Precise point positioning method and device based on single Beidou

Abstract

The invention belongs to the technical field of positioning and navigation, and discloses a precise single-point positioning method and device based on a single Beidou, and the method comprises the steps: building a three-frequency non-difference and non-combination precise single-point positioning observation model based on a Beidou satellite system, estimating the delay of an ionized layer through a non-difference and non-combination method, and extracting the electron content in a line-of-sight direction; carrying out iterative solution on the electron content in the sight line direction by using a multiplication algebraic reconstruction algorithm to obtain the electron density of the ionized layer; taking ionosphere electron density as prior information, and adding ionosphere constraint estimation to obtain a state vector of a receiver; and calculating a signal quality evaluation coefficient of the Beidou satellite system, and according to the signal quality evaluation coefficient, updating the state vector of the receiver by using a hybrid filter to obtain a final positioning position. According to the invention, high-precision regional ionosphere delay modeling and Beidou three-frequency non-difference and non-combination precision single-point positioning under ionosphere constraint are realized, and the positioning precision and robustness of a single Beidou precision single-point positioning system are effectively improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of positioning and navigation, and particularly relates to a precise point positioning method and device based on a single Beidou. BACKGROUND

[0002] Satellite navigation and positioning technology has become an infrastructure-level technology supporting the operation of the modern information society with its core advantages of all-weather, high precision, and wide coverage. It has important application value in the fields of automatic driving, intelligent agriculture, surveying and mapping, emergency rescue, etc. With continuous breakthroughs in satellite constellation networking technology, signal processing algorithms, and terminal integration technology, the application boundaries of satellite navigation and positioning are constantly expanding. From traditional industry informatization tools, it gradually upgrades to core enabling technologies for emerging fields such as smart cities, unmanned systems, and the Internet of Things. Precise Point Positioning (PPP) is a core technology in the satellite navigation and positioning system. By integrating high-precision satellite orbit and clock error products, it can achieve decimeter to centimeter level positioning accuracy with only a single receiver. Its unique advantage of not requiring ground reference stations makes it irreplaceable in wide-area seamless coverage scenarios such as ocean navigation, polar exploration, and aerial remote sensing. Compared with traditional differential positioning technology, PPP has no geographical restrictions and meets the high-precision positioning needs of complex scenarios.

[0003] However, the high-precision implementation of PPP technology highly depends on the error correction of the signal propagation path. Ionospheric delay, as a key error source affecting signal propagation speed, has become one of the core bottlenecks restricting the performance of PPP. Especially in single-Beidou system PPP, the geometric correlation of single-system observations makes ionospheric delay strongly coupled with parameters such as tropospheric delay and satellite orbit error. Traditional parameter separation algorithms are prone to error accumulation in long-arc segment solving, and the time-varying characteristics of ionosphere in dynamic scenarios further increase the difficulty of single-Beidou high-precision PPP.

[0004] In addition, the existing single Beidou navigation positioning scheme has significant limitations: such as the patent CN202510312726.7 discloses a high-precision precise point positioning method based on BDS-3, which uses a traditional ionosphere-free combination model to eliminate the influence of ionospheric delay on positioning accuracy, and lacks regional ionospheric modeling and correction mechanism; the patent CN202211513914.9 discloses a positioning method combined with reference station satellite data and terminal, which does not consider the high compatibility of Beidou multi-frequency signal structure PPP technology, and in addition, the method relies on ionospheric grid model for correction, which is contradictory to the real-time demand of the update cycle; the patent CN202411678867.2 discloses a Beidou precise point positioning method based on double-frequency combination, which uses double-frequency ionosphere-free PPP positioning model to improve positioning accuracy, but the algorithm does not fully utilize the three-frequency signals of Beidou-3, and is still limited to double-frequency combination mode, and cannot construct high-order ionospheric delay constraints through three-frequency observations. SUMMARY

[0005] In view of the problems of the above-mentioned single Beidou PPP scheme in ionospheric delay processing, Beidou multi-frequency data fusion, and regional ionospheric modeling, the present application provides a single Beidou-based precise point positioning method and device, which realizes high-precision regional ionospheric delay modeling and Beidou three-frequency undifferenced non-combination PPP under ionospheric constraints, and effectively improves the positioning accuracy and robustness of the single Beidou PPP system.

