of the troubleshooting method on the performance of the whole ARAIM algorithm. The invention further discloses a GNSS receiver autonomous monitoring device, the method for recognizing fault occurrence, recognizing a fault satellite and eliminating data related to the satellite is added, and the GNSS receiver autonomous monitoring method is suitable for the period when the fault is detected. The research result of the invention provides an important basis for the further development of the robust GNSS processing technology in the future.

Description

Technical Field

[0001] This invention relates to the field of monitoring technology, and in particular to a method and apparatus for autonomous monitoring of a GNSS receiver. Background Technology

[0002] With the rapid development of research fields such as smart cities and precision navigation, industry standards and requirements for Location Based Services (LBS) are becoming increasingly stringent. As an absolute positioning system based on satellite radio navigation, the Global Navigation Satellite System (GNSS) can provide global users with all-weather, high-precision information such as position, speed, and time. Therefore, it has wide applications in fields such as vehicle navigation, surveying and mapping, geological exploration, target tracking, precision agriculture, and military.

[0003] The Global Positioning System (GPS) was developed in the 1960s and officially applied to civil aviation in 1994 when the first GPS device was approved for use in civilian flights. The approval of this GPS receiver comes with regulations and standards that must be followed, including integrity, i.e., the reliability of the measured data. Receiver Autonomous Integrity Monitoring (RAIM) is a method used to determine the integrity of the position solution. Initially, this technology was used for stable flight, but over time and with technological advancements, RAIM has been considered for more complex flight situations. These flight situations primarily include precision approaches and landings, which have more stringent requirements for navigation errors and subsequent horizontal and vertical protection limits. The Galileo and GLONASS satellite constellations, created by the European and Russian governments, can be used in conjunction with the GPS constellation to form a larger Global Navigation Satellite System (GNSS).

[0004] Previously, the ARAIM method only covered single-fault scenarios, while multiple faults required resolution by the airborne receiver. The ARAIM algorithm, however, adds the ability to utilize multiple constellations, correct for multiple fault scenarios, and improve vertical accuracy. Using multiple constellations also increases the possibility of constellation-wide failures, necessitating the exclusion of all satellites in the constellation, which also needs to be considered. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a method and device for autonomous monitoring of GNSS receivers. The present invention adds a method for identifying the occurrence of faults, identifying faulty satellites and excluding data related to the satellites, which is applicable to the period when faults are detected.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] In a first aspect, a GNSS receiver autonomous monitoring device includes a WLS module, a detection threshold calculation module, a fault detection module, a fault troubleshooting module, and a PL calculation module, wherein...

[0008] The WLS module is used to calculate the complete solution and fault mode solution of the positioning coordinates under different assumptions by using the error model provided by pseudorange measurements and integrity support messages (ISM) and weighted least squares.

[0009] The detection threshold calculation module is used to calculate the variance of the residual between the global solution and the solution for each fault mode, and to calculate the threshold T for the k-th fault mode in the q-direction based on this variance. k,q Where 1≤k≤K, 1≤q≤3, K is the total number of fault modes, q=1 represents east, q=2 represents north, and q=3 represents the direction of the sky; T k,q Output to the fault detection module;

[0010] The fault detection module is used to detect faults based on T. k,q Determine if a fault exists: If Then there is no fault, if This indicates either a single satellite failure or a failure of the entire satellite constellation; if a failure exists, the faulty satellite will be output to the troubleshooting module; among which, For the k-th fault mode, the fault mode solution in the q-direction is... τ represents the universal solution; k,q This is the ratio of the difference in the positioning result to the threshold.

[0011] The troubleshooting module is used to remove a faulty satellite from the current positioning calculation after it is identified, so that the faulty satellite will not participate in the positioning calculation for this epoch.

[0012] The PL calculation module is used to calculate the protection level after fault detection, based on the variance of the total set solution, the fault mode solution, and the residual between the total set solution and each fault mode solution. The protection level includes the horizontal protection level HPL and the vertical protection level VPL. The horizontal protection level HPL is calculated in the east and north directions, while the vertical protection level VPL is calculated in the sky direction.

