A ramming point guiding method and system fusing a Beidou positioning signal

Abstract

The present application relates to the technical field of satellite positioning, and particularly relates to a ramming point guiding method and system fusing Beidou positioning signals. The method comprises the following steps: in a plurality of solving satellites at a target positioning moment, according to the signal propagation distance, signal propagation delay and ambiguity solving value of each solving satellite; according to the solving reconstructed phase value and carrier phase observation value of each solving satellite, a cross cost matrix is constructed; feature analysis is performed on the cross cost matrix to obtain solving feature information, wherein the solving feature information comprises mismatch features, instability features and cost features; and the solving feature information is processed according to a preset control strategy to obtain ramming point positioning detection information at the target positioning moment. The present application can inhibit the use of abnormal ramming point positioning results with extremely high confidence but position deviation up to several decimeters, and improve the application effect of real-time kinematic technology in the strong ramming operation scene.

Description

Technical Field

[0001] This invention relates to the technical field of satellite positioning, and specifically to a method and system for guiding point stabilization by integrating BeiDou positioning signals. Background Technology

[0002] Dynamic compaction is a commonly used technique for foundation treatment, and its construction quality is closely related to the accuracy of the compaction point location. To improve construction efficiency and accuracy, existing technologies often use real-time dynamic differential (RTK) technology that integrates global navigation satellite systems (GNSS) such as BeiDou. This technology achieves high-precision real-time guidance of the hammer position by installing a receiver on the dynamic compaction machine.

[0003] However, in application, it was found that in typical dynamic compaction operation scenarios such as port terminals, water edges, and near large steel structure factories, the RTK solution algorithm sometimes outputs a positioning result with extremely high confidence but a positional deviation of several decimeters. Operators and conventional quality monitoring methods, such as simple residual value checks, cannot effectively identify this abnormal positioning result, which makes the application effect of RTK technology in dynamic compaction operation scenarios poor. Summary of the Invention

[0004] The purpose of this invention is to provide a compaction point guidance method and system that integrates BeiDou positioning signals, in order to solve the technical problem of poor application effect of RTK technology in dynamic compaction operation scenarios.

[0005] In a first aspect, one embodiment of the present invention provides a method for guiding point stabilization by integrating BeiDou positioning signals, the method comprising:

[0006] Among the multiple solution satellites at the target positioning time, the solution reconstruction phase value of each solution satellite is determined based on the signal propagation distance, signal propagation delay, and ambiguity solution value of each solution satellite. The target positioning time is one of the multiple positioning times corresponding to the tamping point control process.

[0007] Based on the solved reconstructed phase value and carrier phase observation value of each solver satellite, a cross-cost matrix is ​​constructed. The matrix elements in the cross-cost matrix are used to indicate the difference between the solved reconstructed phase value of the corresponding first satellite and the original carrier phase observation value of the corresponding second satellite. The first satellite is any one of the multiple solver satellites, and the second satellite is any one of the multiple solver satellites.

[0008] Feature analysis is performed on the cross-cost matrix to obtain solution feature information, wherein the solution feature information includes mismatch feature, instability feature and cost feature. The mismatch feature represents the number of observation reconstruction mismatched satellites included in the optimal solution of the cross-cost matrix. The instability feature represents the degree of difference between the optimal solution and the suboptimal solution of the cross-cost matrix. The cost feature represents the average loss of the optimal solution of the cross-cost matrix.

[0009] The solved feature information is processed according to a preset control strategy to obtain the tamping point positioning detection information at the target positioning time.

[0010] In some embodiments, the step of performing feature analysis on the cross-cost matrix to obtain the solution feature information includes:

[0011] The cross cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution and its corresponding optimal permutation matrix. The optimal permutation matrix is ​​used to indicate the assignment relationship between the solved and reconstructed phase values ​​of the satellite and the carrier phase observation values ​​of the satellite in the optimal solution.

[0012] The number of abnormal settlement satellites included in the optimal solution is analyzed based on the optimal permutation matrix to obtain the mismatch characteristics, wherein the solution satellite assigned to the observation reconstruction mismatch satellite in the optimal solution is different from the observation reconstruction mismatch satellite.

[0013] In some embodiments, the step of performing feature analysis on the cross-cost matrix to obtain the solution feature information includes:

[0014] The cross cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution, and the cross cost matrix is ​​subjected to suboptimal assignment processing to obtain the suboptimal solution.

[0015] The ratio of the loss value of the suboptimal solution to the loss value of the optimal solution is calculated to obtain the instability characteristics.

