GPS and BDS dual-frequency RTK method and device based on integrity monitoring

Abstract

The embodiment of the present invention discloses a method and device for GPS and BDS dual-frequency RTK based on integrity monitoring. The embodiment of the present invention obtains the dual-frequency observation data of the current epoch and pre-processes the dual-frequency observation data; performs Kalman filtering on the pre-processed dual-frequency observation data to determine a first floating-point solution, and generates multiple double-difference floating-point solution post-verification residuals according to the first floating-point solution; generates at least one second floating-point solution according to the multiple double-difference floating-point solution post-verification residuals, performs integrity detection according to the first floating-point solution and at least one second floating-point solution, generates a target floating-point solution, and then generates a first fixed solution and multiple double-difference fixed solution post-verification residuals; generates at least one second fixed solution according to the multiple double-difference fixed solution post-verification residuals; performs integrity detection according to the first fixed solution and at least one second fixed solution, and generates a target fixed solution including multiple target ambiguity parameters. Through the above method, accurate ambiguity can be determined to improve the accuracy and reliability of positioning services.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and device for GPS and BDS dual-frequency RTK based on integrity monitoring. Background Art

[0002] The global satellite navigation system can provide high-precision position, speed and timing services around the clock and in all weather conditions. Among them, the most widely known global satellite navigation system is the United States' Global Positioning System (GPS). GPS has uniform coverage around the world and is widely used in multiple industries such as surveying and mapping, digital construction, and autonomous driving. In an open environment, GPS can continuously provide high-precision positioning services, but in an obstructed environment, the number of satellites in a single system is limited, which seriously affects the positioning accuracy. With the comprehensive networking of my country's Beidou Navigation Satellite System (BDS), enough Beidou satellites can be provided for positioning, and then GPS and BDS can be used together to improve the accuracy and reliability of satellite positioning services.

[0003] In the prior art, single-point positioning technology, pseudo-range differential technology and real-time kinematic (RTK) technology based on carrier phase observation value differential are used for position positioning. The single-point positioning technology can provide positioning services with meter-level accuracy, the pseudo-range differential technology can also provide decimeter-level accuracy positioning services, and the RTK technology based on carrier phase observation value differential can achieve centimeter-level positioning services after the ambiguity is fixed. However, due to the complex dynamic environment, occlusion and semi-occlusion environments are inevitable, making it difficult to achieve accurate ambiguity fixation, which in turn affects the accuracy and reliability of the positioning service.

[0004] In summary, how to determine the accurate ambiguity is a problem that needs to be solved at present. Summary of the invention

[0005] In view of this, the embodiments of the present invention provide a method and apparatus for GPS and BDS dual-frequency RTK based on integrity monitoring, which can determine accurate ambiguity, thereby improving the accuracy and reliability of positioning services.

[0006] In a first aspect, an embodiment of the present invention provides a method for calculating ambiguity based on dual-frequency observation data, the method comprising:

[0007] Acquire dual-frequency observation data of the current epoch, wherein the dual-frequency observation data includes a plurality of global positioning system GPS observation data and a plurality of Beidou satellite navigation system BDS observation data;

[0008] Preprocessing the dual-frequency observation data to generate preprocessed dual-frequency observation data;

[0009] Performing Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and a plurality of first ambiguity parameters;

[0010] Generate a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution;

[0011] Generate at least one second floating-point solution according to the plurality of double-difference floating-point solution post-verification residuals, wherein the second floating-point solution comprises a second position parameter and a plurality of second ambiguity parameters;

[0012] Performing integrity detection according to the first floating-point solution and at least one of the second floating-point solutions to generate a target floating-point solution, wherein the target floating-point solution includes a third position parameter and a plurality of third ambiguity parameters;

[0013] Generating a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution, wherein the first fixed solution includes a fourth position parameter and a plurality of fourth ambiguity parameters;

[0014] Generate at least one second fixed solution according to the plurality of double-difference fixed solution post-verification residuals, wherein the second fixed solution comprises a fifth position parameter and a plurality of fifth ambiguity parameters;

[0015] An integrity check is performed based on the first fixed solution and at least one of the second fixed solutions to generate a target fixed solution, wherein the target fixed solution includes a target position parameter and a plurality of target ambiguity parameters.

[0016] Optionally, the method further includes: in response to continuously determining the target ambiguity parameters of a set number of epochs, transferring the target ambiguity parameters to the next epoch of the current epoch.

[0017] Optionally, generating a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution specifically includes:

[0018] Substitute the first floating-point solution into a preset double-difference observation equation to generate a plurality of double-difference floating-point solution post-verification residuals.

[0019] Optionally, generating at least one second floating-point solution according to the post-verification residuals of the multiple double-difference floating-point solutions specifically includes:

[0020] Traversing the plurality of double-difference floating-point decompression residuals at least once, and determining the maximum value among the plurality of double-difference floating-point decompression residuals during each traversal;

[0021] Determine candidate dual-frequency observation data corresponding to the maximum value;

[0022] The candidate dual-frequency observation data are eliminated from the dual-frequency observation data to generate at least one second floating-point solution.

