Method and apparatus for implementing satellite selection and multi-system multi-frequency receiver

Abstract

The application discloses a method and device for selecting satellites and a multi-system multi-frequency receiver, and through the satellites selected according to frequency points and measurement accuracy, the number of observations and the satellites with optimal theoretical observation accuracy are effectively ensured, the problems of large calculation amount when the number of tracked satellites is enough and the quality of observations of different frequency points and different satellites not being considered are solved, and the positioning performance of the multi-system multi-frequency GNSS receiver is improved. Further, the satellites with large gross errors are effectively reduced to enter calculation, the probability of RAIM satellites and iterative calculation is reduced, the problem of position calculation failure caused by the position being polluted by the gross error observation value in a complex environment, the position deviation being difficult to recover in subsequent calculation or the position calculation failure after the number of RAIM false detections is large is effectively solved, and the accuracy and reliability of the pseudorange calculation of the GNSS receiver are effectively improved.

Description

Technical Field

[0001] This application relates to, but is not limited to, satellite navigation technology, and particularly to a method and apparatus for satellite selection and a multi-system multi-frequency receiver. Background Technology

[0002] With the full establishment and continuous improvement of the four major Global Navigation Satellite Systems (GNSS), and the gradual development and improvement of Japan's Quasi-Zenith Satellite System (QZSS) and India's Indian Space Navigation Satellite System (IRNSS), the number of civilian satellite navigation signals and satellites is becoming increasingly abundant, and the application scenarios of GNSS multi-system and multi-frequency systems are becoming increasingly widespread. In China and its surrounding areas, users theoretically have more than 40 visible satellites around the clock. This means that in most GNSS application scenarios, the number of tracking satellites is no longer the primary factor limiting user service performance. However, an excessive number of satellite signals and satellites brings a series of complex operations to GNSS receivers, including frequency selection and switching, a surge in computational load, and the detection and identification of more coarse observations.

[0003] With the current availability of multiple GNSS systems and frequencies, if all tracking satellites were to participate in positioning calculations, the computational load on GNSS receivers would increase dramatically. Calculating the positioning of N GNSS constellations requires at least N+3 satellites. However, once the number of satellites is sufficiently large—that is, after the Dilution of Precision (DOP) decreases to a certain range—further increasing the number of satellites will have a diminishing effect on improving positioning, and may even introduce poorer observations leading to a decrease in accuracy. Therefore, in open scenarios, with a sufficient number of tracking satellites and a good satellite geometric distribution, selecting some observations of relatively good quality for the solution can avoid large matrix operations while achieving ideal positioning accuracy. In obstructed or complex scenarios, some satellites may be blocked, and gross errors have a greater impact on the positioning results. In such cases, selecting satellite observations with smaller errors for the solution can greatly reduce the probability of position deviation. Based on accurate positioning, this can reduce the probability of errors in Receiver Autonomous Integrity Monitoring (RAIM) and the number of iterations, and further help to correctly identify gross errors. Especially in complex dynamic scenarios, a well-developed satellite selection strategy can effectively improve the accuracy and continuity of the positioning solution. Summary of the Invention

[0004] This application provides a method, apparatus, and system multi-frequency receiver for satellite selection, which can improve the positioning performance of multi-system multi-frequency GNSS receivers.

[0005] This invention provides a method for satellite selection, comprising:

[0006] Based on the number of effective satellites at each frequency point in the multi-system multi-frequency global satellite navigation system (GNSS) and the tracking quality information of each satellite at each frequency point, the frequency points that meet the quality conditions of each system are selected as the selected frequency points of each satellite in each system.

[0007] Estimate the accuracy of the observations of each satellite corresponding to the selected frequency point, and select a first preset number of first candidate satellites from all satellites simultaneously tracked by multi-system multi-frequency GNSS based on the estimated accuracy.

[0008] This application also provides a computer-readable storage medium storing computer-executable instructions for performing the satellite selection method described in any of the above embodiments.

