A method for autonomous fault diagnosis and troubleshooting of GNSS terminal

Abstract

The present invention discloses a method for autonomous fault diagnosis and elimination of GNSS terminals based on new information, including the following steps: pre-test data preprocessing; pre-test single-star fault mode inspection; pre-test double-star fault mode inspection; pre-test estimation and overall inspection; when the overall inspection passes, enter the post-test processing link, including: post-test data preprocessing, post-test single-star fault mode inspection, post-test double-star fault mode inspection, post-test estimation and overall inspection; otherwise, there is no need to perform the post-test processing link, but the diagnosis and elimination of faulty satellites are performed according to the conventional RAIM‑FDE method. The present invention effectively overcomes the disadvantage of the conventional RAIM‑FDE method of large amount of calculation, and at the same time effectively overcomes the disadvantage of its only application to the situation of one faulty satellite, and can effectively realize fault detection and elimination under double-star (or even multi-star) faults, significantly improve the efficiency and success rate of observation fault detection, and significantly reduce the power consumption of positioning calculations while improving positioning accuracy.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation and positioning technology, and in particular to a terminal autonomous fault diagnosis and elimination method for GNSS precision positioning. Background Art

[0002] In actual observation, due to various reasons such as environmental occlusion, multipath, interference, etc., GNSS (Global Navigation Satellite System) observations inevitably have large errors or gross errors. If these abnormal observations cannot be accurately and effectively identified, the positioning results will have large deviations, especially for low-cost consumer navigation terminals. Therefore, generally speaking, a threshold value will be set in the positioning solution process. If the residual value of a satellite is higher than the set threshold value, it is considered that the measurement value has a problem, and then it is eliminated so that it does not participate in the equation solution. The detection threshold value is usually set empirically.

[0003] At the same time, after completing the solution of the positioning equation, the residuals are generally tested as a whole, usually using the least square residual method. The least square residual method is a receiver autonomous integrity monitoring (RAIM) algorithm that uses the weighted sum of squares of errors (WSSE) as the detection quantity. It determines the consistency between the various observations by checking whether the value of the weighted sum of squares of errors is too large. If the weighted sum of squares of residuals is greater than the set test threshold, these measurements are inconsistent with each other, which means that some of the measurements are wrong or contain abnormal errors, and the current solution is invalid. Fault diagnosis and elimination, namely RAIM-FDE (Fault Detection and Exclusion), is required.

[0004] A commonly used RAIM-FDE method is the solution separation method. Its basic idea is to assume that only one satellite has an abnormal error among the n observation data, and divide the n (n≥5) observations into n groups, each of which does not contain the i-th observation (i=1,2,…,n). Then, the observation groups after removing the i-th observation are positioned and solved and residuals are checked one by one, and a total of n positioning solutions are performed. If the satellite with the abnormal error does not participate in the solution, the overall test passes, thereby successfully realizing the identification and elimination of faulty data. If all satellites cannot pass the test after traversing, it is considered that the positioning of the current epoch has failed. The disadvantage of this solution separation RAIM-FDE method is that it is very computationally intensive, especially for the joint positioning of multi-satellite systems, and it is only applicable to the case where one satellite fails. For low-cost consumer-grade navigation terminals, the probability of abnormal errors in their observations increases significantly due to multiple reasons such as multipath and signal attenuation. It is even common for multiple observations to have abnormal errors at the same time, which will result in greater RAIM-FDE calculations and energy consumption, longer positioning solution time, and greatly reduced RAIM-FDE effectiveness. Summary of the invention

[0005] In view of this, the present invention provides a terminal autonomous fault diagnosis and troubleshooting method for realizing GNSS precise positioning on a navigation terminal, so as to improve the positioning performance of the GNSS terminal, especially the low-cost consumer-grade navigation terminal.