[0006] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is:

[0007] In a first aspect, a single Beidou-based precise point positioning method is provided, comprising:

[0008] A three-frequency undifferenced non-combination precise point positioning observation model based on the Beidou satellite system is established, ionospheric delay is estimated by the undifferenced non-combination method in the three-frequency undifferenced non-combination precise point positioning observation model, and the line-of-sight electron content is extracted based on the ionospheric delay;

[0009] The line-of-sight electron content is iteratively solved using a multiplication algebra reconstruction algorithm to obtain the ionospheric electron density;

[0010] The ionospheric electron density is used as prior information, and an ionospheric constraint is added to the three-frequency undifferenced non-combination precise point positioning observation model to obtain a single Beidou three-frequency undifferenced non-combination precise point positioning observation model, and the state vector of the receiver is estimated by the undifferenced non-combination method in the single Beidou three-frequency undifferenced non-combination precise point positioning observation model;

[0011] The signal quality evaluation coefficient of the Beidou satellite system is calculated, and the state vector of the receiver is updated using a hybrid filter according to the signal quality evaluation coefficient to obtain the final positioning position.

[0012] The following also provides several optional modes, but not as an additional limitation of the above general scheme, just a further supplement or preferred, without technical or logical contradictions, each optional mode can be combined alone for the above general scheme, but also can be combined between multiple optional modes.

[0013] As preferred, the three-frequency non-difference non-combination precise point positioning observation model based on the Beidou satellite system is established, comprising:

[0014] The receiver observation model for the satellite is constructed, and the receiver observation model for the satellite includes a pseudo-range observation model and a carrier phase observation model;

[0015] Based on the receiver observation model for the satellite, the inter-frequency bias is introduced, and the three-frequency non-difference non-combination precise point positioning observation model based on the Beidou satellite system B1C, B2b and B3I frequency points is constructed.

[0016] As preferred, the line-of-sight direction electron content is iteratively solved using a multiplicative algebraic reconstruction algorithm to obtain the ionospheric electron density, comprising:

[0017] The ionosphere is divided into a plurality of grids with uniform electron density distribution, and the line-of-sight direction electron content is expressed as a linear integral of electron density along the propagation path;

[0018] Based on the linear integral of electron density along the propagation path, the line-of-sight direction electron content is iteratively solved using a multiplicative algebraic reconstruction algorithm to obtain the ionospheric electron density.

[0019] As preferred, the single Beidou three-frequency non-difference non-combination precise point positioning observation model is represented as follows:

[0020]

[0021] In the formula, represents the pseudo-range change amount under the first frequency point of the Beidou satellite system, represents the carrier phase change amount under the first frequency point of the Beidou satellite system, represents the receiver direction cosine coefficient, represents the increment of the receiver coordinates, represents the speed of light, represents the corrected receiver clock bias, represents the corrected ionospheric delay, represents the tropospheric delay, represents the pseudo-range observation noise under the first frequency point of the Beidou satellite system, This indicates the BeiDou satellite system's... Ionospheric delay amplification factor at each frequency point This indicates the BeiDou satellite system's... Carrier phase ambiguity parameters at each frequency point This indicates the BeiDou satellite system's... Carrier phase observation noise at each frequency point Indicates the ionospheric delay scaling factor. This indicates the BeiDou satellite system's... The center frequency at each frequency point Indicates the path between the satellite and the receiver. Indicates in Time Receiver The observed electron density at the coordinate position. Indicates path The total number of electrons in the oblique ionosphere is obtained by integrating the electron density corresponding to the grid of the ionosphere. This indicates the BeiDou satellite system's... Observation noise of ionospheric delay at each frequency point.

[0022] Preferably, the calculation of the signal quality evaluation coefficient of the BeiDou satellite system includes:

[0023] The number of satellites, signal-to-noise ratio, multipath effect, and satellite geometric distribution are taken into account.

[0024] The signal quality evaluation coefficient is obtained by standardizing and weighting the number of satellites, signal-to-noise ratio, multipath effect, and satellite geometric distribution.

[0025] Preferably, the step of updating the receiver's state vector using a hybrid filter based on the signal quality evaluation coefficient to obtain the final positioning position includes:

[0026] If the signal quality evaluation coefficient is less than the threshold, the receiver's state vector is updated using a progressive filter, and the estimated state vector value is output; otherwise, the receiver's state vector is updated using a Kalman filter, and the estimated state vector value is output.

[0027] If the positioning error of the state vector estimate converges, the final positioning position is output based on the state vector estimate; otherwise, the signal quality evaluation coefficient of the BeiDou satellite system at the current moment is recalculated, and the iteration continues.

[0028] Preferably, the progressive filter divides the observation update process into several time intervals, and uses the P-th power of the signal quality evaluation coefficient as the total number of time intervals, where P is the attenuation factor.

