Positioning method and device based on Beidou satellite, electronic equipment and storage medium

Abstract

One or more embodiments of the invention provide a positioning method and device based on a Beidou satellite, electronic equipment and a storage medium. The method comprises the following steps: acquiring carrier phase measurement data, pseudo-range measurement data and Doppler observation values of a plurality of frequency bands of a plurality of satellites through a mobile receiver and a fixed base station; according to the pseudo-range measurement data and the inter-satellite and inter-station double-difference model, double-difference pseudo-range observed quantity is obtained, and initial rough coordinates of the mobile receiver are obtained; according to the carrier phase measurement data, calculating the single-frequency ambiguity of B1 frequency points of the satellites by using a three-frequency carrier ambiguity resolving algorithm, and verifying the fixed state of the single-frequency ambiguity of each satellite; constructing a dynamic factor graph according to the single-frequency ambiguity, the carrier phase measurement data, the pseudo-range measurement data and the Doppler observation value; and obtaining a target positioning coordinate of the mobile receiver by using a sliding window estimator and taking the minimum sum of squares of all residual errors in a preset sliding window as a target function.

Description

TECHNICAL FIELD

[0001] One or more embodiments of the present disclosure relate to the field of satellite navigation positioning technology, and in particular to a Beidou satellite-based positioning method and device, electronic equipment and storage medium. BACKGROUND

[0002] It should be noted that the above introduction to the technical background is only for the convenience of clearly and completely describing the technical solutions of the present disclosure, and for the convenience of understanding by those skilled in the art. The above technical solutions cannot be considered as known to those skilled in the art merely because they are described in the background section of the present disclosure.

[0003] Satellite navigation technology has become one of the key core technologies in the field of positioning, navigation and timing (PNT) due to its all-weather, global coverage, strong real-time and high-precision advantages. With the growing demand for decimeter-level or even centimeter-level high-precision navigation and positioning in the field of power Beidou, such as power substation timing, unmanned aerial vehicle power inspection, real-time kinematic (RTK) technology based on carrier phase observations has become the key to obtaining centimeter-level high-precision positioning, and correct ambiguity fixing is the core of ensuring centimeter-level RTK positioning.

[0004] However, in complex urban scenarios such as urban centers and transportation hubs, the number of available satellites of the global navigation satellite system (GNSS) is reduced, and the accuracy and robustness of RTK positioning are challenged. SUMMARY

[0005] Therefore, the purpose of one or more embodiments of the present disclosure is to provide a Beidou satellite-based positioning method and device, electronic equipment and storage medium to solve the problems in the background.

[0006] To achieve the above purpose, one or more embodiments of the present disclosure provide a Beidou satellite-based positioning method, which comprises: Obtaining carrier phase measurement data, pseudorange measurement data and Doppler observation values of multiple satellites in multiple frequency bands through a mobile receiver and a fixed base station; According to the pseudorange measurement data and the inter-satellite station double-difference model, double-difference pseudorange observations are obtained and the initial coarse coordinates of the mobile receiver are obtained; According to the carrier phase measurement data, a three-frequency carrier ambiguity resolution algorithm is used to calculate the single-frequency ambiguity of the B1 frequency point of the satellite and to verify the fixed state of the single-frequency ambiguity of each satellite; constructing a dynamic factor graph according to the single-frequency ambiguity, the carrier phase measurement data, the pseudo-range measurement data and the Doppler observation value; wherein, the ambiguity float solution of the satellite with the fixing state of failure is included in the to-be-estimated parameter of the dynamic factor graph, and the fixed ambiguity of the satellite with the fixing state of success is included in the constraint condition of the dynamic factor graph; using a sliding window estimator to obtain the target positioning coordinates of the mobile receiver by taking the minimum sum of residual squares in a preset sliding window as an objective function.

[0007] Optionally, the constructing a dynamic factor graph according to the single-frequency ambiguity, the carrier phase measurement data, the pseudo-range measurement data and the Doppler observation value comprises: in response to the existence of the satellite with the fixing state of success, obtaining a single-frequency double-difference carrier phase constraint according to the carrier phase measurement data and the fixed ambiguity of the satellite with the fixing state of success, the single-frequency double-difference carrier phase constraint being a single-epoch state constraint; obtaining a double-difference pseudo-range constraint according to the pseudo-range measurement data, the double-difference pseudo-range constraint being a single-epoch state constraint; obtaining a Doppler velocity constraint between adjacent epochs according to the Doppler observation value.

[0008] Optionally, the using a sliding window estimator to obtain the target positioning coordinates of the mobile receiver by taking the minimum sum of residual squares in a preset sliding window as an objective function comprises: using a sliding window estimator to determine single-frequency double-difference carrier phase residuals, double-difference pseudo-range residuals and Doppler velocity residuals in a preset window; taking the minimum weighted sum of squares of the single-frequency double-difference carrier phase residuals, the double-difference pseudo-range residuals and the Doppler velocity residuals as an objective, solving the to-be-estimated parameter in the dynamic factor graph, the to-be-estimated parameter including the position coordinates of the mobile receiver and the moving speed of the mobile receiver.