[0006] The present invention provides a method for autonomously diagnosing and troubleshooting GNSS terminal faults, comprising the following steps:

[0007] Pre-test data preprocessing, calculate n pseudo-range innovation residuals of n satellites;

[0008] Pre-test single satellite fault mode test: for the n pseudo-range innovation residual values, remove one residual value each time, and calculate the standard deviation of the remaining residual value group; perform an outlier test on the obtained series standard deviation to find the faulty satellite and remove the abnormal observation value;

[0009] Pre-test double-satellite fault mode test: for the remaining m pseudo-range innovation residual values, remove 2 residual values ​​each time, and calculate the standard deviation of the remaining residual value group; perform an outlier test on the obtained series of standard deviations to find the faulty satellite and remove the abnormal observations;

[0010] Pre-test estimation and overall test: Based on the satellite pseudo-range innovation residuals marked as normal, the user's three-dimensional coordinates and receiver clock error are estimated; then, the weighted sum of the squares of the residual values ​​of each satellite is tested overall based on the least squares residual method;

[0011] When the overall inspection is passed, the post-inspection processing phase begins, including:

[0012] Based on the user's three-dimensional coordinates obtained in the pre-test estimation step, post-test data preprocessing: calculation of post-test pseudorange innovation residuals; as well as single-satellite fault mode inspection, double-satellite fault mode inspection, post-test estimation and overall inspection;

[0013] Otherwise, there is no need to perform post-processing and the faulty satellite can be diagnosed and eliminated according to the RAIM-FDE method.

[0014] Furthermore, the step of pre-test or post-test data preprocessing includes:

[0015] Based on the pseudo-range observations, the satellite coordinates and satellite clock errors at the time when the satellite signal is transmitted are calculated respectively;

[0016] Calculate ionospheric delay error and tropospheric delay error;

[0017] Correct pseudorange group delay deviation;

[0018] Deduct various error terms including receiver clock error.

[0019] Furthermore, the pseudorange innovation residual is calculated as follows:

[0020]

[0021] In the formula, X r，0 is the user's approximate coordinates, is the approximate clock error of the user receiver; SYS, s, r represent the GNSS navigation system, satellite number and receiver respectively; i represents the carrier frequency of the received signal; P s r,i is the pseudorange observation of receiver r about satellite s at frequency i (m), i.e., code measurement pseudorange; X s is the coordinate of the satellite; c is the speed of light in vacuum; δt s is the satellite clock error at the time of signal transmission (s); I s r,i is the ionospheric delay error of the receiver r with respect to the satellite s on the slant path at frequency i (m); T r s is the tropospheric delay error (m); b s P,i is the pseudorange group delay bias (m) of the current pseudorange observation P; IFB r s is the pseudorange inter-frequency deviation (m) for the GLONASS satellite system using frequency division multiple access FDMA modulation.

[0022] Furthermore, the steps of the single-star fault mode inspection before or after the inspection specifically include:

[0023] In the first iteration of the pre- or post-iterative estimation, the n pseudorange innovation residual values ​​{v s1 、v s2 ,…,v sn}, each time the i-th (i=1, 2, ..., n) pseudorange residual value is removed to obtain n pseudorange residual value groups with a length of n-1;

[0024] Calculate the standard deviation S of the n residual value groups one by one i , and obtain n new interest residual standard deviation values ​​{S1, S2, ..., S n};

[0025] After traversing all satellites, the standard deviation value set of the innovation residual {S1, S2, …, S n} to perform the Laida criterion test, that is, the 3σ criterion test to identify gross errors, where σ is the above numerical set {S1, S2, …, S n}, find the observation of the satellite corresponding to the innovation residual value outside the range of [-3σ, 3σ], mark it as an abnormal observation and remove it, retain the satellite observations that pass the test, and participate in the subsequent pre-test or post-test iterative estimation;

[0026] For the innovation residual standard deviation value set {S1, S2, …, S n} Sort them from small to large, use the Dixon statistical test criterion, and use the range ratio two-sided test method to identify gross errors. Find the observations of the satellite corresponding to the abnormal innovation residual value at a given significance level, mark them as abnormal observations and eliminate them, and retain the satellite observations that pass the test and participate in the subsequent pre-test or post-test iterative estimation.

