A method of processing dual-antenna GNSS positioning data and related apparatus
Patent Information
- Application Number
- CN202611167953.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-03
- Publication Date
- 2026-11-03
AI Technical Summary
In complex environments, dual-antenna GNSS systems lack a systematic data quality control mechanism, making it difficult to identify and process local data anomalies caused by single-antenna failures, multipath interference, or deterioration of satellite geometry, thus affecting the reliability and security of positioning and attitude determination.
By acquiring satellite positioning observation data from a base station and two rover stations, positioning calculations are performed using a double-difference observation method combining inter-station and inter-satellite differences. Combined with spatial geometric consistency checks and quality control, a fixed spatial baseline formed by two antennas is used as an intrinsic benchmark. The deviation between the dynamic baseline and the actual relative distance is compared in real time to achieve quality control of the dual-antenna GNSS positioning data.
It improves the quality and reliability of dual-antenna GNSS positioning data, ensures positioning accuracy and reliability in complex environments, reduces common errors, and enhances the security and stability of the system.
Smart Images
Figure CN123029580A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of satellite navigation and positioning technology, and in particular to a method and related equipment for processing dual-antenna GNSS positioning data. Background Technology
[0002] In high-precision dynamic positioning and attitude determination fields such as autonomous driving and intelligent construction robot positioning, dual-antenna systems based on GNSS carrier phase relative positioning have become the mainstream solution for acquiring key attitude information such as heading. However, in harsh environments such as complex urban canyons, multipath interference, or partial satellite signal obstruction, single antennas or raw observation data without strict quality control are prone to introducing gross errors or even faults, leading to inaccurate positioning and attitude determination results and seriously threatening system safety and reliability. Traditional single-antenna quality control methods cannot effectively diagnose local faults in the antenna itself or in the signal reception stage. Currently, dual-antenna GNSS systems usually directly use the dual-antenna calculation results, but lack a systematic data quality control mechanism, making it difficult to effectively identify and handle local data anomalies caused by single-antenna faults, multipath interference, or deterioration of satellite geometry in complex environments. Summary of the Invention The main objective of this application is to propose a method and related equipment for processing dual-antenna GNSS positioning data, aiming to improve the quality of dual-antenna GNSS positioning data and enhance positioning reliability.
[0003] To achieve the above objectives, one aspect of this application proposes a method for processing dual-antenna GNSS positioning data, comprising the following steps: Satellite positioning observation data from the base station and the two rover stations are acquired respectively; the two rover stations are set to a fixed relative position. Using the double-difference observation method of inter-station difference and inter-satellite difference, positioning calculation is performed based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station to obtain the baseline positioning calculation data of the corresponding rover station. Based on the baseline positioning calculation data and actual relative distance between the two rover stations, a spatial geometric consistency test is performed to obtain the first test result; Based on the first test result, the baseline positioning calculation data of the two rover stations are subjected to quality control.
[0004] In some embodiments, the satellite positioning observation data includes carrier phase, pseudorange, signal-to-noise ratio, and satellite ephemeris data; the double-difference observation method using inter-station difference and inter-satellite difference, which performs positioning calculations based on the satellite positioning observation data of the reference station and the satellite positioning observation data of each rover station to obtain the baseline positioning calculation data corresponding to the rover station, includes the following steps: The pseudorange difference between the rover station and the reference station relative to the same observation satellite is determined based on the difference between the pseudoranges of the rover station and the reference station. Then, a pseudorange double-difference observation equation is constructed based on the difference between the pseudorange difference between the observation satellite and the pseudorange difference between the reference satellite. The carrier phase inter-station difference corresponding to the observation satellite is determined based on the difference between the carrier phase of the rover station and the reference station relative to the same observation satellite. Then, a carrier phase double-difference observation equation is constructed based on the difference between the carrier phase inter-station difference of the observation satellite and the carrier phase inter-station difference of the reference satellite. The pseudorange double-difference observation equation and the carrier phase double-difference observation equation together form the double-difference observation equation set of the observation satellite. The parameters to be estimated are solved by combining the double-difference observation equations of multiple target observation satellites at the same epoch, and the baseline positioning solution data corresponding to the rover station is obtained.