[0009] Optionally, in response to the existence of the satellite with the fixing state of failure, the to-be-estimated parameter further includes the ambiguity float solution of the satellite with the fixing state of failure.

[0010] Optionally, after obtaining the target positioning coordinates, the method further comprises: in response to the to-be-estimated parameter including the ambiguity float solution of the satellite with the fixing state of failure, obtaining an optimized ambiguity float solution obtained simultaneously with the target positioning coordinates; using a least squares ambiguity decorrelation adjustment method to search for a fixed solution corresponding to the optimized ambiguity float solution; and In response to the ambiguity float solution existing a corresponding fixed solution, the fixed solution is determined as a fixed ambiguity of the satellite and an adjustment of a fixed state of the satellite is successful.

[0011] Optionally, in response to the number of satellites with a successful fixed state being greater than 3, the dynamic factor graph is reconstructed and the target positioning coordinates are updated.

[0012] Optionally, after the carrier phase measurement data, the pseudorange measurement data and the Doppler observation value are obtained, the method further comprises: obtaining satellite ephemeris of the satellites; performing data cleaning on the carrier phase measurement data, the pseudorange measurement data and the Doppler observation value according to the satellite ephemeris and a preset analysis index, to eliminate unusable abnormal data.

[0013] Based on the same inventive concept, one or more embodiments of the present disclosure also provide a Beidou satellite-based positioning device, comprising: a data acquisition module configured to acquire carrier phase measurement data, pseudorange measurement data and Doppler observation value of multiple satellites in multiple frequency bands through a mobile receiver and a fixed base station; a first calculation module configured to obtain double-difference pseudorange observations and initial coarse coordinates of the mobile receiver according to the pseudorange measurement data and an inter-satellite inter-station double-difference model; a second calculation module configured to calculate single-frequency ambiguity of a B1 frequency point of the satellites and check a fixed state of each single-frequency ambiguity of the satellites by using a three-frequency carrier ambiguity resolution algorithm according to the carrier phase measurement data; a third calculation module configured to construct a dynamic factor graph according to the single-frequency ambiguity, the carrier phase measurement data, the pseudorange measurement data and the Doppler observation value; wherein an ambiguity float solution of the satellite with a failed fixed state is included in an estimated parameter of the dynamic factor graph, and a fixed ambiguity of the satellite with a successful fixed state is included in a constraint condition of the dynamic factor graph; a fourth calculation module configured to obtain target positioning coordinates of the mobile receiver by using a sliding window estimator, with a sum of all residual squares in a preset sliding window as an objective function.

[0014] Optionally, the third calculation module is specifically configured to: in response to the satellite with a successful fixed state, obtain a single-frequency double-difference carrier phase constraint according to the carrier phase measurement data and the fixed ambiguity of the satellite with a successful fixed state, the single-frequency double-difference carrier phase constraint being a single-epoch state constraint; Based on the pseudorange measurement data, a double-difference pseudorange constraint is obtained; the double-difference pseudorange constraint is a single-epoch state constraint. Based on the Doppler observations, Doppler velocity constraints between adjacent epochs are obtained.

[0015] Optionally, the fourth computing module is specifically configured as follows: Using a sliding window estimator, determine the single-frequency double-difference carrier phase residual, double-difference pseudorange residual, and Doppler velocity residual within a preset window; With the objective of minimizing the weighted sum of the squared values ​​of the single-frequency double-difference carrier phase residual, the double-difference pseudorange residual, and the Doppler velocity residual, the parameters to be estimated in the dynamic factor diagram are solved. The parameters to be estimated include the position coordinates of the mobile receiver and the moving speed of the mobile receiver.

[0016] Optionally, in response to the existence of a satellite in a fixed state of failure, the parameters to be estimated further include the ambiguity floating-point solution of the satellite in the fixed state of failure.

[0017] Optionally, it is also configured as follows: In response to the parameter to be estimated including the ambiguity floating-point solution of the satellite with a fixed state of failure, an optimized ambiguity floating-point solution is obtained simultaneously with the target positioning coordinates; The least squares fuzzy decorrelation adjustment method is used to search for the fixed solution corresponding to the optimized fuzzy floating-point solution; In response to the existence of a corresponding fixed solution for the ambiguity floating-point solution, the fixed solution is determined as the fixed ambiguity of the satellite, and the fixed state of the satellite is adjusted successfully.

[0018] Optionally, it is also configured as follows: In response to the fact that the number of satellites whose fixed state is determined to be successful is greater than 3, the dynamic factor map is reconstructed and the target positioning coordinates are updated.

[0019] Optionally, it is also configured as follows: Obtain the satellite ephemeris of the satellite; Based on the satellite ephemeris and preset analysis indicators, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations are cleaned to remove unusable and abnormal data.

[0020] Based on the same inventive concept, one or more embodiments of this disclosure also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the positioning method based on BeiDou satellite as described in any of the above.

[0021] Based on the same inventive concept, one or more embodiments of the disclosure also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the Beidou satellite-based positioning method described above.

