An ionospheric modeling method, device, equipment and storage medium

Abstract

The application discloses an ionosphere modeling method, device and equipment and a storage medium. The method comprises the following steps: calculating ionosphere delay corresponding to historical GNSS observation data according to an ionosphere model corresponding to the historical GNSS observation data, and then separating coupled ionosphere delay and differential code bias information; separating receiver differential code bias and satellite differential code bias in the differential code bias information; fitting the change rule of the receiver differential code bias and the satellite differential code bias, and estimating the receiver differential code bias estimate value and the satellite differential code bias estimate value in a modeling period; removing the receiver differential code bias estimate value and the satellite differential code bias estimate value in the GNSS observation data in the modeling period, and then constructing a corresponding ionosphere model in the modeling period according to the removed GNSS observation data. The application can improve the accuracy of the constructed ionosphere model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of GNSS precise data processing, and particularly relates to an ionospheric modeling method, device and equipment and a storage medium. BACKGROUND

[0002] In the process of GNSS positioning, the error caused by the satellite signal passing through the ionosphere is an important factor restricting the positioning accuracy and the positioning convergence time. Therefore, an accurate ionospheric model can provide more accurate ionospheric initial values and weights for the positioning filtering process, thereby improving the positioning accuracy and shortening the positioning convergence time.

[0003] The receiver differential code bias and the satellite differential code bias are important factors restricting the model accuracy in the ionospheric modeling process. Since the differential code bias and the ionospheric delay obtained from the GNSS observation value are coupled with each other, the differential code bias cannot be separated. Therefore, in the modeling process, the differential code bias is separated from the total electron content by assuming that the differential code bias is constant in a short time (one day). The assumption is valid when the receiver state and the environment are stable. However, in the actual production process, the differential code bias cannot be guaranteed to be stable due to the influence of factors such as the temperature and humidity of the receiver environment, the space radiation in the space environment of the satellite, the service life of the receiver and the satellite, and the like, thereby leading to a low accuracy of the constructed ionospheric model. SUMMARY

[0004] The present application provides an ionospheric modeling method, device, equipment and storage medium to solve the technical problem that the differential code bias and the ionospheric delay obtained from the GNSS observation value are coupled with each other, the differential code bias cannot be separated, and the accuracy of the constructed ionospheric model is low.

[0005] To solve the above technical problem, the present application provides an ionospheric modeling method, comprising:

[0006] Obtaining a plurality of historical GNSS observation data of a to-be-modeled region in a preset time period; wherein the historical GNSS observation data comprises historical pseudorange observation data and historical carrier observation data of all base station receivers;

[0007] Calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information comprises a receiver differential code bias and a satellite differential code bias;

[0008] According to the ionospheric model corresponding to the historical GNSS observation data, calculating the ionospheric delay corresponding to the historical GNSS observation data, and then separating the coupled ionospheric delay and differential code bias information;

[0009] According to the separated differential code bias information, separating the receiver differential code bias and the satellite differential code bias in the differential code bias information;

[0010] According to the separated receiver differential code bias, fitting to obtain the change rule of the receiver differential code bias, and according to the separated satellite differential code bias, fitting to obtain the change rule of the satellite differential code bias;

[0011] According to the change rule of the receiver differential code bias, estimating to obtain the receiver differential code bias prediction value in the to-be-modeled period, and according to the change rule of the satellite differential code bias, estimating to obtain the satellite differential code bias prediction value in the to-be-modeled period;

[0012] According to the receiver differential code bias prediction value and the satellite differential code bias prediction value, eliminating the receiver differential code bias prediction value and the satellite differential code bias prediction value in the GNSS observation data in the to-be-modeled period, and then constructing the corresponding ionospheric model in the to-be-modeled period according to the eliminated GNSS observation data.

[0013] As a preferred solution, the ionospheric modeling method further comprises:

[0014] According to the constructed ionospheric model and the corresponding GNSS observation data, eliminating the ionospheric delay in the GNSS observation data, and then performing GNSS positioning according to the eliminated GNSS observation data.

[0015] As a preferred solution, the calculation of the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data comprises:

[0016] According to the historical pseudorange observation data, calculating to obtain the corresponding non-geometry combined pseudorange observation value, and according to the historical carrier observation data, calculating to obtain the corresponding non-geometry combined carrier observation value;

[0017] Calculating the mean value of the sum of the non-geometry combined pseudorange observation value and the non-geometry combined carrier observation value in the same preset arc segment, and then calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data according to the mean value and the non-geometry combined carrier observation value.

