Ionospheric parameter determination method based on user crowdsourcing data

Abstract

The embodiment of the application discloses a method for determining ionospheric parameters based on user crowdsourcing data, and relates to the technical field of satellite navigation and positioning. The method comprises the following steps: acquiring ionospheric data uploaded by multiple user terminals, taking each user terminal as a target station, calculating the standardized residual error corresponding to each user terminal by using the Kriging interpolation method, and eliminating the user terminal whose standardized residual error is greater than the standardized residual error threshold; determining the target grid corresponding to each user terminal on the pre-constructed Q4DIM network, calculating the slant path ionospheric delay corresponding to the target grid, and extracting the slant path ionospheric delay corresponding to the target grid and sending it to the user terminal according to the target grid corresponding to the user terminal. The ionospheric data uploaded by the user terminal in real time can improve the resolution of the ionospheric data, expand the coverage range of the ionospheric product, broadcast accurate ionospheric data to the user terminal, and improve the rapid positioning accuracy of the user terminal far away from the reference station.

Description

Technical Field

[0001] This application relates to the field of satellite navigation and positioning technology, and in particular to a method for determining ionospheric parameters based on user crowdsourced data. Background Technology

[0002] Precise Point Positioning (PPP) can provide centimeter-level positioning to a large number of single-receiver users worldwide simultaneously. However, even with ambiguity resolution (AR) methods (such as correcting phase deviations using uncalibrated phase delay (UPD) products), PPP still requires a long convergence time. This phenomenon is mainly due to insufficient corrections for ionospheric delay or low-precision modeling, which disrupts the integer properties of ambiguity parameters.

[0003] By introducing ionospheric corrections derived from a reference station network, Precise Point Positioning-Real-Time Kinematic (PPP-RTK) can be constructed, taking into account ionospheric constraints, achieving high-precision, fast, and even instantaneous convergence positioning enhancement. Clearly, the effectiveness of ionospheric corrections directly impacts PPP-RTK performance. However, currently, obtaining ionospheric corrections relies on base stations, making it difficult to obtain accurate ionospheric corrections in areas with sparse base station deployment.

[0004] Therefore, there is currently a lack of a method that can accurately provide ionospheric delay to achieve high-precision PPP-RTK services. Summary of the Invention

[0005] This application provides a method for determining ionospheric parameters based on user crowdsourced data, to address the shortcomings of the aforementioned related technologies. The technical solution is as follows:

[0006] In a first aspect, embodiments of this application provide a method for determining ionospheric parameters based on user crowdsourced data, applied to a cloud server, the method comprising:

[0007] Acquire ionospheric data uploaded by multiple user terminals; the ionospheric data includes ionospheric delay along a slant path collected by the user terminal and the corresponding line-of-sight direction information;

[0008] The standardized residual of the slant path ionospheric delay for each user terminal was calculated using Kriging interpolation, and user terminals with standardized residuals greater than the standardized residual threshold were removed.

[0009] The target grid corresponding to each user terminal on the pre-built Q4DIM network is determined based on the retained user terminal's line-of-sight information;

[0010] Obtain the slant path ionospheric delay of each user terminal located on the same target grid, and use the average slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay of the corresponding target grid.

[0011] Based on the target grid corresponding to each user terminal, the slant path ionospheric delay of the corresponding target grid is extracted and sent to the corresponding user terminal.

[0012] In one alternative embodiment of the first aspect, the step of the user terminal collecting ionospheric data includes:

[0013] The distance between the user terminal and the satellite is calculated based on the initial coordinates of each user terminal and the precision satellite orbit product. The satellite clock error correction, tropospheric dry delay correction, satellite pseudorange hardware delay correction, and satellite phase hardware delay correction are also calculated.

[0014] The basic observation equations of GNSS are corrected based on the satellite clock error correction, the tropospheric dry delay correction, the satellite pseudorange hardware delay correction, and the satellite phase hardware delay correction. The oblique ionospheric delay, which eliminates the user-end pseudorange hardware delay and the user-end phase hardware delay, is calculated by Kalman filtering, and the line-of-sight direction information is calculated.

[0015] Gross error detection is performed on the slant path ionospheric delay of each user terminal, and user terminals that meet the preset conditions are removed;

[0016] The calculated line-of-sight direction information and the oblique path through the ionosphere delay are uploaded to the cloud server through the retained user terminal.

[0017] In one alternative of the first aspect, the gross error detection of the slant-to-ionospheric delay for each user terminal includes:

[0018] Obtain the ionospheric delay duration corresponding to the slant path ionospheric delay for each user terminal;

[0019] Obtain the sloping ionospheric delay of each user terminal and the sloping ionospheric delay of a preset number of surrounding user terminals, and calculate the ionospheric delay residual and ionospheric delay variance between the sloping ionospheric delays of each user terminal.