[0022] As can be seen from the above, the Beidou satellite-based positioning method provided by one or more embodiments of the disclosure considers multiple sets of observation information and state information, constructs a dynamic factor graph for RTK positioning, and improves positioning accuracy by using the dynamic factor graph. At the same time, in order to deal with the problem of satellite ambiguity fixing failure, the fixed single-frequency ambiguity is included in the constraint condition, and the fixed single-frequency ambiguity is included in the estimated parameter, so as to process the single-frequency ambiguity by differentiation, construct a factor graph optimization model suitable for the ambiguity state, and further improve the positioning accuracy and robustness. Through the technical solution of the disclosure, the RTK positioning accuracy and robustness can be effectively improved.

[0023] The Beidou satellite-based positioning device, electronic equipment and computer-readable storage medium provided by the disclosure can all implement the steps of the Beidou satellite-based positioning method described above, and therefore also have the beneficial effects of the Beidou satellite-based positioning method described above. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the one or more embodiments of the disclosure or the prior art, the drawings needed to be used in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only one or more embodiments of the disclosure, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0025] Figure 1 Flowchart of the Beidou satellite-based positioning method of one or more embodiments of the disclosure; Figure 2 Structure diagram of the Beidou satellite-based positioning device of one or more embodiments of the disclosure; Figure 3 Hardware structure diagram of the electronic equipment of one or more embodiments of the disclosure. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the disclosure clearer, the disclosure will be further described in detail below with reference to specific embodiments and drawings.

[0027] It should be noted that, unless otherwise defined, technical terms or scientific terms used in one or more embodiments of the present disclosure shall have the common meaning understood by one of ordinary skill in the art to which the present disclosure belongs. The terms "first", "second", and similar terms used in one or more embodiments of the present disclosure do not denote any order, quantity, or importance, but are used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connected" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0028] As described in the background section, ambiguity fixing is the core to ensure the centimeter-level positioning of RTK. The BeiDou-3 Global Navigation Satellite System (BDS-3) has been completed in China, and the BDS has the ability to broadcast multi-frequency signals. Multi-frequency signals can provide more carrier phase observation combination methods, and can generate combined observations with a wavelength of several meters, which is beneficial to ambiguity fixing.

[0029] However, in complex urban scenarios such as urban centers and transportation hubs, the number of available GNSS satellites is reduced, and the performance of conventional RTK positioning methods based on least squares (LSQ) and Kalman filtering (KF) degrades severely in complex urban scenarios. The accuracy and robustness of RTK positioning face challenges.

[0030] The applicant found that the reason for the severe performance degradation of the RTK positioning method in complex urban scenarios is that buildings such as high-rise buildings and viaducts block satellite signals, resulting in a reduction in the number of available GNSS satellites, and signal reflections from buildings produce multipath errors and non-line-of-sight propagation errors, which degrade the quality of carrier phase, pseudorange, and other observation data. Traditional RTK positioning relies on single-epoch observation information and mostly uses least squares or Kalman filtering, which lacks robustness when facing data quality fluctuations, and is prone to ambiguity fixing failure and sudden positioning accuracy degradation.

[0031] Therefore, this disclosure proposes a positioning method based on BeiDou satellites. The technical solution of this disclosure introduces a factor graph optimization framework, combining multi-epoch observations and state information. It uses a sliding window technique to jointly optimize position, velocity, and unfixed ambiguity floating-point solutions, avoiding the impact of single-epoch data quality fluctuations and enhancing positioning robustness. Furthermore, for scenarios where ambiguity fixing fails, optimized ambiguity floating-point solutions are obtained through factor graphs, reducing accuracy loss due to insufficient satellite count. Through this technical solution, positioning accuracy can be improved while enhancing the robustness of RTK positioning in complex scenarios, effectively addressing the impact of changes in ambiguity fixing status.

[0032] refer to Figure 1 This disclosure discloses a positioning method based on the BeiDou satellite according to one or more embodiments, including the following steps: Step S101: Acquire carrier phase measurement data, pseudorange measurement data, and Doppler observations from multiple satellites and multiple frequency bands using a mobile receiver and a fixed base station; Step S102: Based on the pseudorange measurement data and the inter-satellite station double-difference model, obtain the double-difference pseudorange observation and the initial coarse coordinates of the mobile receiver; Step S103: Based on the carrier phase measurement data, calculate the single-frequency ambiguity of the B1 frequency point of the satellite using the three-frequency carrier ambiguity resolution algorithm and verify the fixed state of the single-frequency ambiguity of each satellite; Step S104: Construct a dynamic factor graph based on the single-frequency ambiguity, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations; wherein, the floating-point solution of the ambiguity of the satellite in the fixed state of failure is included in the parameters to be estimated in the dynamic factor graph, and the fixed ambiguity of the satellite in the fixed state of success is included in the constraints of the dynamic factor graph; Step S105: Using a sliding window estimator, with the objective function being the minimum sum of squared residuals within a preset sliding window, the target positioning coordinates of the mobile receiver are obtained.

[0033] In the implementation of this disclosure, the observation equations for pseudorange, carrier phase, and Doppler observations acquired by both mobile receivers and fixed base stations are as follows: ; ; .

[0034] in, , and They represent the first Individual frequency receiver The acquired pseudorange, carrier phase, and Doppler observations, is the geometric distance between the receiver and the satellite, is the line-of-sight unit vector from the receiver to the satellite.