[0029] As a preference, the Kalman filter adopts an improved observation noise covariance matrix, which is a product of an original observation noise covariance matrix and an adaptive factor, and the adaptive factor is negatively correlated with the signal quality evaluation coefficient.

[0030] As a preference, in the iteration process, if the filter adopted at the current time is different from that at the last time, the state vector, the covariance matrix, the filter gain, the state transition matrix and the observation matrix at the last time need to be assigned to the filter at the current time.

[0031] In a second aspect, a single-Beidou-based precise point positioning device is provided, comprising a single-Beidou satellite signal receiving module, a main control module, a storage module, an interactive module and a power management module, wherein:

[0032] The single-Beidou satellite signal receiving module is configured to receive and preprocess single-Beidou satellite signals, and send the preprocessed single-Beidou satellite signals to the main control module.

[0033] The main control module is configured to execute the single-Beidou-based precise point positioning method based on the preprocessed single-Beidou satellite signals to obtain a final positioning position.

[0034] The storage module is configured to store the single-Beidou satellite signals and the final positioning position.

[0035] The interactive module is configured to provide user interaction.

[0036] The power management module is configured to supply power to the single-Beidou satellite signal receiving module, the main control module, the storage module and the interactive module.

[0037] The single-Beidou-based precise point positioning method and device provided by the application introduce precise point positioning technology to solve the problem of few visible satellites in a single-Beidou satellite system in a complex environment, and calculate satellite signal quality in real time, use an adaptive progressive filtering algorithm for dynamic calculation, and can dynamically switch the filtering mode according to the satellite signal quality. This adaptive mechanism enables the system to maintain good positioning performance in different satellite signal environments, whether in open areas or in signal-shielded areas such as urban canyons, and can flexibly respond, ensuring positioning efficiency and accuracy while having stronger environmental adaptability. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 The flowchart of the single-Beidou-based precise point positioning method of the application;

[0039] Figure 2 The flowchart of filtering based on the signal quality evaluation coefficient;

[0040] Figure 3 This is a schematic diagram of the structure of the precision single-point positioning device based on a single Beidou system according to the present invention;

[0041] Figure 4 This is a schematic diagram of the structure of the single Beidou satellite signal receiving module in the single Beidou-based precision single-point positioning device of the present invention;

[0042] Figure 5 This is a schematic diagram of the integrated circuit for the precision single-point positioning device based on a single Beidou system according to the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to limit the invention.

[0045] Example 1:

[0046] like Figure 1 As shown, this embodiment provides a precise point positioning method based on a single BeiDou system, specifically including the following steps:

[0047] Step 1: Based on the B1C, B2b, and B3I frequencies of the BeiDou satellite system, establish a three-frequency non-differential non-combined precise single-point positioning observation model based on the BeiDou satellite system. In the three-frequency non-differential non-combined precise single-point positioning observation model, estimate the ionospheric delay using the non-differential non-combined method. Based on the ionospheric delay, use the DCB file of the satellite end published by IGS to correct the code deviation and extract the line-of-sight electron content (Slant Total Electron Content, STEC).

[0048] Specifically, it receives raw observation data as well as precise ephemeris and precise clock bias data required for precise point positioning. All observation data comes from the BeiDou satellite system, eliminating the need for satellite system filtering and inter-system bias handling during data processing. In ionospheric and tropospheric delay corrections, as well as satellite clock bias and orbital parameter processing, only the BeiDou satellite system model needs to be considered. An observation model is constructed based on the principles of precise point positioning, and the receiver... For satellites The observation model can be expressed as:

[0049]

[0050] wherein denotes the receiver for the satellite , the pseudorange observation, denotes the satellite to the receiver , the geometric distance, which is calculated by the Euclidean distance formula from the three-dimensional position coordinates of the satellite and the three-dimensional position coordinates of the receiver. is the speed of light, is the clock error of the receiver , is the clock error of the satellite , is the ionospheric delay of the satellite to the receiver , is the tropospheric delay of the satellite to the receiver , is the pseudorange observation noise, denotes the receiver for the satellite , the carrier phase observation, denotes the ionospheric delay amplification factor, denotes the hardware delay of the satellite , denotes the hardware delay of the receiver , is the wavelength of the carrier signal, is the integer ambiguity, is the carrier phase observation noise.