[0023] Optionally, generating a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution specifically includes:

[0024] Determine a floating-point solution of the double-difference wide-term ambiguity and a corresponding first variance according to the target floating-point solution;

[0025] Determining a fixed solution for the double difference wide term ambiguity according to the floating point solution for the double difference wide term ambiguity;

[0026] Determine a floating point solution of the double difference raw ambiguity and a corresponding second variance according to the fixed solution of the double difference wide term ambiguity;

[0027] A fixed solution of the double-difference original ambiguity and a plurality of double-difference fixed solution post-verification residuals are determined according to the floating-point solution of the double-difference original ambiguity, wherein the fixed solution of the double-difference original ambiguity is the first fixed solution.

[0028] Optionally, determining a fixed solution of the double-difference original ambiguity according to the floating-point solution of the double-difference original ambiguity specifically includes:

[0029] The floating point solution of the double difference original ambiguity is fixed according to the anonymous function LAMBDA to determine a fixed solution of the double difference original ambiguity.

[0030] Optionally, the method further comprises: in response to the ambiguity of the previous epoch of the current epoch being fixed and the current epoch not having a cycle slip,

[0031] A position parameter pre-fix solution is determined based on the ambiguity of the previous epoch.

[0032] In a second aspect, an embodiment of the present invention provides a device for calculating ambiguity based on dual-frequency observation data, the device comprising:

[0033] An acquisition unit, used for acquiring dual-frequency observation data of a current epoch, wherein the dual-frequency observation data includes a plurality of global positioning system GPS observation data and a plurality of Beidou satellite navigation system BDS observation data;

[0034] A first generating unit, configured to preprocess the dual-frequency observation data to generate preprocessed dual-frequency observation data;

[0035] A first determining unit, configured to perform Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and a plurality of first ambiguity parameters;

[0036] A second generating unit, configured to generate a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution;

[0037] A third generating unit, configured to generate at least one second floating-point solution according to the plurality of double-difference floating-point solution post-verification residuals, wherein the second floating-point solution comprises a second position parameter and a plurality of second ambiguity parameters;

[0038] a second determining unit, configured to perform integrity detection according to the first floating-point solution and at least one of the second floating-point solutions to determine a target floating-point solution, wherein the target floating-point solution includes a third position parameter and a plurality of third ambiguity parameters;

[0039] A fourth generating unit, configured to generate a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution, wherein the first fixed solution includes a fourth position parameter and a plurality of fourth ambiguity parameters;

[0040] A fifth generating unit, configured to generate at least one second fixed solution according to the plurality of double-difference fixed solution post-verification residuals, wherein the second fixed solution comprises a fifth position parameter and a plurality of fifth ambiguity parameters;

[0041] The third determination unit is used to perform integrity detection according to the first fixed solution and at least one of the second fixed solutions to determine a target fixed solution, wherein the target fixed solution includes a target position parameter and a plurality of target ambiguity parameters.

[0042] Optionally, the device further comprises:

[0043] A transfer unit, in response to continuously determining the target ambiguity parameters of a set number of epochs, is used to transfer the target ambiguity parameters to an epoch next to the current epoch.

[0044] Optionally, the second generating unit is specifically used for:

[0045] Substitute the first floating-point solution into a preset double-difference observation equation to generate a plurality of double-difference floating-point solution post-verification residuals.

[0046] Optionally, the third generating unit is specifically used for:

[0047] Traversing the plurality of double-difference floating-point decompression residuals at least once, and determining the maximum value among the plurality of double-difference floating-point decompression residuals during each traversal;

[0048] Determine candidate dual-frequency observation data corresponding to the maximum value;

[0049] The candidate dual-frequency observation data are eliminated from the dual-frequency observation data to generate at least one second floating-point solution.

[0050] Optionally, the fourth generating unit is specifically used for:

[0051] Determine a floating-point solution of the double-difference wide-term ambiguity and a corresponding first variance according to the target floating-point solution;

[0052] Determining a fixed solution for the double difference wide term ambiguity according to the floating point solution for the double difference wide term ambiguity;

[0053] Determine a floating point solution of the double difference raw ambiguity and a corresponding second variance according to the fixed solution of the double difference wide term ambiguity;

[0054] A fixed solution of the double-difference original ambiguity and a plurality of double-difference fixed solution post-verification residuals are determined according to the floating-point solution of the double-difference original ambiguity, wherein the fixed solution of the double-difference original ambiguity is the first fixed solution.

[0055] Optionally, the fourth generating unit is further configured to:

[0056] The floating point solution of the double difference original ambiguity is fixed according to the anonymous function LAMBDA to determine a fixed solution of the double difference original ambiguity.

[0057] Optionally, the device further comprises:

[0058] The fourth determination unit is configured to determine a pre-fixed solution of a position parameter according to the ambiguity of the previous epoch of the current epoch, in response to the ambiguity of the previous epoch of the current epoch being fixed and the current epoch not having a cycle slip.

[0059] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium on which is stored

[0060] The invention also provides a method for storing computer program instructions, which, when executed by a processor, implement the method as described in the first aspect and any possible embodiment of the first aspect.