[0020] The process of removing user terminals that meet preset conditions includes:

[0021] If the duration of the ionospheric delay is greater than or equal to the duration threshold, and the residual of the ionospheric delay is less than or equal to the residual threshold of the ionospheric delay, and the variance of the ionospheric delay is less than or equal to the variance threshold of the ionospheric delay, then the sloping ionospheric delay of the user terminal is determined to be a valid sloping ionospheric delay.

[0022] Obtain all valid slant ionospheric delays for each user terminal within a single epoch;

[0023] If the number of valid slant-to-ionospheric delays for a user terminal within a single epoch is less than a threshold, then the corresponding user terminal is removed.

[0024] In one alternative embodiment of the first aspect, the step of calculating the standardized residual of the slant path ionospheric delay for each user terminal using Kriging interpolation and removing user terminals whose standardized residuals are greater than a standardized residual threshold includes:

[0025] Each user terminal is taken as the target station, and user terminals within a preset range centered on each target station are selected as neighboring reference stations. Kriging interpolation is performed based on the neighboring reference stations to calculate the weight of each neighboring reference station.

[0026] The ionospheric prediction data and prediction variance of the target station are calculated by weighting each adjacent reference station and the corresponding slant path ionospheric delay.

[0027] The prediction residual is calculated based on the difference between the slant path ionospheric delay of the target station and the ionospheric prediction data. The standardized residual of the target station is then calculated based on the prediction variance and the prediction residual.

[0028] Obtain the ionospheric deviation data sequence composed of the standardized residuals of each user terminal, and remove user terminals in the ionospheric deviation data sequence that are greater than the standardized residual threshold.

[0029] In one alternative to the first aspect, the standardized residual threshold is determined based on the following steps:

[0030] Obtain the sequence of slant path ionospheric delay collected by each user terminal within a preset sliding window;

[0031] The median absolute deviation of the ionospheric deviation data sequence is calculated using the following formula:

[0032] ;

[0033] The standardized residual threshold is determined based on the median absolute deviation.

[0034] in, The absolute deviation of the median. Let r be the ionospheric deviation data sequence, and r be the sequence of slant path ionospheric delays collected by each user terminal within the preset sliding window. This is a function used to calculate the median.

[0035] In one alternative embodiment of the first aspect, after acquiring the ionospheric data uploaded by multiple user terminals, the method further includes:

[0036] Based on the time of the ionospheric data collected by each user terminal, the user terminals that fall within the same time period are determined, and the ionospheric data collected by each user terminal is mapped to the ionospheric puncture point at a preset height.

[0037] In one alternative of the first aspect, the line-of-sight direction information includes the longitude, latitude, azimuth, and elevation angle of the ionospheric puncture point connecting the user terminal and the satellite.

[0038] The step of determining the target mesh corresponding to each user terminal on the pre-built Q4DIM network based on the retained user terminal's line-of-sight information includes:

[0039] Calculate the Euclidean distance between each user terminal and each grid on the Q4DIM network based on the line-of-sight information of each user terminal, using the formula:

[0040] ;

[0041] The grid with the smallest Euclidean distance to each user terminal is determined as the target grid corresponding to the user terminal on the pre-constructed Q4DIM network;

[0042] in, Let los be the set of gaze direction information for k users, where the superscript los represents the gaze direction information and the subscript k represents the ordinal number of the user in the set. For each mesh on the Q4DIM network, The coordinates on the four-dimensional coordinate system of the Q4DIM network are The grid, where the superscript grid indicates a Q4DIM network, and the subscript... The grid represents four-dimensional coordinates, where g represents latitude, h represents longitude, m represents altitude, and n represents azimuth; argmin is a function used to find the minimum value. It is the Euclidean norm; For each user terminal, a set of target grids. The four-dimensional coordinates of the target grid are u, v, x, and y. u represents latitude, v represents longitude, x represents altitude, and y represents azimuth.

[0043] Secondly, embodiments of this application also provide an ionospheric parameter determination device based on user crowdsourced data, comprising:

[0044] The data acquisition unit is used to acquire ionospheric data uploaded by multiple user terminals; the ionospheric data includes slant path ionospheric delay and corresponding line-of-sight information collected by the user terminals.

[0045] The gross error removal unit is used to calculate the standardized residual of the slant path ionospheric delay for each user terminal using Kriging interpolation, and remove user terminals whose standardized residual is greater than the standardized residual threshold.

[0046] The grid computing unit is used to determine the target grid corresponding to each user terminal on the pre-built Q4DIM network based on the retained user terminal's line-of-sight information;

[0047] The grid computing unit is also used to obtain the slant path ionospheric delay of each user terminal located on the same target grid, and use the average value of the slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay of the corresponding target grid.

[0048] The data transmission unit is used to extract the slant path ionospheric delay of the target grid corresponding to each user terminal and send it to the corresponding user terminal.

[0049] Thirdly, embodiments of this application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method provided by the first aspect or any implementation thereof of the embodiments of this application.

[0050] Fourthly, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided by the first aspect of the embodiments of this application or any implementation thereof.

