Method and system for constructing and correcting ionosphere mapping function considering space-time distribution

Abstract

The invention discloses a method and a system for constructing and correcting an ionospheric mapping function considering spatial-temporal distribution. Aiming at the problem that the error is difficult to completely eliminate due to the complexity of spatio-temporal change of the ionized layer, the method can be used for solving the problem that the error is difficult to completely eliminate through the combined action of observation data acquisition, STEC calculation, ionized layer thin layer area grid division, VTEC acquisition, BP neural network (BPNN) model construction and sample training model selection. The invention provides an ionosphere model and an ionosphere correction method based on the ionosphere model. The method can adapt to geographical position differences, daily periodic changes and seasonal changes, so that more accurate and reliable positioning services are provided for users.

Description

Technical Field

[0001] The present invention relates to the field of GNSS ionospheric delay correction, and in particular to a construction and correction method and system for an ionospheric mapping function taking into account temporal and spatial distribution. Background Art

[0002] The delay caused by ionospheric refraction is one of the main errors in GNSS applications. Due to the complexity of the temporal and spatial changes of the ionosphere, this error is difficult to completely eliminate. The total electron content (TEC) in the ionosphere is one of the important quantitative parameters used to represent the ionosphere. It is the sum of the electron content integrals of the path between the ground receiver and the satellite. In ionospheric applications, TEC is often divided into the slant total electron content (Slant TEC) on the signal propagation path and the vertical total electron content (Vertical TEC) in the zenith direction. The ionospheric mapping function (MF) is a function that realizes the conversion between the two. It is expressed as the ratio of STEC to VTEC and is one of the important factors affecting the accuracy of ionospheric modeling and the use of ionospheric products.

[0003] Traditional ionospheric delay correction methods, such as the Klobuchar model and other real-time or near-real-time correction services, mostly rely on simplified assumptions and averaged parameters, which are not applicable to all geographic locations or all times, especially when the ionospheric activity is intense. Most of the existing ionospheric model products only provide VTEC at the user's puncture point, which needs to be converted into STEC using a projection function in actual PPP-RTK positioning applications. If accurate STEC information can be provided, the positioning convergence speed can be greatly improved, and the ambiguity fixation rate can also be significantly improved. Therefore, the ionospheric projection function is very important for improving the application capabilities of high-precision positioning. Summary of the invention

[0004] In order to solve the problems that most traditional ionospheric delay correction methods rely on simplified assumptions and averaged parameters and are not applicable to all geographical locations or times, and the STEC information provided by existing ionospheric mapping functions is not accurate, the present invention provides a construction and correction method and system for an ionospheric mapping function that takes into account temporal and spatial distribution. By considering the influence of temporal and spatial distribution, the mapping function is dynamically updated, which can adapt to differences in geographical locations, daily cycle changes and seasonal changes, thereby providing users with more accurate and reliable positioning services.

[0005] According to one aspect of the present invention, there is provided a method for constructing an ionospheric mapping function taking into account temporal and spatial distribution, comprising: Acquire multi-factor data taking into account the temporal and spatial distribution, including observation data at the receiver, position, clock error, ionosphere and differential code bias; Based on the acquired multi-factor data, non-difference and non-combination estimation is performed to calculate the altitude angle, azimuth, longitude, latitude and ionospheric STEC of the ionospheric puncture point; The thin ionosphere region at the receiver is divided into grids, and the VTEC of each grid is calculated in combination with the ionospheric STEC; Construct an ionospheric model, whose input layers are altitude, azimuth, longitude, latitude, time and VTEC, and whose output layer is the corrected ionospheric STEC; VTEC training samples are selected to train the constructed ionosphere model, and the trained ionosphere model is output for ionospheric delay correction.