[0035] In the implementation of the present disclosure, to further improve the positioning accuracy, in the case of obtaining carrier phase measurement data, pseudo-range measurement data and Doppler observation values of multiple satellites and multiple frequency bands, statistical analysis can be performed on indicators such as signal-to-noise ratio and satellite elevation angle to eliminate unusable abnormal data and ensure the reliability of the input data.

[0036] In the embodiment of the present disclosure, the indicators for eliminating data are: satellites that lack available three-frequency carrier phase data, and / or satellites with an elevation angle lower than 10° and a carrier-to-noise ratio less than 10 using pseudo-range single-point positioning.

[0037] In the embodiment of the present disclosure, three-frequency carrier phase, pseudo-range and Doppler observation data collected by mobile receivers and fixed base stations can be integrated under the condition of short baseline (the distance between the mobile station and the base station is not more than 20 km).

[0038] In the implementation of the present disclosure, least squares adjustment can be performed on the inter-satellite and inter-station double-difference model to calculate the initial rough coordinates of the receiver. The initial rough coordinates provide coordinate initial values for subsequent factor graph optimization and ambiguity fixing.

[0039] ​​​​​​​​​​​​​​​​​​​​​​In the implementation of the present disclosure, the inter-satellite and inter-station double difference model is used to calculate double difference pseudo-range observations and double difference carrier phase observations.

[0040] In the embodiment of the present disclosure, the Beidou satellite with the highest elevation angle and without cycle slip is selected as the reference satellite, and the differences are made between the mobile station and the reference station and between the reference satellite and other satellites. In the short baseline condition, the satellite end error, the receiver end error, and the atmospheric and ionospheric related errors can be basically eliminated.

[0041] In the implementation of the present disclosure, the observation equations of the double difference pseudo-range observations and the double difference carrier phase observations are as follows: ; ; Wherein, and represent the double difference pseudo-range and carrier phase observations respectively, represent the frequency carrier phase double difference ambiguity parameters, and represent the residual errors of the double difference pseudo-range and carrier phase, which are modeled as Gaussian white noise.

[0042] In the implementation of the present disclosure, the inter-satellite and inter-station double difference model can also be used to realize triple-frequency combination observations such as ultra-wide lane and wide lane. The above observation can use the long wavelength characteristics to improve the integer ambiguity fixing performance.

[0043] In the implementation of the present disclosure, according to the frequencies broadcast by the Beidou satellite navigation system, appropriate combination coefficients can be selected to combine multi-frequency observations to construct a frequency linear combination with long wavelength, low ionospheric amplification coefficient and low noise level.

[0044] In the embodiment of the present disclosure, the Beidou No. 2 broadcasts signals at B1I (1561.098 MHz), B2I (1207.140 MHz) and B3I (1268.520 MHz) frequencies, while the Beidou No. 3 can broadcast B1I (1561.098 MHz), B1C (1575.42 MHz), B2a (1176.45 MHz) and B3I (1268.520 MHz) and other multi-frequency signals. Since the center frequencies of B1I and B1C are very close, and B1I is broadcast in all Beidou No. 3 satellites, BDS-2 B1I / B2I / B3I and BDS-3 B1I / B3I / B2a signals can be selected for Beidou three-frequency RTK positioning.

[0045] In the implementation of the present disclosure, the frequency, wavelength and double difference ambiguity of the combined triple-frequency observations can be represented as: ; ; wherein, 、 、 and 、 、 are the integer ambiguity of triple-frequency linear combination of double-difference code and carrier phase observations corresponding to BDS-2 and BDS-3 respectively; is the speed of light; 、 、 are the combination coefficients.

[0046] The triple-frequency linear combination of double-difference code and carrier phase observations can be expressed as: ; ; The triple-frequency combination will amplify the residual ionospheric error and carrier phase noise, and the ionospheric scale factor (ISF) and the phase noise factor (PNF) can be expressed as: ; ; Since there are many linear combinations of triple-frequency carrier phase observations, in order to facilitate the ultra-wide lane ambiguity fixing, the linear combination mode with longer wavelength and lower ISF and PNF is selected, and the total noise level of the triple-frequency carrier phase ultra-wide lane combination (0, -1, 1) of BDS-2 and BDS-3 is the smallest. It is the ultra-wide lane combination used in this patent.

[0047] The above process establishes an initial double-difference observation model related only to geometric distance and ambiguity parameters by combining multi-frequency observation information, so as to perform subsequent high-precision RTK positioning.

[0048] In the implementation of the present disclosure, according to the double-difference pseudo-range observation value and the least square method, the double-difference pseudo-range differential positioning result can be further obtained. The double-difference pseudo-range differential positioning observation equation can be: ; wherein, is the difference between the ultra-wide lane observation value and the geometric distance in meters, is the double-difference pseudo-range differential positioning design matrix composed of the difference between the unit vectors of the distances between the mobile receiver and the selected satellites and the reference satellites, and is the to-be-estimated parameter, which contains the three-dimensional coordinate error vector of the lower receiver, ​The observation noise vector is observed. The differential GNSS positioning result is calculated by least square adjustment, and the initial coordinates are provided for subsequent factor graph optimization. On the basis of obtaining the initial coordinates, the moving receiver velocity result is calculated according to the Doppler observation equation, and is used for constructing the Doppler velocity constraint residual.