[0009] This application embodiment further provides a device for satellite selection, including a memory and a processor, wherein the memory stores the following instructions executable by the processor: for performing the steps of the satellite selection method described in any of the above claims.

[0010] This application also provides an apparatus for satellite selection, comprising: a frequency selection module and a first processing module, wherein...

[0011] The frequency selection module is used to select the frequency points of each system that meet the quality conditions as the selected frequency points of each system and each satellite based on the number of effective satellites at each frequency point in the multi-system multi-frequency GNSS and the tracking quality information of each satellite at each frequency point.

[0012] The first processing module is used to estimate the accuracy of the observations of each satellite corresponding to the selected frequency point, and select a first preset number of first candidate satellites as selected satellites from all satellites simultaneously tracked by multi-system multi-frequency GNSS based on the estimated accuracy.

[0013] This application provides another embodiment of a multi-system multi-frequency receiver, including the satellite selection device described in any one of the embodiments of this application.

[0014] In this embodiment, by selecting satellites based on frequency points and measurement accuracy, the number of observations and the satellites with the best theoretical observation accuracy are effectively guaranteed. This solves the problems of large computational load when tracking a large number of satellites and the lack of consideration for the observation quality of different frequency points and different satellites, thereby improving the positioning performance of multi-system multi-frequency GNSS receivers.

[0015] Furthermore, it effectively reduces the number of satellites with large gross errors entering the calculation, thus reducing the probability of RAIM satellites and iterative calculations. It effectively solves the problems of position contamination by gross observations in complex environments, difficulty in recovering position deviations in subsequent calculations, or position calculation failures due to numerous RAIM false detections. This significantly improves the accuracy and reliability of pseudorange calculations for GNSS receivers. Especially in complex scenarios with unstable signals such as various obstructions, interference, and severe multipath events during use, its availability and accuracy are further enhanced.

[0016] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description and the drawings. Attached Figure Description

[0017] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0018] Figure 1 This is a flowchart illustrating one embodiment of the satellite selection method in this application.

[0019] Figure 2 This is a flowchart illustrating another embodiment of the satellite selection method described in this application.

[0020] Figure 3 A schematic diagram illustrating the positioning accuracy of satellite selection methods in related technologies;

[0021] Figure 4 This is a schematic diagram illustrating the positioning accuracy of the satellite selection method in this embodiment of the application;

[0022] Figure 5 This is a schematic diagram of the composition structure of an embodiment of the device for satellite selection in this application.

[0023] Figure 6 This is a schematic diagram of the composition of another embodiment of the device for satellite selection in this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be arbitrarily combined with each other.

[0025] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0027] It is understood that the terms "first" and "second" used in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0028] It is understood that the term "connection" in the following embodiments should be understood as "electrical connection," "communication connection," etc., if the connected circuits, modules, units, etc., have electrical signal or data transmission with each other.

[0029] When used herein, the singular forms of “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising / including” or “having,” etc., specify the presence of the stated features, wholes, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0030] GNSS positioning accuracy is affected by both the observation accuracy and geometric distribution of the satellites involved in the calculation. In related technologies, most common satellite selection algorithms are based on satellite geometry, such as calculating the geometric accuracy factor for different satellite combinations using formulas, or based on spatial geometric distribution, elevation angle, or tracking signal carrier-to-noise ratio. Star selection is performed. Related star selection algorithms all consider optimal spatial distribution or optimal signal tracking performance, aiming to minimize the DOP value or select a higher elevation angle when both observation quality and accuracy are good. Higher-resolution satellites generally perform better, but this satellite selection algorithm is not well-suited for complex scenarios with signal interference. Furthermore, the satellite selection algorithms in these technologies operate independently within each system, failing to fully consider the differences in the accuracy of observations from different satellites and frequencies in real time. In complex urban environments with signal interference, tall buildings obstructing the view, and glass curtain walls, where some satellites or frequencies have a significant impact, the satellite selection algorithms in these technologies cannot effectively select and track more stable system frequencies and higher-precision satellite observations. This can lead to problems such as using observations with poor frequencies or gross errors in the calculation, resulting in decreased position accuracy, RAIM satellite errors, or even calculation failure.