[0018] As a preferred solution, the coupled ionospheric delay and differential code bias information is:

[0019]

[0020] wherein, denotes the ionospheric delay of the history GNSS observation data, f1 denotes the frequency corresponding to the geometry-free combined pseudorange observation value, f2 denotes the frequency corresponding to the geometry-free combined carrier observation value, c denotes the speed of light in vacuum, DCB r,1|2 denotes the receiver differential code bias of the receiver at the frequency f1 and the frequency f2, denotes the satellite differential code bias of the satellite at the frequency f1 and the frequency f2, denotes the mean value of the sum of the geometry-free combined pseudorange observation value and the geometry-free combined carrier observation value within the same preset arc segment.

[0021] As a preferred solution, the calculation of the ionospheric delay corresponding to the history GNSS observation data according to the ionospheric model corresponding to the history GNSS observation data, and then the separation of the coupled ionospheric delay and differential code bias information, comprises:

[0022] determining whether the history GNSS observation data has a corresponding ionospheric model, and when it is determined that the history GNSS observation data has a corresponding ionospheric model, calculating the piercing point coordinates of the history GNSS observation data at the height of the corresponding ionospheric model according to the ionospheric model corresponding to the history GNSS observation data;

[0023] calculating the vertical path value corresponding to the history GNSS observation data according to the piercing point coordinates;

[0024] calculating the ionospheric projection function value corresponding to the history GNSS observation data, and then converting the vertical path value into a corresponding slant path value according to the ionospheric projection function value;

[0025] taking the slant path value as the ionospheric delay corresponding to the history GNSS observation data, and then separating the coupled ionospheric delay and differential code bias information.

[0026] As a preferred solution, the calculation of the ionospheric delay corresponding to the history GNSS observation data according to the ionospheric model corresponding to the history GNSS observation data, and then the separation of the coupled ionospheric delay and differential code bias information, further comprises:

[0027] when it is determined that the history GNSS observation data does not have a corresponding ionospheric model, assuming that the receiver differential code bias and the satellite differential code bias corresponding to the history GNSS observation data are the same within a preset time period, and then solving the ionospheric model corresponding to the history GNSS observation data according to a preset solving equation of the ionospheric model and the differential code bias;

[0028] According to the ionosphere model corresponding to the historical GNSS observation data, the piercing point coordinates of the historical GNSS observation data on the height of the corresponding ionosphere model are calculated;

[0029] According to the piercing point coordinates, the vertical path values corresponding to the historical GNSS observation data are calculated;

[0030] The ionosphere projection function values corresponding to the historical GNSS observation data are calculated, and then the vertical path values are converted into corresponding slant path values according to the ionosphere projection function values;

[0031] The slant path values are taken as the ionosphere delay corresponding to the historical GNSS observation data, and then the coupled ionosphere delay and differential code bias information are separated.

[0032] As a preferred solution, the receiver differential code bias and satellite differential code bias in the differential code bias information are separated according to the separated differential code bias information, including:

[0033] According to the separated differential code bias information, the sum of the satellite differential code bias in the differential code bias information is zero, and the corresponding receiver differential code bias is solved, and then the receiver differential code bias and satellite differential code bias in the differential code bias information are separated.

[0034] On the basis of the above-mentioned embodiments, another embodiment of the present application provides an ionosphere modeling device, comprising: a historical observation data acquisition module, a coupled data calculation module, a coupled data separation module, a differential code bias information separation module, a change rule fitting module, a differential code bias estimation module and an ionosphere model construction module;

[0035] The historical observation data acquisition module is used for acquiring a plurality of historical GNSS observation data of a to-be-modeled region in a preset time period; wherein the historical GNSS observation data comprises historical pseudo-range observation data and historical carrier observation data of all base station receivers;

[0036] The coupled data calculation module is used for calculating the coupled ionosphere delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information comprises receiver differential code bias and satellite differential code bias;

[0037] The coupled data separation module is used for calculating the ionosphere delay corresponding to the historical GNSS observation data according to the ionosphere model corresponding to the historical GNSS observation data, and then separating the coupled ionosphere delay and differential code bias information;

[0038] The differential code bias information separation module is configured to separate the receiver differential code bias and the satellite differential code bias in the differential code bias information according to the separated differential code bias information.

[0039] The variation law fitting module is configured to fit the variation law of the receiver differential code bias according to the separated receiver differential code bias, and fit the variation law of the satellite differential code bias according to the separated satellite differential code bias.

[0040] The differential code bias estimation module is configured to estimate the receiver differential code bias pre-estimation value in the to-be-modeled time period according to the variation law of the receiver differential code bias, and estimate the satellite differential code bias pre-estimation value in the to-be-modeled time period according to the variation law of the satellite differential code bias.