[0013] Secondly, a method for autonomous monitoring of a GNSS receiver includes:

[0014] Using pseudorange measurements and the error model provided by the Integrity Support Message (ISM), the global solution and the failure mode solution are calculated by weighted least squares estimation.

[0015] Calculate the variance of the residuals between the universal solution and the solution for each failure mode, and then calculate the threshold T in the three directions based on this variance. k,q T k,q The output is sent to the fault detection module, with three directions: east, north, and sky.

[0016] The protection level is calculated based on the variance of the total set solution, the fault mode solution, and the residual between the total set solution and each fault mode solution. The protection level includes the horizontal protection level (HPL) and the vertical protection level (VPL). The horizontal protection level (HPL) is calculated in the east and north directions, while the vertical protection level (VPL) is calculated in the sky direction.

[0017] According to T k,q Determine if a fault exists: If Then there is no fault, if If a single satellite or the entire satellite constellation is faulty, then the minimum chi-square statistic is determined based on the protection level to detect the faulty satellite, and the faulty satellite is output to the fault troubleshooting module.

[0018] Once a faulty satellite is identified, all data from that satellite is removed, and it is no longer used for positioning.

[0019] As a further optimization of the autonomous monitoring method for GNSS receivers described in this invention,

[0020] The weight matrix is ​​formed using the diagonal covariance matrix of pseudorange error, taking into account the covariance matrix of user error, the standard deviation of clock error and ephemeris error, and tropospheric delay. The standard deviation of clock error and ephemeris error is provided by ISM.

[0021] The weight matrix W is calculated by inverting the error covariance matrix; then the residual Δx is obtained by weighted least squares estimation.

[0022] Δx=(G T WG) -1 G T WΔρ

[0023] Where G is the Jacobi matrix, i.e., the partial derivative of the pseudorange with respect to different directions, the superscript T indicates the matrix transpose, and Δρ is the pseudorange difference;

[0024] The residual Δx formed by a specific equation that provides the initial matrix is ​​considered the universal solution. The universal solution is also used as the basis for forming the solution for each failure mode. A subset of solutions representing failure modes is systematically formed by removing one satellite at a time and re-performing the least squares estimation.

[0025] As a further optimization of the autonomous monitoring method for GNSS receivers described in this invention, in the detection threshold calculation module...

[0026] The covariance is calculated to compute the S matrix, which represents the change in satellite position from the previous time step to the current time step. This change is calculated solely based on satellite geometry and is ultimately multiplied by the pseudorange difference to form the residual S for the k-th failure mode. (k) :

[0027] S (k) =(G T W (k) G) -1 G T W (k)

[0028] Where k represents the failure mode, S (k) Variance used to calculate the residual between the complete solution and the failure mode solution.

[0029]

[0030] Where the superscript 0 indicates the solution to the universal set; e q C represents a vector where the q-th element has a value of 1, and all other elements have a value of 0. acc For the accuracy nominal error model, S (0) The residuals in the full solution mode;

[0031] After calculating the variance of the corresponding distance between the universal solution and the solution for each failure mode, a threshold is calculated and corresponding tests are performed. Thresholds and tests are calculated for all three directions, with different coefficients to be calculated for each direction. K fa,1 K fa,2 K fa,3 These are the coefficients for the eastward, northward, and celestial directions, respectively; the eastward and northward directions have the same coefficient. The calculation is as follows:

[0032]

[0033]

[0034] Where Q represents the quantile of a Gaussian distribution with zero mean and unit variance, and N... fault P represents the number of possible failure modes. FA_HOR and P FA_VERT The allowable integrity budgets for the horizontal and vertical directions are respectively calculated; then the threshold T is calculated. k,q And calculate the ratio τ k,q Conduct the test:

[0035]

[0036]

[0037] Among them, K fa,q The scaling factor in the q direction;

[0038] If the above test fails, the detected faulty satellite must be excluded from the positioning and the epoch must be repositioned; the fault exists in one of two forms: a single satellite fault or the entire satellite constellation is considered faulty; if the above test passes, the horizontal and vertical protection limits of the position solution are calculated.

