A method for monitoring navigation satellite UERE based on multi-station asynchronous observation data

Abstract

This invention provides a method for monitoring the UERE of navigation satellites based on multi-station asynchronous observation data. The method calculates pseudorange values ​​based on geometric distance and various error correction values. The pseudorange observation values ​​are then subtracted from the calculated pseudorange values ​​to obtain the pseudorange observation value minus the calculated OMC value. Next, using the "median station clock elimination method," the median OMC of each satellite at the same epoch is subtracted from the median OMC of that epoch to obtain the single-station UERE of each satellite. Finally, using the "minimum value multi-station synthesis method," the minimum absolute value of the UERE of the satellite under monitoring at all stations in the same epoch is calculated, and this value is taken as the final UERE monitoring result for that satellite at that epoch. This invention reduces the requirement and dependence on tracking station clock synchronization for UERE monitoring, expands the selection range for UERE monitoring, improves the redundancy and uniformity of UERE monitoring station selection, and achieves continuous global monitoring of the UERE of navigation satellites such as BeiDou. Simultaneously, it improves the accuracy and reliability of the continuous global monitoring results of the UERE of navigation satellites such as BeiDou.

Description

Technical Field

[0001] This invention relates to the field of measurement and testing technology, and specifically to a method for monitoring navigation satellite UERE based on multi-station asynchronous observation data. Background Technology

[0002] User Equivalent Range Error (UERE) is a comprehensive error in the distance observation between the satellite and the user caused by factors such as the navigation satellite's orbit, clock error, atmospheric propagation, and user observation. It is an important parameter for evaluating the downlink signal service performance of navigation satellites and an important indicator for monitoring the integrity of navigation satellite downlink signals.

[0003] Satellite navigation systems determine a user's position by measuring the propagation time of satellite signals to the user's antenna (multiplied by the speed of light as the equivalent distance), based on the precise known positions and times of the satellites. At least four satellites need to be observed to determine the user's three-dimensional position and clock error. The Position Dilution of Precision (PDOP) is a parameter characterizing the geometric strength of the relative positional relationship between the satellites and the user; user positioning accuracy can be simply expressed as UERE * PDOP. The number of satellites and orbital design of the navigation constellation determine the constellation's PDOP performance. UERE originates from various error sources in the space, control, and user segments: ① satellite clock error; ② satellite orbital error; ③ satellite hardware deviation; ④ ionospheric error; ⑤ tropospheric error; ⑥ multipath effect error; ⑦ receiver hardware deviation, etc. A smaller UERE value indicates higher positioning accuracy. In practical applications, UERE can be used to evaluate positioning accuracy, analyze errors, formulate positioning requirements, and monitor satellite performance and integrity.

[0004] With the development of Global Navigation Satellite System (GNSS) systems and applications, the number of available satellite navigation systems has increased. However, following integrity-related events such as the GPS timing anomaly in 2016, the GLONASS ephemeris injection error in 2014, and the Galileo service outage lasting approximately 117 hours in 2019, both GNSS providers and users are increasingly emphasizing the monitoring and alarm capabilities of GNSS system operation. User equivalent distance error (UERE) is a crucial indicator for monitoring the integrity of navigation satellite downlink signals. Existing navigation satellite UERE monitoring technologies have the following problems: UERE calculations based on strictly synchronized station clocks result in independent UERE results from each station. A single station can only monitor satellites within its zenith visibility range. This is particularly problematic for navigation systems with only regional ground monitoring stations, making it impossible to simultaneously monitor the UERE of all satellites in the entire constellation. Furthermore, data quality degradation or anomalies can occur due to the receiving equipment at a single station or the surrounding environment, leading to false alarms or missed alarms. This problem is particularly prominent for GNSS providers with a limited number of ground monitoring stations (with strictly synchronized clock times), uneven global distribution, or even only regional monitoring stations.

[0005] Currently, there is a relatively abundant global tracking station data resource available for UERE monitoring. However, there are problems such as asynchronous station clock times (i.e., the actual clock difference of the station receiver is unknown) and uneven quality of observation data. How to make full use of global tracking station data resources while improving the accuracy and continuity of navigation satellite UERE global monitoring results has become an urgent problem to be solved. Summary of the Invention

[0006] This invention addresses the accuracy and continuity of UERE global monitoring results by providing a navigation satellite UERE monitoring method based on multi-station asynchronous observation data. This method reduces the UERE monitoring requirement and dependence on tracking station clock synchronization, expands the selection range for UERE monitoring, and improves the redundancy and uniformity of UERE monitoring station selection, enabling continuous global monitoring of navigation satellite UERE such as BeiDou. Simultaneously, the provided multi-station UERE integration method significantly reduces false alarms or missed alarms caused by factors such as the equipment of a single station or its surrounding environment, thereby improving the accuracy and reliability of continuous global monitoring results for navigation satellite UERE such as BeiDou.

