Phase multi-path real-time correction method and system based on GNSS (Global Navigation Satellite System) array antenna

Abstract

The invention relates to a GNSS array antenna-based phase multi-path real-time correction method and system. The method comprises the following steps of: constructing a spatial correlation array antenna system; based on an array antenna system, calculating geometric position relations of other antenna units relative to a reference antenna unit, forming single-difference carrier phase residual observation values of different antenna units and the reference antenna unit, and constructing a carrier phase multipath error parameter estimation model; based on a carrier phase multi-path error parameter estimation model, jointly processing a multi-frequency GNSS observation value by using the consistency and frequency correlation of propagation paths of frequency points of a multi-frequency GNSS signal, and establishing a multi-frequency multi-path error redundancy estimation model; based on the multi-frequency multi-path error redundancy estimation model and particle filtering, performing nonlinear estimation on parameters of the carrier phase multi-path error parameter estimation model to obtain multi-path error parameters; and obtaining a carrier phase multipath error value of each frequency point by using the multipath error parameter, and correcting the error value in real time in GNSS positioning calculation.

Description

Technical Field

[0001] This application relates to the field of GNSS high-precision positioning, specifically to a real-time phase multipath correction method and system based on a GNSS array antenna. Background Technology

[0002] High-precision positioning technology using Global Navigation Satellite Systems (GNSS) has become a core tool in fields such as surface deformation and structural health monitoring. Its monitoring accuracy directly impacts the timeliness and reliability of geological disaster early warning and safety assessments for large-scale projects. Among various error sources in GNSS observations, the multipath effect is one of the most significant obstacles to improving monitoring accuracy. This refers to the fact that GNSS signals not only reach the receiver antenna via a direct path but may also be reflected by surrounding buildings and other reflective surfaces before entering the antenna, causing distortions in the observed carrier phase and pseudorange. This error exhibits strong environmental dependence and spatial correlation, making it difficult to effectively eliminate using differential techniques or conventional models.

[0003] Current mainstream post-event correction methods based on site environment modeling rely on long-term observation data to establish empirical models of multipath errors (such as sidereal filtering and hemispherical multipath models), which suffer from time lag. Avoidance strategies based on hardware and site optimization (such as selecting open sites and using stencil antennas) are constrained by terrain and mission requirements, failing to meet ideal installation conditions, and hardware improvements cannot completely eliminate complex reflection signals. As monitoring missions expand to highly reflective environments such as canyons and urban areas, traditional technologies struggle to suppress multipath interference from different directions, resulting in centimeter-level errors in real-time calculations, severely impacting the reliability and timeliness of early warnings. Therefore, developing a technique for real-time estimation and correction of multipath errors has become a key breakthrough for achieving highly reliable real-time deformation monitoring. Summary of the Invention

[0004] This application provides a phase multipath real-time correction method and system based on a GNSS array antenna, which can solve the problem that complex application environments can produce multipath effects in the existing technology, making existing GNSS receivers unable to accurately capture low-frequency deformation signals due to complex multipath effects, thus affecting the application of GNSS technology in the field of high-precision deformation monitoring.

[0005] In a first aspect, embodiments of this application provide a real-time phase multipath correction method based on a GNSS array antenna, comprising: A space-correlated array antenna system is constructed, which includes a planar array composed of multiple antenna elements and a receiver. The spacing between adjacent antennas is 1 / 2 of the wavelength corresponding to the center frequency of the GNSS signal. The receiver synchronously receives multi-frequency GNSS observations from the planar array. Based on the aforementioned spatial correlation array antenna system, one antenna element is selected as the reference antenna element, and the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated to form single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element, and a carrier phase multipath error parameter estimation model is constructed. Based on the carrier phase multipath error parameter estimation model, the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at each frequency point are utilized to jointly process multi-frequency GNSS observations and establish a multi-frequency multipath error redundancy estimation model. Using a particle filter algorithm, based on the multi-frequency multipath error redundancy estimation model, the carrier phase multipath error parameters are nonlinearly estimated to obtain the multipath error parameters. Using the multipath error parameters, the carrier phase multipath error value of each frequency point is obtained, and the error value is corrected in real time during GNSS positioning calculation to obtain the GNSS positioning result after multipath correction.

[0006] In conjunction with the first aspect, in one implementation, based on the spatially correlated array antenna system, one antenna element is selected as a reference antenna element, the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated, single-difference carrier phase residual observations of different antenna elements and the reference antenna element are formed, and a carrier phase multipath error parameter estimation model is constructed, specifically including: Based on the space-correlated array antenna system, one antenna element is selected as the reference antenna element, and the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated. The geometric positional relationship includes distance and azimuth. The single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element are calculated, and a carrier phase multipath error parameter estimation model is constructed based on the geometric position relationship. The parameters in the carrier phase multipath error parameter estimation model include reflection phase value, reflection coefficient, elevation angle and azimuth angle.

[0007] In conjunction with the first aspect, in one implementation, the carrier phase multipath error parameter estimation model is as follows:

[0008]

[0009] in, The observed values ​​of the single-difference carrier phase residuals between the different antenna elements and the reference antenna element. The reflection coefficient is the carrier phase multipath error. and These represent the reflected phase values ​​of the carrier phase multipath error between the reference antenna element and other antenna elements. and These represent the geometric distance and azimuth angle between the antennas, respectively. and These are the elevation angle and azimuth angle of the carrier phase multipath error, respectively.

[0010] In conjunction with the first aspect, in one implementation, based on the carrier phase multipath error parameter estimation model, and utilizing the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at various frequencies, multi-frequency GNSS observations are jointly processed to establish a multi-frequency multipath error redundancy estimation model, specifically including: Based on the carrier phase multipath error parameter estimation model, the reflection phase value of one frequency point is determined from the multi-frequency GNSS observations, namely the reference frequency point reflection phase value. By utilizing the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals, the reflection phase values ​​of other frequencies are correlated with the reflection phase value of this frequency. Based on the aforementioned correlation, the reflection phase value parameters of other frequency points are mapped to the reflection phase value of the reference frequency point, forming common estimation parameters for the multipath error azimuth angle, elevation angle, and reflection phase value of the reference frequency point, thereby reducing the number of parameters to be estimated. A multi-frequency, multi-path error redundancy estimation model is established using the compressed parameters.