[0005] In some embodiments, the process of solving the double-difference observation equations of multiple target observation satellites at the same epoch to obtain the baseline positioning solution data corresponding to the rover station includes the following steps: The parameters to be estimated are determined based on the true double-difference distance parameters and double-difference ambiguity parameters in the double-difference observation equation set. Then, the double-difference observation equation set of multiple target observation satellites at the same epoch is expressed as a matrix equation with all the parameters to be estimated as independent variables. Satellite weights are assigned based on the signal-to-noise ratio of each target observation satellite, resulting in a weight matrix; The baseline positioning solution data of the rover station is obtained by using the least squares parameter estimation method, based on the matrix equation and the weight matrix.
[0006] In some embodiments, the baseline positioning solution data includes the rover's solved position and ambiguity search value. The step of performing a spatial geometric consistency check based on the baseline positioning solution data of the two rover stations and the actual relative distance to obtain a first check result includes the following steps: The solution distance between the two rover stations is calculated based on their solution positions, and then the absolute value of the difference between the solution distance and the actual relative distance between the two rover stations is calculated. The absolute value of the difference is compared with a first threshold, and the ambiguity search value of each mobile station is compared with a second threshold to obtain a first test result.
[0007] In some embodiments, the baseline positioning solution data further includes satellite observation sequences; the quality control of the baseline positioning solution data of the two rover stations based on the first verification result includes the following steps: When the first test result indicates that the absolute value of the difference is less than the first threshold and the ambiguity search value of each rover station is less than the second threshold, the baseline positioning solution data is determined to be correct; otherwise, the baseline positioning solution data is updated by performing an observation value consistency test on the same satellite based on the satellite observation sequence of the two rover stations.
[0008] In some embodiments, the step of performing a consistency check on the observations of the same satellite based on the satellite observation sequences of the two rover stations to update the baseline positioning solution data includes the following steps: Based on the satellite observation sequences described by the two rover stations, a consistency test of the observation values of the same satellite was performed to obtain a second test result; Based on the second test result, a new target observation satellite is selected, and the step of solving the parameters to be estimated by combining the double-difference observation equations of multiple target observation satellites under the same epoch is performed again, so as to update the baseline positioning solution data of the rover station.
[0009] In some embodiments, the step of reselecting the target observation satellite based on the second test result includes the following steps: Based on the second test result, the N satellites with the worst observation consistency are removed from the plurality of target observation satellites, resulting in a new plurality of target observation satellites.
[0010] To achieve the above objectives, another aspect of this application proposes a dual-antenna GNSS positioning data processing system, comprising: The first module is used to acquire satellite positioning observation data from the base station and the two rover stations respectively; the two rover stations are set to a fixed relative position; The second module is used to perform positioning calculations based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station using the double-difference observation method of inter-station difference and inter-satellite difference, so as to obtain the baseline positioning calculation data of the corresponding rover station. The third module is used to perform a spatial geometric consistency check based on the baseline positioning calculation data and the actual relative distance between the two rover stations, and to obtain the first check result; The fourth module is used to perform quality control on the baseline positioning calculation data of the two rover stations based on the first test result.
[0011] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.
[0012] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the above-described method.
[0013] The embodiments of this application include at least the following beneficial effects: This application provides a method and related equipment for processing dual-antenna GNSS positioning data. This scheme acquires satellite positioning observation data from a base station and two rover stations, where the two rover stations are set to a fixed relative position. Then, using a double-difference observation method (inter-station difference and inter-satellite difference), positioning calculations are performed based on the satellite positioning observation data from the base station and each rover station to obtain the baseline positioning calculation data for the corresponding rover station. A spatial geometric consistency check is then performed based on the baseline positioning calculation data of the two rover stations and the actual relative distance, yielding a first check result. Quality control of the baseline positioning calculation data of the two rover stations is then performed based on the first check result. This scheme utilizes the strong constraint of a fixed spatial baseline formed by two antennas as an intrinsic benchmark for data consistency. By comparing the deviation between the baseline of the dynamic two baseline positioning calculation data and the fixed physical baseline (i.e., the actual relative distance) in real time, spatial geometric consistency diagnosis is achieved, thereby realizing quality control of dual-antenna GNSS positioning data and improving positioning reliability. Attached Figure Description
[0014] Figure 1 This is a flowchart of the dual-antenna GNSS positioning data processing method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation
[0015] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.