[0051] The beneficial effects of the technical solutions provided in some embodiments of this application include at least the following:

[0052] This application provides a method for determining ionospheric parameters based on user crowdsourced data. It utilizes crowdsourcing to collect multiple ionospheric data uploaded from various user terminals, reducing the cost of ionospheric data acquisition and allowing for more flexible acquisition of ionospheric data over a wider area. This expands the sources of ionospheric data and avoids the difficulty in obtaining accurate ionospheric data in some areas due to sparse distribution of ground measurement stations. By combining the Q4DIM network with real-time ionospheric data uploaded by user terminals, the resolution of ionospheric data can be improved, expanding the coverage of ionospheric products. The cloud server can broadcast accurate ionospheric data to user terminals, improving the rapid positioning accuracy of users far from the base station. Simultaneously, it enables ionospheric monitoring, thus providing data support for PPP-RTK positioning to achieve precise positioning. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart illustrating a method for determining ionospheric parameters based on user crowdsourced data, provided in an embodiment of this application.

[0055] Figure 2 This is a schematic diagram of the structure of a Q4DIM network for a method of determining ionospheric parameters based on user crowdsourced data, provided in an embodiment of this application.

[0056] Figure 3 This is a schematic diagram of the structure of an ionospheric parameter determination device based on user crowdsourced data provided in an embodiment of this application;

[0057] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0059] 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 modules is not limited to the steps or modules listed, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to such process, method, product, or apparatus.

[0060] It should be noted that the terms "first" and "second" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that "first" and "second" can be interchanged in a specific order or sequence where permitted. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in an order other than those described or illustrated herein.

[0061] It should be noted that obtaining ionospheric corrections generally involves two processes: 1) extracting corrections based on the reference station network; and 2) calculating user-specific corrections. Global Ionosphere Map (GIM) products can provide prior information on ionospheric constraints, but the PPP positioning results obtained in this way have low accuracy and cannot meet the accuracy requirements of PPP-RTK positioning. To calculate user-specific corrections, PPP positioning can be performed synchronously in the regional reference station network to generate accurate slant ionospheric delays (SIDs) along the line-of-sight direction for each reference station, and then spatial interpolation methods can be used to calculate the user-specific corrections. Positioning accuracy is positively correlated with interpolation accuracy, and interpolation accuracy depends on the inter-station distance of the reference station network. In areas lacking reference station coverage, high-precision PPP-RTK services cannot be achieved.

[0062] This application adopts a crowdsourcing approach, using user terminals such as smartphones and cars equipped with high-precision positioning functions as reference stations. By leveraging the characteristics of these crowdsourced data, such as real-time performance, high precision, high-density spatial aggregation in densely populated areas, and wide environmental distribution, it is possible to obtain ionospheric data with broad coverage and higher resolution, thereby achieving high-precision ionospheric data acquisition.

[0063] The present application will now be described in detail with reference to specific embodiments.

[0064] Next, combine Figure 1 Taking the execution of an ionospheric parameter determination method based on user crowdsourced data on a cloud server as an example, this application introduces a method for determining ionospheric parameters based on user crowdsourced data provided in its embodiments. For details, please refer to... Figure 1 , Figure 1This illustration shows a flowchart of a method for determining ionospheric parameters based on user crowdsourced data, provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0065] S101, acquire ionospheric data uploaded by multiple user terminals;

[0066] S102, calculate the standardized residual of the slant path ionospheric delay for each user terminal using the Kriging interpolation method, and remove user terminals whose standardized residual is greater than the standardized residual threshold.

[0067] S103, determine the target grid corresponding to each user terminal on the pre-built Q4DIM network based on the retained user terminal's line of sight direction information;

[0068] S104, obtain the slant path ionospheric delay of each user terminal located on the same target grid, and use the average value of the slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay of the corresponding target grid.

[0069] S105: Based on the target grid corresponding to each user terminal, extract the slant path ionospheric delay of the corresponding target grid and send it to the corresponding user terminal.

[0070] Specifically, in S101, the user terminal includes, but is not limited to, various electronic devices and vehicles with GNSS positioning capabilities, such as mobile phones and automobiles. This application embodiment does not limit this. The ionospheric data collected by the user terminal specifically includes the oblique path ionospheric delay collected by the user terminal and the corresponding line-of-sight direction information. The line-of-sight direction information can be understood as the puncture point information of the line connecting the user terminal's location and the satellite on the ionosphere. Specifically, it includes the longitude, latitude, azimuth, and elevation angle of the ionospheric puncture point. The oblique path ionospheric delay is the ionospheric delay data in the line-of-sight direction.

[0071] Specifically, in S102, each user terminal can be considered as a target station, and the standardized residual of the slant path ionospheric delay of each target station can be calculated using the Kriging interpolation method. User terminals with standardized residuals greater than the standardized residual threshold are then eliminated. This includes:

[0072] For each target station, user terminals within a preset range centered on each target station are selected as neighboring reference stations. Kriging interpolation is performed based on the neighboring reference stations to calculate the weight of each neighboring reference station.