[0011] In conjunction with the first aspect, in one implementation, utilizing the consistent propagation path of multi-frequency GNSS signals, a correlation is established between the reflection phase values ​​of other frequencies and the reflection phase value of this frequency, specifically including: Based on the consistent propagation path of multi-frequency GNSS signals, the wavelength ratio of each frequency point is determined. Using the wavelength ratio relationship, the reflection phase values ​​of other frequency points are proportionally scaled and correlated with the reflection phase value of this frequency point.

[0012] In conjunction with the first aspect, in one implementation, a particle filter algorithm is used to perform nonlinear estimation of the carrier phase multipath error parameters based on the multi-frequency multipath error redundancy estimation model, thereby obtaining the multipath error parameters. Specifically, this includes: The multi-frequency multipath error parameter estimation model is used as the observation equation, and the multi-frequency single-difference carrier phase residual of the carrier phase multipath error parameter estimation model is used as the observation to construct the observation model. Use the identity matrix as the state model; The particle filter algorithm is used to perform state prediction based on the state model, measurement update based on the observation model, and resampling. The multipath error parameters are estimated in real time through the iterative process of state prediction, measurement update, and resampling.

[0013] In conjunction with the first aspect, in one implementation, the carrier phase multipath error value at each frequency point is obtained using the multipath error parameter, and this error value is corrected in real time during GNSS positioning calculation to obtain the multipath-corrected GNSS positioning result, specifically including: Based on the multi-frequency multipath error redundancy estimation model, the multipath error parameters are extended to each frequency point to obtain the carrier phase multipath error value of each frequency point. During the GNSS positioning calculation process, the acquired carrier phase multipath error value is subtracted from the carrier phase observation value to obtain the carrier phase observation value after multipath correction. The corrected carrier phase observations are used to perform GNSS positioning calculations to obtain the multipath-corrected GNSS positioning results.

[0014] Secondly, embodiments of this application provide a real-time phase multipath correction system based on a GNSS array antenna, comprising: An array antenna module is used to: construct a space-correlated array antenna system, the space-correlated array antenna system including a planar array composed of multiple antenna elements and a receiver, the spacing between adjacent antennas being 1 / 2 of the wavelength corresponding to the center frequency of the GNSS signal, and the receiver synchronously receiving multi-frequency GNSS observations from the multi-antenna array; The multi-frequency multipath modeling module is used to: select one antenna element as a reference antenna element based on the space-correlated array antenna system, calculate the geometric positional relationship of other antenna elements relative to the reference antenna element, form single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element, and construct a carrier phase multipath error parameter estimation model; based on the carrier phase multipath error parameter estimation model, utilize the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at each frequency point, jointly process multi-frequency GNSS observation values, and establish a multi-frequency multipath error redundancy estimation model; The particle filter estimation module is used to: employ a particle filter algorithm to perform nonlinear estimation of the carrier phase multipath error parameters based on the multi-frequency multipath error redundancy estimation model, and obtain the multipath error parameters. The error correction and positioning module is used to: obtain the carrier phase multipath error value of each frequency point using the multipath error parameter, and correct the error value in real time in GNSS positioning calculation to obtain the GNSS positioning result after multipath correction.

[0015] The beneficial effects of the technical solutions provided in this application include: This application provides a real-time phase multipath correction method and system based on a GNSS array antenna. By constructing a planar spatial correlation array antenna system with adjacent antenna spacing equal to half the wavelength corresponding to the center frequency of the GNSS signal, spatial correlation is formed, providing a physical basis for accurate estimation of multipath errors. The system utilizes the consistent propagation path of each frequency point of the multi-frequency GNSS signal to establish a multi-frequency multipath error redundancy estimation model. By jointly processing multi-frequency observations, the estimation of multipath error parameters can fully utilize the redundant information of the multi-frequency signals, improving the accuracy and robustness of parameter estimation. A particle filtering algorithm is used to perform nonlinear estimation of the carrier phase multipath error parameter estimation model, avoiding the limitations of traditional linearization methods when dealing with trigonometric function models, ensuring the reliability of parameter estimation. By acquiring the carrier phase multipath error values ​​of each frequency point in real time and performing real-time correction in GNSS positioning calculations, the impact of multipath errors is effectively suppressed. This significantly improves the accuracy and stability of GNSS positioning results without increasing additional hardware costs or requiring long-term observation data. Especially in urban environments or complex terrains with severe multipath interference, it can provide reliable technical support for high-precision positioning. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the phase multipath real-time correction method based on GNSS array antenna in this application. Figure 2 This is a schematic diagram of the phase multipath real-time correction system based on a GNSS array antenna according to this application; Figure 3 This is a schematic diagram of a real-time phase multipath correction method based on a GNSS array antenna. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0018] This application provides a phase multipath real-time correction method and system based on a GNSS array antenna, which can solve the problem that complex application environments can produce multipath effects in the existing technology, making existing GNSS receivers unable to accurately capture low-frequency deformation signals due to complex multipath effects, thus affecting the application of GNSS technology in the field of high-precision deformation monitoring.