[0016] In some embodiments, the step of performing feature analysis on the cross-cost matrix to obtain the solution feature information includes:

[0017] The cross-cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution;

[0018] The cost characteristic is obtained by calculating the ratio of the loss value of the optimal solution to the number of the multiple solution satellites.

[0019] In some embodiments, the step of processing the solved feature information according to a preset control strategy to obtain the tack point positioning detection information at the target positioning time includes:

[0020] If the number of mismatched satellites indicating the mismatch feature is not zero, and / or if the instability feature is less than the instability threshold, output tamping point positioning detection information to indicate tamping point positioning anomalies.

[0021] When the number of mismatched satellites indicating the mismatch feature is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is greater than the cost threshold at the target positioning time, the tamping point positioning detection information is output to indicate that there is an abnormal risk in the tamping point positioning.

[0022] When the number of mismatched satellites indicating observation reconstruction is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is less than or equal to the cost threshold at the target positioning time, tamping point positioning detection information is output to indicate that the tamping point positioning is normal.

[0023] In some embodiments, the step of obtaining the cost threshold at the target positioning time includes:

[0024] Identify low-noise satellites among all visible satellites at the target positioning time to obtain multiple low-noise satellites;

[0025] The central tendency of the background noise intensity of the multiple low-noise satellites is analyzed to determine the cost threshold for the target positioning time.

[0026] In some embodiments, the elevation angle of the low-noise satellite at the target positioning time is greater than an elevation angle threshold.

[0027] In some embodiments, the step of analyzing the central tendency of the background noise intensity of the plurality of low-noise satellites to determine the cost threshold for the target positioning time includes:

[0028] The root mean square of the carrier phase posterior residuals of the multiple low-noise satellites is calculated to obtain the candidate threshold for the target positioning time. The carrier phase posterior residuals are used to indicate the background noise intensity of the corresponding low-noise satellite.

[0029] The cost threshold for the target positioning time is determined based on the candidate threshold for the target positioning time and the cost threshold for the reference time, wherein the reference time is the positioning time preceding the target positioning time.

[0030] In some embodiments, the step of determining the cost threshold for the target positioning time based on a candidate threshold for the target positioning time and a cost threshold for a reference time includes:

[0031] If the number of low-noise satellites is less than the number threshold, the cost threshold of the reference time is determined as the cost threshold of the target positioning time.

[0032] When the number of low-noise satellites is greater than or equal to the number threshold, the weighted result of the candidate threshold for the target positioning time and the cost threshold for the reference time is determined as the cost threshold for the target positioning time.

[0033] Secondly, another embodiment of the present invention provides a point-clearing guidance system that integrates BeiDou positioning signals, the system comprising:

[0034] The reconstruction module is used to determine the reconstructed phase value of each of the multiple solution satellites at the target positioning time based on the signal propagation distance, signal propagation delay and ambiguity resolution value of each solution satellite. The target positioning time is one of the multiple positioning times corresponding to the tamping control process.

[0035] The matrix construction module is used to construct a cross-cost matrix based on the solved reconstructed phase value and carrier phase observation value of each solver satellite. The matrix elements in the cross-cost matrix are used to indicate the difference between the solved reconstructed phase value of the corresponding first satellite and the original carrier phase observation value of the corresponding second satellite. The first satellite is any one of the multiple solver satellites, and the second satellite is any one of the multiple solver satellites.

[0036] The feature analysis module is used to perform feature analysis on the cross cost matrix to obtain solution feature information, wherein the solution feature information includes mismatch feature, instability feature and cost feature. The mismatch feature represents the number of observation reconstruction mismatched satellites included in the optimal solution of the cross cost matrix. The instability feature represents the degree of difference between the optimal solution and the suboptimal solution of the cross cost matrix. The cost feature represents the average loss of the optimal solution of the cross cost matrix.

[0037] The positioning detection module is used to process the solved feature information according to a preset control strategy to obtain the tamping point positioning detection information at the target positioning time.

[0038] Thirdly, in another embodiment of the present invention, an electronic device is provided, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect.