[0007] This invention provides a method for monitoring navigation satellite UERE based on multi-station asynchronous observation data, comprising the following steps:

[0008] S1. Read the observation data from the tracking station to obtain the pseudorange observation value of the navigation signal frequency point j of satellite s measured by the tracking station terminal r at a certain epoch.

[0009] S2. Read the satellite's Earth-fixed coordinates at the time of signal transmission from the broadcast ephemeris and perform Earth rotation correction. Calculate the true geometric distance from the satellite to the tracking station based on the satellite coordinates and the known coordinates of the tracking station terminal r.

[0010] Based on the known coordinates of the receiver, navigation messages, and atmospheric correction models, the calculated values ​​of satellite clock error, tropospheric delay error, ionospheric delay error, relativistic effect correction, and satellite endcode hardware delay are obtained.

[0011] The pseudorange is calculated based on the actual geometric distance from the satellite to the station, the calculated satellite clock error, the calculated tropospheric delay error, the calculated ionospheric delay error, the calculated relativistic effect correction, and the calculated hardware delay of the satellite endcode.

[0012] S3, Pseudo-distance observation values Comparison with pseudorange calculation value The difference between the observed and calculated pseudorange values ​​is obtained by subtracting the pseudorange values.

[0013] Return to step S1 and iteratively calculate the pseudorange observations minus the calculated values ​​for all satellites at the same epoch. After the calculation is completed, store all pseudorange observations minus the calculated values. Proceed to step S4;

[0014] S4. Tracking n satellites with epoch time tracking station terminal r. The values ​​are sorted in ascending order, S = 1, 2, ..., n. Based on the sorting result, a sequence of pseudorange observations minus calculated values ​​is obtained:

[0015] OMC1≤OMC2≤…≤OMC n-1 ≤OMC n ;

[0016] S5. Calculate the median Mdn(OMC) of OMC based on the pseudorange observation value minus the calculated value sequence;

[0017] S6, The satellites at each epoch time Subtract the median Mdn(OMC) of the OMC sequence at each epoch to obtain the UERE for each satellite;

[0018] Return to step S1, iterate through all tracking station terminals r, and obtain the satellite observations of all tracking stations at each epoch.

[0019] S7. Obtain the UERE monitoring results after multi-station integration using the minimum value multi-station integration method.

[0020]

[0021] Where Min() is the minimum value function, || is the absolute value function, and m is the total number of tracking station terminals that have observed satellite S;

[0022] A method for monitoring navigation satellite UERE based on multi-station asynchronous observation data has been completed.

[0023] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, in step S1,

[0024]

[0025] in, dt represents the geometric distance between the satellite and the Earth. r For receiver clock bias, dt s For satellite clock bias, For tropospheric delay error, μ j Let be the ionospheric delay effect coefficient at frequency j. For ionospheric delay error, d rela To correct for relativistic effects, d r,j For receiver endcode hardware delay, Due to satellite end-code hardware latency, This is multipath error.

[0026] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment,

[0027]

[0028] Where f1 is the default frequency point for ionospheric delay error.

[0029] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, involves the following steps in S1 and S2: after reading the tracking station observation data and navigation ephemeris, pseudo-random noise code (PRN) matching and time matching are performed in the navigation ephemeris based on the satellite PRN number read from the observation data. If the matching is successful, the parameters such as satellite coordinates, satellite clock error, and satellite-station geometric distance are calculated. If the matching is unsuccessful, the ephemeris reading and matching continue until the ephemeris data is exhausted.

[0030] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, in step S2,

[0031]

[0032] in, This is a calculated value for the geometric distance between the satellite and the ground. This is the calculated value for satellite clock bias. This is the calculated value of tropospheric delay error. This is the calculated value of ionospheric delay error. The calculated values ​​are corrected for relativistic effects. This is the calculated value for the satellite endcode hardware delay.

[0033] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, in step S3,

[0034]

[0035] in, To account for residual errors, This includes navigation message parameter errors, atmospheric delay correction residual errors, measurement noise, and multipath errors.