[0016] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.
[0017] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.
[0018] GNSS (Global Navigation Satellite System) is a general term for all satellite-based systems that provide positioning, navigation, and timing services, and also includes regional augmentation systems. GNSS receives signals transmitted by multiple satellites, calculates distance using signal propagation time, and determines the precise location, velocity, and time information of the receiving device on Earth.
[0019] This application provides a method and related equipment for processing dual-antenna GNSS positioning data. This scheme utilizes the strong constraint of a fixed spatial baseline formed by two antennas as an intrinsic benchmark for data consistency. By comparing the deviation between the baseline of the dynamic positioning solution data of the two baselines and the fixed physical baseline (i.e., the actual relative distance) in real time, spatial geometric consistency diagnosis is achieved, thereby realizing quality control of dual-antenna GNSS positioning data and improving positioning reliability.
[0020] The dual-antenna GNSS positioning data processing method provided in this application relates to the field of satellite navigation and positioning technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the dual-antenna GNSS positioning data processing method, but is not limited to the above forms.
[0021] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.
[0022] Figure 1 This is an optional flowchart of the dual-antenna GNSS positioning data processing method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S106.
[0023] S101, acquire satellite positioning observation data from the base station and the two rover stations respectively; the two rover stations are set to a fixed relative position; S102, using the double-difference observation method of inter-station difference and inter-satellite difference, the positioning solution is performed based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station to obtain the baseline positioning solution data of the corresponding rover station; S103, Based on the baseline positioning calculation data and actual relative distance between the two rover stations, a spatial geometric consistency test is performed to obtain the first test result; S104. Based on the first test results, perform quality control on the baseline positioning calculation data of the two rover stations.
[0024] Steps S101 to S104 of this embodiment involve acquiring satellite positioning observation data from a base station and two rover stations, with the two rover stations set to a fixed relative position. Then, using a double-difference observation method (inter-station difference and inter-satellite difference), positioning calculations are performed based on the satellite positioning observation data from the base station and each rover station to obtain baseline positioning calculation data for the corresponding rover station. A spatial geometric consistency check is then performed based on the baseline positioning calculation data of the two rover stations and the actual relative distance, yielding a first check result. Quality control of the baseline positioning calculation data of the two rover stations is then performed based on the first check result. This scheme utilizes the strong constraint of a fixed spatial baseline formed by two antennas as an intrinsic benchmark for data consistency. By comparing the deviation between the baseline of the two dynamically calculated baseline positioning data and the fixed physical baseline (i.e., the actual relative distance) in real time, spatial geometric consistency diagnosis is achieved, thereby realizing quality control of dual-antenna GNSS positioning data and improving positioning reliability.