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0020] In a first aspect, embodiments of this application provide a real-time phase multipath correction method based on a GNSS array antenna, comprising: 101: Construct a space-correlated array antenna system. The space-correlated array antenna system includes a planar array composed of multiple antenna elements and a receiver. The spacing between adjacent antennas is 1 / 2 of the wavelength corresponding to the center frequency of the GNSS signal. The receiver synchronously receives multi-frequency GNSS observations from the planar array. 102: Based on the spatial correlation array antenna system, select one antenna element as the reference antenna element, calculate the geometric positional relationship of other antenna elements relative to the reference antenna element, form the single-difference carrier phase residual observation values ​​of different antenna elements and the reference antenna element, and construct a carrier phase multipath error parameter estimation model; 103: Based on the carrier phase multipath error parameter estimation model, taking advantage of the consistent propagation path of each frequency point of multi-frequency GNSS signals, multi-frequency GNSS observations are jointly processed to establish a multi-frequency multipath error parameter redundancy estimation model. 104: Using the particle filter algorithm, based on the multi-frequency multipath error parameter redundancy estimation model, the carrier phase multipath error parameters are nonlinearly estimated to obtain the multipath error parameters; 105: Using multipath error parameters, the carrier phase multipath error value of each frequency point is obtained, and the error value is corrected in real time in GNSS positioning calculation to obtain the GNSS positioning result after multipath correction.

[0021] In this application, a planar spatial correlation array antenna system with adjacent antenna spacing equal to half the wavelength corresponding to the center frequency of the GNSS signal is constructed to form spatial correlation, providing a physical basis for accurate estimation of multipath errors. This system utilizes the consistent propagation path of each frequency point of the multi-frequency GNSS signal to establish a multi-frequency multipath error redundancy estimation model. By jointly processing multi-frequency observations, the estimation of multipath error parameters can fully utilize the redundant information of the multi-frequency signals, improving the accuracy and robustness of parameter estimation. A particle filtering algorithm is used to perform nonlinear estimation of the carrier phase multipath error parameter estimation model, avoiding the limitations of traditional linearization methods when dealing with trigonometric function models, ensuring the reliability of parameter estimation. By acquiring the carrier phase multipath error values ​​of each frequency point in real time and correcting them in real time during GNSS positioning calculations, the impact of multipath errors is effectively suppressed. This significantly improves the accuracy and stability of GNSS positioning results without increasing additional hardware costs or requiring long-term observation data. Especially in urban environments or complex terrains with severe multipath interference, it can provide reliable technical support for high-precision positioning.

[0022] Based on the above embodiments, in this embodiment, based on a spatially correlated array antenna system, one antenna element is selected as a reference antenna element, the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated, single-difference carrier phase residual observations of different antenna elements and the reference antenna element are formed, and a carrier phase multipath error parameter estimation model is constructed, specifically including: First, based on the space-correlated array antenna system, one antenna element is selected as the reference antenna element, and the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated. The geometric positional relationship includes distance and azimuth. The single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element are calculated. Based on the geometric positional relationship, a carrier phase multipath error parameter estimation model is constructed. The parameters in the carrier phase multipath error parameter estimation model include reflection phase value, reflection coefficient, elevation angle and azimuth.

[0023] In practice, the antenna element with the best signal quality or the center position is selected as the reference antenna element based on the physical layout characteristics of the array antenna. This selection takes into account the signal-to-noise ratio and stability of the received signal of the antenna element to ensure the reliability of the reference.

[0024] Subsequently, based on the precise installation coordinates of each antenna element in the array antenna, the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated. These relationships include not only straight-line distance, but also relative azimuth angles in the horizontal plane and three-dimensional spatial angle relationships. These parameters are obtained through the multi-frequency GNSS data acquisition module during antenna installation and input into the processing module during system initialization.

[0025] Based on the calculated distance and azimuth parameters, the system further calculates the carrier phase residual observations between different antenna elements and the reference antenna element. This calculation process considers the basic physical mechanism of multipath effect, namely, the carrier phase multipath error is caused by the superposition of direct and reflected signals, which can be expressed as Equation 1 and can be normalized and simplified to Equation 2: (1); (2); Where ΔΨ is the observed carrier phase residual value between other antenna elements and the reference antenna element. and τ is the normalized reflection coefficient, R is the autocorrelation function, τ is the delay of the direct signal relative to the local signal, δ is the delay of the multipath signal relative to the local signal, and γ is the phase of the reflected signal.

[0026] For each antenna element in the array, due to slight differences in its spatial position, the phase characteristics of the received multipath signal are also slightly different. This difference is closely related to the geometric distance and azimuth angle between the antennas, specifically manifested in Equation 3: the specific reflection phase relationship between the antennas. (3); in and These represent the reflected phase values ​​of the carrier phase multipath error between the reference antenna element and other antenna elements. and These represent the geometric distance and azimuth angle between the antennas, respectively. and These are the elevation angle and azimuth angle of the carrier phase multipath error, respectively.

[0027] In an array antenna system, the spatial correlation of carrier phase multipath error between different antenna elements can be expressed as Equation 4: (4); in, These are the carrier phase residual observations between other antenna elements and the reference antenna element. Let be the reflection coefficient of the carrier phase multipath error. This equation describes the variation of multipath error caused by the positional differences between antenna elements and is the basis for constructing the parameter estimation model.

[0028] In the actual calculation process, the carrier phase observation value is given by Equation 5: (5), in The difference between pseudorange observations between antennas. The difference in blurriness over the entire week. The difference is the receiver clock error. The difference is the carrier phase noise. This represents the difference in carrier phase multipath error. This formula decomposes the observed carrier phase residual into multiple components, facilitating the subsequent separation of the multipath error components from the observations.

[0029] When constructing the carrier phase multipath error parameter estimation model, the system represents the multipath error parameter vector as follows: Where x is the multipath error parameter to be estimated, α1 and α f Let γ1, θ0, and φ0 be the multipath error reflection phase parameters of frequency point 1 and other frequency points f, respectively. γ1, θ0, and φ0 are the reflection phase value, elevation angle, and azimuth angle of the carrier phase multipath error of frequency point 1, respectively. Since the signal propagation path is consistent, the azimuth and elevation angles of other frequency points f and frequency point 1 are the same, which are θ0 and φ0.

[0030] In particular, due to the consistent propagation path of multi-frequency GNSS signals, the system only needs to estimate the reflection phase value of one frequency to calculate the reflection phase values ​​of other frequencies through proportional relationships, which significantly improves the efficiency and reliability of parameter estimation.