[0027] Furthermore, the steps of the double-star fault mode inspection before or after the inspection specifically include:

[0028] After completing the single-satellite fault mode detection before or after verification, according to the permutation and combination method, a new residual group is obtained by removing the pseudo-range innovation residual values ​​of the i-th and j-th satellites each time, and a total of residual groups;

[0029] Calculate the standard deviation S one by one i,j , a total of Calculated times The standard deviation S i,j (i=1,…,n;j=1,…,n,i≠j), forming a numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n};

[0030] If a satellite has been successfully marked as abnormal in the above-mentioned single-satellite fault mode test before or after the test, it has been successfully marked and removed and will no longer participate in the dual-satellite fault mode test step;

[0031] After traversing all satellites, the standard deviation value set of the innovation residual {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n} to perform the Laida criterion test, that is, the 3σ criterion test (where σ is the above numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n}) to identify gross errors, find out the observations of the satellite corresponding to the new information residual value outside the range of [-3σ, 3σ], mark them as abnormal observations and remove them, and retain the satellite observations that pass the test and participate in the subsequent pre-test iterative estimation;

[0032] Then, for the above-mentioned new interest residual standard deviation value set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n}Sort them from small to large, use the Dixon statistical test criterion to identify gross errors based on the range ratio two-sided inspection method, find the observations of the two satellite combinations corresponding to the abnormal innovation residual values ​​at a given significance level, mark them as abnormal observations and eliminate them, retain the satellite observations that pass the test, and participate in the subsequent pre-test or post-test iterative estimation.

[0033] Furthermore, the steps of pre-test or post-test estimation and overall test specifically include:

[0034] Based on the two steps of single-satellite fault mode test and dual-satellite fault mode test, assuming that the i-th and j-th satellites have been marked as abnormal, the residual vector of the satellite pseudorange observation marked as normal is obtained The weight matrix corresponding to the observed quantity is P, and the design matrix is ​​B. Then the estimated parameter vector X can be estimated by the following adjustment formula:

[0035]

[0036] in, is the estimated value of X. According to the above formula, the user’s three-dimensional coordinates and the receiver clock error can be estimated;

[0037] After obtaining the prior or posterior estimation results, the weighted sum of squared residuals ∑ WSSE =V TPV is used to test the consistency between the observations:

[0038] At a given significance level, if ∑ WSSE ≤χ 2 (r), then accept the null hypothesis H0, assuming that there is no abnormal error in the observation at this time, and the positioning solution is valid;

[0039] Otherwise, it is considered that the observation contains missed abnormal errors, the current solution is invalid, and RAIM-FDE needs to be further performed to diagnose and eliminate the faulty satellite.

[0040] The present invention provides a method for autonomous fault diagnosis and troubleshooting of GNSS terminals based on new information. By adopting the two-step method of pre-test and post-test estimation, abnormal observation detection and elimination are performed on the new information residual values ​​of pseudo-range positioning before and after the test based on the Laida criterion and the Dixon criterion. The core idea is that if an observation has an abnormal error, its residual value will have a significant "outlier" phenomenon relative to the residual values ​​of other normal observations, and the standard deviation of the observation data group after eliminating the outlier will be significantly smaller than the standard deviation of the observation data group containing the outlier.

[0041] Compared with the prior art, the beneficial effects of the present invention are: (1) the two-step inspection of pre-test and post-test avoids the inaccuracy and incompleteness of the single judgment of the conventional RAIM-FDE method; (2) the success rate of observation fault detection and positioning accuracy are significantly improved; (3) the disadvantage of the conventional RAIM-FDE method of large amount of calculation is effectively overcome, the efficiency of observation fault detection is significantly improved, and the power consumption of positioning calculation can be significantly reduced; (4) the disadvantage of the conventional RAIM-FDE method that it is only applicable to the case of one faulty satellite is effectively overcome, and fault detection and elimination under dual-satellite (or even multi-satellite) faults can be effectively realized; (5) it is more suitable for low-cost consumer-grade navigation terminals. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is a flow chart of an exemplary embodiment according to the present disclosure. DETAILED DESCRIPTION

[0043] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0044] Attached Figure 1 is a flow chart of an exemplary embodiment according to the present disclosure, as shown in Figure 1 As shown, the specific steps include:

[0045] S01: Pre-test data preprocessing and new information calculation

[0046] Based on the pseudorange observations, the satellite coordinates and satellite clock error at the time of satellite signal transmission are calculated respectively, the ionospheric delay error and the tropospheric delay error are calculated, the pseudorange group delay deviation is corrected, and various error terms such as the receiver clock error are deducted to calculate the pre-verification pseudorange innovation residual.