[0051] Since the differential code bias of the BeiDou triple-frequency undifferenced non-combined pseudorange cannot be absorbed by the ionospheric parameter, the inter-frequency bias needs to be introduced in the triple-frequency undifferenced non-combined PPP observation model established based on the BeiDou satellite system B1C, B2b and B3I frequency points , so that the triple-frequency undifferenced non-combined PPP observation model can be expressed as:

[0052]

[0053] wherein , and are the pseudorange change amounts of the BeiDou satellite system B1C, B2b and B3I frequency points; , and are the carrier phase change amounts of the BeiDou satellite system B1C, B2b and B3I frequency points; , 、 and 、 、 represents the pseudo-range observation noise and carrier phase observation noise under the B1C, B2b and B3I frequency points of the Beidou satellite system; and represents the ionospheric delay amplification factor of B2b and B3I; 、 and represents the ambiguity parameter of the carrier phase of the Beidou B1C, B2b and B3I frequency points after the non-difference non-combination correction; represents the increment of the receiver coordinates; represents the receiver direction cosine coefficient; represents the receiver clock error after the correction of the three-frequency non-difference non-combination PPP observation model; represents the ionospheric delay after the correction of the three-frequency non-difference non-combination PPP observation model; represents the pseudo-range differential code bias introduced in the establishment of the three-frequency non-difference non-combination PPP observation model.

[0054] Under the three-frequency non-difference non-combination PPP observation model, the state vector to be solved is:

[0055]

[0056] In the formula, 、 、 respectively represent the deviation of the actual position of the receiver from the estimated position; represents the deviation of the actual clock error of the receiver from the estimated clock error.

[0057] In the three-frequency non-difference non-combination PPP observation model, the ionospheric delay estimated by the non-difference non-combination method After stripping the satellite end code bias through the differential code bias (DCB) product, the line-of-sight electron content :

[0058]

[0059] wherein represents the slant ionospheric electron content of the i-th observation.

[0060] Step 2, the line-of-sight electron content is iteratively solved using the multiplication algebra reconstruction algorithm to obtain the ionospheric electron density.

[0061] ​Based on the three-dimensional ionosphere assumption, the ionosphere is divided into several grids with uniform electron density distribution, and the line-of-sight electron content which can be expressed as a linear integral of electron density along the propagation path, and after discretization, it is:

[0062]

[0063] wherein represents the total number of grids divided, represents the total number of observations, represents the intercept matrix of the satellite signal passing through the grid, represents the electron density matrix of the grid.

[0064] Therefore, the line-of-sight electron content Using the iterative solution of the multiplication algebraic reconstruction algorithm, the ionospheric electron density can be obtained:

[0065]

[0066] wherein represents the electron density of the th grid after the th iteration, represents the relaxation factor, represents the th row of the intercept matrix, represents the element of the th row and th column of the intercept matrix.

[0067] Step 3, taking the ionospheric electron density as prior information, adding ionospheric constraints to the three-frequency undifferenced non-combined precise point positioning observation model to obtain a single Beidou three-frequency undifferenced non-combined precise point positioning observation model, and estimating the state vector of the receiver in the single Beidou three-frequency undifferenced non-combined precise point positioning observation model by the undifferenced non-combined method.

[0068] Using the ionospheric electron density estimated in advance to construct a regional ionospheric model, adding a virtual observation equation, and using the single Beidou three-frequency undifferenced non-combined PPP positioning with ionospheric constraints as prior information, the observation model can be expressed as:

[0069]

[0070] wherein represents the pseudo-range change of the th frequency of the Beidou satellite system, represents the carrier phase change of the th frequency of the Beidou satellite system, represents the receiver direction cosine coefficient, This represents the increment of the receiver coordinates. Represents the speed of light. This indicates the corrected receiver clock bias. This indicates the corrected ionospheric delay. Indicates tropospheric delay, This indicates the BeiDou satellite system's... pseudorange observation noise at each frequency point This indicates the BeiDou satellite system's... Ionospheric delay amplification factor at each frequency point This indicates the BeiDou satellite system's... Carrier phase ambiguity parameters at each frequency point This indicates the BeiDou satellite system's... Carrier phase observation noise at each frequency point Indicates the ionospheric delay scaling factor. This indicates the BeiDou satellite system's... The center frequency at each frequency point Indicates the path between the satellite and the receiver. Indicates in Time Receiver The observed electron density at the coordinate position. Indicates path The total number of electrons in the oblique ionosphere is obtained by integrating the electron density corresponding to the grid of the ionosphere. This indicates the BeiDou satellite system's... Observation noise of ionospheric delay at each frequency point.