[0031] The parameter estimation model constructed using the above formula fully considers the trigonometric function characteristics of multipath error, accurately describes the spatial correlation changes of multipath signals, and lays the foundation for subsequent parameter estimation using particle filter algorithm. In actual operation, it continuously receives observation data from each antenna element and updates the multipath error parameters in real time, thereby achieving effective modeling and estimation of multipath effects in complex environments.

[0032] Based on the above embodiments, in this embodiment, a multi-frequency multipath error redundancy estimation model is established by jointly processing multi-frequency GNSS observations using the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at each frequency point, based on the carrier phase multipath error parameter estimation model. Specifically, this includes: First, based on the carrier phase multipath error parameter estimation model, the reflection phase value of one frequency point is determined from multi-frequency GNSS observations. Then, utilizing the consistent propagation path of multi-frequency GNSS signals, the reflection phase values ​​of other frequencies are correlated with the reflection phase value of this frequency point. Based on the consistent propagation path of multi-frequency GNSS signals, the wavelength ratio of each frequency point is determined. Using the wavelength ratio, the reflection phase values ​​of other frequencies are proportionally scaled and correlated with the reflection phase value of this frequency point. Next, based on the correlation, the reflection phase value parameters of other frequencies are mapped to the reflection phase value of the reference frequency point, forming common estimation parameters for the multipath error azimuth angle, elevation angle, and the reflection phase value of the reference frequency point, thus compressing the parameters to be estimated. Finally, using the compressed parameters, a multi-frequency multipath error redundancy estimation model is established.

[0033] In practice, the first step is to analyze the characteristics of multipath error at different frequencies based on multi-frequency GNSS observation data acquired by the space-correlated array antenna system. Due to the consistent propagation path of multi-frequency GNSS signals—that is, the multipath signal generated by the same reflection source affects GNSS signals of different frequencies through the same path, exhibiting only phase differences due to frequency variations—this characteristic forms the basis for establishing a multi-frequency correlation model. During model construction, the reflection phase value of one frequency point is first determined from the multi-frequency GNSS observations based on the carrier phase multipath error parameter estimation model. .

[0034] Then, taking advantage of the consistent propagation path of multi-frequency GNSS signals, the reflection phase values ​​of other frequencies are correlated with the reflection phase value of this frequency. Specifically, based on the consistent propagation path of multi-frequency GNSS signals, the wavelength ratio of each frequency is determined, which can be expressed by Equation 6: (6); Where γ f Let λ1 and λ2 be the reflection phase values ​​of the carrier phase multipath error at the f-th frequency point. f Here, γ1 represents the wavelengths at frequencies 1 and f, respectively. This formula shows that, since multipath signals propagate along the same path, the reflection phase value at different frequencies is inversely proportional to the wavelength. This proportional relationship eliminates the need for the system to estimate the reflection phase value for each frequency individually. Instead, it only needs to estimate the reflection phase value γ1 at one frequency (e.g., L1) to calculate the reflection phase values ​​at other frequencies using the wavelength proportionality, thus reducing the number of parameters that need to be estimated.

[0035] In terms of parameter compression, the multipath error parameters corresponding to multi-frequency GNSS observations are compressed into a single-frequency parameter set. Specifically, the vector of parameters to be estimated for multi-frequency phase multipath errors is expressed as Equation 7: (7); Where x is the multipath error parameter to be estimated, and α1 and α2 are... f Let γ1, θ0, and φ0 be the reflection phase parameters of the multipath error at frequency 1 and other frequency points f, respectively. γ1, θ0, and φ0 are the reflection phase value, elevation angle, and azimuth angle of the carrier phase multipath error at frequency 1, respectively. Since the signal propagation path is consistent, the azimuth and elevation angles of other frequency points f and frequency 1 are the same, which are θ0 and φ0. This characteristic further reduces the number of estimation parameters.

[0036] In practical implementation, the system first preprocesses the carrier phase observations at each frequency point to eliminate common error terms such as ionospheric delay, and then calculates the single-difference carrier phase residuals between different antenna elements. Based on Equation 5, the system extracts the multipath error components at each frequency point. Subsequently, using the frequency reflection phase relationship established by Equation 6, the multi-frequency observation data are integrated into a unified parameter estimation framework to estimate the parameter vector x defined in Equation 7.

[0037] The establishment of this multi-frequency correlation model fully utilizes redundant observation information between frequencies, effectively improving the reliability of multipath error estimation. Because multi-frequency observations provide more constraints, the solution space for parameter estimation is more clearly defined, reducing the problem of multiple solutions and improving estimation accuracy. The multi-frequency multipath error correlation model established using the above method not only improves the reliability of parameter estimation but also significantly reduces computational complexity, enabling real-time processing and providing an effective solution for high-precision GNSS positioning in complex environments.

[0038] Based on the above embodiments, this embodiment employs a particle filter algorithm and a multi-frequency multipath error redundancy estimation model to perform nonlinear estimation of carrier phase multipath error parameters, thereby obtaining the multipath error parameters. Specifically, this includes: First, the multi-frequency multipath error parameter estimation model is used as the observation equation, and the multi-frequency single-difference carrier phase residual of the carrier phase multipath error parameter estimation model is used as the observation to construct the observation model. Then, the identity matrix is ​​used as the state model. Next, the particle filter algorithm is used to perform state prediction based on the state equation, perform measurement update based on the observation model, and perform resampling. Finally, through the iterative process of state prediction, measurement update and resampling, the multipath error parameters are estimated in real time.

[0039] In practice, the multi-frequency multipath error parameter estimation model is first used as the observation equation, which is defined by Equation 6. Simultaneously, the multi-frequency single-difference carrier phase residuals are used as observations, which are given by Equation 5.

[0040] Based on the above, the system constructs an observation model: (8) The model organizes the phase residuals of multi-frequency single-difference carriers into observation vectors, which are then used as inputs to the particle filter algorithm.