[0049] In the implementation of the present disclosure, the process of calculating the single-frequency ambiguity of the B1 frequency point of the satellite by using a triple-frequency carrier ambiguity resolution algorithm can include: directly rounding and fixing the ultra-wide lane ambiguity by using the long wavelength advantage of the Beidou triple-frequency ultra-wide lane combination; then solving the wide lane ambiguity by using the fixed ultra-wide lane ambiguity, and further attempting to directly round to realize the rapid fixing of the wide lane ambiguity by wide lane combination; after the ultra-wide lane and wide lane ambiguity fixing is completed, the B1 frequency point single-frequency ambiguity is solved, and the B1 frequency point ambiguity is combined from the fixing results of the previous two stages to be rounded and fixed.

[0050] In the implementation of the present disclosure, the mathematical models of the ultra-wide lane ambiguity, the wide lane ambiguity and the original frequency point ambiguity can be expressed as: ; ; ; Among them, the Beidou triple-frequency ultra-wide lane and wide lane ambiguity combination coefficients are (0, -1, 1) and (1, -1, 0) respectively, and the rounding symbol is 0.25. When the floating point ambiguity and the corresponding integer value are less than 0.25, the ambiguity is considered to be fixed. For a satellite, the ambiguities of the ultra-wide lane, the wide lane and the original frequency point are considered to be fixed only when the ambiguities of the ultra-wide lane, the wide lane and the original frequency point are fixed, and the TCAR ambiguity is considered to be fixed successfully only when four or more satellites are fixed in one epoch.

[0051] After completing the step-by-step ambiguity fixing, the B1 frequency point ambiguity can be marked as two fixed states: fixed successfully or fixed unsuccessfully. In the case of fixed successfully, an integer form of single-frequency fixed ambiguity is obtained; in the case of fixed unsuccessfully, a single-frequency ambiguity floating point solution in the form of a floating point number is obtained.

[0052] In the technical solution of the present disclosure, the fixed state of the B1 frequency point ambiguity is closely related to the construction of the subsequent dynamic factor graph.

[0053] In the implementation of the present disclosure, the single-frequency double-difference carrier phase constraint and the double-difference pseudo-range constraint are introduced to form a single-epoch state constraint, and the Doppler observation value is used to construct a velocity constraint between adjacent epochs to form a dynamic factor graph model containing only position parameters.

[0054] Among them, the single-frequency double-difference carrier phase constraint is related to the B1 frequency ambiguity. When the B1 frequency ambiguity of any satellite is successfully fixed, its single-frequency fixed ambiguity is directly introduced into the constraint condition; when the B1 frequency ambiguity of any satellite is unfixed, its single-frequency ambiguity floating-point solution is introduced as a parameter to be estimated into the dynamic factor graph. By adding ambiguity constraint factors, the ambiguity parameters are jointly optimized in the factor graph model, and the ambiguity floating-point solution and the corresponding positioning result are estimated at the same time.

[0055] When the definition of a dynamic factor graph includes an unfixed single-frequency ambiguity parameter, the state to be estimated can be represented as: ; in, For size All states to be estimated within the sliding window, For a single epoch, the state to be estimated contains Location of the mobile receiver ,speed And single-frequency ambiguity that could not be fixed by the TCAR algorithm , This represents the total number of remaining unfixed ambiguities.

[0056] In the implementation of this disclosure, the objective function of the dynamic factor graph can be modeled as: ; in, The posterior optimal estimate obtained by factor graph optimization includes the estimation results for all states within the window. , and These represent the single-frequency double-difference pseudorange residual, double-difference carrier phase residual, and Doppler constant velocity constraint residual used for RTK positioning, respectively. , and These represent the covariances of the double-difference pseudorange residual, the double-difference carrier phase residual, and the Doppler constant velocity constraint residual, respectively, and are related to the noise levels of the double-difference pseudorange, the double-difference carrier, and the Doppler constant velocity noise level, respectively.

[0057] The single-frequency double-difference pseudorange residual, the double-difference carrier phase residual, and the Doppler constant velocity constraint residual can be expressed as: ; ; ; in, and They are respectively The coordinates of the mobile station to be estimated and the coordinates of the known base station are as follows: and They are respectively The positions of the selected satellite and reference satellite at that moment. The time interval for BeiDou observation data is generally 1 second.

[0058] As mentioned above, when constructing the double-difference carrier phase residual, based on the results of TCAR stepwise ambiguity fixing, the fixed single-frequency double-difference ambiguity is directly substituted into the fixed ambiguity of the observations with fixed ambiguity. If the ambiguity is not fixed, the single-frequency ambiguity of the satellite is used as the parameter to be estimated and optimized together with the position and velocity to obtain the floating-point solution.