[0047] The GNSS undifferenced raw pseudorange observation equation directly describes the relationship between the raw observations between the satellite and the user and various error sources. It is the most primitive and basic observation model in all GNSS data processing and can be expressed as follows:

[0048]

[0049] Where: SYS, s, r represent the GNSS navigation system (GPS, BDS second-generation and third-generation systems, GLONASS and GALILEO can be represented by G, C2 / C3, R and E respectively), satellite number and receiver; i represents the carrier frequency of the received signal (such as L1 of GPS); P s r,i is the pseudorange observation of receiver r about satellite s at frequency i (m), i.e., code measurement pseudorange; ρ r s is the geometric distance between the satellite and receiver antenna phase centers at the time of signal transmission (m), and: r s =||X s -X r ||, here X s is the coordinate of the satellite, and X r is the user's three-dimensional coordinate to be determined; c is the speed of light in a vacuum (c = 299792458.0 m / s); δt r is the receiver clock error at the time of signal reception (s); δt s is the satellite clock error at the time of signal transmission (s); I s r,i is the ionospheric delay error of the receiver r with respect to the satellite s on the slant path at frequency i (m); T r s is the tropospheric delay error (m); b s P,i is the pseudorange group delay deviation of the current pseudorange observation P (m); ε s r,i is the measurement noise of the pseudorange and other unmodeled error terms (m).

[0050] In addition, IFB in the above formula is the pseudo-range frequency deviation (m) for the GLONASS satellite system using frequency division multiple access FDMA modulation, which will vary with the satellite number s. For GPS, BDS, and GALILEO satellite systems using code division multiple access CDMA modulation, there is no IFB deviation term and it does not need to be considered. In addition, the pseudo-range IFB depends not only on the receiver type, but also on the antenna type and the receiver firmware version. It is difficult to express it with a simple or single model. The pseudo-range IFB can even reach several meters. If the influence of IFB is not considered, then according to However, this will cause systematic deviations in the pseudorange residuals of GLONASS. The existence of pseudorange IFB will reduce the positioning performance of GLONASS to varying degrees. Therefore, taking into account the positioning solution of GLONASS pseudorange IFB will further improve the positioning performance. In view of the influence of IFB, two different models of parameterized estimation processing methods are provided here, namely linear model and quadratic model. Among them, the linear model can be expressed as:

[0051]

[0052] is a common constant, κ R,s Indicates the GLONASS frequency number (from -7 to 6), It indicates the slope of IFB depending on the frequency number, which is an additional parameter to be estimated. The quadratic model can be expressed as:

[0053]

[0054] In the formula, is a common constant, κ R,s Indicates the GLONASS frequency number (from -7 to 6), It indicates the slope of IFB depending on the frequency number, Indicates that IFB depends on the quadratic part of the frequency number, and That is, it is the additional parameter to be estimated at this time.

[0055] Therefore, the pseudorange innovation residual can be calculated as follows:

[0056]

[0057] In the formula, X r,0 is the user's approximate coordinates, is the approximate clock error of the user receiver, and the value at the previous moment can be used directly. In this way, if there are n visible satellites, n pseudorange innovation residual values ​​{v s1 、v s2 ,…,v snTo ensure that the positioning solution can be performed normally, the number of visible satellites n must at least reach the necessary number of observations.