[0041] During the execution of the particle filter algorithm, state prediction is performed first: based on the state estimate and state transition model from the previous moment, the state at the current moment is predicted. Specifically, for each particle i, the state transition probability is calculated. Samples are drawn from the data to obtain the predicted state. This step enables Monte Carlo sampling of the state space. Next, a state update is performed: based on the observation model, the weight of each particle is calculated. ,in It is the observation likelihood function, representing the likelihood under a given state. The following observations The probability of the observed multipath error. In this application, the observation likelihood function is constructed based on Equations 4 and 5, reflecting the degree of matching between the predicted multipath error and the actual observed residual.

[0042] Then resampling is performed: normalized weights are calculated. And assess the effective number of particles. When the number of effective particles falls below a threshold, resampling is performed, and a new particle set is drawn based on the particle weights to avoid particle degradation. This process ensures that the particle set can effectively represent the posterior probability distribution of the state.

[0043] Through an iterative process of state prediction, state update, and resampling, the system estimates multipath error parameters in real time. It is particularly noteworthy that, due to the highly nonlinear characteristics of the multipath error model (manifesting as a trigonometric function), traditional linearization methods such as Kalman filtering produce significant errors. In contrast, the particle filter algorithm directly processes the nonlinear model through Monte Carlo sampling, eliminating the need for linearization approximations and enabling more accurate parameter estimation. In practical implementation, the system employs GPU acceleration technology, supporting efficient synchronous processing of 1000 to 5000 particle sets, ensuring the algorithm's real-time performance.

[0044] The particle filter algorithm applied in this application also considers the characteristics of multi-frequency observations. By establishing the inter-frequency reflection phase relationship through Equation 6, multi-frequency observation information is effectively integrated into a unified estimation framework. This not only improves the reliability of parameter estimation but also enhances the algorithm's robustness to observation noise.

[0045] Based on the above embodiments, in this embodiment, multipath error parameters are used to obtain carrier phase multipath error values ​​for each frequency point, and these error values ​​are corrected in real time during GNSS positioning calculation to obtain multipath-corrected GNSS positioning results. Specifically, this includes: first, based on a multi-frequency multipath error redundancy estimation model, extending the multipath error parameters to each frequency point to obtain carrier phase multipath error values ​​for each frequency point; then, during the GNSS positioning calculation, subtracting the obtained carrier phase multipath error values ​​from the carrier phase observation values ​​to obtain multipath-corrected carrier phase observation values; finally, using the corrected carrier phase observation values ​​to perform GNSS positioning calculation to obtain multipath-corrected GNSS positioning results.

[0046] In practice, the process begins by extending the multipath error parameters to each frequency point based on a multi-frequency multipath error redundancy estimation model, thereby obtaining the carrier phase multipath error value for each frequency point. This process starts with the multipath error parameter vector estimated in real time using a particle filter algorithm. Based on the consistent propagation path of multi-frequency GNSS signals, the system first utilizes Equation 6: Calculate the reflection phase value at each frequency point. Then, the system substitutes the calculated reflection phase value into Equation 2: This allows for the calculation of the carrier phase multipath error value at each frequency point. .

[0047] During GNSS positioning calculation, the system subtracts the acquired carrier phase multipath error value from the original carrier phase observation value to obtain the multipath-corrected carrier phase observation value. This process is achieved by reconstructing the positioning observation equation, specifically described by Equation 9: (9) in, The corrected carrier phase residual, The difference between pseudorange observations between antennas. The difference in blurriness over the entire week. The difference is the receiver clock error. The difference is the carrier phase noise. The difference in carrier phase multipath error. The equation represents the modeled carrier phase multipath error. This shows that the system introduces the modeled carrier phase multipath error into the original observation equations, and achieves real-time correction of the multipath error through a subtraction operation. In actual calculations, the system performs this correction process independently for each antenna element and each frequency point, ensuring the accuracy and specificity of the correction.

[0048] During the positioning calculation, the system utilizes the spatial geometry of the array antennas, combined with satellite position information and time synchronization data, to calculate the receiver's precise position. Because multipath errors have been effectively eliminated, systematic biases in the observations are significantly reduced, enabling the positioning calculation to obtain more accurate integer ambiguity fixed solutions.

[0049] In actual operation, the system continuously executes multipath error estimation and correction processes, completing multiple iterations per second to ensure that the correction parameters can reflect environmental changes in a timely manner. Furthermore, the system also considers the handling of correction residuals. When residuals exist between the modeled multipath errors and actual observations, these residuals are incorporated into the weight adjustment of the positioning solution, avoiding new errors caused by over-correction. Through these methods, the system not only effectively suppresses multipath errors but also maintains the robustness and continuity of the positioning solution, providing reliable technical support for high-precision GNSS deformation monitoring applications. It significantly improves the accuracy and stability of GNSS positioning in complex environments without requiring long-term observation data.

[0050] In summary, the positioning method of this application can effectively correct carrier phase multipath errors based on array antennas without requiring long-term observation data, thereby improving GNSS positioning accuracy in complex environments; it can effectively handle the highly nonlinear problems caused by the trigonometric function model of multipath error, improving the accuracy and stability of model solution; by combining observation information from multiple frequencies, it fully utilizes the correlation of multipath errors between frequencies, enhances the redundancy of parameter estimation, thereby improving the reliability of multipath error estimation and the overall robustness of the model.

[0051] Secondly, embodiments of this application provide a real-time phase multipath correction system based on a GNSS array antenna, comprising: an array antenna module, a multi-frequency multipath modeling module, a particle filter estimation module, and an error correction and localization module. The array antenna module is used to: construct a spatial correlation array antenna system, which includes a planar array composed of multiple antenna elements and a receiver. The spacing between adjacent antennas is half the wavelength corresponding to the center frequency of the GNSS signal. The receiver synchronously receives multi-frequency GNSS observations from the planar array. The multi-frequency multipath modeling module is used to: select one antenna element as a reference antenna element based on the spatial correlation array antenna system, calculate the geometric positional relationship between other antenna elements and the reference antenna element, and form the relationship between different antenna elements and the reference antenna element. The system examines the single-difference carrier phase residual observations of the antenna element and constructs a carrier phase multipath error parameter estimation model. Based on this model, it utilizes the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals to jointly process multi-frequency GNSS observations and establish a multi-frequency multipath error redundancy estimation model. A particle filter estimation module is used to perform nonlinear estimation of the carrier phase multipath error parameters using a particle filter algorithm based on the multi-frequency multipath error redundancy estimation model, thereby obtaining the multipath error parameters. An error correction and positioning module is used to obtain the carrier phase multipath error values ​​at each frequency point using the multipath error parameters, and to correct these error values ​​in real time during GNSS positioning calculations, obtaining the multipath-corrected GNSS positioning result.