[0061] In a fourth aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement a method as described in the first aspect and any possible embodiment of the first aspect.

[0062] The embodiment of the present invention obtains dual-frequency observation data of the current epoch, wherein the dual-frequency observation data includes multiple global positioning system GPS observation data and multiple Beidou satellite navigation system BDS observation data; preprocesses the dual-frequency observation data to generate preprocessed dual-frequency observation data; performs Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and multiple first ambiguity parameters; generates multiple double-difference floating-point solution post-verification residuals according to the first floating-point solution; generates at least one second floating-point solution according to the multiple double-difference floating-point solution post-verification residuals, wherein the second floating-point solution includes a second position parameter and multiple second ambiguity parameters; generates a first floating-point solution according to the first floating-point solution; generates a second floating-point solution according to the multiple double-difference floating-point solution post-verification residuals; generates a second floating-point solution according to the second floating-point solution; wherein the second floating-point solution includes a second position parameter and a plurality of second ambiguity parameters; generates a first floating-point solution according to the first floating-point solution ... first floating-point solution according to the second floating-point solution; wherein the first floating-point solution includes a second position parameter and a plurality of second ambiguity parameters; generates a first floating-point solution according to the first floating-point solution; A floating point solution and at least one of the second floating point solutions are tested for integrity to generate a target floating point solution, wherein the target floating point solution includes a third position parameter and multiple third ambiguity parameters; a first fixed solution and multiple double-difference fixed solution post-verification residuals are generated based on the target floating point solution, wherein the first fixed solution includes a fourth position parameter and multiple fourth ambiguity parameters; at least one second fixed solution is generated based on the multiple double-difference fixed solution post-verification residuals, wherein the second fixed solution includes a fifth position parameter and multiple fifth ambiguity parameters; an integrity test is performed based on the first fixed solution and at least one of the second fixed solutions to generate a target fixed solution, wherein the target fixed solution includes a target position parameter and multiple target ambiguity parameters. Through the above method, accurate ambiguity can be determined, thereby improving the accuracy and reliability of positioning services. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0064] Figure 1 is a flow chart of a method for calculating ambiguity based on dual-frequency observation data in an embodiment of the present invention;

[0065] Figure 2 is a flow chart of another method for calculating ambiguity based on dual-frequency observation data in an embodiment of the present invention;

[0066] Figure 3 is a flow chart of another method for calculating ambiguity based on dual-frequency observation data in an embodiment of the present invention;

[0067] Figure 4 is a flow chart of another method for calculating ambiguity based on dual-frequency observation data in an embodiment of the present invention;

[0068] Figure 5 is a flow chart of a method for calculating ambiguity based on dual-frequency observation data in an embodiment of the present invention;

[0069] Figure 6is a schematic diagram of a device for calculating ambiguity based on dual-frequency observation data according to an embodiment of the present invention;

[0070] Figure 7 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0071] The present invention is described below based on the embodiments, but the present invention is not limited to these embodiments. In the detailed description of the present invention below, some specific details are described in detail. It is possible for a person skilled in the art to fully understand the present invention without the description of these details. In order to avoid confusing the essence of the present invention, known methods, processes, procedures, components and circuits are not described in detail.

[0072] In addition, persons of ordinary skill in the art will appreciate that the drawings provided herein are for illustration purposes and are not necessarily drawn to scale.

[0073] Unless the context clearly requires otherwise, the words "include", "comprising" and similar words throughout the application should be interpreted as including rather than exclusive or exhaustive; that is, the meaning is "including but not limited to".

[0074] In the description of the present invention, it should be understood that the terms "first", "second", etc. are used for descriptive purposes only and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0075] In the prior art, single-point positioning technology, pseudo-range differential technology and real-time kinematic (RTK) technology based on carrier phase observation differential are used for position positioning. The single-point positioning technology uses pseudo-range observations for least squares processing. Due to the limited accuracy of pseudo-range observations and the influence of satellite, receiver and propagation path errors, the single-point positioning technology can only provide positioning services with meter-level accuracy. The pseudo-range differential technology performs differential processing on pseudo-range observations through base stations, eliminating most of the errors. However, it is still limited by the accuracy of pseudo-range observations, and the pseudo-range differential technology can only provide decimeter-level accuracy positioning services. The RTK technology based on carrier phase observation differential takes advantage of the high accuracy of carrier observations and can achieve centimeter-level positioning services after the ambiguity is fixed. Specifically, the RTK technology mainly includes three processes: cycle slip detection, Kalman filtering and ambiguity fixation. The cycle slip detection mainly uses a wide-lane phase minus narrow-lane pseudo-range combination (Melbourne-Wubeena The satellite cycle slips are detected by using the combination of MW observations and Geometry-Free (GF) observations. In the solution process, RTK generally only detects the cycle slips and does not repair them to avoid filter divergence caused by repair errors. RTK uses the Kalman filter for parameter estimation. Due to the influence of gross errors and unidentified cycle slips, it is necessary to use an adaptive filter with variance adjustment using an adaptive factor for robust estimation. The ambiguity fixation mainly uses the anonymous function (LAMBDA) method, and partial ambiguity fixation can be performed in a dynamic environment. However, due to the complexity of the dynamic environment, occlusion and semi-occlusion environments are inevitable, making it difficult to achieve accurate ambiguity fixation, which in turn affects the accuracy and reliability of the positioning service.