[0039] Fourthly, in another embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0040] The present invention has the following beneficial effects:

[0041] When multiple solution satellites jointly determine the receiver coordinates, the signal propagation distance and signal propagation delay of each solution satellite are calculated using the determined receiver coordinates. Combined with the ambiguity resolution values ​​of each solution satellite, the ideal carrier phase information of each solution satellite is reconstructed in reverse. Then, combined with the actual carrier phase information of each solution satellite, a cross-cost matrix is ​​constructed and its features are analyzed to obtain mismatch features indicating the internal mathematical structure and logical consistency of the solution model, instability features indicating the stability of the solution model's solution results, and cost features indicating the degree of interference to the solution model. Finally, the reliability of the compaction point positioning result at the target positioning time is accurately evaluated by combining the three features, and the corresponding compaction point positioning detection information is output accordingly to suppress the use of abnormal compaction point positioning results with extremely high confidence but positional deviations of several decimeters, thereby improving the application effect of RTK technology in dynamic compaction operation scenarios. Attached Figure Description

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating a method for guiding the tamping of BeiDou positioning signals according to an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of a tamping point guidance system that integrates BeiDou positioning signals, provided in an embodiment of the present invention.

[0045] Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0046] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a point-based guidance method and system integrating BeiDou positioning signals proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0047] 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 invention pertains.

[0048] The following description, in conjunction with the accompanying drawings, details the specific scheme of the staking guidance method and system that integrates BeiDou positioning signals provided by this invention.

[0049] In one embodiment, the present invention provides a method for guiding tamping points by integrating BeiDou positioning signals, such as... Figure 1 As shown, the method includes:

[0050] Step S1: Among the multiple solution satellites at the target positioning time, determine the solution reconstruction phase value of each solution satellite based on the signal propagation distance, signal propagation delay, and ambiguity solution value of each solution satellite.

[0051] The target positioning time is one of the multiple positioning times corresponding to the tamping point control process.

[0052] When using RTK technology to guide the hammer operation in dynamic compaction scenarios, the hammer's landing point (i.e., the compaction point) is located multiple times to ensure that the overall dynamic compaction effect on the work area meets expectations. The process is as follows: RTK technology is used to locate the compaction point for the current work cycle. Ensuring the hammer is aligned with the located position, the hammer is lowered to complete one hammering operation. After the hammering is completed, the hammer is raised to await guidance for the next compaction point location.

[0053] The aforementioned positioning time can be understood as the time when the tamping point positioning result is obtained under the corresponding work cycle. It should be understood that the tamping hammer does not perform any operation at the positioning time. The reliability of the tamping point positioning result calculated under the corresponding work cycle needs to be verified using the scheme described in this invention. Then, based on the reliability verification result (i.e., the tamping point positioning detection information mentioned later), it is determined whether to control the tamping hammer to continue the hammering operation.

[0054] The above-mentioned tamping point positioning results are obtained through a pre-set GNSS receiver. The tamping point positioning results include at least the three-dimensional spatial coordinates of the receiver calculated at the corresponding positioning time, multiple calculation satellites (visible satellites participating in the calculation) participating in the corresponding operation round, the carrier phase observation value of each calculation satellite in the corresponding operation round, and the ambiguity calculation value of each calculation satellite in the corresponding operation round.

[0055] The signal propagation distance is specifically the geometric distance between the three-dimensional spatial coordinates of the receiver calculated at the corresponding positioning time and the three-dimensional spatial coordinates of the corresponding satellite (obtained through broadcast ephemeris or precise ephemeris). The signal propagation delay is used to indicate the communication path interference between the three-dimensional spatial coordinates of the receiver calculated at the corresponding positioning time and the three-dimensional spatial coordinates of the corresponding satellite (including but not limited to: tropospheric delay calculated using the Saastamoinen model and ionospheric delay calculated using the Klobuchar model).

[0056] The aforementioned calculated and reconstructed phase values ​​are used to indicate the phase values ​​that the corresponding calculated satellite should theoretically observe, obtained from the inversion of the corresponding tack point positioning results at the target positioning time.

[0057] In one example, the resolved reconstructed phase value of the j-th resolver among multiple resolvers at the target positioning time. It can be represented as:

[0058]

[0059] in, Indicates the carrier wavelength of the GNSS signal. Indicates the signal propagation distance of the j-th satellite. Indicates the signal propagation delay of the j-th satellite. Indicates the ambiguity solution value for the j-th satellite.

[0060] Step S2: Construct a cross-cost matrix based on the solved and reconstructed phase values ​​and carrier phase observation values ​​of each satellite.

[0061] The matrix elements in the cross-cost matrix are used to indicate the difference between the solved reconstructed phase value of the corresponding first satellite and the original carrier phase observation value of the corresponding second satellite. The first satellite is any one of the multiple solver satellites, and the second satellite is any one of the multiple solver satellites.

[0062] The aforementioned carrier phase observations are used to indicate the phase values ​​actually observed by the satellite at the target positioning time.

[0063] It should be understood that if the number of multiple solution satellites for the target positioning time is set to be... Then the size of the cross-cost matrix is .