[0052] The multi-frequency multipath modeling module is also used for: selecting an antenna element as a reference antenna element based on a space-correlated array antenna system, calculating the geometric positional relationship of other antenna elements relative to the reference antenna element, including distance and azimuth; calculating the single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element, and constructing a carrier phase multipath error parameter estimation model based on the geometric positional relationship, the parameters in the carrier phase multipath error parameter estimation model including reflection phase value, reflection coefficient, elevation angle and azimuth.

[0053] The carrier phase multipath error parameter estimation model is as follows:

[0054]

[0055] in, These are the single-difference carrier phase residual observations between different antenna elements and the reference antenna element. The reflection coefficient is the carrier phase multipath error. and These represent the reflected phase values ​​of the carrier phase multipath error between the reference antenna element and other antenna elements. and These represent the geometric distance and azimuth angle between the antennas, respectively. and These are the elevation angle and azimuth angle of the carrier phase multipath error, respectively.

[0056] Specifically, the array antenna module is used to construct a space-correlated array antenna system. This system consists of M GNSS antenna elements (M≥5), arranged at equal intervals of 1 / 2 wavelength to form a regular planar array structure. The spacing between adjacent antennas is set to 1 / 2 of the wavelength corresponding to the center frequency of the GNSS signal. This design is based on the spatial sampling principle in antenna array theory, ensuring a clear phase relationship between the multipath signals received by different antenna elements, and effectively capturing the spatial variation characteristics of multipath errors. The array antenna adopts a regular planar layout (such as a square or circular array). This layout gives the system uniform directional response characteristics in the horizontal plane, enabling it to comprehensively sense multipath signals from different directions.

[0057] The array antenna module includes a waterproof housing and multiple GNSS antenna elements built into the waterproof housing. The housing is made of highly weather-resistant composite material, which has excellent waterproof, dustproof and electromagnetic interference protection performance, ensuring that the module can work stably for a long time in complex environments. The antenna elements are based on a low-profile microstrip antenna design. This design not only reduces the size of the antenna, but also reduces the electromagnetic interference of the antenna to the surrounding environment. Structurally, it adopts a multi-feed antenna design. Through phase synthesis of multiple feed points, the phase center stability is significantly improved, enabling it to achieve a phase center accuracy better than 2mm. This ensures the accuracy and consistency of signal reception, which is crucial for carrier phase measurement, because a small change in the phase center can directly lead to positioning errors at the centimeter or even decimeter level.

[0058] The multi-frequency multipath modeling module is used in space-correlated array antenna systems. It selects one antenna element as a reference antenna element, calculates the geometric positional relationship of other antenna elements relative to the reference antenna element, forms single-difference carrier phase residual observations between different antenna elements and the reference antenna element, and constructs a carrier phase multipath error parameter estimation model. Specifically, this module first calculates the precise relative positions between each antenna element, including horizontal distance and azimuth angle, based on measurement data during antenna installation. Then, it uses Equation 3 to calculate the reflection phase value relationship between different antenna elements. Next, it constructs a carrier phase multipath error spatial correlation model based on Equation 4. Building upon this, the module further utilizes the consistent propagation path of multi-frequency GNSS signals at each frequency point, jointly processes multi-frequency GNSS observations, and establishes a multi-frequency multipath error redundancy estimation model. This process establishes the relationship between reflection phase values ​​at different frequencies through Equation 6, thereby integrating multi-frequency observation information into a unified parameter estimation framework to generate a multi-frequency carrier phase multipath error parameter estimation model. The parameter vector of this model is represented as follows: .

[0059] The particle filter estimation module employs a particle filter algorithm based on a multi-frequency multipath error redundancy estimation model to nonlinearly estimate the parameters of the carrier phase multipath error parameter estimation model, thereby obtaining the multipath error parameters. This module integrates a GPU-accelerated particle filter engine, specifically optimized for the highly nonlinear characteristics of the multipath error trigonometric function model, enabling efficient synchronous processing of 1000 to 5000 particle sets. In actual operation, the system uses the multi-frequency multipath error parameter estimation model as the state equation and the multi-frequency carrier phase residual as the observation to construct an observation model. The particle filter algorithm estimates the parameters in real time through an iterative process of state prediction, state update, and resampling, as shown in Equation 10: .

[0060] Because multipath error models are highly nonlinear, traditional linearization methods such as Kalman filtering can introduce significant errors. Particle filtering, however, directly processes the nonlinear model through Monte Carlo sampling, eliminating the need for linear approximation and more accurately reflecting the true evolution of multipath errors. GPU acceleration enables efficient sampling within the state space, allowing for simultaneous state prediction and weight updates on a massive number of particles, ensuring multiple iterations per second and real-time output of multipath error parameters. Regarding the particle count, a range of 1000 to 5000 particles strikes a balance between computational accuracy and real-time performance. Too few particles lead to decreased estimation accuracy, while too many increase computational burden and negatively impact real-time performance.