[0039] As a further optimization of the autonomous monitoring method for GNSS receivers described in this invention,

[0040] In the PL calculation module, protection limits are defined for each direction. Horizontal protection limits are calculated in the east and north directions, while vertical protection limits are calculated in the vertical direction, which refers to the upward direction. The horizontal and vertical protection limits are calculated by solving the following equations to determine the HPL and VPL:

[0041]

[0042] Wherein, the superscript k indicates the current fault mode; the superscript 0 indicates the complete solution; the subscript q indicates the current direction, with q represented by 1 and 2 for the east and north directions, and 3 for the perpendicular direction; T k,3 Indicates the detection threshold; These represent the deviations in the full solution mode and the fault mode, respectively, indicating the worst-case impact on the location solution. These represent the horizontal residuals and vertical residuals under the full solution mode, and the horizontal residuals and standard deviation of the vertical residuals under the failure mode, respectively, N. faultmodes P represents the number of possible failure modes. sat,not monitored and P const,notmonitored PHMI represents the probability that a satellite or constellation is not properly monitored at an epoch. VERT and PHMI HOR It is the integrity budget in the vertical and horizontal directions, where Q represents the quantile of the zero-mean, unit-variance Gaussian distribution, and p fault,k It represents the probability of a failure occurring.

[0043] Displayed deviation Calculate using the following equation:

[0044]

[0045] Among them, b nom,i N represents the maximum deviation of the i-th specific satellite under nominal conditions. sat For the number of satellites, Let S be the S matrix under direction q and fault mode k;

[0046] Because the horizontal protection level HPL takes into account measurements in the north-south and east-west directions, HPL1 and HPL2:

[0047]

[0048] As a further optimization of the autonomous monitoring method for GNSS receivers described in this invention, additional values ​​were also calculated, which are the 95% accuracy limit and the fault-free position error limit (10). -7 The effective monitoring threshold (EMT) is as follows:

[0049] accuracy (95%) = K ACC σ v,acc

[0050] faultfree(10 -7 ) = K FF σ v,acc

[0051] EMT = max(T) k,3 )

[0052] Among them, K ACC K FF It is a pre-defined variable, σ v,acc It is the standard deviation of the solution at the vertical position, σ v,acc The calculation is performed using the following equation:

[0053]

[0054] As a further optimization of the autonomous monitoring method for GNSS receivers described in this invention,

[0055] In the fault detection module, the minimum chi-square statistic is determined from the available fault modes to detect the fault. The relationship between maximum normalized dissociation and the minimum chi-square statistic is as follows:

[0056]

[0057] Where, χ 2 This represents the chi-square statistic; This represents the chi-square statistic calculated after excluding the i-th specific satellite. This represents the chi-square statistics in the q direction after excluding satellite i. This represents the chi-square statistics in the q direction under the complete solution mode. This represents the statistical variance in the q direction after excluding satellite i;

[0058] The chi-square statistic for each failure mode is calculated via a rank-one update using the same method as the location solution and covariance matrix updates:

[0059]

[0060] As a further optimization of the autonomous monitoring method for GNSS receivers described in this invention, in the fault troubleshooting module, after identifying the faulty satellite, all its data are excluded from the variables used to calculate the position solution, and the solution for all visible data is recalculated.

[0061] A computer device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps of the autonomous monitoring method for a GNSS receiver as described above.

[0062] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the GNSS receiver autonomous monitoring method described above.

[0063] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0064] (1) The performance of this method is compared with the location solution generated by the conventional WLS algorithm. Compared with the provided true location, the location solution generated by ARAIM has smaller error and performs better. Specifically, ARAIM can reduce multipath and geometric errors, which have an adverse effect on the WLS location solution.

[0065] (2) The positioning performance of the ARAIM method was further measured by calculating the protection level and it was found that it fully meets the requirements of ICAO SARPs.