[0058] S02: Single-star failure mode inspection before inspection

[0059] In the first iteration of the a priori iterative estimation, the n pseudorange innovation residual values ​​{v s1 、v s2 ,…,v sn} is divided into n groups, each group does not contain the i-th (i=1,2,…,n)th pseudorange residual value, and each group has n-1 pseudorange residual values. Then, the standard deviation S of the residual group after removing the i-th residual value is calculated one by one i , a total of n calculations are performed to obtain n standard deviations of the innovation residuals {S1, S2, …, S n}.

[0060] After traversing all satellites, firstly calculate the value set of the innovation residual standard deviation {S1, S2, …, S n} to perform the Laida criterion test, that is, the 3σ criterion test (where σ is the above numerical set {S1, S2, …, S n}) to identify gross errors, so as to find the observation of the satellite corresponding to the innovation residual value outside the range of [-3σ,3σ], and mark it as an abnormal observation and remove it. The satellite observations that pass the test are retained and participate in the subsequent pre-test iterative estimation. Then, the above innovation residual standard deviation value set {S1, S2, …, S n}Sort them from small to large, use the Dixon statistical test criterion to identify gross errors based on the range ratio double-sided test method, so as to find the observations of the satellite corresponding to the abnormal innovation residual value under a given significance level α, mark them as abnormal observations and eliminate them, and retain the satellite observations that pass the test and participate in the subsequent pre-test iterative estimation.

[0061] S03: Double-star fault mode inspection before inspection

[0062] After completing the pre-test single-satellite fault mode detection, according to the permutation and combination method, a new set of residual groups is obtained by removing the pseudo-range innovation residual values ​​of the i-th and j-th satellites each time, and the total residual group can be obtained Then calculate the standard deviation S of each residual group. i,j , a total of Calculated times The standard deviation S i,j (i=1,…,n;j=1,…,n,i≠j), forming a numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),nIf a satellite has been successfully marked as abnormal in the above-mentioned single-satellite fault mode test, it has been successfully marked and removed, and does not need to and will no longer participate in the dual-satellite fault mode test step.

[0063] After traversing all satellites, first calculate the value set of the innovation residual standard deviation {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n} to perform the Laida criterion test, that is, the 3σ criterion test (where σ is the above numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n}) to identify gross errors, so as to find the observations of the satellite corresponding to the innovation residual value outside the range of [-3σ,3σ], and mark them as abnormal observations for elimination. The satellite observations that pass the test are retained and participate in the subsequent pre-test iterative estimation. Then, the above innovation residual standard deviation value set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n}Sort them from small to large, use the Dixon statistical test criterion to identify gross errors based on the range ratio two-sided test method, so as to find the observations of the two satellite combinations corresponding to the abnormal innovation residual values ​​under a given significance level α, mark them as abnormal observations and eliminate them, and retain the satellite observations that pass the test and participate in the subsequent pre-test iterative estimation.

[0064] S04: A priori estimation and overall testing

[0065] Based on the above two steps, assuming that the i-th and j-th satellites have been marked as abnormal, the residual vector of the satellite pseudorange observation marked as normal is obtained The weight matrix corresponding to the observed quantity is P, and the design matrix is ​​B. Then the estimated parameter vector X can be estimated by the following adjustment formula:

[0066]

[0067] here, represents the estimated value of X. According to the above formula, the user's three-dimensional coordinates and the receiver clock error can be estimated by using least squares or Kalman filtering.

[0068] The overall test is to determine whether there are abnormal errors in the observed quantity and whether the positioning solution is valid. Given that the corresponding weight matrix of the measurement vector L is P and the residual vector is V, the weighted sum of squares of the residual can be expressed as ∑ WSSE =V TPV. Assume that the measurement error components are independent of each other and have a normal distribution with a mean of 0. At the same time, the weight values ​​ω in the diagonal weight matrix P are s is the standard deviation of the corresponding measurement error σ s The inverse of (i.e. ω s =1 / σ s ), then the statistic ∑ WSSE Subject to χ with r degrees of freedom 2 Distribution. Given a significance level α, if ∑ WSSE ≤χ 2 (r), then accept the null hypothesis H0, that is, the observation does not have abnormal errors, and the positioning solution is considered valid; otherwise, accept the alternative hypothesis H1, that the observation contains abnormal errors.