[0059] In the implementation of this disclosure, the aforementioned residual block can be iteratively solved using the gradient descent algorithm to obtain the optimized state estimation result and its corresponding posterior covariance matrix. The posterior covariance can be expressed in the form of: ; in, and Represent The posterior covariance matrix at time points and the factor graph are used to optimize the overall Jacobian matrix. , and , respectively, represent the Jacobian matrices of the double-difference pseudorange, double-difference carrier, and Doppler constant velocity constraint relative to the state to be estimated. , and These represent the posterior position, velocity, and ambiguity floating-point solution covariance matrices, respectively. , and Each is composed of the residual covariance matrices of the objective function.

[0060] In the implementation of this disclosure, after each optimization, it is also possible to: determine whether there is a floating-point solution for the fuzzy parameter; if there is a floating-point solution, then the posterior state estimate is obtained. and covariance matrix The LAMBDA method is used to search for integer values ​​of the fuzziness parameter that satisfy the following relationship: ; in, This is the posterior estimation of floating-point solutions for single-frequency ambiguities in TCAR that are not fixed.

[0061] In the implementation of this disclosure, when a fixed solution is found in the integer ambiguity search, and the number of fixed ambiguity solutions obtained by the TCAR and LAMBDA methods is greater than 3, all fixed ambiguities can be substituted into the corresponding double-difference carrier phase observation equation to reconstruct the dynamic factor map and resolve the target positioning coordinates.

[0062] In the implementation of this disclosure, a sliding window estimator based on factor graph optimization is used. According to the set sliding window size, all residual blocks within the time window are summed to form the optimization objective function. The Gauss-Newton method is used to solve for the joint optimal estimation result of multiple states within the time window.

[0063] In the implementation of this disclosure, when a new time-observed residual block and the state to be estimated are added to the window, if the window size has already reached the set window size, the Schur elimination method is used to marginalize premature observation residual blocks and the state to be estimated.

[0064] It is understandable that this method can be executed by any device, equipment, platform, or cluster of devices with computing and processing capabilities.

[0065] It should be noted that the methods of one or more embodiments of this disclosure can be executed by a single device, such as a computer or server. The methods of this embodiment can also be applied in a distributed scenario, where multiple devices cooperate to complete the process. In such a distributed scenario, one of these devices may execute only one or more steps of the methods of one or more embodiments of this disclosure, and the multiple devices will interact with each other to complete the method described.

[0066] It should be noted that the above description pertains to specific embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0067] Based on the same inventive concept, corresponding to any of the above embodiments, this disclosure also provides a positioning device based on the BeiDou satellite system. For example... Figure 2 As shown, the above-mentioned device includes: The data acquisition module 11 is configured to acquire carrier phase measurement data, pseudorange measurement data and Doppler observations of multiple satellites and multiple frequency bands through a mobile receiver and a fixed base station; The first calculation module 12 is configured to obtain the double-difference pseudorange observation and the initial coarse coordinates of the mobile receiver based on the pseudorange measurement data and the inter-satellite double-difference model. The second calculation module 13 is configured to calculate the single-frequency ambiguity of the B1 frequency point of the satellite and verify the fixed state of the single-frequency ambiguity of each satellite based on the carrier phase measurement data using a three-frequency carrier ambiguity resolution algorithm. The third calculation module 14 is configured to construct a dynamic factor graph according to the single-frequency ambiguity, the carrier phase measurement data, the pseudo-range measurement data and the Doppler observation value; wherein the ambiguity float solution of the satellite with the fixed state of failure is included in the to-be-estimated parameter of the dynamic factor graph, and the fixed ambiguity of the satellite with the fixed state of success is included in the constraint condition of the dynamic factor graph. The fourth calculation module 15 is configured to use a sliding window estimator to obtain the target positioning coordinates of the mobile receiver by taking the minimum sum of residual squares in a preset sliding window as an objective function.

[0068] Optionally, the third calculation module 14 is specifically configured to: in response to the existence of the satellite with the fixed state of success, obtain a single-frequency double-difference carrier phase constraint according to the carrier phase measurement data and the fixed ambiguity of the satellite with the fixed state of success, the single-frequency double-difference carrier phase constraint being a single-epoch state constraint; obtain a double-difference pseudo-range constraint according to the pseudo-range measurement data; the double-difference pseudo-range constraint being a single-epoch state constraint; obtain a Doppler velocity constraint between adjacent epochs according to the Doppler observation value.

[0069] Optionally, the fourth calculation module 15 is specifically configured to: determine single-frequency double-difference carrier phase residuals, double-difference pseudo-range residuals and Doppler velocity residuals in a preset window by using a sliding window estimator; solve the to-be-estimated parameter in the dynamic factor graph by taking the minimum weighted sum of squares of the single-frequency double-difference carrier phase residuals, the double-difference pseudo-range residuals and the Doppler velocity residuals as an objective, the to-be-estimated parameter including the position coordinates of the mobile receiver and the moving speed of the mobile receiver.

[0070] Optionally, in response to the existence of the satellite with the fixed state of failure, the to-be-estimated parameter further includes the ambiguity float solution of the satellite with the fixed state of failure.