[0041] The ionospheric model construction module is configured to remove the receiver differential code bias pre-estimation value and the satellite differential code bias pre-estimation value from the GNSS observation data in the to-be-modeled time period according to the receiver differential code bias pre-estimation value and the satellite differential code bias pre-estimation value, and then construct the corresponding ionospheric model in the to-be-modeled time period according to the removed GNSS observation data.

[0042] On the basis of the above-mentioned embodiments, a further embodiment of the application provides an electronic device, the device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the ionospheric modeling method described in the above-mentioned embodiments of the application when executing the computer program.

[0043] On the basis of the above-mentioned embodiments, a further embodiment of the application provides a storage medium, the storage medium comprising a stored computer program, wherein the computer program controls the device where the storage medium is located to execute the ionospheric modeling method described in the above-mentioned embodiments of the application when running.

[0044] Compared with the prior art, the embodiments of the application have the following beneficial effects:

[0045] The application provides an ionospheric modeling method, which first calculates coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data according to a plurality of historical GNSS observation data of a to-be-modeled region in a preset time period; then calculates ionospheric delay corresponding to the historical GNSS observation data according to an ionospheric model corresponding to the historical GNSS observation data, separates the coupled ionospheric delay and differential code bias information, and separates receiver differential code bias and satellite differential code bias in the differential code bias information according to the separated differential code bias information.

[0046] Therefore, the application can overcome the problem that differential code bias and ionospheric delay are coupled and cannot be separated, and can calculate ionospheric delay corresponding to historical GNSS observation data according to an ionospheric model corresponding to the historical GNSS observation data, so as to decouple and separate the coupled ionospheric delay and differential code bias information. According to the separated differential code bias data, differential code bias prediction values in a modeling period can be fitted and estimated, and the differential code bias prediction values in the GNSS observation data in the modeling period are removed according to the differential code bias prediction values, so that pure GNSS observation data is obtained, and a corresponding ionospheric model in the modeling period is constructed, so that the accuracy of the constructed ionospheric model can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 is a flowchart of an ionospheric modeling method provided by an embodiment of the application;

[0048] Figure 2 is a flowchart of an ionospheric model construction method provided by an embodiment of the application;

[0049] Figure 3 is a structural diagram of an ionospheric modeling device provided by an embodiment of the application. DETAILED DESCRIPTION

[0050] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0051] 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 the present application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "include" and "have" and any variations thereof in the specification and claims of the present application and the above description of drawings are intended to cover non-exclusive inclusion.

[0052] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0053] Reference to“an embodiment” herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase“in an embodiment” in various places in the specification are not necessarily referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. As will be apparent to those of ordinary skill in the art, embodiments described herein can be combined with other embodiments.

[0054] In the description of the embodiments of the application, the term“and / or” only means an association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character“ / ” herein generally represents an“or” relationship between the front and rear associated objects.

[0055] In the description of the embodiments of the application, the term“a plurality of” refers to two or more (including two), and similarly, “a plurality of groups” refers to two or more groups (including two groups), and “a plurality of pieces” refers to two or more pieces (including two pieces).

[0056] In the description of the embodiments of the application, unless otherwise explicitly specified and limited, the technical terms“mounting”,“connecting”,“connecting”,“fixing” and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanical connection, or it can be electrical connection; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the application can be understood according to the specific circumstances.

[0057] Embodiment one

[0058] Please refer to Figure 1 A flowchart of an ionospheric modeling method provided by an embodiment of the application, comprising the following specific steps:

[0059] S1, obtaining a plurality of historical GNSS observation data of a region to be modeled in a preset time period; wherein the historical GNSS observation data comprises historical pseudorange observation data and historical carrier observation data of all base station receivers;

[0060] Specifically, the charged particles in the ionosphere change complexly, and the existing technology usually assumes that the ionosphere does not change significantly within a certain time in the model establishment process, and the observation values within 15 minutes, half an hour, one hour or even two hours are fitted into a model. This assumption can achieve better results in weak solar activity or ionosphere calm period, but in strong solar activity years, near local noon or solar / earth magnetic storm period, the ionosphere is more active, and the total electron content fluctuation in a short time can reach dozens of TECU (Total Electron Content Unit), causing the model established by the above method to have large errors, which cannot be applied to actual GNSS operation or other industry production processes.

[0061] The receiver and satellite differential code bias is another factor that restricts the precision of the ionosphere modeling process. Since the differential code bias and the ionosphere delay obtained from the GNSS observation values are coupled and cannot be separated, it is necessary to separate them from the total electron content of the ionosphere in the modeling process by assuming that the differential code bias is constant within a short time (one day), but the premise for this assumption to be true is that the receiver state and the environment are stable. However, in actual production processes, the receiver environment temperature and humidity, space radiation in the environment where the satellite is located, service life of the receiver and satellite, and other factors cannot guarantee the stability of the differential code bias.