[0071] Under the single BeiDou three-frequency non-differential non-combined precise single-point positioning observation model, the state vector to be solved is... for:

[0072]

[0073] In the formula for , as well as The combination of represents the carrier phase ambiguity vector.

[0074] Step 4: Calculate the signal quality evaluation coefficient of the BeiDou satellite system. Based on the signal quality evaluation coefficient, use a hybrid filter to update the receiver's state vector to obtain the final positioning position.

[0075] like Figure 2 As shown, this embodiment first calculates the signal quality evaluation coefficient by combining the number of visible satellites, signal-to-noise ratio, multipath effect, and satellite geometric distribution factors. The method for calculating the signal quality evaluation coefficient of the BeiDou satellite system is expressed by the following formula:

[0076]

[0077] in It is a satellite signal quality evaluation coefficient; It is the number of satellites received. This is the maximum number of satellites that can be received. This parameter reflects the redundancy of available satellites at the current moment. For the first The signal-to-noise ratio of a satellite is used to characterize the signal strength and the degree of noise interference. It is the first The multipath effect of a single satellite can quantify errors caused by non-line-of-sight propagation such as signal reflection and diffraction. It is a measure of the geometric distribution of satellites, which can reflect the rationality of the spatial distribution of satellites; , , , These represent the weighting coefficients for the number of satellites, signal-to-noise ratio, multipath effect, and satellite geometric distribution, respectively.

[0078] For hybrid filters, construct the current State vector at time step as follows:

[0079]

[0080] In the formula express The deviation between the actual position and the estimated position of the time receiver. express Receiver clock bias after time correction express Time-corrected ionospheric delay express Time Satellite to receiver tropospheric delay, express The carrier phase ambiguity vector at any given time.

[0081] Based on the dynamic model of the positioning device, its filter's state prediction equation and observation equation can be described as follows:

[0082]

[0083] In the formula express The prior state vector at time t. express The prior state vector at time t. is a state transition matrix, describing the change relationship of state from to , and its initial value is a unit matrix; is a process noise vector at , obeying a Gaussian distribution with expectation 0 and covariance ; is an observation vector at ; is an observation matrix at , corresponding to the change relationship between state and observation; is an observation noise vector at , obeying a Gaussian distribution with expectation 0 and covariance .

[0084] The embodiment introduces a hybrid filter to perform state estimation, and the hybrid filter is executed by different filters according to a signal quality evaluation coefficient. If the signal quality evaluation coefficient is less than a threshold value, an asymptotic filter is used to update the state vector of the receiver, and a state vector estimation value is output. Otherwise, a Kalman filter is used to update the state vector of the receiver, and a state vector estimation value is output. If the positioning error of the state vector estimation value converges, a final positioning position is output according to the state vector estimation value. Otherwise, the signal quality evaluation coefficient of the Beidou satellite system at the current time is recalculated, and iteration is continued. Specifically as follows:

[0085] (1) When the obtained evaluation coefficient is less than a set threshold value, an asymptotic filter is used to update the state vector, and a time sequence is introduced to represent the asymptotic process. The observation update process is divided into time intervals, and a signal quality evaluation coefficient is introduced to dynamically adjust, so there is:

[0086]

[0087] In the formula, is a satellite signal quality evaluation coefficient, is a decay factor.

[0088] According to the Bayesian rule, the update process of the asymptotic probability density function from the asymptotic time sequence to can be expressed as:

[0089]

[0090] Wherein represents a probability density function, represents the time sequence value of the th asymptotic update, represents the time sequence value of the th asymptotic update.time series values of the nth order of approximation update, denotes a set of observations at time instant, denotes a set of observations at time instant.

[0091] The observation information is gradually incorporated to achieve the effect of step-by-step update, the first order of approximation process The prediction observation value in the nth order of approximation process can be described as:

[0092]

[0093] In the formula denotes the change relationship between the state and the observation value; is the joint probability density function in the nth order of approximation process, is the posterior probability density function in the nth order of approximation process, denotes the posterior probability density function in the nth order of approximation process; denotes the posterior probability density function in the nth order of approximation process; and respectively denote the predicted state vector and the predicted covariance matrix in the nth order of approximation process; denotes the joint Gaussian distribution in the nth order of approximation process. Since the system assumes that the joint probability density function between the state and the measurement in the positioning process follows a Gaussian distribution, the posterior probability density function of the state , denotes the joint Gaussian distribution in the nth order of approximation process. The observation covariance in the nth order of approximation process can be expressed as: The observation covariance in the nth order of approximation process

[0094] The observation covariance in the nth order of approximation process can be expressed as:

[0095]

[0096] In the formula denotes the predicted observation value in the nth order of approximation process, denotes the first-order Taylor expansion expression of the matrix form of in the nth order of approximation process is the updated covariance in the nth order of approximation process. Similarly, the cross-covariance of the state and the measurement in the nth order of approximation process

[0097] Similarly, the cross-covariance of the state and the measurement in the nth order of approximation process ​​​​​​​It can be represented as:

[0098]

[0099] In the formula express The prior state vector in the asymptotic process.