[0031] Therefore, this application proposes a method for satellite selection to improve the positioning performance of multi-system, multi-frequency GNSS receivers, such as... Figure 1 As shown, it includes:

[0032] Step 100: Based on the number of effective satellites at each frequency point in the multi-system multi-frequency GNSS and the tracking quality information of each satellite at each frequency point, select the frequency points of each system that meet the quality conditions as the selected frequency points of each satellite in each system.

[0033] In one exemplary instance, this step may also include:

[0034] The GNSS receiver acquires the current observations and the ephemeris information of each satellite. In one embodiment, the ephemeris information is processed to obtain the elevation and azimuth angles, DOP values, pseudorange values, etc., of each satellite.

[0035] In one exemplary instance, step 100 may include:

[0036] Multiple frequency points tracked simultaneously by various systems ... Based on the effective number of satellites at each frequency point and the average carrier-to-noise ratio tracked by each satellite Average tracking time The overall quality weights for each frequency point are calculated according to formula (1). ... Each system selects one or more required frequency points according to the weight value, which are then used as satellite frequency points for subsequent positioning calculations.

[0037] (1)

[0038] Where i = 1, 2…n; proportionality coefficient proportionality coefficient proportionality coefficient Different scaling factors can be set as needed based on the importance of different parameters. The larger the scaling factor, the greater the weight of that parameter when selecting frequency points. As a constant term, it is given based on empirical values ​​for different frequencies of various systems; different A relatively large value can ensure the relative priority of use of each frequency point when other parameters are the same.

[0039] Using formula (1), the values ​​at each of the n frequency points are calculated separately. ... Sort them in descending order, if The largest value indicates that the Li frequency point of the system is optimal, and the Li frequency point is the single-frequency selected frequency point. The principle is similar for dual-frequency or multi-frequency systems; the selected frequency points are those that meet the dual-frequency or multi-frequency combination and are sorted from largest to smallest. It can be seen that the selected frequency point in the embodiment of this application is the optimal frequency point.

[0040] In formula (1), according to The multiple weights of these calculations may be used to calculate... It is the maximum. At this point, if the frequency point is empirically optimal... If the value is set relatively large, then, depending on different frequency points This ensures that the frequency point that is optimal based on experience will be used first.

[0041] In one embodiment, in actual use, the effective number of satellites at each frequency point Carrier-to-noise ratio Tracking time A reasonable threshold can be set based on experience. For example, when a certain frequency point has a certain threshold value for this item (such as the number of effective satellites or the carrier-to-noise ratio), it can be set. or tracking time If the value exceeds the set threshold, then it can be considered that the item has met the optimal condition set for it.

[0042] Step 100 ensures that a sufficient number of satellites and frequency observations with optimal accuracy are available.

[0043] Step 101: Estimate the accuracy of the observations of each satellite corresponding to the selected frequency point, and select a first preset number of candidate satellites from all satellites simultaneously tracked by multi-system multi-frequency GNSS based on the estimated accuracy.

[0044] In one exemplary instance, the accuracy of observations at selected frequency points for each satellite in each system can be estimated based on a stochastic model. Here, a stochastic model is a technical term used in the field to describe the observations and their statistical correlations in an adjustment problem. In this application, the stochastic model of the observations refers to the measurement noise variance of the observations.

[0045] In one exemplary instance, for each selected frequency point of each system, the satellites corresponding to the selected frequencies are analyzed based on information about each satellite, such as the satellite's elevation angle and tracking carrier-to-noise ratio. And tracking time and other related parameters, the measurement noise variance of the observations of each satellite corresponding to the selected frequency point is calculated according to the random model (that is, formula (2) in this application). And calculate the measurement noise variance. All the particles (assuming to be) (number) satellites, according to accuracy Select the first preset quantity based on high and low. The first alternative satellite. In one embodiment, if the measurement noise variance is calculated... Total number of satellites Less than the first preset number Then, calculate the measurement noise variance. All satellites All of them were selected as the first alternative satellites.