[0069] Therefore, after obtaining the prior estimation result, the weighted sum of squared residuals ∑ WSSE =V T PV is used to test the consistency between observations. WSSE ≤χ 2 (r), the null hypothesis H0 is accepted, that is, there is no abnormal error in the observation at this time, the positioning solution is valid, and the post-verification processing stage is entered; otherwise, it is considered that there are missed abnormal errors in the observation at this time, and the current solution is invalid. At this time, there is no need to perform post-verification processing, but further perform the conventional RAIM-FDE method to diagnose and eliminate the faulty satellite.

[0070] S05: Post-verification data preprocessing and new information calculation

[0071] After obtaining the result of the pre-test estimation, the post-test estimation step is performed. In the present disclosure, each post-test processing step adopts the same method as the corresponding pre-test step.

[0072] Similarly, based on the pseudorange observations, the satellite coordinates and satellite clock errors at the time of satellite signal transmission are calculated, the ionospheric delay error and the tropospheric delay error are calculated, the pseudorange group delay deviation is corrected, and various error terms such as the receiver clock error are deducted to calculate the post-verification pseudorange innovation residual. At this time, the GNSS non-differenced original pseudorange observation equation is also expressed as in the above formula (1). Therefore, the post-verification pseudorange innovation residual can be calculated as follows:

[0073]

[0074] In the formula, is the user coordinate estimated before the test, is the user receiver clock error estimated a priori.

[0075] S06: Post-test single-star failure mode test

[0076] In the first iteration of the post-validation iterative estimation, the n pseudo-range innovation residual values ​​{v s1 、v s2 ,…,v sn} is divided into n groups, each group does not contain the i-th (i=1,2,…,n)th pseudorange residual value, and each group has n-1 pseudorange residual values. Then, the standard deviation S of the residual group after removing the i-th residual value is calculated one by one i , a total of n calculations are performed to obtain n standard deviations of the innovation residuals {S1, S2, …, S n}.

[0077] After traversing all satellites, firstly calculate the value set of the innovation residual standard deviation {S1, S2, …, S n} to perform the Laida criterion test, that is, the 3σ criterion test (where σ is the above numerical set {S1, S2, …, S n}) to identify gross errors, so as to find the observation of the satellite corresponding to the innovation residual value outside the range of [-3σ,3σ], and mark it as an abnormal observation and remove it. The satellite observations that pass the test are retained and participate in the subsequent pre-test iterative estimation. Then, the above innovation residual standard deviation value set {S1, S2, …, S n} Sort from small to large, use the Dixon statistical test criterion to identify gross errors based on the range ratio double-sided inspection method, so as to find the observation of the satellite corresponding to the abnormal innovation residual value under a given significance level α, and mark it as an abnormal observation to be eliminated, and retain the satellite observations that pass the test and participate in the subsequent pre-test iterative estimation. It should be noted here that the satellite observations that have been marked as abnormal in the pre-test fault detection will no longer participate in the post-test single-satellite fault detection process.

[0078] S07: Post-test dual-star failure mode test

[0079] After completing the post-verification single-satellite fault mode detection, the permutation and combination method is used again to remove the pseudo-range innovation residual values ​​of the i-th and j-th satellites each time to obtain a new residual group, and the total number of residuals is Then calculate the standard deviation S of each residual group. i,j , a total of Calculated times The standard deviation S i,j (i=1,…,n;j=1,…,n,i≠j), forming a numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),nIf a satellite has been successfully marked as abnormal in the above-mentioned post-test single-satellite fault mode test, it has been successfully marked and removed, and does not need to and will no longer participate in the dual-satellite fault mode test step.