[0073] The ionospheric prediction data and prediction variance of the target station are calculated by weighting each adjacent reference station and the corresponding slant path ionospheric delay.

[0074] The prediction residual is calculated based on the difference between the slant path ionospheric delay of the target station and the ionospheric prediction data. The standardized residual of the target station is then calculated based on the prediction variance and the prediction residual.

[0075] Obtain the ionospheric deviation data sequence composed of the standardized residuals of each user terminal, and remove user terminals in the ionospheric deviation data sequence that are greater than the standardized residual threshold.

[0076] The preset range can be understood as a circular area with a preset radius centered on the target station, or it can be an area of ​​any shape with the target station as the geometric center. This application does not limit this.

[0077] For example, the variance between the target station and its neighboring reference station at a distance of d can be defined to construct the distance empirical variation function:

[0078] ;

[0079] in, This represents the distance between the reference station and the target station; a reference station and a target station with a distance of d constitute a reference station pair. Indicates distance as The number of reference station pairs; For the slant path ionospheric delay of the target station, The slant path ionospheric delay is the reference station's delay, where the subscript i represents the sequence number of each user terminal, i.e., the target station. The distance is The variance of the reference station pair is specifically the variance of the slant path ionospheric delay collected by the two user terminals in the reference station pair.

[0080] Using the spherical variogram to fit the empirical data, based on the above distance empirical variogram, we obtain:

[0081] ;

[0082] in, This represents the nugget effect and can be used to explain measurement noise. The sill value represents the maximum variance; This indicates a variable range, which can be used to determine the size of a preset range.

[0083] Based on the above empirical variation function, neighboring reference stations within a preset range of radius a, centered on the target station i, are selected for Kriging interpolation. The weight of each neighboring reference station is calculated, and the Kriging model can be expressed as follows:

[0084] ;

[0085] , , ;

[0086] in, The ionospheric puncture point (IPP) of target station i is defined as the longitude and latitude of the ionospheric puncture point. Indicates the ionospheric puncture point (IPP) of the adjacent reference station j. Indicates another neighboring reference station of target station i Ionospheric puncture point IPP, The weight of the slant path ionospheric delay for the adjacent reference station j; This can be understood as comparing adjacent reference station j with another adjacent reference station. As a reference station pair, calculate the neighboring reference station j and another neighboring reference station. The variance between adjacent reference station j and another adjacent reference station The distance between them can be calculated from the corresponding ionospheric puncture point (IPP), and then substituted into the distance empirical variation function to calculate the distance between adjacent reference station j and another adjacent reference station. The variance between them. Similarly, Indicates adjacent reference station j and The variance between them; It is a Lagrange multiplier.

[0087] Furthermore, the weights of each neighboring reference station j are calculated by solving the Kriging model. ;

[0088] Furthermore, based on the calculated weights of each neighboring reference station j around the target station i... Slant path ionospheric delay for each adjacent reference station j Weighted calculations are performed to obtain ionospheric prediction data. Based on weights Measurement data of adjacent reference station j and variance between measurement data Weighted calculations are performed to obtain the prediction variance. .

[0089] Specifically, the ionospheric prediction data are calculated. and the corresponding prediction variance Apply the formula:

[0090] ;

[0091] Furthermore, the slant path ionospheric delay of target station i With ionospheric prediction data The predicted residuals are calculated by subtracting the two values. Apply the formula:

[0092] ;

[0093] Based on predicted residuals and prediction variance The standardized residuals of target station i were calculated. Apply the formula:

[0094] ;

[0095] Understandably, by repeating step S102 with each user terminal as the target station, the ionospheric bias data sequence composed of the standardized residuals of each user terminal i can be obtained. .

[0096] Specifically, in the ionospheric deviation data sequence Standardized residuals of user terminal i If the residual value exceeds the standardized residual threshold, the corresponding user terminal i and the ionospheric data uploaded by the user terminal are removed. .

[0097] In some embodiments, the calculation process for the standardized residual threshold may include the following steps:

[0098] Based on a preset sliding window, the oblique path ionospheric delay sequence r collected by each user terminal within the preset sliding window can be obtained, and the median of the oblique path ionospheric delay sequence can be calculated. .

[0099] For example, the preset sliding window can be set to 15 minutes.

[0100] Furthermore, the standardized residuals in the ionospheric bias data sequence Z are calculated separately. Median of ionospheric delay sequence with oblique path The difference, i.e. ;

[0101] Furthermore, the median of the difference between each standardized residual and the median of the slant path ionospheric delay sequence is calculated, i.e. The absolute deviation of the median was calculated. .

[0102] Specifically, the median absolute deviation (MAD) of the standardized residuals in the ionospheric deviation data sequence within the sliding window is calculated using the following formula:

[0103] ;

[0104] in, The absolute deviation of the median. The ionospheric deviation data sequence is defined as r, where r is the sequence of ionospheric delays along the oblique path acquired by each user terminal within a preset sliding window. This is a function used to calculate the median.