[0036] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, in step S4, firstly determines whether the number of satellites is greater than or equal to 2; if so, proceeds... If the sorting is not correct, return to step S1.

[0037] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, in step S5,

[0038]

[0039] The navigation satellite UERE monitoring method based on multi-station asynchronous observation data described in this invention, as a preferred embodiment, in step S6,

[0040]

[0041] in, To account for residual errors, This includes residual errors in navigation message parameters, atmospheric delay correction, measurement noise, and multipath.

[0042] This application discloses a method for monitoring the equivalent distance error (UERE) of navigation satellite users based on multi-station asynchronous observation data. The method involves first reading observation data from global tracking stations whose clocks are not synchronized to obtain information such as the observation epoch time, number of satellites, satellite number, and corresponding pseudorange observations; then reading the broadcast ephemeris to calculate the satellite's Earth-solid coordinates at the signal transmission time and considering Earth's rotation correction, fixing the known coordinates of the station, calculating the true geometric distance from the satellite to the station, and simultaneously calculating corrections for error terms such as satellite clock error, tropospheric delay, ionospheric delay, satellite TGD, and relativistic effects based on models such as navigation messages and atmospheric corrections; calculating the pseudorange value based on the geometric distance and various error corrections; subtracting the pseudorange observation value from the pseudorange calculation value to obtain the pseudorange observation value minus the calculated value OMC; then, based on the "median clock elimination method," subtracting the median OMC of that epoch from the OMC of each satellite at the same epoch to obtain the single-station UERE of each satellite; finally, based on the "minimum value multi-station synthesis method," calculating the minimum absolute value of the UERE of the satellite under monitoring among all stations at the same epoch, and using its corresponding value as the final UERE monitoring result for that satellite at that epoch.

[0043] The present invention has the following advantages:

[0044] (1) The existing technology, such as the patent "CN114814891A A method for monitoring the integrity of a satellite navigation system", involves the monitoring calculation of UERE based on the ground monitoring station of the Beidou satellite navigation system. The station clocks are strictly synchronized (i.e., the receiver clock difference is 0 or precisely known), and the system monitoring station is deployed in a regional area. Therefore, it is necessary to use inter-satellite links and other means to achieve continuous global monitoring. However, the method of the present invention can be applied to global tracking stations with asynchronous station clocks (i.e., the true value of the receiver clock difference is unknown). It can achieve continuous global monitoring of navigation satellite UERE without the need for other monitoring means.

[0045] (2) Based on the global tracking station data with asynchronous station clocks, this invention uses the median method to eliminate station clocks, which reduces the requirements of UERE monitoring for tracking station clock synchronization, expands the station selection conditions for UERE monitoring, and improves the station selection range, redundancy and uniformity of global monitoring, thereby enabling continuous global monitoring of UERE.

[0046] (3) The present invention adopts the minimum value method of multi-station UERE integration, which greatly reduces the monitoring false alarms or missed alarms caused by single-station equipment, surrounding environment, local spatial environment or model anomalies and low elevation angles, thereby improving the accuracy and reliability of UERE global continuous monitoring results. Attached Figure Description

[0047] Figure 1 Here is a flowchart of a navigation satellite UERE monitoring method based on multi-station asynchronous observation data;

[0048] Figure 2 This is a sequence diagram of UERE monitoring results for the B1I frequency point of the BeiDou PRN25 satellite, based on a global tracking station using the "median station clock elimination method," which is a navigation satellite UERE monitoring method based on multi-station asynchronous observation data.

[0049] Figure 3 This is a sequence diagram of UERE monitoring results for the B1I frequency point of the BeiDou PRN25 satellite, based on a navigation satellite UERE monitoring method using multi-station asynchronous observation data and the "minimum value multi-station comprehensive method". Detailed Implementation

[0050] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0051] Example 1

[0052] like Figure 1 As shown, a method for monitoring the UERE of navigation satellites based on multi-station asynchronous observation data is presented. This method uses pseudorange observations from globally redundant tracking stations with known coordinates but unsynchronized station clocks. It calculates the pseudorange observation minus the calculated value (Observed Minus Computed, OMC) using broadcast ephemeris and a related error correction model. The UERE of a single station is then calculated using the "median station clock elimination method," and finally, the final UERE monitoring value is calculated using the "minimum value multi-station synthesis method." This achieves continuous, accurate, and reliable global monitoring of the UERE of navigation satellites such as BeiDou / GNSS. The specific steps are as follows:

