A Beidou satellite multi-fault detection and elimination method and device based on combined detection

Abstract

The present invention discloses a Beidou satellite multi-fault detection and elimination method and device by combined detection. The method of the present invention firstly uses the Beidou carrier phase observation equation without integer ambiguity to perform positioning solution, obtain positioning solution, residual value and variance matrix; uses #imgabs0# to check the overall detection of satellite faults, and then uses the method to detect and eliminate multiple faults of Beidou satellites by combining detection and elimination. w‑ The inspection is performed by local detection and identification, and the MHSS ARAIM multiple fault identification is performed after removing the satellite observation value. The Beidou satellite multiple fault detection and elimination method proposed in the present invention reduces the calculation burden, makes up for the shortcomings of the MHSS ARAIM algorithm, and has great advantages in both robustness and timeliness.

Description

Technical Field

[0001] The invention belongs to the field of global satellite navigation systems, and in particular to a Beidou satellite multi-fault detection and elimination method and device using combined detection. Background Art

[0002] Based on the Beidou / INS fusion dynamic positioning technology, which can meet the precise needs of dynamic positioning, integrity monitoring, which determines the reliability of dynamic positioning results, is more important. Receiver Autonomous Integrity Monitoring (RAIM) responds quickly and completely autonomously to satellite failures without external intervention. Therefore, integrity monitoring using RAIM is an essential part of reliable dynamic positioning.

[0003] Based on RAIM, the Enhanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm was derived, which has the ability to detect multiple satellite failures and can independently guarantee the reliability and integrity of the system during the precision approach phase of navigation. Based on multivariate hypothesis testing, Pervan proposed the Multiple Hypothesis Solution Separation (MHSS) algorithm under multiple fault assumptions in 1998. By evaluating the integrity risk of the navigation positioning results, it determines whether the integrity monitoring is exceeded. Based on the MHSS algorithm, Blanch et al. proposed the MHSS ARAIM algorithm under multiple faults and multiple systems, and introduced the implementation process of the algorithm in detail, and discussed the improvement and simplification of the algorithm. The MHSS ARAIM algorithm evaluates the integrity risk by expanding the traditional grouping solution and using multiple hypothesis methods. It has strong theoretical basis, is simple and easy to implement, and is currently the most widely used ARAIM algorithm.

[0004] With the continuous increase in the number of Beidou / GNSS satellites, the probability of satellite failure is also increasing. However, when the number of faults is large, the MHSS ARAIM algorithm has problems such as too many calculation subsets and too much calculation, which requires high data processing and is difficult to meet timeliness. In recent years, some scholars have applied gross error detection and elimination methods to the detection and identification of satellite faults, mainly including quasi-adjustment method, Danish method, robust estimation method, etc. The reliability and accuracy of the quasi-adjustment method need to be further verified. The parameters of the Danish method are uncertain and the theoretical basis is not strong enough. Robust estimation can reduce the impact of gross error values ​​on positioning accuracy. When the number of faults increases to 4, the navigation positioning results will still have a large deviation. In addition, signal shielding and interruption in complex environments increase the probability of satellite failures, and an efficient and accurate satellite fault detection and elimination method is needed. Summary of the invention

[0005] Aiming at the problems of too many calculation subsets and too much calculation amount in the Multi-Hypothesis Segmentation Solution Autonomous Integrity Monitoring (MHSS ARAIM) algorithm when there are many satellite faults in complex environments, the present invention combines satellite multiple fault detection and elimination in the residual domain and the position domain in turn, so as to make up for the shortcomings of the algorithm and improve the robustness performance.