[0006] As a further technical solution, non-difference and non-combination estimation is performed based on the acquired multi-factor data, including: Perform a non-difference non-combination estimation based on the observed data to obtain the carrier phase observation value, pseudo-range observation value and receiver differential code deviation; According to the carrier phase observation value, the pseudorange observation value and the receiver differential code deviation, combined with the position and clock error of the receiver, a secondary non-difference non-combined estimation is performed to obtain the ionospheric STEC.

[0007] As a further technical solution, the thin ionosphere area at the receiver is divided into grids, and the VTEC of each grid is calculated in combination with the ionosphere STEC, including: The thin ionosphere region is divided according to a 2′x2′ grid; The STEC that passes through the same grid within several minutes is taken as a set of data, and the data with elevation angle greater than 80° are selected for VTEC calculation; Based on the selected STEC data set, VTEC is calculated using the ionospheric mapping function MF, and the calculation results of the selected STEC data set are averaged as the VTEC reference result of the current grid.

[0008] As a further technical solution, the training of the ionosphere model further includes: The number of neuron nodes in the hidden layer of the ionosphere model is determined using the a posteriori method; The VTEC grid data starting from the first day of the year, with a certain number of days as intervals and ending on the 365th day are selected as training samples to train the ionosphere model.

[0009] According to one aspect of the present invention, there is provided an ionospheric delay correction method, which is implemented based on the method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution, and the method comprises: Get the ephemeris and position at the receiver; Calculate the attribute parameters of the ionospheric piercing point according to the acquired ephemeris and position, including altitude angle, azimuth angle, longitude and latitude; Based on the calculated ionospheric puncture point, VTEC is calculated by interpolation combined with the ionospheric delay at the receiver. The calculated altitude, azimuth, longitude, latitude and VTEC, together with the receiver time, are fed into the trained ionospheric model to output the corrected STEC.

[0010] According to one aspect of the present invention, there is provided a system for constructing an ionospheric mapping function taking into account temporal and spatial distribution, comprising: The data acquisition module is used to acquire multi-factor data taking into account the temporal and spatial distribution, including the observation data, position, clock error, ionosphere and differential code deviation at the receiver; The STEC calculation module is used to perform non-difference and non-combination estimation based on the acquired multi-factor data to calculate the altitude angle, azimuth, longitude, latitude and ionospheric STEC of the ionospheric puncture point; The VTEC calculation module is used to grid the thin ionosphere area at the receiver and calculate the VTEC of each grid in combination with the ionosphere STEC; Model building module, used to build ionospheric model, whose input layers are altitude angle, azimuth, longitude, latitude, time and VTEC, and output layer is corrected ionospheric STEC; The model training module is used to select VTEC training samples, train the constructed ionospheric model, and output the trained ionospheric model for ionospheric delay correction.

[0011] According to one aspect of the present invention, an ionospheric delay correction system is provided, which is implemented based on a constructed ionospheric model, and the system comprises: A first processing module, used to obtain ephemeris and position at a receiver; The second processing module is used to calculate the attribute parameters of the ionospheric puncture point according to the acquired ephemeris and position, including altitude angle, azimuth angle, longitude and latitude; A third processing module is used to interpolate the calculated ionospheric puncture point in combination with the ionospheric delay at the receiver to calculate VTEC; The fourth processing module is used to send the calculated altitude angle, azimuth angle, longitude, latitude and VTEC, together with the receiver time, into the trained ionospheric model and output the corrected STEC.

[0012] According to one aspect of the present invention, there is provided a device for constructing an ionospheric mapping function taking into account the temporal and spatial distribution, comprising a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of a method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution.

[0013] According to one aspect of the present invention, an ionospheric delay correction device is provided, comprising a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of an ionospheric delay correction method.

[0014] According to one aspect of the present specification, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions enable the computer to execute the steps of a method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution or to execute the steps of an ionospheric delay correction method.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Compared with the common single-layer projection functions MSLM MF, Klobuchar MF, and PLOY MF, the BP MF mapping function constructed in the present invention takes into account the influence of factors such as different longitudes, latitudes, times, and azimuths, and combines real-time or near real-time ionospheric monitoring data to dynamically update the mapping function, thereby further improving the real-time and accuracy of the correction.