[0105] Finally, the standardized residual threshold is determined based on the median absolute deviation.

[0106] For example, in the absolute deviation of the median The standardized residual threshold is obtained by multiplying the value by a preset deviation coefficient. For example, a deviation coefficient of 100 is selected. The obtained standardized residual threshold is The magnitude of the deviation coefficient depends on the actual situation. If more user terminals need to be retained, a larger deviation coefficient can be selected. This application does not limit this.

[0107] For example, when The corresponding slant path ionospheric delay is marked as a gross error, and the corresponding user terminal and the ionospheric data collected by that user terminal are removed.

[0108] In this way, the standardized residual threshold can be determined dynamically and in real time, and thus the standardized residual threshold can be updated in real time based on the actual collected data.

[0109] In some embodiments, after S101, the cloud server can preprocess the ionospheric data collected by each user terminal, determine the user terminals falling in the same time period based on the time of the ionospheric data collected by each user terminal, and map the ionospheric data collected by each user terminal to the ionospheric puncture point at a preset height.

[0110] Specifically, this is equivalent to unifying the timing of ionospheric data collected by each user terminal. For example, user terminals can be clustered according to the time period in which the collection time falls, thereby achieving time-time unification. That is, ionospheric data collected in the same time period is regarded as time-synchronized and unified data. The longitude, latitude, azimuth, and elevation angle of the collected ionospheric puncture point can be mapped onto the ionospheric plane at a preset altitude, such as an ionospheric plane at an altitude of 350 kilometers.

[0111] In some embodiments, in S103, the pre-built Q4DIM network can be represented as The dimensions of the Q4DIM network include latitude, longitude, elevation, and azimuth:

[0112] ;

[0113] in, Indicate latitude, Indicates longitude, Indicates elevation angle, Indicates azimuth;

[0114] Specifically, express The coordinates in the four-dimensional coordinate system are The grid, where the superscript grid indicates a Q4DIM network, and the subscript... The grid represents the four-dimensional coordinates, where g represents the latitude, h represents the longitude, m represents the elevation angle, and n represents the azimuth angle.

[0115] like Figure 2 As shown, the four-dimensional Q4DIM network is visualized as a parametrically compressed two-dimensional representation, with the horizontal axis combining latitude and longitude, and the vertical axis integrating elevation and azimuth.

[0116] After removing outliers through calculations S101-S102, the set of all remaining user-end gaze direction information can be represented as: The superscript *los* indicates the direction of the gaze, and the subscript *k* indicates the ordinal number of the user in the set, such as... Figure 2 As shown, some user terminals are marked with red dots.

[0117] Specifically, the Euclidean distance between each user terminal and each grid on the Q4DIM network can be calculated based on the line-of-sight information of each user terminal, using the formula:

[0118] ;

[0119] The grid with the minimum Euclidean distance to each user terminal is determined as the target grid corresponding to that user terminal on the pre-constructed Q4DIM network; argmin is a function used to find the minimum value. It is the Euclidean norm; For each user terminal, a set of target grids. Let u represent the latitude of the target grid, v represent the longitude of the target grid, x represent the elevation angle of the target grid, and y represent the azimuth angle of the target grid.

[0120] This allows us to determine the target mesh for each user on the Q4DIM network.

[0121] Further, perform the steps in S104:

[0122] Obtain the slant path ionospheric delay for each user terminal located on the same target grid. Use the average slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay for the corresponding grid, applying the formula:

[0123] ;

[0124] Specifically, Represents the target mesh A collection of all client terminals. Indicates location within the target grid The number of user terminals can be understood as the number of target meshes to be calculated. superior The average slant path ionospheric delay of each user terminal was calculated. ,Will As the target grid Angled path ionospheric delay;

[0125] For example, Figure 2 The grid in the 5th row and 2nd column has 5 user terminals. By calculating the average of the slant path ionospheric delays of these 5 user terminals, the slant path ionospheric delay of this grid can be obtained.

[0126] Furthermore, in step S105, based on the target grid corresponding to each user terminal, the oblique path ionospheric delay of the corresponding target grid can be broadcast to the user terminal located within the target grid. This allows the user terminal within the grid to perform PPP-RTK positioning calculations based on the oblique path ionospheric delay updated in S101-S105, which helps improve positioning accuracy.

[0127] In some embodiments, prior to S101, ionospheric data is collected via a user terminal, specifically including:

[0128] S11, calculate the distance between the user terminal and the satellite based on the initial coordinates of each user terminal and the precision satellite orbit product, and calculate the satellite clock error correction, tropospheric dry delay correction, satellite pseudorange hardware delay correction and satellite phase hardware delay correction.

[0129] The initial coordinates of each user terminal can be calculated using Standard Point Positioning (SPP).