[0066] (3) The fault detection and elimination capabilities of the ARAIM method were also verified. Direct testing showed that a 10-meter fault injected into the carrier smoothing pseudorange data could be successfully detected and eliminated. Tests showed that faults larger than 10 meters could always be detected and eliminated, while faults smaller than 10 meters were sometimes missed. Although several false eliminations occurred, these false eliminations were caused by errors due to geometric changes, thus further demonstrating the capability of ARAIM. Attached Figure Description

[0067] Figure 1 This is a schematic diagram illustrating the steps involved in using the ARAIM method. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0069] The core idea of ​​this invention is to create unique fault modes for each satellite and constellation using the deconstruction RAIM technique. Each fault mode is calculated by comparing the impact of a specific satellite on the position solution with the difference between the total solution and the total solution. If a fault is detected, the satellite farthest from the total solution is considered the faulty satellite. Data from this faulty satellite is excluded from the current time period's data, and the total solution is reconstructed and evaluated. Although the position solution results from deconstruction and residual-based RAIM are the same, they differ fundamentally. The deconstruction method provides a better level of protection and can handle a variety of faults because it establishes a test threshold, chi-square test statistic, and protection level for the data.

[0070] Figure 1 It demonstrates how the method works and how the results of the previous step, the value of ISM, and the set budget value flow into the next step.

[0071] This method includes the following steps:

[0072] (1) WLS module

[0073] The solution, residuals, and corresponding covariance were calculated using the least squares method. These calculations employed a geometric matrix, pseudorange measurements, and a weighting matrix. The weighting matrix was formed using the diagonal covariance matrix of the pseudorange error. This matrix considered the covariance matrix of the user error, the standard deviations of clock and ephemeris errors, and the tropospheric delay. The standard deviations of clock and ephemeris errors were provided by ISM.

[0074]

[0075]

[0076] The inverse of this covariance matrix is ​​used to compute the weighted matrix. Then, this geometric matrix and the pseudo-distance difference can be used to form the residuals through weighted least squares estimation.

[0077] Δx=(G T WG) -1 G T WΔρ

[0078] G is the Jacobian matrix, and W is the weighting matrix. The residuals formed by a specific equation providing the initial matrix are considered the universal solution. This is a solution that includes all visible satellites, which, if considered fault-free, satisfy integrity and can therefore be trusted. The universal solution is also used as the basis for forming solutions for each fault mode.

[0079] Once the "principal solution" is formed in the full set of solutions, subset solutions representing possible failure modes can be generated. These solutions are systematically formed by removing one satellite at a time and re-performing least-squares estimation. The difference between the full set solution and the subset solution after removing satellites is calculated. The following equations illustrate the position update and covariance update:

[0080]

[0081] In the above formula, lowercase letters g and w represent the data portion generated by the i-th satellite.

[0082] (2) Detection threshold calculation module

[0083] Next, the covariance is calculated to compute the S matrix, which represents the difference in satellite position from the previous time step. This is calculated solely based on satellite geometry and finally multiplied by the pseudorange difference to form the residuals. In the equations below, k represents the failure mode under consideration:

[0084]

[0085] The result of this calculation is then used to calculate the variance of the residuals between the global solution and the failure mode solution, as shown below.

[0086]

[0087] After calculating the variance of the distance between the universal solution and the solution for each failure mode, the threshold can be calculated and the corresponding test performed. Thresholds and tests are calculated for all three directions, with different coefficients required for each direction; the coefficients for the east and north directions are the same.

[0088]

[0089]

[0090] The threshold T can then be calculated and tested using the following method:

[0091]

[0092]

[0093] If the above equations fail the test, the data must be excluded because a fault exists. The fault may exist in one of two forms: a single satellite failure or the entire satellite constellation being considered faulty; if the above tests pass, the horizontal protection limits, vertical protection limits, and other performance parameters of the position solution can be calculated.