[0025] In step S101 of some embodiments, a base station is set up in an open area, and a GNSS antenna is mounted at the front and rear of the moving vehicle as rover stations P1 and P2, respectively, so that the relative positions of the two rover stations are fixed. The moving vehicle is placed in the open area to observe GNSS data, and then the satellite positioning observation data of the base station and the two rover stations are read. The satellite positioning observation data includes carrier phase, pseudorange, signal-to-noise ratio, and satellite ephemeris data, etc. Baselines are established for the base station and the two rover stations respectively. The coordinates P1(X1, Y1, Z1) and P2(X2, Y2, Z2) of the two rover stations are solved using a post-relative positioning method, and then the fixed baseline between the two rover stations is solved, as shown below: (1) Fixed baseline length (That is, the actual relative distance between the two mobile stations) is: (2) In step S102 of some embodiments, a double-difference observation method using inter-station difference and inter-satellite difference is employed to perform positioning calculations based on satellite positioning observation data from the base station and satellite positioning observation data from each rover station, thereby obtaining baseline positioning calculation data for the corresponding rover station. Specifically, for the baseline between the base station and any rover station, double-difference observation equations for inter-station difference and inter-satellite difference are constructed based on the carrier phase and pseudorange observed by the base station and the rover station with different satellites, respectively. By solving multiple double-difference observation equations, the baseline positioning calculation data for the rover station is obtained. The baseline positioning calculation data may include the rover station's calculated position, ambiguity search value, and satellite observation sequence. The satellite observation sequence refers to the observation-related data of all target satellites in this calculation, which may include pseudorange residuals, carrier phase residuals, and signal-to-noise ratios, etc. Specifically, the satellite observation sequence may include at least one of a pseudorange residual sequence, a carrier phase residual sequence, and a signal-to-noise ratio sequence.
[0026] In some embodiments, step S102 may include, but is not limited to, the following steps: S201. The pseudorange difference between the rover station and the base station relative to the same observation satellite is determined based on the difference between the pseudoranges of the rover station and the base station. Then, the pseudorange double difference observation equation is constructed based on the difference between the pseudorange difference between the observation satellite and the pseudorange difference between the base satellite. S202, the carrier phase difference between the rover station and the reference station relative to the same observation satellite is determined based on the difference in carrier phase between the rover station and the reference station. Then, the carrier phase double-difference observation equation is constructed based on the difference between the carrier phase difference between the observation satellite and the carrier phase difference between the reference satellite. The pseudorange double-difference observation equation and the carrier phase double-difference observation equation together form the double-difference observation equation set of the observation satellite. S203, by combining the double-difference observation equations of multiple target observation satellites under the same epoch, the parameters to be estimated are solved, and the baseline positioning solution data of the corresponding rover station is obtained.
[0027] In this embodiment, a real-time dynamic positioning data processing model is constructed. When the mobile carrier is in motion, the two baselines constructed by the base station and the two rover stations are processed independently. The process for each baseline (i.e., the baseline positioning solution data of each rover station) is as follows: Carrier phase, pseudorange, signal-to-noise ratio, and broadcast ephemeris data are read from the base station and rover respectively to construct the carrier phase. and pseudo-distance The original observation equations are expressed as follows: (3) in, and They are designated as satellite and rover station numbers, This represents the geometric distance from the satellite to the receiver. and These represent the receiver and satellite clock biases, respectively. At the speed of light, For tropospheric wet delay parameters, Ionospheric delay in the direction of satellite incidence. and These are the sets of carrier phase hardware delay, relativistic effects, Earth's rotation, tidal and multipath effects errors, and other unmodeled errors. and These represent the pseudorange and carrier phase observation noise, respectively. The carrier phase wavelength, For the carrier phase ambiguity parameter, except for the one in equation (3) Except for the symbol which is in weeks, all other symbols are in meters.
[0028] Differential analysis is performed based on the pseudorange-to-station difference and carrier phase-to-station difference of different satellites, and corresponding pseudorange double-difference observation equations are constructed. Double-difference observation equations for carrier phase The pseudorange double-difference observation equation and the carrier phase double-difference observation equation together form the observation satellite's... The double-difference observation equations are expressed as follows: (4) In the formula, It is a double difference operator. The reference satellite can be the satellite with the highest elevation angle in the selected field of view. Indicates mobile station and base station Compared to the same observation satellite The pseudo-distance between stations; Indicates mobile station and base station Relative to the reference satellite The pseudo-distance between stations; Indicates mobile station and base station Compared to the same observation satellite Inter-station carrier phase difference; Indicates mobile station and base station Relative to the reference satellite The carrier phase difference between stations. By using double-difference operation, errors such as satellite orbit error, receiver and satellite clock error are eliminated. At the same time, since the distance between the two stations is short, double-difference can also greatly reduce ionospheric and tropospheric delay errors. Therefore, it can be seen from formula (4) that The parameter to be estimated in the double-difference observation equation system is the satellite-to-Earth distance. (i.e., true double-difference distance parameters) and double-difference ambiguity parameters .