[0076] Therefore, how to determine the accurate ambiguity is a problem that needs to be solved at present.

[0077] In order to solve the above problem, a method for calculating ambiguity based on dual-frequency observation data is proposed in the embodiment of the present invention. Figure 1 As shown, Figure 1 : is a flow chart of a method for calculating ambiguity based on dual-frequency observation data according to an embodiment of the present invention, which specifically includes:

[0078] Step S101: Acquire dual-frequency observation data of the current epoch, wherein the dual-frequency observation data includes a plurality of global positioning system GPS observation data and a plurality of Beidou satellite navigation system BDS observation data.

[0079] Specifically, the global positioning system GPS and the Beidou satellite navigation system BDS are collectively referred to as satellites, and the dual-frequency observation data include pseudorange and carrier phase, the pseudorange is the distance between the satellite and the receiver; the epoch is time, and the specific value of the epoch is related to the sampling frequency of the receiver. It is assumed that the sampling frequency is 1HZ and the epoch is seconds.

[0080] Step S102: preprocess the dual-frequency observation data to generate preprocessed dual-frequency observation data.

[0081] Specifically, the preprocessing is gross error elimination, and after the dual-frequency observation data are subjected to gross error elimination, preprocessed dual-frequency observation data are generated.

[0082] Step S103: Perform Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and a plurality of first ambiguity parameters.

[0083] Specifically, the first ambiguity parameter in the first floating-point solution is a decimal value. Since there are multiple satellites, there are multiple corresponding first ambiguity parameters in the first floating-point solution.

[0084] Step S104: generating a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution.

[0085] Specifically, the first floating-point solution is substituted into a preset double-difference observation equation to generate a plurality of double-difference floating-point solution post-verification residuals.

[0086] In an embodiment of the present invention, the unknowns in the pre-set double-difference observation equation are position parameters and ambiguity parameters. The first position parameters and multiple first ambiguity parameters included in the first floating-point solution are substituted into the double-difference observation equation. The result of the double-difference observation equation is the residual after double-difference floating-point solution verification. Since the number of the first ambiguity parameters is multiple, the number of the residuals after double-difference floating-point solution verification is multiple.

[0087] Step S105: Generate at least one second floating-point solution according to the verified residuals of the multiple double-difference floating-point solutions, wherein the second floating-point solution includes a second position parameter and a plurality of second ambiguity parameters.

[0088] Specifically, the multiple double-difference floating-point solution residuals are traversed at least once, and the maximum value among the multiple double-difference floating-point solution residuals is determined in each traversal; the candidate dual-frequency observation data corresponding to the maximum value is determined; the candidate dual-frequency observation data is eliminated from the dual-frequency observation data to generate at least one second floating-point solution.

[0089] For example, assuming that the multiple double-difference floating-point solution residuals are traversed five times, the maximum value among the multiple double-difference floating-point solution residuals is determined in each traversal; or, the multiple double-difference floating-point solution residuals are sorted in order from large to small, and the top 5 double-difference floating-point solution residuals are determined; the candidate dual-frequency observation data sent by the satellite corresponding to the maximum value is eliminated one by one, and at the same time, the maximum value is removed from the multiple double-difference floating-point solution residuals, and the dual-frequency observation data from which the candidate dual-frequency observation data is eliminated is subjected to Kalman filtering to generate a second floating-point solution, wherein five second floating-point solutions are generated by five traversals.

[0090] In the embodiment of the present invention, the specific number of traversals is determined according to actual conditions. Assuming that there are still abnormal satellites after 5 traversals, the above process is continued to determine a new second floating point solution.

[0091] Step S106: Perform integrity check on the first floating-point solution and at least one of the second floating-point solutions to generate a target floating-point solution, wherein the target floating-point solution includes a third position parameter and a plurality of third ambiguity parameters.

[0092] Specifically, the first floating-point solution and the five second floating-point solutions are subjected to an integrity check, the integrity check is to compare the positions, abnormal satellites corresponding to outliers in the first floating-point solution and the five second floating-point solutions are eliminated, and correct position parameters are determined, and the floating-point solution corresponding to the correct position parameters is the target floating-point solution, which includes a third position parameter and multiple third ambiguity parameters.

[0093] Step S107: generating a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution, wherein the first fixed solution comprises a fourth position parameter and a plurality of fourth ambiguity parameters.

[0094] Specifically, the first fixed solution and multiple double-difference fixed solution post-verification residuals are generated according to the target floating-point solution. The specific processing flow is as follows: Figure 2 As shown, the details are as follows:

[0095] Step S201: Determine a floating-point solution of the double-difference wide-term ambiguity and a corresponding first variance according to the target floating-point solution.

[0096] Specifically, the fourth ambiguity parameter in the target floating-point solution is a single-difference ambiguity, and a single-difference to double-difference wide-term ambiguity conversion matrix is ​​used to calculate a double-difference wide-term ambiguity floating-point solution and a corresponding first variance.