[0071] Optionally, the fourth calculation module 15 is further configured to: in response to the to-be-estimated parameter including the ambiguity float solution of the satellite with the fixed state of failure, obtain an optimized ambiguity float solution obtained simultaneously with the target positioning coordinates; search for a fixed solution corresponding to the optimized ambiguity float solution by using a least squares ambiguity decorrelation adjustment method; in response to the existence of the fixed solution corresponding to the ambiguity float solution, determine the fixed solution as the fixed ambiguity of the satellite and adjust the fixed state of the satellite to success.

[0072] Optionally, the fourth calculation module 15 is further configured to: In response to determining that the number of satellites with a successful fixing state is greater than 3, reconstructing the dynamic factor graph and updating the target positioning coordinates.

[0073] Optionally, the device is further configured to: obtain satellite ephemeris of the satellites; perform data cleaning on the carrier phase measurement data, the pseudorange measurement data and the Doppler observation value according to the satellite ephemeris and a preset analysis index, to eliminate unusable abnormal data.

[0074] For the convenience of description, the above device is described in various modules in terms of functions. Of course, the functions of each module can be implemented in one or more software and / or hardware when implementing one or more embodiments of the present disclosure.

[0075] The device of the above embodiment is used to implement the corresponding method in the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described here.

[0076] Figure 3 A more specific hardware structure of an electronic device is shown, which can include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040 and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030 and the communication interface 1040 are connected to each other through the bus 1050 for communication within the device.

[0077] The processor 1010 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., for executing related programs to implement the technical solutions provided by the embodiments of the present disclosure.

[0078] The memory 1020 can be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present disclosure are implemented by software or firmware, the related program codes are stored in the memory 1020 and called and executed by the processor 1010.

[0079] The input / output interface 1030 is configured to connect an input / output module to realize information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0080] The communication interface 1040 is configured to connect a communication module (not shown in the figure) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired manner (for example, a USB, a network cable, etc.) or through a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.).

[0081] The bus 1050 includes a channel to transmit information between various components (for example, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040) of the device.

[0082] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only contain components necessary for implementing the embodiments of the present disclosure, and does not necessarily contain all the components shown in the figure.

[0083] The electronic device of the above embodiment is used to realize the corresponding method in the above embodiment, and has the beneficial effects of the corresponding method embodiment, which will not be described here.

[0084] The computer readable medium of the embodiment includes permanent and non-permanent, removable and non-removable media, which can be realized by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0085] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this disclosure, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of one or more embodiments of this disclosure as described above, which are not provided in detail for the sake of brevity.

[0086] Additionally, to simplify the description and discussion, and to avoid obscuring one or more embodiments of this disclosure, the provided drawings may or may not show well-known power / ground connections to integrated circuit (IC) chips and other components. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring one or more embodiments of this disclosure, and this also takes into account the fact that the details of implementation of these block diagram apparatuses are highly dependent on the platform on which one or more embodiments of this disclosure will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuitry) are set forth to describe exemplary embodiments of this disclosure, it will be apparent to those skilled in the art that one or more embodiments of this disclosure may be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0087] Although this disclosure has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0088] This disclosure includes one or more embodiments intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A positioning method based on BeiDou satellites, characterized in that, include: Carrier phase measurement data, pseudorange measurement data, and Doppler observations from multiple satellites and multiple frequency bands are acquired using mobile receivers and fixed base stations. Based on the pseudorange measurement data and the inter-satellite / inter-station double-difference model, the double-difference pseudorange observations are obtained, and the initial coarse coordinates of the mobile receiver are obtained. Based on the carrier phase measurement data, the single-frequency ambiguity of the B1 frequency point of the satellite is calculated using a three-frequency carrier ambiguity resolution algorithm, and the fixed state of the single-frequency ambiguity of each satellite is verified. A dynamic factor graph is constructed based on the single-frequency ambiguity, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations; wherein, the floating-point ambiguity solution of the satellite in the fixed state of failure is included as a parameter to be estimated in the dynamic factor graph, and the fixed ambiguity of the satellite in the fixed state of success is included as a constraint condition in the dynamic factor graph. Using a sliding window estimator, with the objective function being to minimize the sum of squared residuals within a preset sliding window, the target positioning coordinates of the mobile receiver are obtained.

2. The method according to claim 1, characterized in that, A dynamic factor graph is constructed based on the single-frequency ambiguity, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations, including: In response to the existence of a satellite with a fixed state of success, a single-frequency double-difference carrier phase constraint is obtained based on the carrier phase measurement data and the fixed ambiguity of the satellite with a fixed state of success. The single-frequency double-difference carrier phase constraint is a single-epoch state constraint. Based on the pseudorange measurement data, a double-difference pseudorange constraint is obtained; the double-difference pseudorange constraint is a single-epoch state constraint. Based on the Doppler observations, Doppler velocity constraints between adjacent epochs are obtained.

3. The method according to claim 2, characterized in that, Using a sliding window estimator, with the objective function being the minimum sum of squared residuals within a preset sliding window, the target positioning coordinates of the mobile receiver are obtained, including: Using a sliding window estimator, determine the single-frequency double-difference carrier phase residual, double-difference pseudorange residual, and Doppler velocity residual within a preset window; With the objective of minimizing the weighted sum of the squared values ​​of the single-frequency double-difference carrier phase residual, the double-difference pseudorange residual, and the Doppler velocity residual, the parameters to be estimated in the dynamic factor diagram are solved. The parameters to be estimated include the position coordinates of the mobile receiver and the moving speed of the mobile receiver.