[0130] S12, based on the satellite clock error correction, the tropospheric dry delay correction, the satellite pseudorange hardware delay correction, and the satellite phase hardware delay correction, the basic observation equation of GNSS is corrected for errors. The oblique ionospheric delay, which eliminates the user-end pseudorange hardware delay and the user-end phase hardware delay, is calculated by Kalman filtering, and the line-of-sight direction information is calculated.

[0131] S13, Perform gross error detection on the slant path ionospheric delay of each user terminal and remove user terminals that meet the preset conditions;

[0132] S14, the calculated line-of-sight direction information and the oblique path through the ionosphere delay are uploaded to the cloud server through the retained user terminal.

[0133] Specifically, in S13, the gross error detection of the slant-through ionospheric delay for each user terminal includes:

[0134] Obtain the ionospheric delay duration corresponding to the slant path ionospheric delay for each user terminal;

[0135] Obtain the slant ionospheric delay of each user terminal and the slant ionospheric delay of a preset number of surrounding user terminals, and calculate the ionospheric delay residual and ionospheric delay variance between the slant ionospheric delays of each user terminal.

[0136] Here, the surrounding area of ​​a user terminal can be understood as a preset area centered on a user terminal. The preset number of user terminals around it can be understood as other user terminals falling within the preset area, which can be selected from near to far from the user terminal at the center, in order to calculate the ionospheric delay residual and ionospheric delay variance between the slant path ionospheric delays of each user terminal.

[0137] The process of removing user terminals that meet preset conditions includes:

[0138] If the duration of the ionospheric delay is greater than or equal to the duration threshold, and the residual of the ionospheric delay is less than or equal to the residual threshold of the ionospheric delay, and the variance of the ionospheric delay is less than or equal to the variance threshold of the ionospheric delay, then the sloping ionospheric delay of the user terminal is determined to be a valid sloping ionospheric delay.

[0139] Obtain all valid slant ionospheric delays for each user terminal within a single epoch;

[0140] If the number of valid slant-to-ionospheric delays for a user terminal within a single epoch is less than a threshold, then the corresponding user terminal is removed.

[0141] Specifically, the preset condition can be understood as the number of effective slant path delays through the ionosphere being less than a quantity threshold. If the number of all effective slant path delays through the ionosphere for a single user terminal within a single epoch is less than the quantity threshold, then the preset condition is met.

[0142] For example, the duration threshold can be set to 5 minutes, the ionospheric delay residual threshold to 1 TECU (Total Electron Content Unit), the ionospheric delay variance threshold to 0.5 TECU, and the quantity threshold to 8.

[0143] It should be noted that the ionospheric delay of each satellite is not always present. Therefore, the duration of the ionospheric delay corresponding to the slant path ionospheric delay can be understood as the period from the extraction time of the ionospheric delay, during which the ionospheric delay is uninterrupted and continues until the end time of the ionospheric delay. The time interval between the extraction time and the end time is taken as the duration of the ionospheric delay.

[0144] In this way, as many effective slant path ionospheric delays as possible are retained. The preset condition can be understood as follows: if fewer than 8 effective slant path ionospheric delays are retained, user terminals with fewer effective slant path ionospheric delays are removed.

[0145] Understandably, when the user initially calculates the slant path delay and line-of-sight direction information, the calculation can be performed by combining the basic observation equations of GNSS with precise satellite orbit products, precise satellite clock error products, tropospheric dry delay calculation models, DCB (Different Code Bias) products, phase deviation products, etc., and given known prior parameters (for example), and then the calculation results can be obtained.

[0146] In some embodiments, the user terminal executes steps S11-S14 to upload the calculated line-of-sight direction information and the oblique path ionospheric delay to the cloud server. Then, the cloud server executes steps S101 to S105 based on the ionospheric data uploaded by the user terminal, thereby sending the oblique path ionospheric delay updated based on the ionospheric data from the crowdsourced user terminal to the user terminal. Further, the user terminal can jump to S11 based on the oblique path ionospheric delay fed back by the cloud server and continue to execute steps S11-S14, repeating the process.

[0147] In this way, the user terminal can improve its positioning accuracy by using the oblique path ionospheric delay fed back by the cloud server, and the cloud server can dynamically update the oblique path ionospheric delay based on the oblique path ionospheric delay collected by the user terminal in real time.

[0148] The following are apparatus embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the method embodiments of this application.

[0149] Please see below. Figure 3This is a schematic diagram of an ionospheric parameter determination device based on user crowdsourced data, provided as an exemplary embodiment of this application. This device can be implemented as all or part of a terminal through software, hardware, or a combination of both, or it can be integrated as an independent module on a server. The ionospheric parameter determination device based on user crowdsourced data in this embodiment can be applied to a terminal or the cloud. The device 30 includes a data acquisition unit 301, a gross error removal unit 302, a grid calculation unit 303, and a data transmission unit 304, wherein:

[0150] The data acquisition unit 301 is used to acquire ionospheric data uploaded by multiple user terminals; the ionospheric data includes the slant path ionospheric delay collected by the user terminal and the corresponding line-of-sight direction information;

[0151] The gross error removal unit 302 is used to calculate the standardized residual of the slant path ionospheric delay of each user terminal using the Kriging interpolation method, and remove user terminals whose standardized residual is greater than the standardized residual threshold.