[0053] Step (1) Single-station UERE calculation based on the "median station clock elimination method"

[0054] The tracking station's observation data is read to obtain the observation epoch time, number of satellites, satellite number, and corresponding pseudorange observation information; at a certain epoch, the pseudorange observation value obtained by the tracking station terminal r measuring the navigation signal frequency j of satellite s is... It can then be expressed as follows:

[0055]

[0056] In the formula, dt represents the geometric distance between the satellite and the Earth. r For receiver clock bias, dt s For satellite clock bias, For tropospheric delay error, μ j Let be the ionospheric delay effect coefficient at frequency j. d represents the ionospheric delay error corresponding to frequency f1. relaTo correct for relativistic effects, d r,j For receiver endcode hardware delay, Due to satellite end-code hardware latency, For multipath error, μ j Ionospheric delay effect coefficient;

[0057]

[0058] Step (2) involves obtaining the pseudorange calculation value based on the receiver's known coordinates, navigation message, atmospheric corrections, and other models.

[0059] The satellite's Earth-fixed coordinates at the signal transmission time are calculated by reading the broadcast ephemeris and considering Earth's rotation correction. The known coordinates of the station are fixed, and the true geometric distance from the satellite to the station is calculated. Simultaneously, corrections for error terms such as satellite clock error, tropospheric delay, ionospheric delay, satellite TGD, and relativistic effects are calculated based on models such as navigation messages and atmospheric corrections. The pseudorange value is then obtained using the following formula.

[0060]

[0061] In the formula, This is a calculated value for the geometric distance between the satellite and the ground. This is the calculated value for satellite clock bias. This is the calculated value of tropospheric delay error. This is the calculated value of ionospheric delay error. The calculated values ​​are corrected for relativistic effects. This is the calculated value for the satellite endcode hardware delay.

[0062] Step (3) involves subtracting the pseudorange observation from the calculated pseudorange value, i.e., subtracting equation (1) from equation (2), to obtain the pseudorange observation minus the calculated value OMC. At this point, OMC mainly includes residual errors such as receiver clock error, pseudorange noise, and multipath error, as shown in the following equation:

[0063]

[0064] In the formula, It is a comprehensive residual error that includes errors such as navigation message parameters, atmospheric delay correction, measurement noise, and multipath errors.

[0065] By iterating through all observed satellites at that epoch, the OMC values ​​of each satellite at a given epoch of the tracking station are obtained.

[0066] Step (4) involves the n satellites with epoch terminal r. The values ​​(S = 1, 2, ..., n) are sorted in ascending order, and the following sequence is obtained based on the sorting result:

[0067] OMC1≤OMC2≤…≤OMC n-1 ≤OMC n (4)

[0068] Step (5): Calculate the median of the OMC sequence after sorting the above epochs using the following formula.

[0069]

[0070] Step (6): Subtract the median of the OMC sequence of the epoch (which is likely the true value of the receiver clock error) from the OMC of each satellite (e.g., satellite S) in the following formula to obtain the UERE of each satellite.

[0071] As shown in step (3), the receiver clock bias (including receiver endcode hardware delay) has the largest impact on the OMC. However, since the tracking station is not strictly time-synchronized, the receiver clock bias is unknown and cannot be directly eliminated. One solution is to use the "median method" to eliminate the station clock bias. That is, take the median of the OMC of all satellites at the same epoch as the receiver clock bias, and subtract it from the OMC of all satellites at that epoch to obtain the UERE calculation value of each satellite. Theoretically, the receiver clock bias should be the same for all satellites at the same epoch. The number of visible satellites at any location in the world for major GNSS systems is basically more than 5. Taking the GPS system as an example, its publicly released single-satellite integrity risk probability is 1e. -5 (That is, theoretically, the entire GPS constellation will experience no more than two integrity events per year). Further calculations show that the probability of two or more satellites failing simultaneously is approximately 4.98e. -8 (That is, theoretically, it will not happen once in a hundred years), so it can be ignored. Therefore, using the median method not only ensures that the space signal of the satellite corresponding to the selected OMC median has not experienced an integrity failure, but also that the median's resistance to gross errors makes it closer to the true value of the receiver clock error.

[0072]

[0073] In the formula, It represents the comprehensive residual error, including errors such as navigation message parameters, atmospheric delay correction, measurement noise, and multipath errors.