[0100] According to the definition of the update equation for the posterior state estimation, the th The state vector is updated gradually. It can be described as:

[0101]

[0102] in, Indicates the first The filter gain of each asymptotic update can be described as:

[0103]

[0104] In the formula Indicates the first The cross-covariance of states and measurements in the sub-asymptotic process. Indicates the first Observational covariance in the asymptotic process.

[0105] According to the definition of covariance, we can obtain the... The covariance of the next asymptotic update It can be described as:

[0106]

[0107] Therefore, the filter update process can be described as follows:

[0108]

[0109] (2) When the calculated evaluation coefficient is greater than or equal to the set threshold, the Kalman filter is used to estimate the state vector. The state vector is directly estimated, and the prediction part can be expressed as:

[0110]

[0111] In the formula as well as They represent State prediction and covariance prediction at time points. It is a state transition matrix, describing the transition from state to state. Time's up The relationship of change over time, express The posterior state vector at time t. denotes the posterior covariance matrix of the time instant.

[0112] The filter update process is to use the observation value of the current time instant to correct the predicted state to obtain a more accurate state estimate value , so the update formula of the estimate value can be defined as:

[0113]

[0114] wherein is the filter gain at the time instant; and are the state vector and the covariance matrix updated by the Kalman filter at the time instant, is the covariance matrix before updating at the time instant, is the unit matrix, denotes the observation matrix, corresponding to the change relationship between the state and the observation. The satellite mass evaluation coefficient is introduced to construct an adaptive factor , the adaptive factor and the signal quality evaluation coefficient are negatively correlated:

[0115]

[0116] wherein and

[0117] are the preset coefficients. The observation noise covariance matrix is dynamically adjusted , so the adaptive improved observation noise covariance matrix

[0118] at the time instant can be expressed as:

[0119] Therefore, it is updated by the update part of the Kalman filter, and the process can be described as:

[0120]

[0121]

[0122] ​​​In the implementation of step 4, if the evaluation coefficient is less than the threshold value, it indicates that the satellite signal quality is poor, and the progressive filtering method is used to gradually introduce part of the observation information to update the state and covariance at each iteration. If the evaluation coefficient is greater than or equal to the threshold value, it indicates that the satellite signal quality is good, and the Kalman filter method is used to update the state using the observation information. During the iteration process of step 4, the filter state at the last time is judged. If the filter used at the current time is different from that at the last time, the state vector, covariance matrix, filter gain, state transition matrix, and observation matrix at the last time are assigned to the filter at the current time; otherwise, the filter processing is directly continued without assignment. After obtaining the updated state, the iteration is updated until the error level converges, and the final state vector is output. The final position residual (x, y, h) is extracted from the final state vector, and the final positioning position is obtained by superimposing the final positioning position (x, y, h) and the initial positioning position (x0, y0, h0). )and the initial positioning position (x0, y0, h0).

[0123] Example 2:

[0124] As shown in Figure 3 , the present embodiment provides a single Beidou-based precise point positioning device, which comprises a single Beidou satellite signal receiving module, a main control module, a storage module, an interactive module, and a power management module.

[0125] The single Beidou satellite signal receiving module is built with UMD982 of Hand Chip Star as the core, and its internal structure diagram is shown in Figure 4 . It comprises a radio frequency module and a data processing module, and receives the original signals transmitted by Beidou satellites through a Beidou BT-800D satellite antenna, which can support the reception of Beidou B1I / B1C / B2I / B2A / B2B / B3I frequency band signals. After the signal is amplified by a low-noise amplifier, it is filtered and down-converted to an intermediate frequency signal. The intermediate frequency signal is sampled by an ADC (Analog to Digital Converter) to convert the satellite signal from the analog domain to the digital domain. The data processing module captures and tracks the signals processed by the radio frequency module. On the one hand, it outputs raw observation data including satellite pseudorange, carrier phase measurement, etc. On the other hand, the module can also receive the orbit and clock error correction information of the satellite navigation system broadcast by PPP-B2b, so as to obtain precise clock error, precise ephemeris, and ionospheric and tropospheric correction parameters, etc., providing data basis for single Beidou precise point positioning. The single Beidou satellite signal receiving module is connected with the main control module through a serial port to realize data transmission.