[0152] The grid computing unit 303 is used to determine the target grid corresponding to each user terminal on the pre-built Q4DIM network based on the retained user terminal's line-of-sight information;

[0153] The grid computing unit 303 is also used to obtain the slant path ionospheric delay of each user terminal located on the same target grid, and use the average value of the slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay of the corresponding target grid.

[0154] The data transmission unit 304 is used to extract the slant path ionospheric delay of the target grid corresponding to each user terminal and send it to the corresponding user terminal.

[0155] It should be noted that the apparatus 30 provided in the above embodiments, when executing the ionospheric parameter determination method based on user crowdsourced data, is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus provided in the above embodiments and the ionospheric parameter determination method embodiments based on user crowdsourced data belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0156] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0157] Please see Figure 4This is a structural block diagram of an electronic device provided in an embodiment of this application.

[0158] like Figure 4 As shown, the electronic device 400 includes a processor 401 and a memory 402.

[0159] In this embodiment, the processor 401 is the control center of the computer system, and can be a processor of a physical machine or a processor of a virtual machine. The processor 401 may include one or more processing cores, such as a 4-core processor or an 8-core processor. The processor 401 can be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array).

[0160] Processor 401 may also include a main processor and a coprocessor. The main processor is a processor used to process data in the wake-up state, also known as a CPU (Central Processing Unit). The coprocessor is a low-power processor used to process data in the standby state.

[0161] Memory 402 may include one or more computer-readable storage media, which may be non-transitory. Memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments of this application, the non-transitory computer-readable storage media in memory 402 is used to store at least one instruction, which is executed by processor 401 to implement the method in the embodiments of this application.

[0162] In some embodiments, the electronic device 400 further includes a peripheral device interface 403 and at least one peripheral device 404. The processor 401, memory 402, and peripheral device interface 403 can be connected via a bus or signal line. Each peripheral device 404 can be connected to the peripheral device interface 403 via a bus, signal line, or circuit board. Specifically, the peripheral device 404 includes: a display screen, a camera, and audio circuitry. The peripheral device interface 403 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 401 and memory 402.

[0163] In some embodiments of this application, the processor 401, memory 402, and peripheral device interface 403 are integrated on the same chip or circuit board; in other embodiments of this application, any one or two of the processor 401, memory 402, and peripheral device interface 403 can be implemented on separate chips or circuit boards. This application does not specifically limit the implementation in this regard.

[0164] The block diagram of the electronic device shown in the embodiments of this application does not constitute a limitation on the electronic device 400. The electronic device 400 may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0165] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the methods in any of the foregoing embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0166] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0167] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for determining ionospheric parameters based on user crowdsourced data, characterized in that, Applied to cloud servers, the method includes: Acquire ionospheric data uploaded by multiple user terminals; the ionospheric data includes ionospheric delay along a slant path collected by the user terminal and the corresponding line-of-sight direction information; The standardized residual of the slant path ionospheric delay for each user terminal was calculated using Kriging interpolation, and user terminals with standardized residuals greater than the standardized residual threshold were removed. The target grid corresponding to each user terminal on the pre-built Q4DIM network is determined based on the retained user terminal's line-of-sight information; Obtain the slant path ionospheric delay of each user terminal located on the same target grid, and use the average slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay of the corresponding target grid. Based on the target grid corresponding to each user terminal, the slant path ionospheric delay of the corresponding target grid is extracted and sent to the corresponding user terminal.

2. The method for determining ionospheric parameters based on user crowdsourced data according to claim 1, characterized in that, The steps for collecting ionospheric data at the user terminal include: The distance between the user terminal and the satellite is calculated based on the initial coordinates of each user terminal and the precision satellite orbit product. The satellite clock error correction, tropospheric dry delay correction, satellite pseudorange hardware delay correction, and satellite phase hardware delay correction are also calculated. The basic observation equations of GNSS are corrected based on the satellite clock error correction, the tropospheric dry delay correction, the satellite pseudorange hardware delay correction, and the satellite phase hardware delay correction. The oblique ionospheric delay, which eliminates the user-end pseudorange hardware delay and the user-end phase hardware delay, is calculated by Kalman filtering, and the line-of-sight direction information is calculated. Gross error detection is performed on the slant path ionospheric delay of each user terminal, and user terminals that meet the preset conditions are removed; The calculated line-of-sight direction information and the oblique path through the ionosphere delay are uploaded to the cloud server through the retained user terminal.