[0046] In one exemplary instance, as shown in formula (2), the measurement noise variance of the observations of the j-th satellite among the satellites corresponding to the selected frequency point is... This can be expressed as the statistical sum of the error terms included in the measured value:

[0047] (2)

[0048] In formula (2), ; This indicates the error terms related to the satellite clock and ephemeris at the satellite end. This represents the remaining error term after modeling the errors in the ionosphere and troposphere. Represents the random noise term of the measurement. The error term represents the multipath effect caused by the measurement environment. This indicates the typical ranging accuracy for different GNSS satellite systems. This indicates the typical ranging accuracy for different frequencies. In one embodiment, , The settings are related to the characteristics of each GNSS system and frequency point, and can be configured based on experience and receiver tracking characteristics. The relative magnitude of the value ensures that, when other aspects of accuracy are comparable, the system satellite with higher accuracy will be given priority. The relative size ensures that, when other aspects of accuracy are comparable, satellites with higher accuracy frequencies can be used preferentially.

[0049] In one exemplary instance, the accuracy of the j-th satellite The value is shown in formula (3):

[0050] (3)

[0051] In formula (3), This represents the accuracy setting based on the effective positioning status and continuity of the j-th satellite. If the satellite has never participated in positioning, then... .

[0052] In one exemplary instance, when measuring noise variance Based on this, for satellites that have already participated in positioning calculations continuously, the number of satellites can be increased. To improve the accuracy of satellite j, this solves the problem of measurement noise variance when there are a sufficient number of satellites. The frequent switching between several similar satellites ensures the stability of the final satellite used for positioning calculation.

[0053] The satellite selection method provided in this application effectively ensures the number of observations and the satellites with the best theoretical observation accuracy by selecting satellites based on frequency points and measurement accuracy. It solves the problems of large computational load when tracking a large number of satellites and the lack of consideration for the observation quality of different frequency points and different satellites, thereby improving the positioning performance of multi-system multi-frequency GNSS receivers.

[0054] In one exemplary instance, such as Figure 2 As shown in the embodiments of this application, the method for satellite selection may further include:

[0055] Step 102: Based on the distribution of pre-test residual values ​​of each satellite, perform gross error verification on the first candidate satellite to select the second candidate satellite, so as to reduce the number of satellites with residuals greater than the preset residual threshold from entering the solution;

[0056] Step 103: Select a second preset number of satellites from the second candidate satellites as the selected satellites.

[0057] In one exemplary instance, step 102 may include:

[0058] The first candidate satellites are selected, and the observations of each first candidate satellite are checked for gross errors based on the distribution of the pre-approval residual values ​​of each satellite. Satellites with residuals greater than the first preset residual threshold are removed.

[0059] For the remaining satellites after the first gross error check, the current position information is initially estimated based on the accuracy of the observations of the remaining satellites and using the observations of the satellites with the highest observation accuracy and the most consistent residual distribution.

[0060] Based on the estimated position information, the observation residuals of all first candidate satellites are calculated. A second gross error check is performed on the residuals of each satellite and the overall residuals. Satellites with residuals greater than a second preset residual threshold are removed. The measurement weights of satellites whose residuals meet the residual condition (i.e., the residuals are moderate, such as the residuals being greater than a third preset residual threshold but less than a second preset residual threshold) are reduced. This yields the final number of satellites that pass the check. A second, relatively high-quality alternative satellite.

[0061] The second preset residual threshold is greater than the third preset residual threshold. In practical applications, the first preset residual threshold can be set smaller to ensure that the satellite observations used to calculate the estimated position are reliable.