[0126] The main control module uses an STM32H743VIT6 processor to build a precise point positioning solution (i.e., to perform the single-Beidou-based precise point positioning method described in Embodiment 1) and control the storage module and the interaction module. The main control module establishes a connection with the single-Beidou satellite signal receiving module through a serial port and realizes data reading and analysis, reads the data transmitted by the receiving module in real time, converts the data into information required for precise point positioning, such as pseudorange, carrier phase, precise clock difference, precise satellite orbit, ionospheric and tropospheric correction parameters, and places the information in the corresponding buffer area, and sets the original data buffer area to 1MB ring buffer area; a 256KB SRAM special area is set in the main control module to deploy the precise point positioning algorithm, and real-time positioning solution is performed in combination with the analyzed data. In the subsequent positioning solution process, an adaptive progressive filtering algorithm is used for dynamic solution, and the filtering algorithm can update the state variables in real time; the main control module receives instructions and setting information input by the user through the interaction module in real time. These data are judged, and the output settings and storage settings of the system are switched according to different instructions and setting information; the main control module can transmit the raw data, ephemeris, and positioning results obtained by positioning solution, etc. read from the single-Beidou satellite signal receiving module to the storage module according to the setting information.

[0127] The interaction module uses a 6x6 horizontal key and a patch LED-MMBT3904 to build a system function setting and system state description, so that the user can control whether the system stores positioning data through the key, and select a specified data output format in a preset format; the user can understand whether the system is in a data storage, satellite signal receiving, etc. state through the LED array of the system.

[0128] The storage module realizes the data storage and setting saving function of the system, uses SanDisk SD card as the storage medium, has a large storage capacity, and is used for long-term storage of raw observation, satellite ephemeris, and positioning solution results. The W25Q128-Flash chip is used to save the configuration after the user changes the system settings using the interaction module.

[0129] The power management module realizes power supply for the precise point positioning device and ensures the normal work of each module. The device is powered by a format 12V model airplane battery, uses a DC-DC converter SY8303AIC to generate 5V power supply, and uses an RT9133 to generate 3.3V power supply.

[0130] As shown in Figure 5 The single-Beidou-based precise point positioning device of the embodiment is a hardware device built based on an embedded platform, integrates a single-Beidou satellite signal receiving module, a main control module, a storage module, an interaction module, and a power management module, and has reasonable hardware design and high function integration.

[0131] Each technical feature of the above-described embodiments can be combined with any other technical feature, and for the sake of brevity, not all possible combinations are described, but it is understood that the scope of the present disclosure encompasses all such possible combinations.

[0132] The above-described embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the application. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of the present application. Therefore, the scope of protection of the present application should be subject to the appended claims.

Claims

1. A single-Beidou-based precise point positioning method, characterized in that, The precise point positioning method based on a single BeiDou system includes: A three-frequency non-differential non-combined precise single-point positioning observation model based on the BeiDou satellite system was established. In the three-frequency non-differential non-combined precise single-point positioning observation model, the ionospheric delay was estimated by the non-differential non-combined method, and the electron content in the line-of-sight direction was extracted based on the ionospheric delay. The electron content along the line of sight is iteratively solved using a multiplicative algebraic reconstruction algorithm to obtain the ionospheric electron density. Using ionospheric electron density as prior information, ionospheric constraints are added to the three-frequency non-differential non-combined precise single-point positioning observation model to obtain a single Beidou three-frequency non-differential non-combined precise single-point positioning observation model. The receiver's state vector is estimated in the single Beidou three-frequency non-differential non-combined precise single-point positioning observation model by non-differential non-combined method. Calculate the signal quality evaluation coefficient of the BeiDou satellite system, and update the receiver's state vector using a hybrid filter based on the signal quality evaluation coefficient to obtain the final positioning position.

2. The single-BeiDou-based precise point positioning method according to claim 1, characterized in that, The establishment of a three-frequency, non-differential, non-combined, precise single-point positioning observation model based on the BeiDou satellite system includes: Construct a receiver observation model for the satellite, which includes a pseudorange observation model and a carrier phase observation model; Based on the receiver's observation model of the satellite, inter-frequency bias is introduced to construct a three-frequency non-differential non-combined precise single-point positioning observation model based on the B1C, B2b, and B3I frequencies of the BeiDou satellite system.