[0074] By iterating through all tracking stations, the UERE of the satellite observed by all tracking stations at the given epoch time is obtained;

[0075] Step (7), final UERE calculation based on the "minimum value multi-station synthesis method"

[0076] The minimum absolute UERE value of each satellite at all stations in the same epoch is calculated using the following formula, and this value is selected as the final UERE monitoring result for that satellite in that epoch. According to step (6), the UERE value of the satellite to be monitored at a single tracking station at a certain epoch can be obtained. In the case of globally uniform multi-redundant station selection, a single satellite will be observed by multiple tracking stations at the same time, so multiple UERE monitoring results for that satellite can be calculated at the same epoch. However, due to the influence of changes in the surrounding environment or signal interference, the quality of the observation data of a single station may decrease or the received navigation message parameters may be abnormal. In addition, due to the influence of abnormal space environments such as ionospheric activity and the limited accuracy of broadcast ionospheric models, the residual error of ionospheric correction for satellites observed at low elevation angles in some areas may increase sharply. All of the above situations may lead to a situation where the satellite downlink signal is normal but the UERE monitoring result of the station is abnormal. If the UERE monitoring result of the station for the satellite is accepted at this time, it will cause a false alarm. The primary purpose of using UERE to monitor the downlink signal status of navigation satellites is to detect anomalies in the satellite's space signals, rather than to monitor anomalies in the user-end environment, terminal equipment, or the space environment. Therefore, one solution is to first sort the absolute UERE values ​​of the satellite from multiple stations at the same epoch, then select the UERE corresponding to the smallest absolute value in the sequence as the final UERE monitoring result for that satellite at that epoch. This result is then compared with an alarm threshold or limit to determine if it exceeds the limit. Definition: Assuming that m stations observe satellite frequency point j at the same epoch, the UERE calculation method for satellite frequency point j after integrating multiple station observations is as follows:

[0077]

[0078] In the formula, Min() is the minimum value function, and || is the absolute value function;

[0079] Example:

[0080] To accurately reflect the UERE calculation and monitoring results, this invention uses observation data from 43 global tracking stations of the International GNSS Monitoring and Evaluation System (iGMAS) and the International GNSS Service Organization (IGS) for the entire day of April 29, 2024. All tracking station clocks were not synchronized, and the true value of the receiver clock difference was unknown. The B1I frequency point of the BeiDou C25 satellite, where the satellite was in good condition and the space signal was normal on that day, is used as a monitoring and calculation example.

[0081] like Figure 2The table shows the UERE result sequence of each station obtained by the aforementioned global tracking stations on April 29, 2024, based on steps (1) to (6) using the "median station clock elimination method". It can be seen that under the premise that the satellite is healthy and the space signal is normal, the UERE time series variation range of each station is basically ±10 meters, and the short-term UERE of individual stations even reaches 20 to 50 meters. This is because a single station may be affected by the surrounding environment, such as obstruction or signal interference, which may lead to a decrease or even anomaly in the quality of the observation data. Other abnormalities may occur, such as local space environment anomalies like ionospheric scintillation and activity, abnormal local ionospheric models, and low elevation angles. These situations may cause a sharp increase in the ionospheric correction residuals of some affected stations. All of the above situations may lead to a situation where the satellite downlink signal is normal, but the UERE monitoring results of individual stations are too large or even abnormal. If the UERE monitoring results of that station are accepted at this time, it will cause false alarms.

[0082] Considering that UERE here is primarily used to monitor for anomalies in the accuracy of satellite-end space signals (mainly broadcast orbits and clock biases), rather than to monitor anomalies in the user-end environment, terminal equipment, or local space environment, therefore, in Figure 2 Based on the monitoring results, according to step (7), the UERE monitoring results after multi-station integration are calculated using the "minimum value multi-station integration method", such as... Figure 3 As shown, under the premise that the satellite is healthy and the space signal is normal, the UERE after multi-station integration basically varies within ±2.5 meters. This can greatly reduce the monitoring gross errors caused by individual station equipment, surrounding environment, local space environment or model anomalies, and low elevation angles, thereby improving the accuracy and reliability of navigation satellite UERE global continuous monitoring results.