[0064] In one example, the element value of a matrix element is specifically the squared residual between the row value of the matrix element corresponding to the resolved reconstructed phase value of the solved satellite (which can be understood as the first satellite) and the column value of the matrix element corresponding to the original carrier phase observation value of the solved satellite (which can be understood as the second satellite). In this example, the above element value is used to quantify the degree of difference between the resolved reconstructed phase value and the original carrier phase observation value of the two solved satellites corresponding to the sequence element.

[0065] Step S3: Perform feature analysis on the cross cost matrix to obtain solution feature information.

[0066] The solution feature information includes mismatch feature, instability feature and cost feature. The mismatch feature represents the number of observation reconstruction mismatched satellites included in the optimal solution of the cross cost matrix. The instability feature represents the degree of difference between the optimal solution and the suboptimal solution of the cross cost matrix. The cost feature represents the average loss of the optimal solution of the cross cost matrix.

[0067] Specifically, the steps for obtaining mismatch features include:

[0068] The cross cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution and its corresponding optimal permutation matrix. The optimal permutation matrix is ​​used to indicate the assignment relationship between the solved and reconstructed phase values ​​of the satellite and the carrier phase observation values ​​of the satellite in the optimal solution.

[0069] The number of abnormal settlement satellites included in the optimal solution is analyzed based on the optimal permutation matrix to obtain the mismatch characteristics, wherein the solution satellite assigned to the observation reconstruction mismatch satellite in the optimal solution is different from the observation reconstruction mismatch satellite.

[0070] The above optimal assignment process aims to find n matrix elements with different rows and columns in the cross cost matrix (assuming the number of multiple solution satellites at the target positioning time is n), and minimize the sum of the element values ​​of the n matrix elements with different rows and columns found.

[0071] In this invention, the Hungarian algorithm is used to complete the above-mentioned optimal assignment process. In practical applications, other optimal assignment algorithms can also be selected to complete the above-mentioned process, and this invention does not limit this.

[0072] When the internal mathematical structure of the solution model corresponding to RTK technology is self-consistent, the carrier phase observation value with the smallest difference between the solution and reconstructed phase values ​​of each solution satellite should come from the corresponding solution satellite itself. However, when the internal mathematical structure of the aforementioned solution model conflicts due to interference, the carrier phase observation value with the smallest difference between the solution and reconstructed phase values ​​of one satellite may come from another solution satellite.

[0073] Based on the above settings, by statistically analyzing the number of abnormal settlement satellites included in the optimal solution, the degree of logical consistency of the internal mathematical structure of the calculation model can be quantified, and the reliability of the corresponding tackling point positioning results can be evaluated accordingly.

[0074] In one example, for ease of calculation, the matrix element corresponding to two solution satellites with an assignment relationship is defined as having a value of 1, and the matrix element corresponding to two solution satellites without an assignment relationship has a value of 0.

[0075] In this example, it is assumed that the number of multiple solution satellites at the target positioning time is . In the case of target localization time mismatch characteristics It can be represented as:

[0076]

[0077] in, The optimal permutation matrix at the target localization time. The trace (the sum of the values ​​of the diagonal elements).

[0078] Specifically, the steps for obtaining instability characteristics include:

[0079] The cross cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution, and the cross cost matrix is ​​subjected to suboptimal assignment processing to obtain the suboptimal solution.

[0080] The ratio of the loss value of the suboptimal solution to the loss value of the optimal solution is calculated to obtain the instability characteristics.

[0081] The above optimal assignment process aims to find n matrix elements with different rows and columns in the cross cost matrix (assuming the number of multiple solution satellites at the target positioning time is n) after excluding the aforementioned optimal solution, and minimize the sum of the element values ​​of the n matrix elements with different rows and columns found.

[0082] In this invention, the Murty algorithm is used to complete the above-mentioned suboptimal assignment process.

[0083] The aforementioned loss value is specifically the sum of the element values ​​of multiple matrix elements indicated by the corresponding solution in the cross-cost matrix.

[0084] For the solution model, due to strong interference, the pseudo-fixed solution (referring to the positioning result with extremely high confidence but a positional deviation of several decimeters) is often mathematically unstable, and there may be other suboptimal solutions with similar loss values ​​in the solution space.

[0085] Based on the above settings, by actively exploring the suboptimal solution space and quantifying the difference in loss values ​​between the optimal and suboptimal solutions, the stability of the obtained optimal solution in terms of mathematical logic can be accurately assessed, and the reliability of the corresponding tackling point location results can be evaluated accordingly.