3. The single-BeiDou-based precise point positioning method according to claim 1, wherein, The step of iteratively solving for the electron content along the line of sight using a multiplicative algebraic reconstruction algorithm to obtain the ionospheric electron density includes: The ionosphere is divided into several grids with uniform electron density distribution, and the electron content along the line of sight is expressed as a linear integral of the electron density along the propagation path. The electron density of the ionosphere is obtained by iteratively solving the electron content in the line-of-sight direction using a multiplicative algebraic reconstruction algorithm based on the linear integral of the electron density along the propagation path.

4. The single-BeiDou-based precise point positioning method according to claim 1, wherein, The single-BeiDou three-frequency non-differential non-combined precise single-point positioning observation model is expressed as follows: In the formula, This indicates the BeiDou satellite system's... pseudorange variation at each frequency point This indicates the BeiDou satellite system's... Carrier phase change at each frequency point This represents the receiver's direction cosine coefficient. This represents the increment of the receiver coordinates. Represents the speed of light. This indicates the corrected receiver clock bias. This indicates the corrected ionospheric delay. Indicates tropospheric delay, This indicates the BeiDou satellite system's... pseudorange observation noise at each frequency point This indicates the BeiDou satellite system's... Ionospheric delay amplification factor at each frequency point This indicates the BeiDou satellite system's... Carrier phase ambiguity parameters at each frequency point This indicates the BeiDou satellite system's... Carrier phase observation noise at each frequency point Indicates the ionospheric delay scaling factor. This indicates the BeiDou satellite system's... The center frequency at each frequency point Indicates the path between the satellite and the receiver. Indicates in Time Receiver The observed electron density at the coordinate position. Indicates path The total number of electrons in the oblique ionosphere is obtained by integrating the electron density corresponding to the grid of the ionosphere. This indicates the BeiDou satellite system's... Observation noise of ionospheric delay at each frequency point.

5. The single-BeiDou-based precise point positioning method according to claim 1, wherein, The calculation of the signal quality evaluation coefficient of the BeiDou satellite system includes: The number of satellites, signal-to-noise ratio, multipath effect, and satellite geometric distribution are taken into account. The signal quality evaluation coefficient is obtained by standardizing and weighting the number of satellites, signal-to-noise ratio, multipath effect, and satellite geometric distribution.

6. The single-BeiDou-based precise point positioning method according to claim 1, wherein, The step of updating the receiver's state vector using a hybrid filter based on signal quality evaluation coefficients to obtain the final positioning location includes: If the signal quality evaluation coefficient is less than the threshold, the receiver's state vector is updated using a progressive filter, and the estimated state vector value is output; otherwise, the receiver's state vector is updated using a Kalman filter, and the estimated state vector value is output. If the positioning error of the state vector estimate converges, the final positioning position is output based on the state vector estimate; otherwise, the signal quality evaluation coefficient of the BeiDou satellite system at the current moment is recalculated, and the iteration continues.

7. The single-BeiDou-based precise point positioning method according to claim 6, wherein, The progressive filter divides the observation update process into several time intervals, and uses the P-th power of the signal quality evaluation coefficient as the total number of time intervals, where P is the attenuation factor.

8. The single-BeiDou-based precise point positioning method according to claim 6, wherein, The Kalman filter adopts an improved observation noise covariance matrix which is a product of an original observation noise covariance matrix and an adaptive factor, and the adaptive factor is negatively correlated with a signal quality evaluation coefficient.

9. The single-BeiDou-based precise point positioning method according to claim 6, wherein, In the iteration process, if the filter used at the current time is different from that used at the last time, the state vector, covariance matrix, filter gain, state transition matrix and observation matrix at the last time need to be assigned to the filter at the current time.

10. A single-Beidou-based precise point positioning device, characterized in that, The single-Beidou-based precise point positioning device comprises a single-Beidou satellite signal receiving module, a main control module, a storage module, an interactive module and a power management module, wherein: The single-Beidou satellite signal receiving module is used for receiving and preprocessing single-Beidou satellite signals and sending the preprocessed single-Beidou satellite signals to the main control module; The main control module is used for executing the single-Beidou-based precise point positioning method according to any one of claims 1-9 based on the preprocessed single-Beidou satellite signals to obtain a final positioning position; The storage module is used for storing the single-Beidou satellite signals and the final positioning position; The interactive module is used for providing user interaction; The power management module is used for powering the single-Beidou satellite signal receiving module, the main control module, the storage module and the interactive module.

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