[0061] The error correction and positioning module utilizes multipath error parameters to obtain carrier phase multipath error values ​​for each frequency point and performs real-time correction on these error values ​​during GNSS positioning calculation, resulting in a multipath-corrected GNSS positioning result. This module embeds a multipath error correction interface into the GNSS real-time high-precision positioning algorithm. First, based on a multi-frequency multipath error redundancy estimation model, the multipath error parameters are extended to each frequency point, and the carrier phase multipath error value for each frequency point is calculated using Equation 2. Then, during the GNSS positioning calculation, the obtained carrier phase multipath error value is subtracted from the original carrier phase observation value. This process is achieved by reconstructing the positioning observation equation, specifically described by Equation 9. Finally, the corrected carrier phase observation value is used for GNSS positioning calculation to obtain the multipath-corrected GNSS positioning result. This module includes a main control processing unit, which comprises a GPU processor and an FPGA coprocessor. It adopts a heterogeneous computing architecture, efficiently leveraging the parallel computing capabilities of the GPU and the pipelined processing advantages of the FPGA to ensure continuous and stable system operation. In practical applications, this module can process multi-frequency observation data from array antennas in real time, perform multiple multipath error corrections and positioning calculations per second, and output centimeter-level positioning results. It is particularly suitable for high-precision GNSS deformation monitoring applications such as landslide monitoring and bridge deformation monitoring.

[0062] In the overall system workflow, after the array antenna module synchronously receives multi-frequency GNSS observations, the multi-frequency multipath modeling module calculates the relative distance and azimuth angle based on the antenna coordinate difference, generating a multi-frequency carrier phase multipath error parameter estimation model. The particle filter estimation module uses this model to perform nonlinear parameter estimation and outputs multipath error parameters in real time. The error correction and positioning module then applies these parameters to the original observations to perform real-time multipath error correction and output high-precision positioning results. The multi-channel receiver uses an atomic clock as the core time reference source, supports synchronous acquisition of multi-channel GNSS multi-frequency signals, and outputs a high-performance 10MHz reference clock or 1PPS signal. This signal is distributed via a frequency allocation module, which integrates bandpass filtering, power allocation, and isolators. Through low-noise amplification and signal isolation technology, it ensures no interference between multiple outputs and extremely low phase noise, providing a unified frequency reference for the entire system and guaranteeing inter-channel time synchronization accuracy ≤1ns and a sampling rate ≥1Hz.

[0063] Through the above systematic design, the present invention can suppress multipath effects in real time, significantly enhance the stability and reliability of positioning in complex environments, provide solid equipment support for high-precision GNSS deformation monitoring applications, and effectively solve the technical problem that existing GNSS receivers cannot accurately capture low-frequency deformation signals in complex multipath environments.

[0064] The functions of each module in the above-mentioned phase multipath real-time correction system based on GNSS array antenna correspond to the steps in the above-mentioned phase multipath real-time correction method embodiment based on GNSS array antenna. Their functions and implementation processes will not be described in detail here.

[0065] Thirdly, embodiments of this application provide a phase multipath real-time correction device based on a GNSS array antenna. The phase multipath real-time correction device based on a GNSS array antenna can be a personal computer (PC), laptop computer, server, or other device with data processing capabilities.

[0066] In this embodiment of the application, the phase multipath real-time correction device based on GNSS array antenna may include a processor, a memory, a communication interface, and a communication bus.

[0067] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0068] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces. These interfaces enable interconnection of internal components within the GNSS array antenna-based phase multipath real-time correction device, and also facilitate interconnection between the device and other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0069] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0070] The processor can be a general-purpose processor, which can call a real-time phase multipath correction program based on a GNSS array antenna stored in memory and execute the real-time phase multipath correction method based on a GNSS array antenna provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the real-time phase multipath correction program based on a GNSS array antenna is called can be referred to in the various embodiments of the real-time phase multipath correction method based on a GNSS array antenna of this application, and will not be repeated here.

[0071] Fourthly, embodiments of this application also provide a computer-readable storage medium.

[0072] The present application stores a real-time phase multipath correction program based on a GNSS array antenna on a computer-readable storage medium, wherein when the real-time phase multipath correction program based on a GNSS array antenna is executed by a processor, the steps of the real-time phase multipath correction method based on a GNSS array antenna as described above are implemented.

[0073] The method implemented when the phase multipath real-time correction program based on GNSS array antenna is executed can be referred to in the various embodiments of the phase multipath real-time correction method based on GNSS array antenna in this application, and will not be repeated here.

[0074] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0075] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0076] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0077] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0078] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0079] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0080] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A real-time phase multipath correction method based on a GNSS array antenna, characterized in that, It includes: A space-correlated array antenna system is constructed, which includes a planar array composed of multiple antenna elements and a receiver. The spacing between adjacent antennas is 1 / 2 of the wavelength corresponding to the center frequency of the GNSS signal. The receiver synchronously receives multi-frequency GNSS observations from the planar array. Based on the aforementioned spatial correlation array antenna system, one antenna element is selected as the reference antenna element, and the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated to form single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element, and a carrier phase multipath error parameter estimation model is constructed. Based on the carrier phase multipath error parameter estimation model, the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at each frequency point are utilized to jointly process multi-frequency GNSS observations and establish a multi-frequency multipath error parameter redundancy estimation model. The particle filter algorithm is used to perform nonlinear estimation of the carrier phase multipath error parameters based on the multi-frequency multipath error parameter redundancy estimation model to obtain the multipath error parameters. Using the multipath error parameters, the carrier phase multipath error value of each frequency point is obtained, and the error value is corrected in real time during GNSS positioning calculation to obtain the GNSS positioning result after multipath correction.

2. The real-time phase multipath correction method based on GNSS array antenna as described in claim 1, characterized in that, Based on the aforementioned spatial correlation array antenna system, one antenna element is selected as the reference antenna element. The geometric positional relationship of other antenna elements relative to the reference antenna element is calculated, forming single-difference carrier phase residual observations between different antenna elements and the reference antenna element. A carrier phase multipath error parameter estimation model is then constructed, specifically including: Based on the space-correlated array antenna system, one antenna element is selected as the reference antenna element, and the geometric positional relationship of other antenna elements relative to the reference antenna element is calculated. The geometric positional relationship includes distance and azimuth. The single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element are calculated, and a carrier phase multipath error parameter estimation model is constructed based on the geometric position relationship. The parameters in the carrier phase multipath error parameter estimation model include reflection phase value, reflection coefficient, elevation angle and azimuth angle.