[0029] Furthermore, the distance between the satellite and the ground Converted to positional parameters, it is represented as follows: (5) In the formula, The double difference direction cosine is specifically... , , .in, These are the initial coordinates of the rover. Approximate position of the rover to the satellite i The distance.
[0030] In this embodiment, by constructing a double-difference observation equation for pseudorange and carrier phase, the common errors between the base station and the rover can be effectively eliminated or significantly reduced, including satellite clock error, satellite ephemeris error, receiver clock error, and ionospheric and tropospheric delay errors in the case of short baseline. The remaining core parameters to be estimated in the observation equation are simplified to the position increment (baseline vector) of the rover relative to the base station and integer ambiguity, which simplifies the solution process and improves the positioning accuracy of subsequent calculations.
[0031] In some embodiments, step S203 may include, but is not limited to, the following steps: S301, the parameters to be estimated are determined based on the true double-difference distance parameters and double-difference ambiguity parameters in the double-difference observation equation set, and then the double-difference observation equation set of multiple target observation satellites at the same epoch is expressed as a matrix equation with all the parameters to be estimated as independent variables. S302, satellite weights are assigned based on the signal-to-noise ratio of each target observation satellite to obtain the weight matrix; S303 uses the least squares parameter estimation method to estimate parameters based on matrix equations and weight matrices, and obtains the baseline positioning solution data of the rover station.
[0032] In this embodiment, the satellite distance is... and double difference ambiguity parameters As parameters to be estimated, the double-difference observation equations (pseudorange double-difference observation equations or carrier phase double-difference observation equations) for multiple satellites at the same epoch are written in matrix form as follows: (6) In the formula, For the residual vector, The coefficient matrix, For the parameter to be estimated, The constant term (the satellite-to-ground distance calculated by subtracting the satellite and station coordinates from the measured satellite-to-ground distance) is as follows: (7) In the formula, For the coordinates of the measuring station, n This represents the number of double-difference observations.
[0033] A signal-to-noise ratio (SNR) weighting strategy is used to assign weights to the target satellites participating in the positioning calculation, and the weight matrix is determined. As shown in equations (8) and (9): (8) In the formula, for pseudorange observations , For carrier phase observations , Then the weight matrix The expression is: (9) In the formula, diag represents the diagonal element of the square matrix, and the subscript number represents the corresponding satellite number.
[0034] The least squares parameter estimation method is used to estimate the parameters for each epoch. The formula for solving the parameters to be estimated is as follows: (10) Find the floating-point solution and and its variance-covariance matrix .
[0035] After calculation, the LAMBDA method is used to search for floating-point ambiguity, i.e. (11) Find the fixed fuzzy solution and output the fuzzy search value.
[0036] (12) The two baselines are solved independently using the above process, and the rover coordinates for the current epoch are output separately. and pseudorange and carrier phase residual sequence , , , Signal-to-noise ratio sequence of two rover stations , Fuzzy search ratio value and .
[0037] In this embodiment, the variances of pseudorange and carrier phase observations are calculated based on the satellite's signal-to-noise ratio (SNR). Then, the reciprocal of the variance is used as the weight to form a diagonal matrix, where each weight is only related to the corresponding satellite's SNR. In the subsequent least squares solution, satellites with higher SNRs contribute more to the solution results, thereby improving the overall positioning accuracy.
[0038] In step S103 of some embodiments, a spatial geometric consistency check is performed based on the baseline positioning calculation data of the two rover stations and the actual relative distance to obtain a first check result.
[0039] In some embodiments, step S103 may include, but is not limited to, the following steps: S401, calculate the solution distance between the two rover stations based on their solution positions, and then calculate the absolute value of the difference between the solution distance and the actual relative distance between the two rover stations; S402, compare the absolute value of the difference with the first threshold, and compare the ambiguity search value of each rover station with the second threshold to obtain the first test result.