[0016] 2. The present invention takes into account the geographical and temporal variations of the ionosphere and can adapt to different geographical locations and times, including corrections when the ionospheric activity is abnormal (such as during solar storms), and is more adaptable than traditional models. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings used in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A schematic flow chart of a method for constructing an ionospheric mapping function taking into account both temporal and spatial distribution provided in an embodiment of the present invention.

[0019] Figure 2 A schematic flow chart of a method for correcting an ionospheric mapping function taking into account temporal and spatial distribution provided in an embodiment of the present invention.

[0020] Figure 3 A schematic diagram of a system for constructing an ionospheric mapping function taking into account temporal and spatial distribution provided by an embodiment of the present invention.

[0021] Figure 4 A schematic diagram of a correction system for an ionospheric mapping function taking into account temporal and spatial distribution provided by an embodiment of the present invention.

[0022] Figure 5 A schematic diagram of an ionospheric model for obtaining VTEC provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In view of the problems existing in the traditional ionospheric delay correction method, the present invention provides a mapping function that can be dynamically updated in real time from the perspective of the ionospheric mapping function, which can adapt to the differences in geographical locations, daily cycle changes and seasonal changes, and make up for the delay caused by ionospheric refraction, thereby providing users with more accurate and reliable positioning services.

[0024] The terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions, for example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to the steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention are arbitrarily combined with each other to form a new technical solution. This combination is not restricted by the sequence of steps and / or the structural composition mode, but must be based on the ability of ordinary technicians in this field to achieve. When the combination of technical solutions is contradictory or cannot be achieved, it should be considered that this combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0026] The embodiment of the present invention provides a method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution. First, the observation data, position, clock error, ionosphere and differential code deviation at a receiver are obtained. These factors take into account the temporal and spatial distribution, so that the calculated ionosphere model can adapt to the difference in geographical location, daily cycle change and seasonal change; then, non-difference non-combination estimation is performed according to the obtained multi-factor data, and the altitude angle, azimuth angle, longitude, latitude and ionospheric STEC of the ionospheric puncture point are calculated; then, the ionospheric thin layer area at the receiver is grid-divided, and the VTEC of each grid is calculated in combination with the ionospheric STEC; finally, an ionospheric model is constructed, the input layer of which is the altitude angle, azimuth angle, longitude, latitude, time and VTEC, and the output layer is the corrected ionospheric STEC, VTEC training samples are selected, the constructed ionosphere model is trained, and the trained ionosphere model is output for ionospheric delay correction.

[0027] See also Figure 1 , a method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution provided by an embodiment of the present invention specifically comprises the following steps: Step 1, obtain multi-factor data, including observation data, position, clock error, ionosphere and differential code deviation at the receiver. Among them, the observation data selects the observation data with a sampling rate of 30 seconds from the Chinese CORS station. As an implementation method, the obtained observation data, ephemeris, ionosphere and DCB products can be obtained from ftp: / / ftp.aiub.unibe.ch.

[0028] Step 2, calculation of STEC, includes PPP estimation and puncture point calculation.

[0029] This step uses the non-differenced non-combined PPP to calculate the ionospheric STEC. Non-differenced non-combined PPP is a positioning model that can retain more observation data without amplifying observation noise. Non-differenced grouping and PPP uses ionospheric STEC as a parameter to be estimated in the observation equation, and can solve the ionospheric STEC while solving other conventional parameters.

[0030] The PPP estimation includes: performing a non-differenced non-combined PPP estimation according to the observation data to obtain a carrier phase observation value, a pseudorange observation value and a receiver differential code bias; performing a second non-differenced non-combined PPP estimation according to the carrier phase observation value, the pseudorange observation value and the receiver differential code bias in combination with the position and clock error of the receiver to obtain the ionospheric STEC.