[0062] Considering that the above assumption is harsh, the present application obtains a high-frequency ionosphere model by first solving the initial value of the receiver and satellite differential code bias, and then gradually establishing an ionosphere model and estimating the time-varying differential code bias. Please refer to Figure 2 The flowchart of the ionosphere model of the present application is as follows:

[0063] Step one: collect all the historical GNSS observation data of the receivers of all base stations in the ionosphere to be modeled in the previous day, and calculate the center of the region as the modeling reference center position; wherein the historical GNSS observation data includes historical pseudorange observation data and historical carrier observation data of all base station receivers.

[0064] S2, calculate the coupled ionosphere delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information includes: receiver differential code bias and satellite differential code bias;

[0065] Preferably, the calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data comprises: calculating corresponding non-geometric combined pseudo-range observation value according to the historical pseudo-range observation data, and calculating corresponding non-geometric combined carrier observation value according to the historical carrier observation data; calculating the mean value of the sum of the non-geometric combined pseudo-range observation value and the non-geometric combined carrier observation value in the same preset arc segment, and then calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data according to the mean value and the non-geometric combined carrier observation value.

[0066] Preferably, the coupled ionospheric delay and differential code bias information is:

[0067]

[0068] wherein, represents the non-geometric combined carrier observation value in meters, STEC represents the ionospheric delay, f1 represents the frequency corresponding to the non-geometric combined pseudo-range observation value, f2 represents the frequency corresponding to the non-geometric combined carrier observation value, c represents the speed of light in vacuum, and DCB r,1|2 represents the receiver differential code bias of the receiver at frequencies f1 and f2, represents the satellite differential code bias of the satellite at frequencies f1 and f2, represents the mean value of the sum of the non-geometric combined pseudo-range observation value and the non-geometric combined carrier observation value in the same preset arc segment.

[0069] Step two: using the historical GNSS observation data collected in step one, the phase-smoothed pseudo-range or undifferenced non-combined PPP method is used to calculate the ionospheric delay and differential code bias information corresponding to each historical GNSS observation value.

[0070] In a specific embodiment, the calculation process of the phase-smoothed pseudo-range method is given. First, the non-geometric combined observation value of the pseudo-range and the carrier is obtained by using the historical GNSS observation data:

[0071]

[0072] wherein, and represent the non-geometric combined pseudo-range observation value and the non-geometric combined carrier observation value in meters, STEC represents the slant TEC on the GNSS signal path, f1 and f2 represent the frequencies corresponding to the two observation values participating in the calculation, c is the speed of light in vacuum, and DCB r,1|2 and respectively represent the differential code bias of the receiver and the satellite at frequencies f1 and f2, b r,f and denote the carrier hardware delay of the receiver and satellite respectively, λ f denotes the carrier wavelength at frequency f, denotes the ambiguity cycle of the carrier observation, t denotes the observation time.

[0073] in formula (1) b r,f and The assumption is stable and unchanged within an observation arc segment, so after removing the cycle slip, the average of the observations within the same arc segment can be obtained as follows:

[0074]

[0075] where n is the number of observations within a continuous arc segment, denotes the average of the sum of the geometry-free combined pseudorange observation and the geometry-free combined carrier observation within a continuous arc segment, and after obtaining this average, the following formula (1) can be obtained:

[0076]

[0077] Further, the STEC (as ionospheric delay) can be obtained by phase-smoothing the pseudorange observation:

[0078]

[0079] The above formula (4) is the coupled ionospheric delay and differential code bias information.

[0080] S3, according to the ionospheric model corresponding to the historical GNSS observation data, calculating the ionospheric delay corresponding to the historical GNSS observation data, and then separating the coupled ionospheric delay and differential code bias information;

[0081] Preferably, the ionospheric delay corresponding to the historical GNSS observation data is calculated according to the ionospheric model corresponding to the historical GNSS observation data, and then the coupled ionospheric delay and differential code bias information is separated, comprising: judging whether the historical GNSS observation data exists corresponding ionospheric model, when it is determined that the historical GNSS observation data exists corresponding ionospheric model, calculating the piercing point coordinates of the historical GNSS observation data at the height of the corresponding ionospheric model according to the ionospheric model corresponding to the historical GNSS observation data; calculating the vertical path value corresponding to the historical GNSS observation data according to the piercing point coordinates; calculating the ionospheric projection function value corresponding to the historical GNSS observation data, and then converting the vertical path value to the corresponding slant path value according to the ionospheric projection function value; taking the slant path value as the ionospheric delay corresponding to the historical GNSS observation data, and then separating the coupled ionospheric delay and differential code bias information.