[0097] Step S202: Determine a fixed solution for the double difference wide term ambiguity according to the floating point solution for the double difference wide term ambiguity.

[0098] Specifically, the floating-point solution of the double difference wide term ambiguity is fixed according to the anonymous function LAMBDA to determine a fixed solution of the double difference wide term ambiguity, wherein the ambiguity in the fixed solution is an integer.

[0099] Step S203: Determine a floating point solution of the double difference original ambiguity and a corresponding second variance according to the fixed solution of the double difference wide term ambiguity.

[0100] Specifically, a single difference ambiguity filter is constrained according to a fixed solution of the double difference wide term ambiguity to determine an updated single difference ambiguity, and a single difference to double difference wide term ambiguity conversion matrix is ​​used to calculate a floating point solution of the double difference original ambiguity and a corresponding second variance.

[0101] Step S204: determining a fixed solution of the double-difference original ambiguity and a plurality of double-difference fixed solution post-verification residuals according to the floating-point solution of the double-difference original ambiguity, wherein the fixed solution of the double-difference original ambiguity is the first fixed solution.

[0102] Specifically, determining the fixed solution of the double-difference original ambiguity according to the floating-point solution of the double-difference original ambiguity specifically includes: fixing the floating-point solution of the double-difference original ambiguity according to an anonymous function LAMBDA to determine the fixed solution of the double-difference original ambiguity.

[0103] Step S108: Generate at least one second fixed solution based on the post-verification residuals of the multiple double-difference fixed solutions, wherein the second fixed solution includes a fifth position parameter and multiple fifth ambiguity parameters.

[0104] Specifically, the plurality of double-difference fixed solution residuals are traversed at least once, and the maximum value among the plurality of double-difference fixed solution residuals is determined in each traversal; the ambiguity parameter corresponding to the maximum value is determined, and the ambiguity parameter corresponding to the maximum value is eliminated from the plurality of ambiguity parameters of the target floating-point solution, and the ambiguity parameter corresponding to the maximum value is determined by the above method. Figure 2 The processing process generates at least one second fixed solution.

[0105] For example, assuming that the multiple double-difference fixed solution residuals are traversed 5 times, the maximum value among the multiple double-difference fixed solution residuals is determined in each traversal; or, the multiple double-difference fixed solution residuals are sorted in order from large to small, and the double-difference fixed solution residuals ranked in the top 5 are determined; the ambiguity parameters corresponding to the maximum value are eliminated one by one, and at the same time, the maximum value is removed from the multiple double-difference fixed solution residuals, and the target floating-point solution with the ambiguity parameters corresponding to the maximum value eliminated is subjected to the above Figure 2 The processing process in generates a second fixed solution, wherein 5 traversals generate 5 second floating-point solutions.

[0106] In the embodiment of the present invention, the specific number of traversals is determined according to actual conditions. Assuming that there are still abnormal satellites after 5 traversals, the above process is continued to determine a new second fixed solution.

[0107] Step S109: Perform integrity detection according to the first fixed solution and at least one of the second fixed solutions to generate a target fixed solution, wherein the target fixed solution includes a target position parameter and a plurality of target ambiguity parameters.

[0108] Specifically, the first fixed solution and the five second fixed solutions are subjected to an integrity check, the integrity check is to compare the positions, the abnormal satellites corresponding to the outliers in the first fixed solution and the five second fixed solutions are eliminated, and the correct position parameters are determined. The fixed solution corresponding to the correct position parameters is the target fixed solution, which includes the target position parameters and multiple target ambiguity parameters. Since the abnormal satellites have been eliminated, the target ambiguity parameters are shown.

[0109] In the embodiment of the present invention, accurate target ambiguity parameters can be determined in the above manner, and the use of the target ambiguity parameters can improve the accuracy and reliability of satellite positioning services.

[0110] In a possible implementation, after step S109, the method further includes the following steps: Figure 3 As shown, Figure 3 FIG. 1 is a flow chart of another method for calculating ambiguity based on dual-frequency observation data according to an embodiment of the present invention, which specifically includes:

[0111] Step S110: In response to continuously determining the target ambiguity parameters of a set number of epochs, the target ambiguity parameters are transferred to the next epoch of the current epoch.

[0112] Assuming that, for each satellite, the target ambiguity parameters are determined for 10 consecutive epochs, and the elevation angle of the satellite is greater than or equal to the set angle, the target ambiguity parameters are transferred to the next epoch of the current epoch of the satellite, wherein the set angle can be 30 degrees or other set angles, which is determined according to the actual situation.

[0113] In a possible implementation, before step S101, the method further includes the following steps: Figure 4 As shown, Figure 4 FIG. 1 is a flow chart of another method for calculating ambiguity based on dual-frequency observation data according to an embodiment of the present invention, which specifically includes:

[0114] Step S111: In response to the ambiguity of the previous epoch of the current epoch being fixed and no cycle slip occurring in the current epoch, a pre-fixed solution of position parameters is determined according to the ambiguity of the previous epoch.