[0040] For example, the position is calculated based on the position of the two rover stations. and Calculate the baseline vector length (i.e., the solved distance) between the two rover stations, and determine whether the calculated baseline vector length is consistent with the fixed baseline length (i.e., the actual relative distance). (13) and, and If all values are greater than 3, the current solution is considered correct. If the above conditions are not met, further steps are required.
[0041] In this embodiment, spatial geometric consistency is verified by comparing the deviation between the dynamically calculated baseline and the fixed physical baseline in real time, thereby verifying the reliability of the calculation results and enabling quality control of the output positioning data.
[0042] In step S104 of some embodiments, the baseline positioning calculation data of the two rover stations are subjected to quality control based on the first inspection result.
[0043] In some embodiments, step S104 may include, but is not limited to, the following steps: S501, when the first test result indicates that the absolute value of the difference is less than the first threshold and the ambiguity search value of each rover station is less than the second threshold, the baseline positioning solution data is determined to be correct; otherwise, the consistency of observation values of the same satellite is checked based on the satellite observation sequences of the two rover stations to update the baseline positioning solution data.
[0044] In this embodiment, if the first test result indicates that the difference between the calculated baseline vector length and the fixed baseline length is less than a first threshold and the ambiguity search value of each rover station is less than a second threshold, the baseline positioning solution data is determined to be correct, and the calculated rover station positions and other data can be further output. If the first test result indicates that the difference between the calculated baseline vector length and the fixed baseline length is greater than or equal to the first threshold, or the ambiguity search value of any rover station is less than the second threshold, the positioning data calculated at this time is considered to have a large error. Subsequently, the baseline positioning solution data is updated by repositioning the data based on the satellite observation sequences of the two rover stations to verify the consistency of observation values on the same satellite, thereby achieving quality control of the rover station positioning data.
[0045] In some embodiments, the step S501, which involves performing a consistency check on the same satellite based on the satellite observation sequences of the two rover stations to update the baseline positioning solution data, may include, but is not limited to, the following steps: S601, Based on the satellite observation sequences of the two rover stations, the consistency of the observation values of the same satellite is checked, and the second check result is obtained; S602, based on the second test result, reselect the target observation satellite and re-execute the step of solving the parameters to be estimated by combining the double difference observation equations of multiple target observation satellites under the same epoch, so as to update the baseline positioning solution data of the rover station.
[0046] In this embodiment, after obtaining the baseline positioning solution data of the two rover stations, based on the data, if the difference between the calculated baseline vector length and the fixed baseline length is greater than or equal to a first threshold, or if the ambiguity search value of any rover station is less than a second threshold, then the observation value consistency test is further performed on the same satellite according to the satellite observation sequence of the two rover stations to obtain a second test result. The observation value consistency test can be at least one of the signal-to-noise ratio observation value consistency test, carrier phase residual consistency test, and pseudorange residual consistency test. The second test result can represent the degree of consistency of the observation values of each satellite. Based on the results of the second test, target observation satellites are reselected. For example, several observation satellites with good consistency in signal-to-noise ratio (SNR) observations, carrier phase residuals, or pseudorange residuals are selected as new target observation satellites for re-observation and positioning calculation. Alternatively, several observation satellites with good overall evaluation of consistent SNR, carrier phase residuals, and pseudorange residuals are selected as new target observation satellites for re-observation and positioning calculation. Or, the observations with the worst consistency in SNR, carrier phase residuals, and pseudorange residuals are removed, and the remaining observation satellites are selected as new target observation satellites for re-observation and positioning calculation. In this embodiment, when the calculation results do not meet geometric constraints, the consistency test of observation values is used to select satellites with better observation quality for re-observation and positioning calculation, thereby improving the accuracy of the positioning calculation.
[0047] In some embodiments, the step S602 of reselecting the target observation satellite based on the second verification result may include, but is not limited to, the following steps: S701, based on the second test results, the N satellites with the worst observation consistency are removed from the multiple target observation satellites to obtain a new set of multiple target observation satellites.