[0086] It should be understood that the larger the value of the instability characteristic, the stronger the stability of the obtained optimal solution in terms of mathematical logic, and the more reliable the corresponding stabilization point location result.

[0087] For example, the instability characteristics at the moment of target positioning It can be represented as:

[0088]

[0089] in, The loss value for the suboptimal solution. The loss value for the optimal solution. For extremely small positive numbers (e.g., the machine precision of a computer) ), used to avoid denominator A value of zero will cause the calculation to fail.

[0090] Specifically, the step of obtaining the cost feature includes:

[0091] The cross-cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution;

[0092] The cost characteristic is obtained by calculating the ratio of the loss value of the optimal solution to the number of the multiple solution satellites.

[0093] In the above settings, the ratio of the loss value of the optimal solution to the number of multiple solution satellites is calculated to quantify the overall noise intensity of the solution model in the real world due to various factors (such as fitting noise and propagation path noise caused by the solution model's inability to accurately simulate the real world).

[0094] Step S4: Process the solved feature information according to the preset control strategy to obtain the target positioning detection information at the target positioning time.

[0095] Specifically, the step of processing the solved feature information according to a preset control strategy to obtain the tack point positioning detection information at the target positioning time includes:

[0096] If the number of mismatched satellites indicating the mismatch feature is not zero, and / or if the instability feature is less than the instability threshold, output tamping point positioning detection information to indicate tamping point positioning anomalies.

[0097] When the number of mismatched satellites indicating the mismatch feature is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is greater than the cost threshold at the target positioning time, the tamping point positioning detection information is output to indicate that there is an abnormal risk in the tamping point positioning.

[0098] When the number of mismatched satellites indicating observation reconstruction is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is less than or equal to the cost threshold at the target positioning time, tamping point positioning detection information is output to indicate that the tamping point positioning is normal.

[0099] In the application, when the output of tamping point positioning detection information indicating abnormal tamping point positioning is triggered, a red light alarm can be activated, and the tamping hammer can be locked to prevent it from falling. The control lock on the tamping hammer will only be released after the relevant personnel have completed the error correction and noise suppression of the solution model and detected the tamping point positioning detection information indicating abnormal risk / normal tamping point positioning. This is to prevent engineering quality accidents caused by using incorrect positioning coordinates during construction.

[0100] When outputting tamping point positioning detection information indicating an abnormal risk in tamping point positioning, a yellow light prompt can be triggered to warn relevant personnel that the currently positioned tamping point coordinates may be incorrect. In this case, the currently positioned tamping point coordinates can still be used for construction, but the log recording this round of construction operations will be supplemented with a statement that the tamping point coordinates used in this round of construction have a certain abnormal risk.

[0101] When the output of tamping point positioning detection information indicates that the tamping point positioning is normal, a green light indicator can be triggered.

[0102] The cost threshold at the target positioning time mentioned above is used to indicate the noise intensity of the background noise at the target positioning time in the settlement model.

[0103] It should be understood that if the number of mismatched satellites in the observed reconstruction is not zero (indicating that in the mathematically optimal matching scheme, the observation values ​​of some satellites have decoupled from their own models and matched the models of other satellites, which means that in terms of the geometric relationship of signal propagation, the RTK solver has sacrificed the correctness of individual satellites in order to pursue the minimum overall residual, and the solution result may fundamentally deviate from the true geometric relationship of the satellite signal), and / or if the instability feature is less than the instability threshold (indicating that due to the randomness of interference, a seemingly reasonable mathematical solution may be constructed for a set of incorrect ambiguities), it can be considered that the solution model has a large error due to interference, and the tamping and positioning work should be temporarily suspended. Tamping and positioning can only continue after effective noise suppression is carried out in combination with the actual working conditions.

[0104] When the number of mismatched satellites indicated by the mismatch feature is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is greater than the cost threshold at the target positioning time, it can be considered that although the solution model and its related numerical information exhibit mathematical consistency and rationality, the overall noise intensity exhibited during the solution process is high. Therefore, the accuracy of the output tamping point positioning result may not be high under this condition. Although this high noise problem will not cause the tamping operation to be suspended in a single round, the risk of positioning deviation under the accumulation of high noise still needs to be guarded against.

[0105] For example, the aforementioned instability threshold can be set to 1.5 based on experience (obtained by collecting a large number of samples with pseudo-fixed solutions) (in practical applications, the value can be between 1.2 and 1.5).

[0106] In this invention, a corresponding cost threshold is acquired at each positioning time for use. By combining the satellite status and environmental conditions at the corresponding positioning time, the noise intensity of the background noise in the settlement model at the corresponding positioning time is adaptively quantified, and more accurate and reliable tamping point positioning detection information is output.