[0031] The calculation of ionospheric STEC uses the carrier phase observations and pseudorange observations of a single satellite to estimate the receiver position and clock errors through a model, and then calculates the ionospheric STEC. The specific method is:

[0032] Where STEC is the tilted total electron content, is the pseudorange observation value, is the carrier phase observation value, and DCB is the receiver differential code deviation.

[0033] This step uses non-differential non-combined PPP to calculate the puncture point attribute parameters (longitude Lat, latitude Lon, azimuth Alt, altitude Elev). Compared with the traditional dual-frequency differential technology, non-differential non-combined PPP does not require additional base station data and has the advantages of low cost and wide application range.

[0034] The puncture point is the intersection of the satellite receiver line and the thin layer of the ionosphere.

[0035]

[0036] In the formula, is the angle of the piercing point at the center of the earth, is the satellite altitude angle, r is the radius of the earth (r=6371km), and H is the height of the ionosphere thin layer (H=375km).

[0037]

[0038] In the formula, is the longitude and latitude of the puncture point, is the receiver longitude and latitude, is the azimuth of the satellite.

[0039] Step 3, ionospheric thin layer regional grid division. The ionosphere is at an altitude of 60km-2000km from the ground, but the electron content is mainly concentrated at an altitude of 300km-500km. The electron density of the ionosphere is the highest and the electron content is the largest within this altitude range. In order to facilitate the study of ionospheric characteristics, all electron contents in the ionosphere are usually fitted to an ideal thin layer at a certain altitude during the ionospheric modeling process. The embodiment of the present invention divides the data into ionospheric thin layer regional grids according to the position of each station satellite puncture point. According to the divided grid, the spatial resolution can be improved, information can be fully acquired, it is suitable for local analysis, and data processing is simplified.

[0040] The specific steps are: Step 3.1, divide the ionospheric thin layer region according to a 2′x2′ grid; In step 3.2, the STEC that passes through the same grid within 5 minutes is taken as a set of data, and the data with an elevation angle greater than 80° are selected for the subsequent VTEC calculation.

[0041] Step 4, get VTEC. See Figure 5In this step, the data that passes through the same grid within 5 minutes and has an altitude angle greater than 80° are selected to calculate VTEC using MSLM MF, and the average is taken as the VTEC reference result of the grid. This is because the VTEC that passes through the same grid within 5 minutes is approximately the same. At the same time, it is considered that the MSLM MF conversion error can be ignored when the altitude angle is greater than 80 degrees. When the altitude angle is greater than 80 degrees, the path of the signal passing through the atmosphere is shorter, and the impact of ionospheric delay is relatively small, which can improve the applicability and practicality of the algorithm.

[0042]

[0043] In the formula, STEC is the inclined total electron content on the signal propagation path, VTEC is the vertical total electron content in the zenith direction, is the satellite altitude angle, is the satellite zenith angle at the puncture point, r is the radius of the earth (r=6371km), and H is the height of the ionosphere thin layer (H=375km).

[0044]

[0045] Where STEC is the inclined total electron content on the signal propagation path, and VTEC is the vertical total electron content in the zenith direction.

[0046] Step 5: Construct a BP neural network (BPNN) model as the ionosphere model. Select BP neural network (BPNN) to construct the ionosphere mapping function. When the sample is large enough, BPNN can accurately fit the nonlinear relationship between input and output.

[0047] The BP neural network structure includes an input layer, a hidden layer and an output layer. The present invention selects six neurons consisting of altitude angle, azimuth, longitude, latitude, time and VTEC as the input layer, and the output layer is STEC of the ionosphere, and uses a posteriori method to determine the optimal number of neuron nodes in the hidden layer. This is because in the hidden layer, the number of neurons determines the performance of BPNN. Too few neurons may lead to underfitting, and too many neurons may lead to overfitting, which will also affect the efficiency of model training.