[0082] Preferably, the ionosphere model corresponding to the historical GNSS observation data is used to calculate the ionosphere delay corresponding to the historical GNSS observation data, and then the coupled ionosphere delay and differential code bias information is separated, and the method further comprises: when it is determined that the historical GNSS observation data does not have a corresponding ionosphere model, it is assumed that the receiver differential code bias corresponding to the historical GNSS observation data and the satellite differential code bias are the same in a preset time period, and then the ionosphere model corresponding to the historical GNSS observation data is solved according to a preset ionosphere model and a differential code bias solving equation; the piercing point coordinates of the historical GNSS observation data at the height of the corresponding ionosphere model are calculated according to the ionosphere model corresponding to the historical GNSS observation data; the vertical path value corresponding to the historical GNSS observation data is calculated according to the piercing point coordinates; the ionosphere projection function value corresponding to the historical GNSS observation data is calculated, and then the vertical path value is converted into a corresponding slant path value according to the ionosphere projection function value; the slant path value is taken as the ionosphere delay corresponding to the historical GNSS observation data, and then the coupled ionosphere delay and differential code bias information is separated.

[0083] S4, separating the receiver differential code bias and the satellite differential code bias in the differential code bias information according to the separated differential code bias information;

[0084] Preferably, the method of separating the receiver differential code bias and the satellite differential code bias in the differential code bias information according to the separated differential code bias information comprises: according to the separated differential code bias information, setting the sum of the satellite differential code biases in the differential code bias information to zero, solving the corresponding receiver differential code bias, and then separating the receiver differential code bias and the satellite differential code bias in the differential code bias information.

[0085] Step three: if the existing ionosphere model product at the time corresponding to the historical GNSS observation value of the modeling area can be obtained, the product can be used to separate the differential code bias of the receiver and the satellite from the ionosphere delay, and obtain the time-varying differential code bias of the receiver and the satellite. The existing ionosphere model product is used as a known value, and the ionosphere delay value is subtracted from the phase smoothing pseudo-range observation value obtained in step two, so that the combined value of the receiver and satellite differential code bias can be obtained.

[0086] The two are separated by zero mean assumption, considering the time-varying characteristics of both, the receiver and satellite differential code bias of each epoch are estimated, since the differential code bias changes slowly, the last epoch of receiver and satellite differential code bias modified value is used as a constraint to carry out Kalman filter estimation, control its rate of change, after a period of time, the stable Kalman filter output result can be obtained. The specific implementation process is as follows:

[0087] 1、Calculate the ionospheric model results corresponding to all historical GNSS observation values of the same epoch, get the vertical path TEC corresponding to the historical GNSS observation value, denoted as Where s represents the satellite number, r represents the receiver number, t represents the current epoch.

[0088] First, calculate the piercing point coordinates of historical GNSS observation value in ionospheric model height:

[0089] z=π / 2-El

[0090]

[0091] α=z-z'

[0092]

[0093]

[0094] In the formula: A is the satellite azimuth angle, El is the satellite elevation angle, R E is the radius of the earth (6378km), H is the piercing point height, which is set to 506.7km, and λ are the latitude and longitude of the station, and λ IPP are the latitude and longitude of the piercing point. Then calculate the vertical path using the ionospheric model, the specific calculation method is different according to the model.

[0095] 2、Calculate the ionospheric projection function value MF corresponding to the historical GNSS observation value, and convert the vertical path model value in step 1 to the oblique path model value

[0096]

[0097]

[0098] In the formula, R is the radius of the earth, H0=506.7KM, a=0.9782.

[0099] 3、On the basis of formula (3) in step two, remove the ionospheric STEC represented by on the right side of the equation to get DCBr,1|2 and the combined value of all satellites is set to zero, the DCB r,1|2 and is separated, and is calculated as follows:

[0100]

[0101]

[0102] L = HX (7)

[0103] where L represents the combined value of all DCB r,1|2 and calculated using equation (3) and equation (6) in step two, H is the design matrix, the last row represents the zero mean constraint, and X is the current epoch DCB r,1|2 (t) and value to be solved, where the order in X is the previous DCB r,1|2 (t).

[0104] 4. Calculate the time-varying receiver differential code bias and satellite differential code bias value for each epoch using Kalman filtering.

[0105] Step four: If the ionospheric model product corresponding to the receiver differential code bias and the satellite differential code bias cannot be obtained in step three, first assume that the receiver differential code bias and the satellite differential code bias are the same within a day, and use the least squares method to solve the ionospheric mathematical model parameters and the differential code bias together to achieve the separation of the two.