[0062] In this embodiment, step 102 filters out satellites with large residuals in each system based on the pre-approval residual distribution. Then, the satellites with the best pseudorange quality are selected to initially estimate the current position information. Based on this current position information, the observation residuals of all candidate satellites are initially calculated. The residuals of each satellite and the overall residuals are detected. Finally, satellites with large residuals are either removed or have their measurement weights reduced. This effectively reduces the number of satellites with large gross errors entering the calculation, reducing the probability of RAIM satellites and iterative calculations. It effectively solves the problems of position contamination by gross observations in complex environments, difficulty in recovering position deviations in subsequent calculations, or position calculation failures due to numerous RAIM false detections. This effectively improves the accuracy and reliability of GNSS receiver pseudorange calculations. Especially in complex scenarios with unstable signals such as various obstructions, interference, and severe multipath events during use, its usability and accuracy are further improved.

[0063] In one exemplary instance, prior to the first gross error check in step 102, the following may also be included:

[0064] If it is determined that the number of first candidate satellites in each system is relatively large (for example, the number of first candidate satellites is greater than the preset first number), then satellites with residuals greater than the fourth preset residual threshold (the fourth preset residual threshold is greater than the first preset residual threshold) are removed based on the pre-examination residual distribution of each satellite in each system.

[0065] If it is determined that the number of first candidate satellites in each system or a single system is too small (for example, the number of first candidate satellites is less than the preset second number), then frequency offset compensation is performed on these systems or the satellites within each system to supplement the number of first candidate satellites to the first preset number. The first preset quantity will be supplemented. A number of satellites are selected as the first candidate satellites for the pre-test residual distribution detection in step 102.

[0066] In one exemplary instance, in step 102, when calculating the observation residuals of all first candidate satellites based on the estimated position information, the accuracy of the position information directly affects the accuracy of the calculated observation residuals and the validity of the check. Therefore, in addition to directly estimating the position information based on the observations of the remaining satellites after the first gross error check, according to the accuracy of the observations of the remaining satellites, using the observations of the satellites with the highest observation accuracy and the most consistent residual distribution, one method is to obtain other modules with higher accuracy from the receiver. For example, a GNSS receiver can use carrier observations or Doppler observations to perform higher accuracy position calculations. Another method is to obtain it through other means, such as the effective position maintained by the GNSS inertial navigation module, or the effective position obtained through map matching, vision, etc.

[0067] In one exemplary instance, step 103 may include:

[0068] Based on the second number of final approvals The observations and measurement weights of a second, high-quality candidate satellite are selected, along with a second preset number. The satellites were selected as the final satellites.

[0069] This step further improves the positioning performance of the multi-system, multi-frequency GNSS receiver.

[0070] In one exemplary instance, the method for satellite selection provided in this application embodiment may further include:

[0071] Position calculation is performed based on observations from a second preset number of satellites to obtain user location information.

[0072] The satellite selection method provided in this application embodiment, compared with the satellite selection algorithm in related technologies, fully considers the differences in the accuracy of observations of different frequencies and different satellites under different environments when there are enough available satellites for current multi-system multi-frequency GNSS receivers. It comprehensively selects frequencies and observations and performs targeted processing on observations with large gross errors, selecting a reasonable number of satellite observations with good quality to participate in the positioning calculation with a small amount of computation.

[0073] This application also provides a computer-readable storage medium storing computer-executable instructions for performing the satellite selection method described in any of the preceding claims.

[0074] This application further provides an apparatus for satellite selection, including a memory and a processor, wherein the memory stores the following instructions executable by the processor for performing the steps of the satellite selection method described in any of the preceding claims.