[0006] The present invention proposes a Beidou satellite multi-fault detection and elimination method by combined detection, comprising the following steps:

[0007] Step 1: Construct the residual domain The test quantity and its threshold are used for overall detection, and the residual domain is compared The size of the test quantity and the threshold is determined to determine whether the Beidou satellite has a fault. If there is a fault, proceed to step 2;

[0008] Step 2, Construction w- The inspection quantity and its threshold are used for local detection, and the w- The size of the test quantity and its threshold value is used to determine the Beidou satellite that has a fault, and the corresponding Beidou carrier phase observation value with a fault w- The test quantities are sorted from large to small, and we get w- Check the quantum set, w- The Beidou carrier phase observation value corresponding to the maximum value in the test quantum set is deleted;

[0009] Step 3, for w- The remaining Beidou carrier phase observations in the quantum set are checked, and the multi-hypothesis solution separation autonomous integrity monitoring algorithm MHSS ARAIM is used to identify Beidou satellite multiple faults to confirm whether the faulty Beidou satellite has been successfully eliminated.

[0010] Furthermore, the specific implementation of step 1 is as follows:

[0011] Step 1.1, perform positioning calculation based on Beidou carrier phase observation values ​​without integer ambiguity to obtain positioning solution, residual value and variance matrix;

[0012] Step 1.2: construct the residual domain for the residual value in step 1.1 Inspection quantity and its threshold ;

[0013] Step 1.3, based on the residual domain constructed in step 1.2 The inspection quantity and threshold are used for overall detection. It is considered that the BeiDou satellite has no faults, and the MHSS ARAIM fault-free calculation is performed. If it is considered that there is a fault with the Beidou satellite, local detection in step 2 is performed.

[0014] Furthermore, the residual domain Inspection quantity and its threshold The calculation formula is as follows:

[0015]

[0016] In the formula, and Respectively represent the residual domain Test volume and threshold, W and v are the weight matrix vector and the residual value vector respectively, n is the number of Beidou carrier phase observations, m represents the number of unknown parameters in the location solution, F express Distribution function, is the false alarm rate.

[0017] Furthermore, the weight matrix vector is obtained through the positioning solution in step 1.1.

[0018] Furthermore, the specific implementation of step 2 is as follows:

[0019] Step 2.1: Perform positioning calculation based on the Beidou carrier phase observation value without integer ambiguity to obtain the residual value, and further construct the residual value w- Inspection quantity and its threshold ;

[0020] Step 2.2, according to step 2.1 w- The test quantity and its threshold value, when The first k The BeiDou satellite corresponding to the BeiDou carrier phase observation value is faulty. w- The test quantities are sorted from large to small, and we get w- Check the quantum set, take w- The maximum value in the test quantum concentration is eliminated, and its corresponding Beidou carrier phase observation value is eliminated.

[0021] Furthermore, w- Inspection quantity and its threshold The calculation formula is as follows;

[0022]

[0023] In the formula, k Indicates k BeiDou carrier phase observations, and Indicates k Beidou carrier phase observation value corresponding tow- Test quantity and residual value, express w- Test threshold, The variance matrix is k diagonal elements, is the confidence level 1- The critical value of the normal distribution under .

[0024] Furthermore, the specific implementation of step 3 is as follows;

[0025] Step 3.1, assuming that k After obtaining Beidou carrier phase observation values, the remaining Beidou carrier phase observation values ​​are positioned and solved to obtain the difference between the separation solution and the positioning solution and the difference between their variance values;

[0026] Step 3.2: Construct the localization domain based on the difference between the separation solution and the localization solution in step 3.1, as well as the difference in variance value. Inspection quantity :

[0027]

[0028] In the formula Mark the east, north and sky directions of the positioning solution respectively. Indicates A vector with 1 elements and all other elements being 0. , and They are , and No. Quantity, and denote the partition solution and the localization solution respectively, Represents the difference between the separation solution variance value and the positioning solution variance value;

[0029] Step 3.3, construct the positioning domain according to step 3.2 Test threshold :

[0030]

[0031] in:

[0032]

[0033] In the formula, Indicates the location domain Test threshold, is the standard normal distribution function, and Respectively represent the continuity risk probability in the horizontal direction and the elevation direction, Indicates the number of separations of multiple hypothesis solutions;

[0034] Step 3.4: According to steps 3.2 and 3.3, the test quantities in the three coordinate directions are Test, when all the tests in all directions are satisfied:

[0035]

[0036] The first k Beidou satellite faults were successfully identified and eliminated;

[0037] If present:

[0038]

[0039] The first k Beidou satellites are not faulty, then they are removed w- Check the Beidou carrier phase observation value corresponding to the second maximum value in the quantum concentration and repeat steps 3.1-3.4.