[0080] After traversing all satellites, first calculate the value set of the innovation residual standard deviation {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n} to perform the Laida criterion test, that is, the 3σ criterion test (where σ is the above numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n}) to identify gross errors, so as to find the observations of the satellite corresponding to the innovation residual value outside the range of [-3σ,3σ], and mark them as abnormal observations for elimination. The satellite observations that pass the test are retained and participate in the subsequent post-test iterative estimation. Then, the above innovation residual standard deviation value set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n} Sort from small to large, use the Dixon statistical test criterion to identify gross errors based on the range ratio double-sided inspection method, so as to find the observations of the two satellite combinations corresponding to the abnormal innovation residual values ​​under a given significance level α, and mark them as abnormal observations for elimination. The satellite observations that pass the test are retained and participate in the subsequent post-test iterative estimation. It should be noted here that the satellite observations that have been marked as abnormal in the pre-test fault detection are also no longer involved in the post-test binary fault detection process.

[0081] S08: Post-test estimation and overall testing

[0082] Based on the above two steps, assuming that the i-th and j-th satellites have been marked as abnormal, the residual vector of the satellite pseudorange observation marked as normal is obtained The weight matrix corresponding to the observed quantity is P, and the design matrix is ​​B. Then the estimated parameter vector X can be estimated by the following adjustment formula:

[0083]

[0084] According to the above formula, the user's posterior three-dimensional coordinates and the receiver clock error can be estimated. After obtaining the posterior estimation result, the posterior residual square weighted sum ∑ WSSE =V T PV is used to test the consistency between observations. WSSE ≤χ 2(r), the null hypothesis H0 is accepted, that is, there is no abnormal error in the observation at this time, and the positioning solution is valid; otherwise, it is considered that there are still missed abnormal errors in the observation at this time, and the current solution is invalid, and then RAIM-FDE is executed to diagnose and eliminate the faulty satellite.

[0085] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A GNSS terminal autonomous fault diagnosis and troubleshooting method, characterized in that: The following steps are involved: Pre-test data preprocessing, calculate n pseudo-range innovation residuals of n satellites; Pre-test single satellite fault mode test: for the n pseudo-range innovation residual values, remove one residual value each time, and calculate the standard deviation of the remaining residual value group; perform an outlier test on the obtained series standard deviation to find the faulty satellite and remove the abnormal observation value; Pre-test binary star fault mode test: for the remaining m pseudorange innovation residual values, remove 2 residual values ​​each time, and calculate the standard deviation of the remaining residual value group; Perform outlier tests on a series of standard deviations obtained to identify faulty satellites and eliminate abnormal observations; Pre-test estimation and overall verification: Estimate the user's 3D coordinates and receiver clock error based on the satellite pseudorange innovation residuals marked as normal; Then, the weighted sum of squares of residual values ​​of each satellite is tested overall based on the least square residual method; When the overall inspection is passed, the post-inspection processing phase begins, including: Based on the user's three-dimensional coordinates obtained in the pre-test estimation step, post-test data preprocessing: calculation of post-test pseudorange innovation residuals; as well as single-satellite fault mode inspection, double-satellite fault mode inspection, post-test estimation and overall inspection; Otherwise, there is no need to perform post-processing, and the faulty satellite can be diagnosed and eliminated according to the RAIM-FDE method; The pseudorange innovation residual is calculated as follows: In the formula, X r，0 is the user's approximate coordinates, is the approximate clock error of the user receiver; SYS, s, r represent the GNSS navigation system, satellite number and receiver respectively; i represents the carrier frequency of the received signal; P s r,i is the pseudorange observation of receiver r about satellite s at frequency i (m), i.e., code measurement pseudorange; X s is the coordinate of the satellite; c is the speed of light in vacuum; δt s is the satellite clock error at the time of signal transmission (s); I s r,i is the slant path ionospheric delay error of receiver r with respect to satellite s at frequency i (m); is the tropospheric delay error (m); b s P,i is the pseudorange group delay deviation of the current pseudorange observation P (m); is the pseudorange inter-frequency deviation (m) for the GLONASS satellite system using frequency division multiple access FDMA modulation.

2. The method according to claim 1, characterized in that The step of pre-test or post-test data preprocessing includes: Based on the pseudo-range observations, the satellite coordinates and satellite clock errors at the time when the satellite signal is transmitted are calculated respectively; Calculate ionospheric delay error and tropospheric delay error; Correct pseudorange group delay deviation; Deduct various error terms including receiver clock error.