[0075] In one embodiment, assuming the same multi-system, multi-frequency GNSS receiver collects GNSS data in urban areas with high-rise buildings, dense trees, and severe obstruction from overpasses, and performs pseudorange post-processing positioning calculations, for the same data, the positioning accuracy obtained using the method described in related technologies that does not involve selecting alternative satellites or verifying observations is as follows: Figure 3 As shown, the positioning accuracy obtained by selecting satellites according to the embodiment of this application is as follows: Figure 4 As shown in the statistical results, the positioning accuracy obtained by the satellite selection method provided in this application embodiment is significantly better than the positioning accuracy obtained by the related technology without selecting alternative satellites and checking the observations. The satellite selection method provided in this application embodiment effectively improves the pseudorange positioning accuracy in complex scenarios.

[0076] Figure 5 This is a schematic diagram of the composition of the device for satellite selection in the embodiments of this application, as shown below. Figure 5 As shown, it includes: a frequency selection module and a first processing module, wherein,

[0077] The frequency selection module is used to select the frequency points that meet the quality conditions of each system as the selected frequency points of each system and each satellite, based on the number of effective satellites at each frequency point in the multi-system multi-frequency GNSS and the tracking quality information of each satellite at each frequency point.

[0078] The first processing module is used to estimate the accuracy of the observations of each satellite corresponding to the selected frequency point, and select a first preset number of first candidate satellites from all satellites simultaneously tracked by multi-system multi-frequency GNSS based on the estimated accuracy.

[0079] In one exemplary instance, such as Figure 6 As shown in the embodiments of this application, the apparatus for satellite selection may further include: an acquisition module, used to acquire observations at the current time and acquire ephemeris information of each satellite. In one embodiment, by calculating the ephemeris information, the elevation angle and azimuth angle, DOP value, pseudorange value, etc., of each satellite can be obtained.

[0080] The satellite selection device provided in this application effectively ensures the number of observations and the satellites with the best theoretical observation accuracy by selecting satellites based on frequency points and measurement accuracy. It solves the problems of large computational load when tracking a large number of satellites and the lack of consideration for the observation quality of different frequency points and different satellites, thereby improving the positioning performance of multi-system multi-frequency GNSS receivers.

[0081] In one exemplary instance, such as Figure 6As shown, the satellite selection apparatus provided in this application embodiment may further include: a second processing module, used to perform gross error verification on the first candidate satellites and select a second candidate satellite based on the distribution of the pre-verification residual values ​​of each satellite, so as to reduce the number of satellites with residuals greater than a preset residual threshold from entering the calculation; and to select a second preset number of satellites from the second candidate satellites as the selected satellites.

[0082] In one exemplary instance, the second processing module performs gross error checking on the first candidate satellite to select a second candidate satellite, including:

[0083] The first candidate satellites are selected, and the observations of each first candidate satellite are checked for gross errors based on the distribution of the pre-approval residual values ​​of each satellite. Satellites with residuals greater than the first preset residual threshold are removed.

[0084] For the remaining satellites after the first gross error check, the current position information is initially estimated using the observations of the satellites with the highest observation accuracy and consistent residual distribution, based on the accuracy of the remaining satellite observations.

[0085] Based on the estimated position information, the observation residuals of all first candidate satellites are calculated. A second gross error check is performed on the residuals of each satellite and the overall residuals. Satellites with residuals greater than the second preset residual threshold are removed. The measurement weights of satellites whose residuals meet the residual conditions are reduced to obtain the second number of second candidate satellites that finally pass the check.

[0086] Wherein, the second preset residual threshold is greater than the third preset residual threshold; the residual condition includes: the residual is greater than the third preset residual threshold and less than the second preset residual threshold.

[0087] In one exemplary instance, the second processing module is further configured to:

[0088] Before the first gross error check, if it is determined that the number of first-selection satellites in each system is relatively large (e.g., the number of first-selection satellites is greater than the preset first number), then, based on the pre-test residual distribution of each satellite in each system, satellites with residuals greater than the fourth preset residual threshold (the fourth preset residual threshold is greater than the first preset residual threshold) are removed; or,

[0089] If it is determined that the number of first candidate satellites in each system or a single system is too small (for example, the number of first candidate satellites is less than the preset second number), then frequency offset compensation is performed on these systems or the satellites within each system to supplement the number of first candidate satellites to the first preset number. The first preset quantity will be supplemented. A number of satellites are selected as the first candidate satellites for the pre-test residual distribution detection in step 102.