3. The method for determining ionospheric parameters based on user crowdsourced data according to claim 2, characterized in that, The gross error detection of the slant-to-ionospheric delay for each user terminal includes: Obtain the ionospheric delay duration corresponding to the slant path ionospheric delay for each user terminal; Obtain the sloping ionospheric delay of each user terminal and the sloping ionospheric delay of a preset number of surrounding user terminals, and calculate the ionospheric delay residual and ionospheric delay variance between the sloping ionospheric delays of each user terminal. The process of removing user terminals that meet preset conditions includes: If the duration of the ionospheric delay is greater than or equal to the duration threshold, and the residual of the ionospheric delay is less than or equal to the residual threshold of the ionospheric delay, and the variance of the ionospheric delay is less than or equal to the variance threshold of the ionospheric delay, then the sloping ionospheric delay of the user terminal is determined to be a valid sloping ionospheric delay. Obtain all valid slant ionospheric delays for each user terminal within a single epoch; If the number of valid slant-to-ionospheric delays for a user terminal within a single epoch is less than a threshold, then the corresponding user terminal is removed.

4. The method for determining ionospheric parameters based on user crowdsourced data according to claim 1, characterized in that, The step of calculating the standardized residual of the slant path ionospheric delay for each user terminal using Kriging interpolation, and then removing user terminals whose standardized residuals are greater than a standardized residual threshold, includes: Each user terminal is taken as the target station, and user terminals within a preset range centered on each target station are selected as neighboring reference stations. Kriging interpolation is performed based on the neighboring reference stations to calculate the weight of each neighboring reference station. The ionospheric prediction data and prediction variance of the target station are calculated by weighting each adjacent reference station and the corresponding slant path ionospheric delay. The prediction residual is calculated based on the difference between the slant path ionospheric delay of the target station and the ionospheric prediction data. The standardized residual of the target station is then calculated based on the prediction variance and the prediction residual. Obtain the ionospheric deviation data sequence composed of the standardized residuals of each user terminal, and remove user terminals in the ionospheric deviation data sequence that are greater than the standardized residual threshold.

5. The method for determining ionospheric parameters based on user crowdsourced data according to claim 4, characterized in that, The standardized residual threshold is determined based on the following steps: Obtain the sequence of slant path ionospheric delay collected by each user terminal within a preset sliding window; The median absolute deviation of the ionospheric deviation data sequence is calculated using the following formula: ； The standardized residual threshold is determined based on the median absolute deviation. in, The absolute deviation of the median. Let r be the ionospheric deviation data sequence, and r be the sequence of slant path ionospheric delays collected by each user terminal within the preset sliding window. This is a function used to calculate the median.

6. The method for determining ionospheric parameters based on user crowdsourced data according to claim 1, characterized in that, After acquiring ionospheric data uploaded by multiple user terminals, the process further includes: Based on the time of the ionospheric data collected by each user terminal, the user terminals that fall within the same time period are determined, and the ionospheric data collected by each user terminal is mapped to the ionospheric puncture point at a preset height.

7. A method for determining ionospheric parameters based on user crowdsourced data according to any one of claims 1-6, characterized in that, The line-of-sight information includes the longitude, latitude, azimuth, and elevation angle of the ionospheric puncture point connecting the user terminal to the satellite. The step of determining the target mesh corresponding to each user terminal on the pre-built Q4DIM network based on the retained user terminal's line-of-sight information includes: Calculate the Euclidean distance between each user terminal and each grid on the Q4DIM network based on the line-of-sight information of each user terminal, using the formula: ； The grid with the smallest Euclidean distance to each user terminal is determined as the target grid corresponding to the user terminal on the pre-constructed Q4DIM network; in, Let los be the set of gaze direction information for k users, where the superscript los represents the gaze direction information and the subscript k represents the ordinal number of the user in the set. For each mesh on the Q4DIM network, The coordinates on the four-dimensional coordinate system of the Q4DIM network are The grid, where the superscript grid indicates a Q4DIM network, and the subscript... The grid represents four-dimensional coordinates, where g represents latitude, h represents longitude, m represents altitude, and n represents azimuth; argmin is a function used to find the minimum value. It is the Euclidean norm; For each user terminal, a set of target grids. The four-dimensional coordinates of the target grid are u, v, x, and y. u represents latitude, v represents longitude, x represents altitude, and y represents azimuth.

8. A device for determining ionospheric parameters based on user crowdsourced data, characterized in that, include: The data acquisition unit is used to acquire ionospheric data uploaded by multiple user terminals; the ionospheric data includes slant path ionospheric delay and corresponding line-of-sight information collected by the user terminals. The gross error removal unit is used to calculate the standardized residual of the slant path ionospheric delay for each user terminal using Kriging interpolation, and remove user terminals whose standardized residual is greater than the standardized residual threshold. The grid computing unit is used to determine the target grid corresponding to each user terminal on the pre-built Q4DIM network based on the retained user terminal's line-of-sight information; The grid computing unit is also used to obtain the slant path ionospheric delay of each user terminal located on the same target grid, and use the average value of the slant path ionospheric delay of all user terminals on the same target grid as the slant path ionospheric delay of the corresponding target grid. The data transmission unit is used to extract the slant path ionospheric delay of the target grid corresponding to each user terminal and send it to the corresponding user terminal.

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

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

Images