[0048] In this embodiment, a consistency check is performed by comparing the signal-to-noise ratio observations of the same satellite from both antennas, i.e., identifying... The satellite with the largest signal-to-noise ratio difference is identified; by comparing the carrier phase residual and pseudorange residual of the same satellite with dual antennas and their consistency, the satellite number is determined. and The satellite number with the largest difference is removed, and the positioning calculation process from step S101 to step S102 is repeated. Then, the spatial geometric consistency check in step S103 is performed. If it passes, the process exits and the final result is obtained. If it fails, the process can be iterated again until it passes or the number of available satellites is less than 6.
[0049] This application proposes a dual-antenna GNSS positioning data quality control method, aiming to construct a systematic real-time quality control system for dual-antenna GNSS positioning data. Its core is to fully utilize the strong constraint of a fixed spatial baseline formed by the two antennas as an intrinsic benchmark for data consistency. This application designs a multi-level parallel computation framework for quality indicators, simultaneously extracting single-antenna observation quality (such as signal-to-noise ratio and multipath effects) and dual-antenna joint solution quality (such as baseline residuals and ambiguity fixation reliability). Furthermore, by comparing the deviation between the dynamically calculated baseline and the fixed physical baseline in real time, spatial geometric consistency diagnosis is achieved; by analyzing the differences in observations of the same satellite by the two antennas, the intrinsic consistency of the observations is verified. Based on this, a faulty satellite identification and iterative processing strategy is established. Suspicious data is identified based on real-time diagnostic results, and available observations are dynamically adjusted in iterative estimation to eliminate problematic data and obtain effective results. The method proposed in this application is applicable to other satellite navigation and positioning systems and all their frequencies.
[0050] This application also provides a dual-antenna GNSS positioning data processing system, including: The first module is used to acquire satellite positioning observation data from the base station and the two rover stations respectively; the two rover stations are set to a fixed relative position; The second module is used to perform positioning calculations based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station using the double difference observation method of inter-station difference and inter-satellite difference, so as to obtain the baseline positioning calculation data of the corresponding rover station. The third module is used to perform spatial geometric consistency verification based on the baseline positioning calculation data and actual relative distance between the two rover stations, and obtain the first verification result; The fourth module is used to perform quality control on the baseline positioning calculation data of the two rover stations based on the results of the first test.
[0051] It is understood that the methods described in the above method embodiments are applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.
[0052] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.
[0053] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0054] Please see Figure 2 , Figure 2 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.
[0055] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.
[0056] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.
[0057] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.
[0058] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0059] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
[0060] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.
[0061] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.
[0062] The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.
[0063] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.
[0064] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0065] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.
[0066] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.
[0067] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0068] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.
[0069] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0070] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.
Claims
1. A method for processing dual-antenna GNSS positioning data, characterized in that, Includes the following steps: Satellite positioning observation data from the base station and the two rover stations are acquired respectively; the two rover stations are set to a fixed relative position. Using the double-difference observation method of inter-station difference and inter-satellite difference, positioning calculation is performed based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station to obtain the baseline positioning calculation data of the corresponding rover station. Based on the baseline positioning calculation data and actual relative distance between the two rover stations, a spatial geometric consistency test is performed to obtain the first test result; Based on the first test result, the baseline positioning calculation data of the two rover stations are subjected to quality control.
2. The method for processing dual-antenna GNSS positioning data according to claim 1, characterized in that, The satellite positioning observation data includes carrier phase, pseudorange, signal-to-noise ratio, and satellite ephemeris data; the double-difference observation method using inter-station difference and inter-satellite difference performs positioning calculations based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station to obtain the baseline positioning calculation data corresponding to the rover station, including the following steps: The pseudorange difference between the rover station and the reference station relative to the same observation satellite is determined based on the difference between the pseudoranges of the rover station and the reference station. Then, a pseudorange double-difference observation equation is constructed based on the difference between the pseudorange difference between the observation satellite and the pseudorange difference between the reference satellite. The carrier phase inter-station difference corresponding to the observation satellite is determined based on the difference between the carrier phase of the rover station and the reference station relative to the same observation satellite. Then, a carrier phase double-difference observation equation is constructed based on the difference between the carrier phase inter-station difference of the observation satellite and the carrier phase inter-station difference of the reference satellite. The pseudorange double-difference observation equation and the carrier phase double-difference observation equation together form the double-difference observation equation set of the observation satellite. The parameters to be estimated are solved by combining the double-difference observation equations of multiple target observation satellites at the same epoch, and the baseline positioning solution data corresponding to the rover station is obtained.