[0090] In one exemplary instance, such as Figure 6 As shown, the device for satellite selection provided in this application embodiment may further include: a calculation module, used to perform position calculation based on the observations of a second preset number of satellites to obtain user position information.

[0091] The satellite selection method provided in this application embodiment, compared with the satellite selection algorithm in related technologies, fully considers the differences in the accuracy of observations of different frequencies and different satellites under different environments when there are enough available satellites for current multi-system multi-frequency GNSS receivers. It comprehensively selects frequencies and observations and performs targeted processing on observations with large gross errors, selecting a reasonable number of satellite observations with good quality to participate in the positioning calculation with a small amount of computation.

[0092] This application also provides a multi-system multi-frequency receiver, including the satellite selection apparatus described in any of the above claims.

[0093] Although the embodiments disclosed in this application are as described above, the content described is merely for the purpose of understanding this application and is not intended to limit this application. Any person skilled in the art to which this application pertains may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this application; however, the scope of patent protection of this application shall still be determined by the scope defined in the appended claims.

Claims

1. A method for satellite selection, characterized in that, include: Based on the number of effective satellites at each frequency point in the multi-system, multi-frequency global navigation satellite system (GNSS) and the tracking quality information of each satellite at each frequency point, frequency points that meet the quality conditions of each system are selected as the selected frequency points for each satellite of each system, including: multiple frequency points simultaneously tracked by each system. ... Based on the effective number of satellites at each frequency point and the average carrier-to-noise ratio tracked by each satellite Average tracking time The overall quality weight of each frequency point is calculated according to the following formula. ... Each system selects one or more required frequency points according to the weight values, which are then used as the selected frequency points. , i = 1, 2…n; where, the proportionality coefficient proportionality coefficient proportionality coefficient Different scaling coefficients can be set as needed, depending on the importance of different parameters. As a constant term, it is given based on empirical values ​​for different frequency points of each system; Estimate the accuracy of the observations of each satellite corresponding to the selected frequency point, and select a first preset number of first candidate satellites from all satellites simultaneously tracked by multi-system multi-frequency GNSS based on the estimated accuracy.

2. The method according to claim 1, further comprising: Based on the distribution of pre-test residual values ​​of each satellite, the first candidate satellite is subjected to gross error verification to select the second candidate satellite, so as to reduce the number of satellites whose residuals exceed the preset residual threshold from entering the solution. Select a second preset number of satellites from the second candidate satellites as the selected satellites.

3. The method according to claim 1 or 2, wherein, The number of effective satellites at the frequency point or the aforementioned carrier-to-noise ratio or the tracking time Exceeding their respective set threshold values.

4. The method according to claim 1 or 2, wherein, The step of selecting a first preset number of candidate satellites as the selected satellites includes: For each satellite corresponding to the selected frequency point of each selected system, the measurement noise variance of the observations of each satellite corresponding to the selected frequency point is calculated based on the information of each satellite. ; calculate the variance of the measurement noise All satellites, according to accuracy Select the first preset quantity based on high and low. The first candidate satellite.

5. The method according to claim 4, wherein, If the measurement noise variance is calculated If the total number of all satellites is less than a first preset number, the measurement noise variance is calculated. All of the satellites were selected as the first candidate satellites.

6. The method according to claim 4, wherein, The measurement noise variance of the observations of the j-th satellite among the satellites corresponding to the selected frequency points. This is expressed as the statistical sum of the error terms included in the measured value: ； in, , This indicates the calculation of the measurement noise variance. The total number of all satellites; This indicates the error terms related to the satellite clock and ephemeris at the satellite end. This represents the remaining error term after modeling the errors in the ionosphere and troposphere. Represents the random noise term of the measurement. The error term represents the multipath effect caused by the measurement environment. This indicates the typical ranging accuracy for different GNSS satellite systems. This indicates the typical ranging accuracy for different frequencies.