3. The method according to claim 1, characterized in that The steps of the single-star failure mode inspection before or after the inspection specifically include: In the first iteration of the pre- or post-iterative estimation, the n pseudorange innovation residual values ​​{v s1 、v s2 ,…,v sn }, each time the i-th (i=1, 2, ..., n) pseudorange residual value is removed to obtain n pseudorange residual value groups with a length of n-1; Calculate the standard deviation S of the n residual value groups one by one i , and obtain n new interest residual standard deviation values ​​{S1, S2, ..., S n }; After traversing all satellites, the standard deviation value set of the innovation residual {S1, S2, …, S n } to perform the Laida criterion test, that is, the 3σ criterion test to identify gross errors, where σ is the above numerical set {S1, S2, …, S n }, find the observation of the satellite corresponding to the innovation residual value outside the range of [-3σ, 3σ], mark it as an abnormal observation and remove it, retain the satellite observations that pass the test, and participate in the subsequent pre-test or post-test iterative estimation; For the innovation residual standard deviation value set {S1, S2, …, S n } Sort them from small to large, use the Dixon statistical test criterion, and use the range ratio two-sided test method to identify gross errors. Find the observations of the satellite corresponding to the abnormal innovation residual value at a given significance level, mark them as abnormal observations and eliminate them, and retain the satellite observations that pass the test and participate in the subsequent pre-test or post-test iterative estimation.

4. The method according to claim 3, characterized in that: The steps of double-star fault mode inspection before or after inspection specifically include: After completing the single-satellite fault mode detection before or after verification, according to the permutation and combination method, a new residual group is obtained by removing the pseudo-range innovation residual values ​​of the i-th and j-th satellites each time, and a total of residual groups; Calculate the standard deviation S one by one i,j , a total of Calculated times The standard deviation S i,j (i=1,…,n;j=1,…,n,i≠j), forming a numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n }; If a satellite has been successfully marked as abnormal in the above-mentioned single-satellite fault mode test before or after the test, it has been successfully marked and removed and will no longer participate in the dual-satellite fault mode test step; After traversing all satellites, the standard deviation value set of the innovation residual {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n } to perform the Laida criterion test, that is, the 3σ criterion test (where σ is the above numerical set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n }) to identify gross errors, find out the observations of the satellite corresponding to the new information residual value outside the range of [-3σ, 3σ], mark them as abnormal observations and remove them, and retain the satellite observations that pass the test and participate in the subsequent pre-test iterative estimation; Then, for the above-mentioned new interest residual standard deviation value set {S 1,2 , S 1,3 ,…,S i,j ,…,S (n-1),n }Sort them from small to large, use the Dixon statistical test criterion to identify gross errors based on the range ratio two-sided inspection method, find the observations of the two satellite combinations corresponding to the abnormal innovation residual values ​​at a given significance level, mark them as abnormal observations and eliminate them, retain the satellite observations that pass the test, and participate in the subsequent pre-test or post-test iterative estimation.

5. The method according to claim 4, characterized in that The steps of pre-test or post-test estimation and overall test specifically include: Based on the two steps of single-satellite fault mode test and dual-satellite fault mode test, assuming that the i-th and j-th satellites have been marked as abnormal, the residual vector of the satellite pseudorange observation marked as normal is obtained The weight matrix corresponding to the observed quantity is P, and the design matrix is ​​B. Then the estimated parameter vector X can be estimated by the following adjustment formula: in, is the estimated value of X. According to the above formula, the user’s three-dimensional coordinates and the receiver clock error can be estimated; After obtaining the prior or posterior estimation results, the weighted sum of squared residuals ∑ WSSE =V T PV is used to test the consistency between the observations: At a given significance level, if ∑ WSSE ≤χ 2 (r), then accept the null hypothesis H0, assuming that there is no abnormal error in the observation at this time, and the positioning solution is valid; Otherwise, it is considered that the observation contains missed abnormal errors, the current solution is invalid, and RAIM-FDE needs to be further performed to diagnose and eliminate the faulty satellite.

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