[0107] The step of obtaining the cost threshold at the target positioning time includes:

[0108] Identify low-noise satellites among all visible satellites at the target positioning time to obtain multiple low-noise satellites;

[0109] The central tendency of the background noise intensity of the multiple low-noise satellites is analyzed to determine the cost threshold for the target positioning time.

[0110] The low-noise satellite's elevation angle at the target positioning time is greater than the elevation angle threshold.

[0111] In typical dynamic compaction scenarios, there are numerous water surfaces, flat concrete floors, and large metal structures. These interfaces reflect GNSS signals, creating multipath signals. These multipath signals, along with the signals directly transmitted by the satellite, enter the receiver antenna and contaminate carrier phase measurements.

[0112] Further analysis revealed that multipath signals mainly originate from signal reflections from the ground and low-rise structures. Based on the above settings, by identifying low-noise satellites at high elevation angles (which are less affected by multipath signals than visible satellites at lower elevation angles), the interference of multipath signals can be effectively suppressed. This allows for dynamic adaptation to the actual working conditions of dynamic compaction operations, ensuring that the cost threshold for the corresponding positioning time is more accurate and reliable.

[0113] The above-mentioned elevation angle threshold is an adjustable parameter, and users can adjust its value as needed. In this invention, the value of the above-mentioned elevation angle threshold can be set to 60 degrees based on experience.

[0114] Further, the step of analyzing the central tendency of the environmental noise intensity of the multiple low-noise satellites to determine the cost threshold for the target positioning time includes:

[0115] The root mean square of the carrier phase posterior residuals of the multiple low-noise satellites is calculated to obtain the candidate threshold for the target positioning time. The carrier phase posterior residuals are used to indicate the environmental noise intensity of the corresponding low-noise satellite.

[0116] The cost threshold for the target positioning time is determined based on the candidate threshold for the target positioning time and the cost threshold for the reference time, wherein the reference time is the positioning time preceding the target positioning time.

[0117] The step of determining the cost threshold for the target positioning time based on the candidate threshold for the target positioning time and the cost threshold for the reference time includes:

[0118] If the number of low-noise satellites is less than the number threshold, the cost threshold of the reference time is determined as the cost threshold of the target positioning time.

[0119] When the number of low-noise satellites is greater than or equal to the number threshold, the weighted result of the candidate threshold for the target positioning time and the cost threshold for the reference time is determined as the cost threshold for the target positioning time.

[0120] Among them, the carrier phase posterior residual should be understood as the difference between the actual observed value and the theoretical observed value reconstructed based on the estimated parameters after the corresponding visible satellite has completed the parameter estimation of the GNSS observation equation (such as receiver position, clock error, ambiguity, etc.).

[0121] When the number of multiple low-noise satellites is less than the number threshold, it can be considered that the number of low-noise satellites used to measure the intensity of environmental noise is too small. The candidate threshold calculated based on this may be too affected by extreme values, and the threshold data that can accurately reflect the intensity of environmental noise at the corresponding positioning time cannot be obtained. Therefore, the reliable threshold data (i.e., the cost threshold) determined at the previous positioning time is used as the threshold data for the current positioning time to ensure the reliability and stability of the threshold data.

[0122] When the number of multiple low-noise satellites is greater than or equal to the number threshold, it can be considered that the number of low-noise satellites used to measure the intensity of environmental noise is sufficient, and the corresponding candidate threshold calculated at the time is relatively reliable. By fusing the reliable threshold data determined at the previous positioning time to suppress instantaneous fluctuations, more accurate and reliable threshold data can be obtained for use.

[0123] In this invention, the aforementioned quantity threshold is set to 2 based on experience.

[0124] For example, if the target positioning time is set to the first of multiple positioning times... For each positioning time, the candidate threshold for the target positioning time is... It can be represented as:

[0125]

[0126] in, For the first The total number of multiple low-noise satellites at a given positioning time. Indicates the first A set of satellites corresponding to multiple low-noise satellites at a given positioning time. Indicates the first The first positioning time at the first positioning time The square of the carrier phase a posteriori residual of a low-noise satellite.

[0127] If the target positioning time is set to the nth of multiple positioning times At each positioning time, then in When the number of targets is greater than or equal to the aforementioned threshold, the cost threshold for target localization is... It can be represented as:

[0128]

[0129] in, Indicates the first The cost threshold for each positioning moment. The smoothing coefficient (greater than 0.1 and less than 0.3) is used to adjust the sensitivity of the cost threshold at the target localization time to its candidate thresholds.