[0106] Then use the obtained ionospheric mathematical model to solve the time-varying receiver differential code bias and the satellite differential code bias using the method in step three. Use the phase-smoothed pseudorange observation value obtained using equation (3) in step two to establish the solving equation of the ionospheric model and the differential code bias, which has one set of ionospheric model parameters for each period, and the same differential code bias parameter for each satellite and receiver within a day:

[0107]

[0108]

[0109]

[0110] L = HX (8)

[0111] where ion i (t n ) represents the ionospheric model at t nThe i-th ionospheric model parameter in the time period. Through the above manner, the ionospheric model and the DCB under the constant assumption can be obtained r,1|2 and In order to obtain the time-varying DCB r,1|2 and The ionospheric model in the above formula is brought into step three, and the time-varying DCB is obtained according to the method of step three r,1|2 (t) and

[0112] S5, according to the separated receiver differential code bias, the change rule of the receiver differential code bias is fitted, and according to the separated satellite differential code bias, the change rule of the satellite differential code bias is fitted;

[0113] Step five: analyze the time-varying receiver differential code bias and satellite differential code bias obtained in step three or step four, and use a mathematical model to fit or a time-frequency analysis method to find the change rule of each receiver differential code bias and satellite differential code bias. Since the receiver differential code bias is mainly affected by temperature, and the satellite differential code bias is mainly affected by equipment aging, a simple polynomial can be used for fitting, and the fitting result is:

[0114]

[0115] Where, A i represents the polynomial coefficient, n represents the polynomial order, t represents the local time (in seconds), and the receiver DCB data collected in history is fitted by the least square method.

[0116] S6, according to the change rule of the receiver differential code bias, the receiver differential code bias prediction value in the to-be-modeled period is estimated, and according to the change rule of the satellite differential code bias, the satellite differential code bias prediction value in the to-be-modeled period is estimated;

[0117] Step six: using the change rule obtained in step five, in the required modeling period, according to the change rule of the receiver differential code bias, the receiver differential code bias prediction value is estimated, and according to the change rule of the satellite differential code bias, the satellite differential code bias prediction value is estimated.

[0118] S7, according to the receiver differential code bias prediction value and the satellite differential code bias prediction value, the receiver differential code bias prediction value and the satellite differential code bias prediction value are removed in the GNSS observation data in the to-be-modeled period, and then the corresponding ionospheric model in the to-be-modeled period is constructed according to the removed GNSS observation data.

[0119] Preferably, the ionospheric modeling method further comprises: according to the constructed ionospheric model and corresponding GNSS observation data, removing ionospheric delay in the GNSS observation data, and then performing GNSS positioning according to the GNSS observation data after the removal.

[0120] Step seven: remove the receiver differential code bias estimate and the satellite differential code bias estimate from the GNSS observation value in the to-be-modeled period, and estimate the pure ionospheric delay information for modeling, and use the Kalman filtering method in the modeling process to estimate the ionospheric delay model parameters and the receiver and satellite differential code biases.

[0121] The data obtained in steps one to five are integrated to calculate the ionospheric model parameters in the to-be-modeled period (1s) of the ultra-high frequency, then the initial values of the receiver and satellite differential code biases in the period are estimated using formula (9), the ionospheric delay values are obtained by removing the differential code bias effect using formula (3), and the ionospheric model, DCB r,1|2 (t) and are solved using the equation described in formula (8) and the Kalman filtering method, finally the solving results are added to the differential code bias law estimation process of step five, and steps five and six are repeated. Finally, according to the constructed ionospheric model and corresponding GNSS observation data, the ionospheric delay in the GNSS observation data is removed, and then GNSS positioning is performed according to the GNSS observation data after the removal.

[0122] Embodiment two

[0123] Please refer to Figure 3 , a structure schematic diagram of an ionospheric modeling device provided by an embodiment of the present application, the device comprising: a historical observation data acquisition module, a coupling data calculation and separation module, a differential code bias information separation module, a change law fitting module, a differential code bias estimation module, and an ionospheric model construction module.

[0124] The historical observation data acquisition module is configured to acquire a plurality of historical GNSS observation data of a to-be-modeled region in a preset period; wherein the historical GNSS observation data comprises historical pseudorange observation data and historical carrier observation data of all base station receivers.

[0125] The coupling data calculation module is configured to calculate the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information comprises receiver differential code bias and satellite differential code bias.

[0126] The coupling data separation module is configured to calculate ionospheric delay corresponding to the historical GNSS observation data according to an ionospheric model corresponding to the historical GNSS observation data, and then separate the coupled ionospheric delay and differential code bias information.

[0127] The differential code bias information separation module is configured to separate receiver differential code bias and satellite differential code bias in the differential code bias information according to the separated differential code bias information.

[0128] The variation law fitting module is configured to fit a variation law of the receiver differential code bias according to the separated receiver differential code bias, and fit a variation law of the satellite differential code bias according to the separated satellite differential code bias.