[0115] Specifically, the ambiguity of the previous epoch of the current epoch is fixed and no cycle slip occurs in the current epoch. The ambiguity of the previous epoch can be directly used to perform a least squares operation on the carrier phase of the current epoch to determine a pre-fixed solution for the position parameters.

[0116] In an embodiment of the present invention, the position parameter pre-fixed solution may be integrity checked with the first floating-point solution and the five second floating-point solutions; meanwhile, the position parameter pre-fixed solution may also be integrity checked with the first fixed solution and the five second fixed solutions.

[0117] The following is a detailed description of a flow chart of a method for calculating ambiguity based on dual-frequency observation data through a complete embodiment. Figure 5 As shown, specifically including:

[0118] Step S501: Obtain dual-frequency observation data of the current epoch.

[0119] Step S502: performing gross error elimination and cycle slip detection on the dual-frequency observation data to determine pre-processed dual-frequency observation data.

[0120] Step S503: In response to the fact that no cycle slip occurs in the current epoch, determine whether the ambiguity of the previous epoch is fixed; if fixed, execute step S504; if not fixed, execute step S505.

[0121] Step S504: determine a pre-fixed solution of position parameters according to the ambiguity of the previous epoch.

[0122] Step S505: construct a double-difference observation equation.

[0123] Wherein, the double difference observation equation determines the weight according to the altitude angle.

[0124] Step S506: After performing Kalman filtering on the pre-processed dual-frequency observation data, a double-difference floating-point solution residual is determined according to the double-difference observation equation.

[0125] Step S507, perform integrity check on the residual after verification of the double-difference floating-point solution. If the integrity check is successful, generate the target floating-point solution and execute step S508. If the integrity check is recognized, end this processing and receive the dual-frequency observation data of the next epoch.

[0126] Step S508: Determine the residual after double-difference fixed solution verification.

[0127] Step S509: perform integrity check on the residual after verification of the double-difference fixed solution. If the integrity check is successful, generate the target fixed solution and execute step S510. If the integrity check is recognized, end this processing and receive the dual-frequency observation data of the next epoch.

[0128] Step S510: transfer the target ambiguity parameters in the target fixed solution to the next epoch of the current epoch.

[0129] Figure 6 is a device for calculating ambiguity based on dual-frequency observation data according to an embodiment of the present invention. Figure 6 As shown, the apparatus of this embodiment includes an acquisition unit 601, a first generation unit 602, a first determination unit 603, a second generation unit 604, a third generation unit 605, a second determination unit 606, a fourth generation unit 607, a fifth generation unit 608 and a third determination unit 609;

[0130] Among them, the acquisition unit 601 is used to acquire the dual-frequency observation data of the current epoch, wherein the dual-frequency observation data includes multiple global positioning system GPS observation data and multiple Beidou satellite navigation system BDS observation data; the first generation unit 602 is used to preprocess the dual-frequency observation data to generate preprocessed dual-frequency observation data; the first determination unit 603 is used to perform Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and a plurality of first ambiguity parameters; the second generation unit 604 is used to generate a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution; the third generation unit 605 is used to generate at least one second floating-point solution according to the plurality of double-difference floating-point solution post-verification residuals, wherein the second floating-point solution includes a second position parameter and a plurality of second ambiguity parameters; The second determining unit 606 is used to perform an integrity check based on the first floating-point solution and at least one of the second floating-point solutions to determine a target floating-point solution, wherein the target floating-point solution includes a third position parameter and multiple third ambiguity parameters; the fourth generating unit 607 is used to generate a first fixed solution and multiple double-difference fixed solution post-verification residuals based on the target floating-point solution, wherein the first fixed solution includes a fourth position parameter and multiple fourth ambiguity parameters; the fifth generating unit 608 is used to generate at least one second fixed solution based on the multiple double-difference fixed solution post-verification residuals, wherein the second fixed solution includes a fifth position parameter and multiple fifth ambiguity parameters; the third determining unit 609 is used to perform an integrity check based on the first fixed solution and at least one of the second fixed solutions to determine a target fixed solution, wherein the target fixed solution includes a target position parameter and multiple target ambiguity parameters.

[0131] Furthermore, the device also includes:

[0132] A transfer unit, in response to continuously determining the target ambiguity parameters of a set number of epochs, is used to transfer the target ambiguity parameters to an epoch next to the current epoch.

[0133] Optionally, the second generating unit is specifically used for:

[0134] Substitute the first floating-point solution into a preset double-difference observation equation to generate a plurality of double-difference floating-point solution post-verification residuals.

[0135] Furthermore, the third generating unit is specifically used for:

[0136] Traversing the plurality of double-difference floating-point decompression residuals at least once, and determining the maximum value among the plurality of double-difference floating-point decompression residuals during each traversal;

[0137] Determine candidate dual-frequency observation data corresponding to the maximum value;

[0138] The candidate dual-frequency observation data are eliminated from the dual-frequency observation data to generate at least one second floating-point solution.