[0040] Furthermore, the calculation formula for the difference between the separation solution and the positioning solution and the difference in their variance values ​​in step 3.1 is as follows:

[0041] In the formula, and denote the partition solution and the localization solution respectively, represents the difference between the partition solution and the localization solution, represents the difference between the separation solution variance and the positioning solution variance. and denote the coefficient matrices of the partition solution and the localization solution, respectively. represents the variance matrix.

[0042] Furthermore, when there are two or more Beidou satellite failures, w - Check multiple Beidou carrier phase observation values ​​corresponding to the maximum value in the quantum concentration, and repeat steps 3.1-3.4 until the Beidou satellite fault is successfully identified and eliminated.

[0043] The present invention also provides a Beidou satellite multiple fault detection and elimination device with combined detection, comprising:

[0044] one or more processors;

[0045] The storage device is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the Beidou satellite multiple fault detection and elimination method of combined detection as described in the above scheme. The beneficial effects of the present invention are:

[0046] The present invention proposes a Beidou satellite multi-fault detection and elimination scheme of combined detection, which detects in the residual domain and the position domain in turn, reduces the calculation burden, makes up for the shortcomings of the MHSS ARAIM algorithm, and improves the reliability of fault identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a method flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings.

[0049] The embodiment of the present invention provides a Beidou satellite multiple fault detection and elimination method by combined detection. Verify the overall detection satellite failure (step 1); use w- The test is to perform local detection of satellite faults (step 2); finally, the MHSSARAIM satellite multiple fault identification is performed (step 3). Figure 1 A Beidou satellite multiple fault detection and elimination method provided in an embodiment of the present invention includes the following steps:

[0050] Step 1: Utilization The inspection is to conduct overall detection to determine whether there is any fault in the Beidou satellite, including:

[0051] Step 1.1: First, perform positioning calculation based on the Beidou carrier phase observation value without integer ambiguity (hereinafter referred to as satellite observation value) to obtain the positioning solution, residual value and variance matrix.

[0052] Step 1.2: First, construct the residual domain for the residual value in step 1.1 The test quantity and its threshold,

[0053]

[0054] In the formula, and Respectively represent the residual domain The test quantity and its threshold, W and v are the weight matrix (obtained from the positioning solution in step 1.1) and the residual value vector, respectively. n is the number of Beidou carrier phase observations, m represents the number of unknown parameters in the location solution, F express Distribution function, is the false alarm rate.

[0055] Step 1.3: According to step 1.2 The inspection quantity and threshold are used for overall detection. The satellite observations are considered to be fault-free and the multi-hypothesis solution separation autonomous integrity monitoring (MHSS ARAIM) fault-free correlation calculation is performed. It is considered that there is a fault in the satellite observation value, and the local inspection and identification in step 2 is performed.

[0056] Step 2: Pass w- The inspection conducts local detection to determine the satellite that has failed, including:

[0057] Step 2.1: Further construct the residual value vector of step 1.1 w- The test quantity and its threshold,

[0058]

[0059] In the formula, k Indicates k Satellite observations, and Indicates k Satellite observations w- Test quantity and residual value, express w- Test threshold, The variance matrix is k diagonal elements, is the confidence level 1- The critical value of the normal distribution under is a constant.

[0060] Step 2.2: According to step 2.1 w- The test quantity and its threshold value, when The first k There are faults in satellite observation values. w- The test quantities are sorted from large to small, and we get w- Fault detection sub-set. w- Check the maximum value in the quantum concentration, remove the corresponding satellite observation value, and then perform MHSS ARAIM fault identification in step 3.