[0129] The differential code bias estimation module is configured to estimate a receiver differential code bias pre-estimate value in a to-be-modeled time period according to the variation law of the receiver differential code bias, and estimate a satellite differential code bias pre-estimate value in the to-be-modeled time period according to the variation law of the satellite differential code bias.

[0130] The ionospheric model construction module is configured to remove the receiver differential code bias pre-estimate value and the satellite differential code bias pre-estimate value from GNSS observation data in the to-be-modeled time period according to the receiver differential code bias pre-estimate value and the satellite differential code bias pre-estimate value, and then construct a corresponding ionospheric model in the to-be-modeled time period according to the removed GNSS observation data.

[0131] It should be noted that the apparatus embodiments described above are only illustrative, and the units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. In addition, the connection relationship between the modules in the apparatus embodiment provided by the present application indicates that there is a communication connection between them, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0132] Those skilled in the art can clearly understand that, for the convenience and brevity, the specific working process of the apparatus described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0133] Embodiment Three

[0134] Correspondingly, the embodiment of the present application provides an electronic device, the device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the ionospheric modeling method described in the above embodiment of the present application when executing the computer program.

[0135] The electronic device can be a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The device can include but is not limited to a processor and a memory.

[0136] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor and the like. The processor is a control center of the device, and connects all parts of the device through various interfaces and lines.

[0137] Embodiment four

[0138] Correspondingly, the embodiment of the present application provides a storage medium, the storage medium comprising a stored computer program, wherein the computer program controls the device where the storage medium is located to execute the ionospheric modeling method described in the above embodiment of the present application when running.

[0139] The memory can be used to store the computer program, and the processor realizes various functions of the device by running or executing the computer program stored in the memory, and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function and the like; the data storage area can store data created according to the use of the mobile phone and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0140] The storage medium is a computer readable storage medium, and the computer program is stored in the computer readable storage medium. When the computer program is executed by a processor, steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0141] The above is the preferred embodiment of the present application. It should be noted that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which are also considered within the scope of protection of the present application.

Claims

1. A method of ionospheric modeling, characterized by, The method comprises the following steps: acquiring a plurality of historical GNSS observation data of a region to be modeled within a preset time period; wherein the historical GNSS observation data comprises historical pseudorange observation data and historical carrier observation data of all base station receivers; calculating coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information comprises receiver differential code bias and satellite differential code bias; calculating ionospheric delay corresponding to the historical GNSS observation data according to an ionospheric model corresponding to the historical GNSS observation data, and then separating the coupled ionospheric delay and differential code bias information; separating the receiver differential code bias and the satellite differential code bias in the differential code bias information according to the separated differential code bias information; fitting the variation law of the receiver differential code bias according to the separated receiver differential code bias, and fitting the variation law of the satellite differential code bias according to the separated satellite differential code bias; estimating the receiver differential code bias prediction value within the modeling period according to the variation law of the receiver differential code bias, and estimating the satellite differential code bias prediction value within the modeling period according to the variation law of the satellite differential code bias; eliminating the receiver differential code bias prediction value and the satellite differential code bias prediction value in the GNSS observation data within the modeling period according to the receiver differential code bias prediction value and the satellite differential code bias prediction value, and then constructing the corresponding ionospheric model within the modeling period according to the eliminated GNSS observation data.

2. The ionospheric modeling method of claim 1, wherein, The method further comprises the following steps: eliminating the ionospheric delay in the GNSS observation data according to the constructed ionospheric model and the corresponding GNSS observation data, and then performing GNSS positioning according to the eliminated GNSS observation data.

3. The ionospheric modeling method of claim 1, wherein, The calculation of the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data comprises the following steps: calculating the corresponding non-geometric combined pseudorange observation value according to the historical pseudorange observation data, and calculating the corresponding non-geometric combined carrier observation value according to the historical carrier observation data; calculating the mean value of the sum of the non-geometric combined pseudorange observation value and the non-geometric combined carrier observation value within the same preset arc segment, and then calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data according to the mean value and the non-geometric combined carrier observation value.

4. The ionospheric modeling method of claim 3, wherein, The coupled ionospheric delay and differential code bias information is as follows: wherein, represents the ionospheric delay, f1 represents the frequency corresponding to the geometry-free combined pseudorange observation, f2 represents the frequency corresponding to the geometry-free combined carrier observation, c represents the speed of light in vacuum, DCB r,1|2 represents the receiver differential code bias of the receiver at the frequency f1 and the frequency f2, represents the satellite differential code bias of the satellite at the frequency f1 and the frequency f2, represents the mean of the sum of the geometry-free combined pseudorange observation and the geometry-free combined carrier observation within the same preset arc segment.