[0094] (3) PL Calculation Module

[0095] Similar to calculating test thresholds, protection limits are defined per direction. Horizontal protection limits are calculated in the east and north directions, while vertical protection limits are calculated in the sky direction. The horizontal and vertical protection limits can be calculated by solving the following equations to determine the variables HPL and VPL:

[0096]

[0097] In the above formula, σ represents the variance calculated in a given direction, and P sat,not monitored and P const,notmonitored PHMI represents the probability that a satellite or constellation is not properly monitored at that epoch. VERT and PHMI HOR It is the integrity budget in the vertical and horizontal directions, and Q represents the quantile of the zero-mean, unit-variance Gaussian distribution. These represent the deviations in the full solution mode and the fault mode, respectively, indicating the worst-case impact on the location solution. These represent the standard deviations of the horizontal and vertical residuals under the full solution mode, and the horizontal and vertical residuals under the failure mode, respectively; p fault This represents the probability of a fault occurring. The subscripts and superscripts k, q, and 0 used in the first two equations represent the current fault mode, current direction, and global solution, respectively. The displayed deviation and fault probability variables can be calculated using the following equations:

[0098]

[0099] Since the horizontal protection level takes into account measurements in both the north-south and east-west directions, it must be calculated as follows:

[0100]

[0101] In addition to these protection levels, other performance criteria can be found using the generated solution. Additional values ​​calculated in this algorithm are the 95% accuracy limit, the fault-free location error limit, and the effective monitoring threshold (EMT), as follows:

[0102] accuracy (95%) = K ACC σ v,acc

[0103] faultfree(10 -7 ) = K FF σ v,acc

[0104] EMT = max(T) k,3 )

[0105]

[0106] In the first two equations, the variable K is a preset value that can be adjusted before running the algorithm. σ v,acc It is the standard deviation of the solution at the vertical position.

[0107] (4) Fault detection module

[0108] If the above threshold test is not passed, a fault is considered to exist. To detect this fault, the minimum chi-square statistic must be determined from the available fault modes. The relationship between maximum normalization dissociation and the minimum chi-square statistic is shown below.

[0109]

[0110] Where, χ 2 This represents the chi-square statistic; This represents the chi-square statistic calculated after excluding the i-th specific satellite. This represents the chi-square statistics in the q direction after excluding satellite i. This represents the chi-square statistics in the q direction under the complete solution mode. This represents the statistical variance in the q direction after excluding satellite i;

[0111] Since this is an effective strategy for detecting single satellite faults, in this algorithm, multiple faulty satellites can be detected by running the dataset multiple times for testing and fault detection and then elimination steps until the test of the complete solution passes.

[0112] The chi-square statistic for each failure mode can be calculated using the same method as the location solution and covariance matrix update, via rank-one correction.

[0113]

[0114] In the above formula, lowercase g and w represent the data portions generated by the i-th satellite. The result of this calculation produces the chi-square statistic for all visible data, with the contribution of suspected faulty satellites subtracted.

[0115] (5) Troubleshooting module

[0116] Once a faulty satellite is identified, all its data must be excluded from the variables used to calculate the position solution, and the solution for all visible data needs to be recalculated. A very simple approach is used to exclude data from the selected satellite. A method is written that uses a stored faulty satellite index to remove all data for that satellite from the necessary variables. When constructing new data, it is crucial to ensure that the correct satellite data is removed and that this data is also removed from all data used in subsequent steps to rerun the integrity test. To ensure this, the faulty satellite index and the variable sizes before and after exclusion are specifically displayed during testing.

[0117] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps of the autonomous monitoring method for a GNSS receiver according to any embodiment.

[0118] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the autonomous monitoring method for a GNSS receiver according to any embodiment.