[0130] exist When the number is less than the aforementioned threshold, the cost threshold for target localization. It can be represented as: .

[0131] In one embodiment, the present invention provides a point-stabilization guidance system that integrates BeiDou positioning signals, such as... Figure 2 As shown, the system 200 includes:

[0132] The reconstruction module 201 is used to determine the reconstructed phase value of each of the multiple reconstructed satellites at the target positioning time based on the signal propagation distance, signal propagation delay and ambiguity resolution value of each reconstructed satellite. The target positioning time is one of the multiple positioning times corresponding to the tamping control process.

[0133] The matrix construction module 202 is used to construct a cross-cost matrix based on the solved reconstructed phase value and carrier phase observation value of each solved satellite. The matrix elements in the cross-cost matrix are used to indicate the difference between the solved reconstructed phase value of the corresponding first satellite and the original carrier phase observation value of the corresponding second satellite. The first satellite is any one of the multiple solved satellites, and the second satellite is any one of the multiple solved satellites.

[0134] The feature analysis module 203 is used to perform feature analysis on the cross cost matrix to obtain solution feature information, wherein the solution feature information includes mismatch feature, instability feature and cost feature. The mismatch feature represents the number of observation reconstruction mismatched satellites included in the optimal solution of the cross cost matrix. The instability feature represents the degree of difference between the optimal solution and the suboptimal solution of the cross cost matrix. The cost feature represents the average loss of the optimal solution of the cross cost matrix.

[0135] The positioning detection module 204 is used to process the solved feature information according to a preset control strategy to obtain the tamping point positioning detection information at the target positioning time.

[0136] It should be noted that the system provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the tamping guidance system and the tamping guidance method embodiment that integrates BeiDou positioning signals provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiment, which will not be repeated here.

[0137] This invention also provides an electronic device. Please refer to [link to relevant documentation]. Figure 3 The electronic device may include a processor 301, a memory 302, and a program 3021 stored in the memory 302 and capable of running on the processor 301.

[0138] When program 3021 is executed by processor 301, it can achieve the following: Figure 1 Any steps in the corresponding method embodiments and the achievement of the same beneficial effects will not be repeated here.

[0139] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by hardware related to program instructions, and the program can be stored in a readable medium.

[0140] This invention also provides a readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described functions. Figure 1 Any step in the corresponding method embodiment can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0141] The computer-readable storage medium of this invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0142] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0143] The program code contained on the storage medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0144] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or terminal. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0145] This invention also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement the tamping guidance method that integrates BeiDou positioning signals provided in the above embodiments.

[0146] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0147] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for guiding tamping points by integrating BeiDou positioning signals, characterized in that, The method includes: Among the multiple solution satellites at the target positioning time, the solution reconstruction phase value of each solution satellite is determined based on the signal propagation distance, signal propagation delay, and ambiguity solution value of each solution satellite. The target positioning time is one of the multiple positioning times corresponding to the tamping point control process. Based on the solved reconstructed phase value and carrier phase observation value of each solver satellite, a cross-cost matrix is ​​constructed. The matrix elements in the cross-cost matrix are used to indicate the difference between the solved reconstructed phase value of the corresponding first satellite and the original carrier phase observation value of the corresponding second satellite. The first satellite is any one of the multiple solver satellites, and the second satellite is any one of the multiple solver satellites. Feature analysis is performed on the cross-cost matrix to obtain solution feature information, wherein the solution feature information includes mismatch feature, instability feature and cost feature. The mismatch feature represents the number of observation reconstruction mismatched satellites included in the optimal solution of the cross-cost matrix. The instability feature represents the degree of difference between the optimal solution and the suboptimal solution of the cross-cost matrix. The cost feature represents the average loss of the optimal solution of the cross-cost matrix. The solved feature information is processed according to a preset control strategy to obtain the tamping point positioning detection information at the target positioning time. The step of processing the solved feature information according to a preset control strategy to obtain the tamping point positioning detection information at the target positioning time includes: If the number of mismatched satellites in the observation reconstruction indicated by the mismatch feature is not zero, and / or the instability feature is less than the instability threshold, output tamping point positioning detection information to indicate tamping point positioning anomalies; When the number of mismatched satellites indicating the mismatch feature is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is greater than the cost threshold at the target positioning time, the tamping point positioning detection information is output to indicate that there is an abnormal risk in the tamping point positioning. When the number of mismatched satellites indicating observation reconstruction is zero, the instability feature is greater than or equal to the instability threshold, and the cost feature is less than or equal to the cost threshold at the target positioning time, output tamping point positioning detection information to indicate that the tamping point positioning is normal. The steps for obtaining the cost threshold at the target positioning time include: Identify low-noise satellites among all visible satellites at the target positioning time to obtain multiple low-noise satellites; The central tendency of the background noise intensity of the multiple low-noise satellites is analyzed to determine the cost threshold for the target positioning time.