4. The method according to claim 3, characterized in that, In response to the existence of a satellite in a fixed state of failure, the parameters to be estimated also include the ambiguity floating-point solution of the satellite in the fixed state of failure.

5. The method according to claim 4, characterized in that, After obtaining the target positioning coordinates, the method further includes: In response to the parameter to be estimated including the ambiguity floating-point solution of the satellite with a fixed state of failure, an optimized ambiguity floating-point solution is obtained simultaneously with the target positioning coordinates; The least squares fuzzy decorrelation adjustment method is used to search for the fixed solution corresponding to the optimized fuzzy floating-point solution; In response to the existence of a corresponding fixed solution for the ambiguity floating-point solution, the fixed solution is determined as the fixed ambiguity of the satellite, and the fixed state of the satellite is adjusted successfully.

6. The method according to claim 5, characterized in that, In response to the fact that the number of satellites whose fixed state is determined to be successful is greater than 3, the dynamic factor map is reconstructed and the target positioning coordinates are updated.

7. The method according to claim 1, characterized in that, After acquiring the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations, the method further includes: Obtain the satellite ephemeris of the satellite; Based on the satellite ephemeris and preset analysis indicators, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations are cleaned to remove unusable and abnormal data.

8. A positioning device based on the BeiDou satellite system, characterized in that, include: The data acquisition module is configured to acquire carrier phase measurement data, pseudorange measurement data, and Doppler observations from multiple satellites and multiple frequency bands via a mobile receiver and a fixed base station. The first calculation module is configured to obtain the double-difference pseudorange observations and the initial coarse coordinates of the mobile receiver based on the pseudorange measurement data and the inter-satellite double-difference model. The second calculation module is configured to calculate the single-frequency ambiguity of the B1 frequency point of the satellite based on the carrier phase measurement data using a three-frequency carrier ambiguity resolution algorithm and to verify the fixed state of the single-frequency ambiguity of each satellite. The third calculation module is configured to construct a dynamic factor graph based on the single-frequency ambiguity, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations; wherein, the floating-point solution of the ambiguity of the satellite in the fixed state of failure is included in the parameters to be estimated in the dynamic factor graph, and the fixed ambiguity of the satellite in the fixed state of success is included in the constraints of the dynamic factor graph. The fourth calculation module is configured to use a sliding window estimator to obtain the target positioning coordinates of the mobile receiver by minimizing the sum of squared residuals within a preset sliding window as the objective function.

9. The apparatus according to claim 8, characterized in that, The third calculation module is specifically configured as follows: In response to the existence of a satellite with a fixed state of success, a single-frequency double-difference carrier phase constraint is obtained based on the carrier phase measurement data and the fixed ambiguity of the satellite with a fixed state of success. The single-frequency double-difference carrier phase constraint is a single-epoch state constraint. Based on the pseudorange measurement data, a double-difference pseudorange constraint is obtained; the double-difference pseudorange constraint is a single-epoch state constraint. Based on the Doppler observations, Doppler velocity constraints between adjacent epochs are obtained.

10. The apparatus according to claim 9, characterized in that, The fourth calculation module is specifically configured as follows: Using a sliding window estimator, determine the single-frequency double-difference carrier phase residual, double-difference pseudorange residual, and Doppler velocity residual within a preset window; With the objective of minimizing the weighted sum of the squared values ​​of the single-frequency double-difference carrier phase residual, the double-difference pseudorange residual, and the Doppler velocity residual, the parameters to be estimated in the dynamic factor diagram are solved. The parameters to be estimated include the position coordinates of the mobile receiver and the moving speed of the mobile receiver.

11. The apparatus according to claim 10, characterized in that, In response to the existence of a satellite in a fixed state of failure, the parameters to be estimated also include the ambiguity floating-point solution of the satellite in the fixed state of failure.

12. The apparatus according to claim 11, characterized in that, It is also configured as: In response to the parameter to be estimated including the ambiguity floating-point solution of the satellite with a fixed state of failure, an optimized ambiguity floating-point solution is obtained simultaneously with the target positioning coordinates; The least squares fuzzy decorrelation adjustment method is used to search for the fixed solution corresponding to the optimized fuzzy floating-point solution; In response to the existence of a corresponding fixed solution for the ambiguity floating-point solution, the fixed solution is determined as the fixed ambiguity of the satellite, and the fixed state of the satellite is adjusted successfully.

13. The apparatus according to claim 12, characterized in that, It is also configured as: In response to the fact that the number of satellites whose fixed state is determined to be successful is greater than 3, the dynamic factor map is reconstructed and the target positioning coordinates are updated.

14. The apparatus according to claim 8, characterized in that, It is also configured as: Obtain the satellite ephemeris of the satellite; Based on the satellite ephemeris and preset analysis indicators, the carrier phase measurement data, the pseudorange measurement data, and the Doppler observations are cleaned to remove unusable and abnormal data.

15. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executed by the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 7.

16. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1 to 7.

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