[0083] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for monitoring navigation satellite UERE based on multi-station asynchronous observation data, characterized in that: Includes the following steps: S1. Read the observation data from the tracking station to obtain the pseudorange observation value of the navigation signal frequency point j of satellite s measured by the tracking station terminal r at a certain epoch. S2. Read the satellite's Earth-fixed coordinates at the time of signal transmission from the broadcast ephemeris and perform Earth rotation correction. Calculate the true geometric distance from the satellite to the tracking station based on the satellite coordinates and the known coordinates of the tracking station terminal r. Based on the known coordinates of the receiver, navigation messages, and atmospheric correction models, the calculated values ​​of satellite clock error, tropospheric delay error, ionospheric delay error, relativistic effect correction, and satellite endcode hardware delay are obtained. The pseudorange calculation value is obtained based on the actual geometric distance from the satellite to the station, the calculated satellite clock error, the calculated tropospheric delay error, the calculated ionospheric delay error, the calculated relativistic effect correction, and the calculated satellite endcode hardware delay. S3, the pseudo-range observation values With the pseudorange calculated value The difference between the observed and calculated pseudorange values ​​is obtained by subtracting the pseudorange values. Return to step S1 and iteratively calculate the difference between the pseudorange observations and the calculated values ​​for all satellites at the same epoch. After the calculation is completed, store all the pseudorange observations minus the calculated values. Proceed to step S4; S4. For the n satellites with epoch tracking station terminal r... The values ​​are sorted in ascending order, S = 1, 2, ..., n. Based on the sorting result, a sequence of pseudorange observations minus calculated values ​​is obtained: OMC1≤OMC2≤…≤OMC n-1 ≤OMC n ; S5. Calculate the median Mdn(OMC) of the OMC based on the pseudorange observation value minus the calculated value sequence; S6. The satellites at the given epoch time... Subtract the median Mdn(OMC) of the OMC sequence at the given epoch to obtain the UERE for each satellite; Return to step S1, iterate through all tracking station terminals r, and obtain the satellite observations of all tracking stations at the given epoch time. S7. Obtain the UERE monitoring results after multi-station integration using the minimum value multi-station integration method. Where Min() is the minimum value function, || is the absolute value function, and m is the total number of tracking station terminals that have observed satellite S; A method for monitoring navigation satellite UERE based on multi-station asynchronous observation data has been completed.

2. The navigation satellite UERE monitoring method based on multi-station asynchronous observation data according to claim 1, characterized in that: In step S1, in, dt represents the geometric distance between the satellite and the Earth. r For receiver clock bias, dt S For satellite clock bias, For tropospheric delay error, μ j Let be the ionospheric delay effect coefficient at frequency j. For ionospheric delay error, d rela To correct for relativistic effects, d r,j For receiver endcode hardware delay, Due to satellite end-code hardware latency, This is multipath error.

3. The navigation satellite UERE monitoring method based on multi-station asynchronous observation data according to claim 2, characterized in that: Where f1 is the default frequency point for calculating the ionospheric delay error.

4. The navigation satellite UERE monitoring method based on multi-station asynchronous observation data according to claim 1, characterized in that: In steps S1 and S2, after reading the tracking station observation data and navigation ephemeris, satellite PRN number matching and time matching are performed in the navigation ephemeris based on the satellite PRN number read from the observation data. If the matching is successful, satellite coordinates, satellite clock error and satellite station geometric distance are calculated. If the matching is unsuccessful, the ephemeris is read again for matching until the ephemeris data is finished.

5. A method for monitoring navigation satellite UERE based on multi-station asynchronous observation data according to claim 2, characterized in that: In step S2, in, This is a calculated value for the geometric distance between the satellite and the ground. This is the calculated value for satellite clock bias. This is the calculated value of tropospheric delay error. This is the calculated value of ionospheric delay error. The calculated values ​​are corrected for relativistic effects. This is the calculated value for the satellite endcode hardware delay.

6. The navigation satellite UERE monitoring method based on multi-station asynchronous observation data according to claim 5, characterized in that: In step S3, in, To account for residual errors, This includes navigation message parameter errors, atmospheric delay correction residual errors, measurement noise, and multipath errors.

7. The navigation satellite UERE monitoring method based on multi-station asynchronous observation data according to claim 1, characterized in that: In step S4, first determine if the number of satellites is greater than or equal to 2. If so, proceed. If the order is not specified, the solution cannot be found.

8. The navigation satellite UERE monitoring method based on multi-station asynchronous observation data according to claim 1, characterized in that: In step S5, 9. A method for monitoring navigation satellite UERE based on multi-station asynchronous observation data according to claim 1, characterized in that: In step S6, in, To account for residual errors, This includes residual errors in navigation message parameters, atmospheric delay correction, measurement noise, and multipath.

Images