7. The method according to claim 4, wherein, The accuracy of the j-th satellite among the satellites corresponding to the selected frequency point The value is shown in the following formula: ； in, This indicates the accuracy setting based on the effective status and continuity of the positioning already participated in by the j-th satellite.

8. The method according to claim 2, wherein, The step of performing gross error verification on the first candidate satellite to select the second candidate satellite includes: The first candidate satellites are selected, and the observations of each first candidate satellite are checked for gross errors based on the distribution of the pre-approval residual values ​​of each satellite. Satellites with residuals greater than the first preset residual threshold are removed. For the remaining satellites after the first gross error check, the current position information is initially estimated using the observations of the satellites with the highest observation accuracy and consistent residual distribution, based on the accuracy of the observations of the remaining satellites. Based on the estimated position information, the observation residuals of all the first candidate satellites are calculated. A second gross error check is performed on the residuals of each satellite and the overall residuals. Satellites with residuals greater than the second preset residual threshold are removed. The measurement weights of satellites whose residuals meet the residual conditions are reduced. The second number of the second candidate satellites that pass the final check are obtained. Wherein, the second preset residual threshold is greater than the third preset residual threshold; the residual condition includes: the residual is greater than the third preset residual threshold and less than the second preset residual threshold.

9. The method according to claim 8, further comprising, before the first gross error check: If the number of the first candidate satellites in each system is greater than a preset first number, satellites with residuals greater than a fourth preset residual threshold are removed based on the pre-examination residual distribution of each satellite in each system. If it is determined that the number of first candidate satellites in each system or a single system is less than a preset second number, frequency point deviation compensation is performed on these systems or each satellite in the system to supplement the number of first candidate satellites to a first preset number, and the first preset number of satellites after the supplementation are used as the first candidate satellites to perform the step of the distribution of the pre-examination residual values ​​of each satellite. Wherein, the fourth preset residual threshold is greater than the first preset residual threshold.

10. The method according to claim 8, wherein, The step of selecting a second preset number of satellites from the second candidate satellites as the selected satellites includes: Based on the observations and measurement weights of the second number of candidate satellites, a second preset number of satellites are selected as the final selected satellites.

11. A computer-readable storage medium storing computer-executable instructions for performing the satellite selection method according to any one of claims 1 to 10.

12. A device for satellite selection, comprising a memory and a processor, wherein, The memory stores the following instructions that can be executed by a processor: for performing the steps of the method for satellite selection as described in any one of claims 1 to 10.

13. A device for satellite selection, characterized in that, include: Frequency selection module, first processing module, wherein, The frequency selection module is used to select frequency points that meet the quality conditions of each system as the selected frequency points for each satellite of each system, based on the number of effective satellites at each frequency point in the multi-system multi-frequency GNSS and the tracking quality information of each satellite at each frequency point. This includes: selecting multiple frequency points that are simultaneously tracked by each system. ... Based on the effective number of satellites at each frequency point and the average carrier-to-noise ratio tracked by each satellite Average tracking time The overall quality weight of each frequency point is calculated according to the following formula. ... Each system selects one or more required frequency points according to the weight values, which are then used as the selected frequency points. , i = 1, 2…n; where, the proportionality coefficient proportionality coefficient proportionality coefficient Different scaling coefficients can be set as needed, depending on the importance of different parameters. As a constant term, it is given based on empirical values ​​for different frequency points of each system; The first processing module is used to estimate the accuracy of the observations of each satellite corresponding to the selected frequency point, and select a first preset number of first candidate satellites as selected satellites from all satellites simultaneously tracked by multi-system multi-frequency GNSS based on the estimated accuracy.

14. A multi-system multi-frequency receiver, characterized in that, Includes the satellite selection apparatus as described in claim 13.

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