[0119] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0120] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0121] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0122] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0123] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0124] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A GNSS receiver autonomous monitoring device, characterized in that: It includes a WLS module, a detection threshold calculation module, a fault detection module, a fault elimination module and a PL calculation module, wherein: The WLS module is used to calculate the full set solution and the failure mode solution of the positioning coordinates under different assumptions by using the pseudo-range measurement value and the error model provided by the integrity support message ISM through the weighted least square method; The detection threshold calculation module is used to calculate the variance of the residual between the full set solution and each fault mode solution, and calculate the threshold T of the kth fault mode and q direction based on the variance. k,q , where 1≤k≤K, 1≤q≤3, K is the total number of fault modes, q=1 represents east, q=2 represents north, and q=3 represents the direction of the sky; T k,q Output to the fault detection module; Fault detection module, used to detect k,q Determine whether there is a fault: If There is no fault if If there is a single satellite failure or a whole satellite constellation failure, the faulty satellite is output to the fault elimination module; wherein, is the k-th fault mode and the fault mode solution in the q direction, represents the full set of solutions; τ k,q is the ratio of the positioning result difference to the threshold; The fault elimination module is used to remove the faulty satellite from the current positioning after the faulty satellite is identified, so that the faulty satellite does not participate in the positioning calculation of the current epoch; The PL calculation module is used to calculate the protection level according to the global solution, the fault mode solution, and the variance of the residual between the global solution and each fault mode solution after the fault detection; wherein the protection level includes the horizontal protection level HPL and the vertical protection level VPL, the horizontal protection level HPL is calculated in the east and north directions, and the vertical protection level VPL is calculated in the sky direction.

2. A GNSS receiver autonomous monitoring method, characterized in that: include: Using pseudorange measurements and the error model provided by the integrity support message ISM, the full set solution and the failure mode solution are calculated through weighted least squares estimation; Calculate the variance of the residual between the full set solution and each fault mode solution, and calculate the thresholds T in three directions based on the variance k,q , T k,q Output to the fault detection module, where the three directions are east, north and sky; The protection level is calculated according to the variance of the residual between the full set solution, the fault mode solution and each fault mode solution; wherein the protection level includes the horizontal protection level HPL and the vertical protection level VPL, the horizontal protection level HPL is calculated in the east and north directions, and the vertical protection level VPL is calculated in the sky direction; According to T k,q Determine whether there is a fault: If There is no fault if If there is a single satellite failure or a whole satellite constellation failure, then a minimum chi-square statistic is determined based on the protection level to detect the faulty satellite, and the faulty satellite is output to the fault elimination module; When a faulty satellite is identified, all data of the faulty satellite is removed and it no longer participates in positioning.

3. A GNSS receiver autonomous monitoring method according to claim 2, characterized in that: The weight matrix is ​​formed by using the diagonal covariance matrix of pseudorange errors, taking into account the covariance matrix of user errors, the standard deviations of clock and ephemeris errors, and tropospheric delay, where the standard deviations of clock and ephemeris errors are provided by ISM. The weight matrix W is calculated by inverting the error covariance matrix; then the residual Δx is formed by weighted least squares estimation: Δx=(G T (WG) -1 G T WDr Where G is the Jacobian matrix, i.e., the partial derivative of the pseudorange in different directions, the superscript T represents the matrix transpose, and Δρ is the pseudorange difference; The residual Δx formed by the specific equations providing the initial matrix is ​​considered to be the full set solution, which is also used as the basis for forming the solution for each failure mode, systematically forming subset solutions representing the failure mode by removing one satellite at a time and re-performing the least squares estimation.