3. The method for processing dual-antenna GNSS positioning data according to claim 2, characterized in that, The method of solving the double-difference observation equations of multiple target observation satellites at the same epoch to obtain the baseline positioning solution data corresponding to the rover station includes the following steps: The parameters to be estimated are determined based on the true double-difference distance parameters and double-difference ambiguity parameters in the double-difference observation equation set. Then, the double-difference observation equation set of multiple target observation satellites at the same epoch is expressed as a matrix equation with all the parameters to be estimated as independent variables. Satellite weights are assigned based on the signal-to-noise ratio of each target observation satellite, resulting in a weight matrix; The baseline positioning solution data of the rover station is obtained by using the least squares parameter estimation method, based on the matrix equation and the weight matrix.
4. The method for processing dual-antenna GNSS positioning data according to claim 2, characterized in that, The baseline positioning solution data includes the rover's solved position and ambiguity search value. The step of performing a spatial geometric consistency check based on the baseline positioning solution data of the two rover stations and the actual relative distance to obtain a first check result includes the following steps: The solution distance between the two rover stations is calculated based on their solution positions, and then the absolute value of the difference between the solution distance and the actual relative distance between the two rover stations is calculated. The absolute value of the difference is compared with a first threshold, and the ambiguity search value of each mobile station is compared with a second threshold to obtain a first test result.
5. The method for processing dual-antenna GNSS positioning data according to claim 4, characterized in that, The baseline positioning solution data also includes satellite observation sequences; the quality control of the baseline positioning solution data of the two rover stations based on the first test result includes the following steps: When the first test result indicates that the absolute value of the difference is less than the first threshold and the ambiguity search value of each rover station is less than the second threshold, the baseline positioning solution data is determined to be correct; otherwise, the baseline positioning solution data is updated by performing an observation value consistency test on the same satellite based on the satellite observation sequence of the two rover stations.
6. The method for processing dual-antenna GNSS positioning data according to claim 5, characterized in that, The step of performing a consistency check on the observations of the same satellite based on the satellite observation sequences of the two rover stations, in order to update the baseline positioning solution data, includes the following steps: Based on the satellite observation sequences described by the two rover stations, a consistency test of the observation values of the same satellite was performed to obtain a second test result; Based on the second test result, a new target observation satellite is selected, and the step of solving the parameters to be estimated by combining the double-difference observation equations of multiple target observation satellites under the same epoch is performed again, so as to update the baseline positioning solution data of the rover station.
7. The method for processing dual-antenna GNSS positioning data according to claim 6, characterized in that, The step of reselecting the target observation satellite based on the second test result includes the following steps: Based on the second test result, the N satellites with the worst observation consistency are removed from the plurality of target observation satellites, resulting in a new plurality of target observation satellites.
8. A system for processing dual-antenna GNSS positioning data, characterized in that, include: The first module is used to acquire satellite positioning observation data from the base station and the two rover stations, respectively. The two mobile stations are set in fixed relative positions; The second module is used to perform positioning calculations based on the satellite positioning observation data of the base station and the satellite positioning observation data of each rover station using the double-difference observation method of inter-station difference and inter-satellite difference, so as to obtain the baseline positioning calculation data of the corresponding rover station. The third module is used to perform a spatial geometric consistency check based on the baseline positioning calculation data and the actual relative distance between the two rover stations, and to obtain the first check result; The fourth module is used to perform quality control on the baseline positioning calculation data of the two rover stations based on the first test result.
9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.