5. The ionospheric modeling method of claim 1, wherein, The calculation of the ionospheric delay corresponding to the historical GNSS observation data according to the ionospheric model corresponding to the historical GNSS observation data, and then the separation of the coupled ionospheric delay and differential code bias information comprises the following steps: determining whether the historical GNSS observation data has a corresponding ionospheric model, and when it is determined that the historical GNSS observation data has a corresponding ionospheric model, calculating the piercing point coordinates of the historical GNSS observation data at the height of the corresponding ionospheric model according to the ionospheric model corresponding to the historical GNSS observation data; According to the piercing point coordinates, the vertical path value corresponding to the historical GNSS observation data is calculated; The ionospheric projection function value corresponding to the historical GNSS observation data is calculated, and then the vertical path value is converted into the corresponding slant path value according to the ionospheric projection function value; The slant path value is taken as the ionospheric delay corresponding to the historical GNSS observation data, and then the coupled ionospheric delay and differential code bias information are separated.

6. The ionospheric modeling method of claim 5, wherein, The ionospheric model corresponding to the historical GNSS observation data is calculated, and then the coupled ionospheric delay and differential code bias information are separated, and the method further comprises: When it is determined that the historical GNSS observation data does not exist corresponding ionospheric model, it is assumed that the receiver differential code bias and the satellite differential code bias corresponding to the historical GNSS observation data are the same in a preset time period, and then the ionospheric model corresponding to the historical GNSS observation data is solved according to the preset ionospheric model and the solving equation of the differential code bias; According to the piercing point coordinates, the vertical path value corresponding to the historical GNSS observation data is calculated; The ionospheric projection function value corresponding to the historical GNSS observation data is calculated, and then the vertical path value is converted into the corresponding slant path value according to the ionospheric projection function value; The slant path value is taken as the ionospheric delay corresponding to the historical GNSS observation data, and then the coupled ionospheric delay and differential code bias information are separated. The receiver differential code bias and the satellite differential code bias in the differential code bias information are separated according to the separated differential code bias information, and the method further comprises:

7. The ionospheric modeling method of claim 1, wherein, According to the separated differential code bias information, the sum of the satellite differential code bias in the differential code bias information is zero, and the corresponding receiver differential code bias is solved, and then the receiver differential code bias and the satellite differential code bias in the differential code bias information are separated. It comprises:

8. An ionospheric modeling apparatus characterized by comprising: The historical observation data acquisition module, the coupled data calculation module, the coupled data separation module, the differential code bias information separation module, the change law fitting module, the differential code bias estimation module and the ionospheric model construction module; The historical observation data acquisition module is used for acquiring a plurality of historical GNSS observation data of a preset time period in a region to be modeled; wherein the historical GNSS observation data comprises historical pseudorange observation data and historical carrier observation data of all base station receivers; The coupled data calculation module is used for calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information comprises receiver differential code bias and satellite differential code bias; The coupled data calculation module is used for calculating the coupled ionospheric delay and differential code bias information corresponding to each historical GNSS observation data; wherein the differential code bias information comprises receiver differential code bias and satellite differential code bias; The coupling data separation module is configured to calculate ionospheric delay corresponding to the historical GNSS observation data according to an ionospheric model corresponding to the historical GNSS observation data, and then separate coupled ionospheric delay and differential code bias information. The differential code bias information separation module is configured to separate receiver differential code bias and satellite differential code bias in the differential code bias information according to the separated differential code bias information. The variation law fitting module is configured to fit a variation law of the receiver differential code bias according to the separated receiver differential code bias, and fit a variation law of the satellite differential code bias according to the separated satellite differential code bias. The differential code bias estimation module is configured to estimate a receiver differential code bias prediction value in a to-be-modeled time period according to the variation law of the receiver differential code bias, and estimate a satellite differential code bias prediction value in the to-be-modeled time period according to the variation law of the satellite differential code bias. The ionospheric model construction module is configured to remove the receiver differential code bias prediction value and the satellite differential code bias prediction value from GNSS observation data in the to-be-modeled time period according to the receiver differential code bias prediction value and the satellite differential code bias prediction value, and then construct an ionospheric model corresponding to the to-be-modeled time period according to the removed GNSS observation data.

9. An electronic device, comprising: The storage medium includes a stored computer program, wherein the computer program controls a device where the storage medium is located to perform the ionospheric modeling method according to any one of claims 1 to 7 when the computer program is running.

10. A storage medium, characterized by The storage medium includes a stored computer program, wherein the computer program controls a device where the storage medium is located to perform the ionospheric modeling method according to any one of claims 1 to 7 when the computer program is running.

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