[0061] Step 3: Use the MHSS ARAIM algorithm to identify multiple satellite faults, including:

[0062] Step 3.1: Eliminate the k After obtaining satellite observations, the remaining satellite observations are positioned and solved to obtain the difference between the separation solution and the positioning solution and the difference in their variance values:

[0063]

[0064] In the formula, and denote the partition solution and the localization solution respectively, represents the difference between the partition solution and the localization solution, represents the difference between the separation solution variance and the positioning solution variance. and denote the coefficient matrices of the partition solution and the localization solution, respectively. represents the variance matrix.

[0065] Step 3.2: Construct the positioning domain based on the difference between the separation solution and the positioning solution in step 3.1, as well as the difference in variance value. Inspection quantity:

[0066]

[0067] In the formula Mark the east, north and sky directions of the positioning solution respectively. express Direction location domain Inspection quantity, Indicates A vector with 1 elements and all other elements being 0. , and They are , and No. Quantity.

[0068] Step 3.3: Construct according to step 3.2 Test threshold:

[0069]

[0070] in:

[0071]

[0072] In the formula, represents the test threshold, represents the test threshold coefficient, is the standard normal distribution function, and Respectively represent the continuity risk probability in the horizontal direction and the elevation direction, Represents the number of separations of the multiple hypothesis solution.

[0073] Step 3.4: According to the results of steps 3.2 and 3.3, the three coordinate directions The corresponding test quantity is Check, when all The tests all meet:

[0074]

[0075] The first k Beidou satellite faults were successfully identified and eliminated. and Respectively Direction Inspection volume and inspection threshold.

[0076] If exists test:

[0077]

[0078] The first k Beidou satellites are not faulty, then they are removed w- Check the satellite observation value corresponding to the second maximum value in the quantum concentration and repeat steps 3.1-3.4;

[0079] Step 3.5: When there are two or more Beidou satellite failures, remove w- Check the multiple satellite observations corresponding to the maximum value in the quantum set and perform steps 3.1-3.5.

[0080] In specific implementation, the above process can use computer software technology to realize automatic operation of the process, and the system device that runs the method process of the present invention should also be within the protection scope of the present invention.

[0081] On the other hand, an embodiment of the present invention further provides a Beidou satellite multiple fault detection and elimination device with combined detection, comprising:

[0082] one or more processors;

[0083] A storage device is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement a Beidou satellite multi-fault detection and elimination method of combined detection as described in the above scheme.

[0084] According to the technical solution of the present invention, the statistical results of Beidou satellite multi-fault detection and elimination test in Table 1 are obtained. The results in Table 1 show that the Beidou satellite multi-fault detection and elimination of combined detection has higher availability and a smaller protection level value.

[0085] Table 1 Statistical results of Beidou satellite multi-fault detection and elimination test

[0086]

[0087] The specific embodiments described herein are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in similar ways, but they will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A Beidou satellite multi-fault detection and elimination method based on combined detection, comprising the following steps: Step 1: Construct the residual domain The test quantity and its threshold are used for overall detection, and the residual domain is compared The size of the test quantity and the threshold is determined to determine whether the Beidou satellite has a fault. If there is a fault, proceed to step 2; The specific implementation of step 1 is as follows: Step 1.1, perform positioning calculation based on Beidou carrier phase observation values ​​without integer ambiguity to obtain positioning solution, residual value and variance matrix; Step 1.2: construct the residual domain for the residual value in step 1.1 Inspection quantity and its threshold ; Step 1.3, based on the residual domain constructed in step 1.2 Inspection quantity and threshold For overall detection, It is considered that the BeiDou satellite has no faults, and the MHSS ARAIM fault-free calculation is performed. If the BeiDou satellite is considered to be faulty, the local detection in step 2 is performed; Step 2, Construction w- The inspection quantity and its threshold are used for local detection, and the w- The size of the test quantity and its threshold value is used to determine the Beidou satellite that has a fault, and the corresponding Beidou carrier phase observation value with a fault w- The test quantities are sorted from large to small, and we get w- Check the quantum set, w- The Beidou carrier phase observation value corresponding to the maximum value in the test quantum set is deleted; Step 3: w- The remaining Beidou carrier phase observations in the quantum set are checked, and the multi-hypothesis solution separation autonomous integrity monitoring algorithm MHSS ARAIM is used to identify Beidou satellite multiple faults to confirm whether the faulty Beidou satellite has been successfully eliminated.

2. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 1 is characterized in that: Residual domain Inspection quantity and its threshold The calculation formula is as follows: In the formula, and Respectively represent the residual domain Test volume and threshold, W and v are the weight matrix vector and the residual value vector respectively, n is the number of Beidou carrier phase observations, m represents the number of unknown parameters in the location solution, F express Distribution function, is the false alarm rate.

3. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 1 is characterized in that: The weight matrix vector is obtained through the positioning solution in step 1.

1.

4. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 1 is characterized in that: The specific implementation of step 2 is as follows: Step 2.1: Perform positioning calculation based on the Beidou carrier phase observation value without integer ambiguity to obtain the residual value, and further construct the residual value w- Inspection quantity and its threshold ; Step 2.2, according to step 2.1 w- Inspection quantity and its threshold ,when The first k The BeiDou satellite corresponding to the BeiDou carrier phase observation value is faulty. w- The test quantities are sorted from large to small, and we get w- Check the quantum set, take w- The maximum value in the test quantum concentration is eliminated, and its corresponding Beidou carrier phase observation value is eliminated.

5. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 4 is characterized in that: w- Inspection quantity and its threshold The calculation formula is as follows; In the formula, k Indicates k BeiDou carrier phase observations, and Indicates k Beidou carrier phase observation value corresponding to w- Test quantity and residual value, express w- Test threshold, The variance matrix is k diagonal elements, is the confidence level 1- The critical value of the normal distribution under .

6. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 1 is characterized in that: The specific implementation of step 3 is as follows; Step 3.1, assuming that k After obtaining Beidou carrier phase observation values, the remaining Beidou carrier phase observation values ​​are positioned and solved to obtain the difference between the separation solution and the positioning solution and the difference between their variance values; Step 3.2: Construct the localization domain based on the difference between the separation solution and the localization solution in step 3.1, as well as the difference in variance value. Inspection quantity : In the formula Mark the east, north and sky directions of the positioning solution respectively. Indicates A vector with 1 elements and all other elements being 0. , and They are , and No. Quantity, and denote the partition solution and the localization solution respectively, Represents the difference between the separation solution variance value and the positioning solution variance value; Step 3.3: construct the positioning domain according to step 3.2 Test threshold : in: In the formula, Indicates the location domain Test threshold, is the standard normal distribution function, and Respectively represent the continuity risk probability in the horizontal direction and the elevation direction, Indicates the number of separations of multiple hypothesis solutions; Step 3.4: According to steps 3.2 and 3.3, the test quantities in the three coordinate directions are Test, when all the tests in all directions are satisfied: The first k Beidou satellite faults were successfully identified and eliminated; If present: The first k Beidou satellites are not faulty, then they are removed w- Check the Beidou carrier phase observation value corresponding to the second maximum value in the quantum concentration and repeat steps 3.1-3.

4.

7. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 6 is characterized in that: The calculation formula for the difference between the separation solution and the positioning solution and their variance values ​​in step 3.1 is as follows: In the formula, and denote the partition solution and the localization solution respectively, represents the difference between the partition solution and the localization solution, represents the difference between the separation solution variance and the positioning solution variance. and denote the coefficient matrices of the partition solution and the localization solution, respectively. represents the variance matrix.

8. The Beidou satellite multiple fault detection and elimination method of combined detection according to claim 6 is characterized in that: When there are two or more Beidou satellite failures, remove w - Check multiple Beidou carrier phase observation values ​​corresponding to the maximum value in the quantum concentration, and repeat steps 3.1-3.4 until the Beidou satellite fault is successfully identified and eliminated.

9. A combined detection Beidou satellite multiple fault detection and elimination device, characterized in that: include: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement a Beidou satellite multi-fault detection and elimination method for combined detection as described in any one of claims 1 to 8.

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