4. The GNSS receiver autonomous monitoring method according to claim 2, characterized in that: In the detection threshold calculation module, The covariance is calculated to calculate the S matrix, and the change in satellite position from the previous time step to the current time step, which is calculated only based on the satellite geometry, and finally multiplied by the pseudorange difference to form the residual S for the kth fault mode ( k ): S (k) =(G T W (k) G) -1 G T W (k) Where k represents the failure mode, S( k ) is used to calculate the variance of the residual between the full set solution and the failure mode solution Among them, the superscript 0 represents the full set solution; e q represents a vector whose qth value is 1 and all other values ​​are 0; C acc is the accuracy nominal error model, S( 0 ) is the residual in the full solution mode; After calculating the variance of the corresponding distance between the full set solution and each fault mode solution, the threshold is calculated and the corresponding test is performed. The threshold and test are calculated for all three directions. Each direction has a different coefficient to be calculated, K fa,1 , K fa,2 , K fa,3 They are the coefficients for the east direction, the coefficients for the north direction, and the coefficients for the sky direction. The east direction and the north direction have the same coefficients. The calculation is as follows: Where Q represents the quantile of a zero-mean unit-variance Gaussian distribution, and N fault is the number of possible failure modes, P FA_HOR and P FA_VERT are the integrity budgets allowed in the horizontal and vertical directions respectively; then the threshold T is calculated k,q , and calculate the ratio τ k,q To test: Among them, K fa,q is the proportional coefficient in the q direction; If the above test fails, the detected faulty satellite must be excluded from the positioning and the epoch must be repositioned; the fault exists in one of two forms: a single satellite failure or the entire satellite constellation is considered to be faulty; if the above test passes, the horizontal protection limit and vertical protection limit of the position solution are calculated.

5. The GNSS receiver autonomous monitoring method according to claim 2, characterized in that: In the PL calculation module, the protection limit is defined for each direction. The horizontal protection limit is calculated in the east and north directions, while the vertical protection limit is calculated in the vertical direction, which refers to the sky direction. The horizontal and vertical protection limits are calculated by solving the following equations to calculate HPL and VPL: Wherein, the superscript k indicates the current fault mode; the superscript 0 indicates the full set solution; the subscript q indicates the current direction, the east and north directions are represented by 1 and 2, and the vertical direction is represented by 3; T k,3 represents the detection threshold; are the corresponding deviations in full solution mode and fault mode, respectively, indicating the worst impact on the position solution, They are the horizontal residual and vertical residual in the full solution mode, the horizontal residual and vertical residual standard deviation in the fault mode, and N faultmodes is the number of possible failure modes; P sat,notmonitored and P const,notmonitored They represent the probability that the satellite or constellation is not monitored correctly at the epoch, PHMI VERT and PHMI HOR is the integrity budget in the vertical and horizontal directions, Q represents the quantile of the zero-mean unit variance Gaussian distribution, and p fault,k is the probability of failure occurring; Displayed Deviation Calculated by the following equation: Among them, b nom,i represents the maximum deviation of the i-th specific satellite in the nominal state, N sat is the number of satellites, is the S matrix under direction q and fault mode k; As the horizontal protection level HPL takes into account the measurements HPL1, HPL2 in the north-south and east-west directions:

6. A GNSS receiver autonomous monitoring method according to claim 5, characterized in that: The additional values ​​of the calculation are also calculated, which are the accuracy limit of 95% accuracy (95%), the fault-free position error limit faultfree (10 -7 ) and the effective monitoring threshold EMT, as shown below: accuracy(95%)=K ACC σ v,acc faultfree(10 -7 )=K FF σ v,acc EMT=max(T k,3 ) Among them, K ACC , K FF is a pre-set variable, σ v,acc is the standard deviation of the vertical position solution, σ v,acc The calculation is done by the following equation:

7. The GNSS receiver autonomous monitoring method according to claim 2, characterized in that: In the fault detection module, the minimum chi-square statistic is determined from the available fault modes to detect this fault. The relationship between the maximum normalized solution separation and the minimum chi-square statistic is as follows: Among them, χ 2 represents the chi-square statistic; represents the chi-square statistic calculated after excluding the i-th specific satellite, It represents the chi-square statistic after excluding satellite i in the q direction, represents the chi-square statistic in the q direction in the full solution mode, It represents the statistical variance in the q direction after excluding the i satellite; The chi-square statistic for each failure mode is calculated in the same way as the location solution and covariance matrix update, via a rank-one update:

8. The GNSS receiver autonomous monitoring method according to claim 6, characterized in that: In the troubleshooting module, once the faulty satellite is identified, all its data is excluded from the variables used to calculate the position solution, and the solution for all visible data is recalculated.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the GNSS receiver autonomous monitoring method according to any one of claims 2 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the GNSS receiver autonomous monitoring method according to any one of claims 2 to 7 are implemented.

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