[0139] Furthermore, the fourth generating unit is specifically used for:

[0140] Determine a floating-point solution of the double-difference wide-term ambiguity and a corresponding first variance according to the target floating-point solution;

[0141] Determining a fixed solution for the double difference wide term ambiguity according to the floating point solution for the double difference wide term ambiguity;

[0142] Determine a floating point solution of the double difference raw ambiguity and a corresponding second variance according to the fixed solution of the double difference wide term ambiguity;

[0143] A fixed solution of the double-difference original ambiguity and a plurality of double-difference fixed solution post-verification residuals are determined according to the floating-point solution of the double-difference original ambiguity, wherein the fixed solution of the double-difference original ambiguity is the first fixed solution.

[0144] Furthermore, the fourth generating unit is further configured to:

[0145] The floating point solution of the double difference original ambiguity is fixed according to the anonymous function LAMBDA to determine a fixed solution of the double difference original ambiguity.

[0146] Furthermore, the device also includes:

[0147] The fourth determination unit is configured to determine a pre-fixed solution of a position parameter according to the ambiguity of the previous epoch of the current epoch, in response to the ambiguity of the previous epoch of the current epoch being fixed and the current epoch not having a cycle slip.

[0148] In an embodiment of the present invention, a computer program instruction is further provided. When the computer program instruction is executed by a processor, the method described in any one of the above embodiments is implemented.

[0149] In an embodiment of the present invention, a computer-readable storage medium is further provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method described in any one of the above embodiments is implemented.

[0150] Figure 7 is a schematic diagram of an electronic device according to an embodiment of the present invention. Figure 7 The electronic device shown is a device for calculating ambiguity based on dual-frequency observation data, which includes a general computer hardware structure, which at least includes a processor 701 and a memory 702. The processor 701 and the memory 702 are connected via a bus 703. The memory 702 is suitable for storing instructions or programs executable by the processor 701. The processor 701 can be an independent microprocessor or a collection of one or more microprocessors. Therefore, the processor 701 executes the instructions stored in the memory 702 to execute the method flow of the embodiment of the present invention as described above to realize data processing and control of other devices. The bus 703 connects the above-mentioned multiple components together, and at the same time connects the above-mentioned components to the display controller 704 and the display device and the input / output (I / O) device 705. The input / output (I / O) device 705 can be a mouse, a keyboard, a modem, a network interface, a touch input device, a somatosensory input device, a printer, and other devices known in the art. Typically, the input / output device 705 is connected to the system through an input / output (I / O) controller 706.

[0151] As will be appreciated by those skilled in the art, various aspects of the embodiments of the present invention may be implemented as a system, method or computer program product. Therefore, various aspects of the embodiments of the present invention may take the form of a complete hardware implementation, a complete software implementation (including firmware, resident software, microcode, etc.), or an implementation that combines software aspects with hardware aspects, which may generally be referred to herein as a "circuit," "module," or "system." In addition, various aspects of the embodiments of the present invention may take the form of a computer program product implemented in one or more computer-readable media having a computer-readable program code implemented thereon.

[0152] Any combination of one or more computer-readable media can be utilized. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, (but not limited to) electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or apparatuses, or any suitable combination of the foregoing. More specific examples (non-exhaustive enumeration) of computer-readable storage media will include the following: an electrical connection with one or more wires, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of an embodiment of the present invention, a computer-readable storage medium can be any tangible medium that can contain or store a program used by an instruction execution system, device or apparatus or a program used in conjunction with an instruction execution system, device or apparatus.

[0153] A computer readable signal medium may include a propagated data signal having a computer readable program code implemented therein, such as in baseband or as part of a carrier wave. Such propagated signals may take any of a variety of forms, including but not limited to electromagnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any of the following computer readable media: not a computer readable storage medium, and may communicate, propagate, or transmit a program used by or in conjunction with an instruction execution system, device, or apparatus.

[0154] Program code embodied on a computer readable medium may be transmitted using any appropriate medium including, but not limited to, wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0155] The computer program code for performing operations for various aspects of the embodiments of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, Smalltalk, C++, etc., and conventional process programming languages ​​such as "C" programming language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer as a stand-alone software package; partially on the user's computer and partially on a remote computer; or completely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through 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., by using the Internet of an Internet service provider).

[0156] The flowchart legend and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present invention described above describe various aspects of the embodiment of the present invention.It will be understood that each block of the flowchart legend and / or block diagram and the combination of the blocks in the flowchart legend and / or block diagram can be implemented by computer program instructions.These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that the instructions (executed by the processor of the computer or other programmable data processing device) create a device for implementing the function / action specified in the flowchart and / or block diagram block or block.

[0157] These computer program instructions may also be stored in a computer-readable medium that can direct a computer, other programmable data processing device, or other apparatus to operate in a particular manner, so that the instructions stored in the computer-readable medium produce an article of manufacture including instructions for implementing the functions / actions specified in the flowchart and / or block diagram blocks or blocks.

[0158] The computer program instructions may also be loaded onto a computer, other programmable data processing device or other apparatus so that a series of operable steps are performed on the computer, other programmable device or other apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide a process for implementing the functions / actions specified in the flowchart and / or block diagram block or blocks.