2. The method for guiding the tamping of BeiDou positioning signals according to claim 1, characterized in that, The steps of performing feature analysis on the cross-cost matrix to obtain the solution feature information include: The cross cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution and its corresponding optimal permutation matrix. The optimal permutation matrix is ​​used to indicate the assignment relationship between the solved and reconstructed phase values ​​of the satellite and the carrier phase observation values ​​of the satellite in the optimal solution. The number of abnormal settlement satellites included in the optimal solution is analyzed based on the optimal permutation matrix to obtain the mismatch characteristics, wherein the solution satellite assigned to the observation reconstruction mismatch satellite in the optimal solution is different from the observation reconstruction mismatch satellite.

3. The method for guiding the tamping of points by integrating BeiDou positioning signals according to claim 1, characterized in that, The steps of performing feature analysis on the cross-cost matrix to obtain the solution feature information include: The cross cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution, and the cross cost matrix is ​​subjected to suboptimal assignment processing to obtain the suboptimal solution. The ratio of the loss value of the suboptimal solution to the loss value of the optimal solution is calculated to obtain the instability characteristics.

4. The method for guiding the tamping of BeiDou positioning signals according to claim 1, characterized in that, The steps of performing feature analysis on the cross-cost matrix to obtain the solution feature information include: The cross-cost matrix is ​​subjected to optimal assignment processing to obtain the optimal solution; The cost characteristic is obtained by calculating the ratio of the loss value of the optimal solution to the number of the multiple solution satellites.

5. The method for guiding the tamping of BeiDou positioning signals according to claim 1, characterized in that, The low-noise satellite's elevation angle at the target positioning time is greater than the elevation angle threshold.

6. The method for guiding the tamping of points by integrating BeiDou positioning signals according to claim 1, characterized in that, The step of analyzing the central tendency of the background noise intensity of the multiple low-noise satellites to determine the cost threshold for the target positioning time includes: The root mean square of the carrier phase posterior residuals of the multiple low-noise satellites is calculated to obtain the candidate threshold for the target positioning time. The carrier phase posterior residuals are used to indicate the background noise intensity of the corresponding low-noise satellite. The cost threshold for the target positioning time is determined based on the candidate threshold for the target positioning time and the cost threshold for the reference time, wherein the reference time is the positioning time preceding the target positioning time.

7. The method for guiding the tamping of points by integrating BeiDou positioning signals according to claim 6, characterized in that, The steps for determining the cost threshold for the target positioning time based on the candidate threshold and the cost threshold for the reference time include: If the number of low-noise satellites is less than the number threshold, the cost threshold of the reference time is determined as the cost threshold of the target positioning time. When the number of low-noise satellites is greater than or equal to the number threshold, the weighted result of the candidate threshold for the target positioning time and the cost threshold for the reference time is determined as the cost threshold for the target positioning time.

8. A point-stabilizing guidance system integrating BeiDou positioning signals, used to implement the point-stabilizing guidance method integrating BeiDou positioning signals as described in any one of claims 1-7, characterized in that, The system includes: The reconstruction module is used to determine the reconstructed phase value of each of the multiple solution satellites at the target positioning time based on the signal propagation distance, signal propagation delay and ambiguity resolution value of each solution satellite. The target positioning time is one of the multiple positioning times corresponding to the tamping control process. The matrix construction module is used to construct a cross-cost matrix based on the solved reconstructed phase value and carrier phase observation value of each solver satellite. The matrix elements in the cross-cost matrix are used to indicate the difference between the solved reconstructed phase value of the corresponding first satellite and the original carrier phase observation value of the corresponding second satellite. The first satellite is any one of the multiple solver satellites, and the second satellite is any one of the multiple solver satellites. The feature analysis module is used to perform feature analysis on the cross cost matrix to obtain solution feature information, wherein the solution feature information includes mismatch feature, instability feature and cost feature. The mismatch feature represents the number of observation reconstruction mismatched satellites included in the optimal solution of the cross cost matrix. The instability feature represents the degree of difference between the optimal solution and the suboptimal solution of the cross cost matrix. The cost feature represents the average loss of the optimal solution of the cross cost matrix. The positioning detection module is used to process the solved feature information according to a preset control strategy to obtain the tamping point positioning detection information at the target positioning time.

Images