3. The real-time phase multipath correction method based on GNSS array antenna as described in claim 2, characterized in that, The carrier phase multipath error parameter estimation model is as follows: in, The observed values ​​of the single-difference carrier phase residuals between the different antenna elements and the reference antenna element. The reflection coefficient is the carrier phase multipath error. and These represent the reflected phase values ​​of the carrier phase multipath error between the reference antenna element and other antenna elements. and These represent the geometric distance and azimuth angle between the antennas, respectively. and These are the elevation angle and azimuth angle of the carrier phase multipath error, respectively.

4. The real-time phase multipath correction method based on GNSS array antenna as described in claim 1, characterized in that, Based on the carrier phase multipath error parameter estimation model, and utilizing the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at various frequencies, a multi-frequency GNSS observation model is established by jointly processing the multi-frequency multipath error redundancy estimation values. Specifically, this includes: Based on the carrier phase multipath error parameter estimation model, the reflection phase value at the reference frequency is determined from the multi-frequency GNSS observations; By utilizing the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals, the reflection phase values ​​of other frequency points are correlated with the reflection phase values ​​of the reference frequency point; Based on the aforementioned correlation, the reflection phase value parameters of other frequency points are mapped to the reflection phase value of the reference frequency point to form common estimation parameters for the multipath error azimuth angle, elevation angle, and reflection phase value of the reference frequency point, so as to compress the parameters to be estimated. A multi-frequency, multi-path error redundancy estimation model is established using the compressed parameters.

5. The real-time phase multipath correction method based on GNSS array antenna as described in claim 4, characterized in that, Taking advantage of the consistent propagation path of multi-frequency GNSS signals, a correlation is established between the reflection phase values ​​of other frequencies and the reflection phase value of this frequency. Specifically, this includes: Based on the consistent propagation path of multi-frequency GNSS signals, the wavelength ratio of each frequency point is determined. Using the wavelength ratio relationship, the reflection phase values ​​of other frequency points are proportionally scaled and correlated with the reflection phase value of this frequency point.

6. The real-time phase multipath correction method based on GNSS array antenna as described in claim 1, characterized in that, Using a particle filter algorithm, based on the aforementioned multi-frequency multipath error redundancy estimation model, nonlinear estimation of the carrier phase multipath error parameters is performed to obtain the multipath error parameters, specifically including: The multi-frequency multipath error parameter estimation model is used as the observation equation, and the multi-frequency single-difference carrier phase residual of the carrier phase multipath error parameter estimation model is used as the observation to construct the observation model. Use the identity matrix as the state model; The particle filter algorithm is used to perform state prediction based on the state model, measurement update based on the observation model, and resampling. The multipath error parameters are estimated in real time through the iterative process of state prediction, measurement update, and resampling.

7. The real-time phase multipath correction method based on GNSS array antenna as described in claim 1, characterized in that, Using the aforementioned multipath error parameters, the carrier phase multipath error value for each frequency point is obtained, and this error value is corrected in real time during GNSS positioning calculation to obtain the multipath-corrected GNSS positioning result, specifically including: Based on the multi-frequency multipath error redundancy estimation model, the multipath error parameters are extended to each frequency point to obtain the carrier phase multipath error value of each frequency point. During the GNSS positioning calculation process, the acquired carrier phase multipath error value is subtracted from the carrier phase observation value to obtain the carrier phase observation value after multipath correction. The corrected carrier phase observations are used to perform GNSS positioning calculations to obtain the multipath-corrected GNSS positioning results.

8. A phase multipath real-time correction system based on a GNSS array antenna, characterized in that, It includes: An array antenna module is used to: construct a space-correlated array antenna system, the space-correlated array antenna system including a planar array composed of multiple antenna elements and a receiver, the spacing between adjacent antennas being 1 / 2 of the wavelength corresponding to the center frequency of the GNSS signal, and the receiver synchronously receiving multi-frequency GNSS observations from the multi-antenna array; The multi-frequency multipath modeling module is used to: select an antenna element as a reference antenna element based on the space correlation array antenna system, calculate the geometric positional relationship of other antenna elements relative to the reference antenna element, form single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element, and construct a carrier phase multipath error parameter estimation model. Based on the carrier phase multipath error parameter estimation model, the consistency of propagation paths and frequency correlation of multi-frequency GNSS signals at each frequency point are utilized to jointly process multi-frequency GNSS observations and establish a multi-frequency multipath error redundancy estimation model. The particle filter estimation module is used to: employ a particle filter algorithm to perform nonlinear estimation of the carrier phase multipath error parameters based on the multi-frequency multipath error redundancy estimation model, and obtain the multipath error parameters. The error correction and positioning module is used to: obtain the carrier phase multipath error value of each frequency point using the multipath error parameter, and correct the error value in real time in GNSS positioning calculation to obtain the GNSS positioning result after multipath correction.

9. The phase multipath real-time correction system based on GNSS array antenna as described in claim 8, characterized in that: The multi-frequency multipath modeling module is also used for: selecting an antenna element as a reference antenna element based on the spatial correlation array antenna system, calculating the geometric positional relationship of other antenna elements relative to the reference antenna element, the geometric positional relationship including distance and azimuth angle; calculating the single-difference carrier phase residual observation values ​​between different antenna elements and the reference antenna element, and constructing a carrier phase multipath error parameter estimation model based on the geometric positional relationship, the parameters in the carrier phase multipath error parameter estimation model including reflection phase value, reflection coefficient, elevation angle and azimuth angle.

10. The phase multipath real-time correction system based on a GNSS array antenna as described in claim 9, characterized in that: The carrier phase multipath error parameter estimation model is as follows: in, The observed values ​​of the single-difference carrier phase residuals between the different antenna elements and the reference antenna element. The reflection coefficient is the carrier phase multipath error. and These represent the reflected phase values ​​of the carrier phase multipath error between the reference antenna element and other antenna elements. and These represent the geometric distance and azimuth angle between the antennas, respectively. and These are the elevation angle and azimuth angle of the carrier phase multipath error, respectively.

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