[0159] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for calculating ambiguity based on dual-frequency observation data, characterized in that: The method includes: Acquire dual-frequency observation data of the current epoch, wherein the dual-frequency observation data includes a plurality of global positioning system GPS observation data and a plurality of Beidou satellite navigation system BDS observation data; Preprocessing the dual-frequency observation data to generate preprocessed dual-frequency observation data; Performing Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and a plurality of first ambiguity parameters; Generate a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution; Generate at least one second floating-point solution according to the plurality of double-difference floating-point solution post-verification residuals, wherein the second floating-point solution comprises a second position parameter and a plurality of second ambiguity parameters; Performing integrity detection according to the first floating-point solution and at least one of the second floating-point solutions to generate a target floating-point solution, wherein the target floating-point solution includes a third position parameter and a plurality of third ambiguity parameters; Generating a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution, wherein the first fixed solution includes a fourth position parameter and a plurality of fourth ambiguity parameters; Generate at least one second fixed solution according to the plurality of double-difference fixed solution post-verification residuals, wherein the second fixed solution comprises a fifth position parameter and a plurality of fifth ambiguity parameters; An integrity check is performed based on the first fixed solution and at least one of the second fixed solutions to generate a target fixed solution, wherein the target fixed solution includes a target position parameter and a plurality of target ambiguity parameters.

2. The method according to claim 1, characterized in that The method further includes: In response to continuously determining the target ambiguity parameters for a set number of epochs, the target ambiguity parameters are transferred to an epoch next to the current epoch.

3. The method according to claim 1, characterized in that The generating a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution specifically includes: Substitute the first floating-point solution into a preset double-difference observation equation to generate a plurality of double-difference floating-point solution post-verification residuals.

4. The method according to claim 1, characterized in that Generating at least one second floating-point solution according to the residuals after verification of the multiple double-difference floating-point solutions specifically includes: Traversing the plurality of double-difference floating-point decompression residuals at least once, and determining the maximum value among the plurality of double-difference floating-point decompression residuals during each traversal; Determine candidate dual-frequency observation data corresponding to the maximum value; The candidate dual-frequency observation data are eliminated from the dual-frequency observation data to generate at least one second floating-point solution.

5. The method according to claim 1, characterized in that The step of generating a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution specifically includes: Determine a floating-point solution of the double-difference wide-term ambiguity and a corresponding first variance according to the target floating-point solution; Determining a fixed solution for the double difference wide term ambiguity according to the floating point solution for the double difference wide term ambiguity; Determine a floating point solution of the double difference raw ambiguity and a corresponding second variance according to the fixed solution of the double difference wide term ambiguity; A fixed solution of the double-difference original ambiguity and a plurality of double-difference fixed solution post-verification residuals are determined according to the floating-point solution of the double-difference original ambiguity, wherein the fixed solution of the double-difference original ambiguity is the first fixed solution.

6. The method according to claim 5, characterized in that Determining a fixed solution of the double-difference original ambiguity according to the floating-point solution of the double-difference original ambiguity specifically includes: The floating point solution of the double difference original ambiguity is fixed according to the anonymous function LAMBDA to determine a fixed solution of the double difference original ambiguity.

7. The method according to claim 1, characterized in that The method further includes: In response to the ambiguity of the previous epoch of the current epoch being fixed and the current epoch not having a cycle slip, a position parameter pre-fix solution is determined according to the ambiguity of the previous epoch.

8. A device for calculating ambiguity based on dual-frequency observation data, characterized in that: The device includes: An acquisition unit, used for acquiring dual-frequency observation data of a current epoch, wherein the dual-frequency observation data includes a plurality of global positioning system GPS observation data and a plurality of Beidou satellite navigation system BDS observation data; A first generating unit, configured to preprocess the dual-frequency observation data to generate preprocessed dual-frequency observation data; A first determining unit, configured to perform Kalman filtering on the preprocessed dual-frequency observation data to determine a first floating-point solution, wherein the first floating-point solution includes a first position parameter and a plurality of first ambiguity parameters; A second generating unit, configured to generate a plurality of double-difference floating-point solution post-verification residuals according to the first floating-point solution; A third generating unit, configured to generate at least one second floating-point solution according to the plurality of double-difference floating-point solution post-verification residuals, wherein the second floating-point solution comprises a second position parameter and a plurality of second ambiguity parameters; a second determining unit, configured to perform integrity detection according to the first floating-point solution and at least one of the second floating-point solutions to determine a target floating-point solution, wherein the target floating-point solution includes a third position parameter and a plurality of third ambiguity parameters; A fourth generating unit, configured to generate a first fixed solution and a plurality of double-difference fixed solution post-verification residuals according to the target floating-point solution, wherein the first fixed solution includes a fourth position parameter and a plurality of fourth ambiguity parameters; A fifth generating unit, configured to generate at least one second fixed solution according to the plurality of double-difference fixed solution post-verification residuals, wherein the second fixed solution comprises a fifth position parameter and a plurality of fifth ambiguity parameters; The third determination unit is used to perform integrity detection according to the first fixed solution and at least one of the second fixed solutions to determine a target fixed solution, wherein the target fixed solution includes a target position parameter and a plurality of target ambiguity parameters.

9. A computer-readable storage medium, characterized in that: Computer program instructions are stored thereon, and the computer program instructions are executed by a processor to implement the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1 to 7.

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