[0048] The optimal number of neuron nodes in the hidden layer is determined as follows: The optimal number of neuron nodes in the hidden layer is determined by the a posteriori method, and the hidden layer nodes are traversed from 6 to 13, and the verification accuracy of each number of nodes is output. According to the results, when the number of hidden layer neuron nodes is 8, the RMS of the model is the smallest.

[0049] Step 6, select a sample training model to achieve ionospheric delay correction. To ensure the modeling efficiency of the model and take into account the seasonal changes in the ionospheric mapping relationship, the optimal number of hidden layer nodes obtained in step 5 is 8. The present invention selects VTEC grid data starting from DOY1, with an interval of 7 days and ending at DOY365, totaling 52 days, for modeling.

[0050] The model is trained using the selected samples, and when the training accuracy is reached, the trained model is output for ionospheric delay correction.

[0051] See also Figure 2 The embodiment of the present invention provides an ionospheric delay correction method, which is implemented based on the method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution described in the above embodiment, and includes the following steps: Step S1, obtaining ephemeris and position at the receiver.

[0052] Among them, the ephemeris product can be obtained from ftp: / / ftp.aiub.unibe.ch.

[0053] Step S2, calculate the attribute parameters of the ionospheric puncture point according to the acquired ephemeris and position, including altitude angle, azimuth angle, longitude and latitude. Here, the puncture point can be calculated according to the ephemeris and position, or it can be calculated by non-difference non-combined PPP estimation.

[0054] Step S3, interpolating the calculated ionospheric puncture point in combination with the ionospheric delay at the receiver to calculate VTEC.

[0055] Step S4, the calculated altitude angle, azimuth angle, longitude, latitude and VTEC, together with the receiver time, are sent to the trained ionospheric model, and the corrected STEC is output.

[0056] The embodiment of the present invention takes into account the geographical and temporal changes of the ionosphere, and can adapt to different geographical locations and times by dynamically updating the mapping function, including corrections when the ionospheric activity is abnormal (such as during a solar storm), and has stronger adaptability than traditional models.

[0057] The implementation basis of each embodiment of the present invention is implemented by programmed processing by a device with a processor function. Therefore, in engineering practice, the technical solutions and functions of each embodiment of the present invention are encapsulated into various modules. Based on this reality, on the basis of the above embodiments, an embodiment of the present invention provides a system for constructing an ionospheric mapping function taking into account the temporal and spatial distribution, and the system is used to execute a method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution in the above method embodiment.

[0058] See also Figure 3The system includes: a data acquisition module, which is used to acquire multi-factor data taking into account the temporal and spatial distribution, including observation data, position, clock error, ionosphere and differential code deviation at the receiver; an STEC calculation module, which is used to perform non-difference non-combination estimation based on the acquired multi-factor data, and calculate the altitude angle, azimuth angle, longitude, latitude and ionospheric STEC of the ionospheric puncture point; a VTEC calculation module, which is used to grid the ionospheric thin layer area at the receiver, and calculate the VTEC of each grid in combination with the ionospheric STEC; a model construction module, which is used to construct an ionospheric model, whose input layer is the altitude angle, azimuth angle, longitude, latitude, time and VTEC, and the output layer is the corrected ionospheric STEC; a model training module, which is used to select VTEC training samples, train the constructed ionospheric model, and output the trained ionospheric model for ionospheric delay correction.

[0059] The embodiment of the present invention provides a system for constructing an ionospheric mapping function that takes into account the temporal and spatial distribution. The system aims to solve the problems that most traditional ionospheric delay correction methods rely on simplified assumptions and averaged parameters, are not applicable to all geographical locations or times, and the STEC information provided by the existing ionospheric mapping function is not accurate enough. Figure 3 Several modules in it dynamically update the mapping function by considering the influence of spatiotemporal distribution, which can adapt to the differences in geographical locations, daily cycle changes and seasonal changes, thereby providing users with more accurate and reliable positioning services.

[0060] It should be noted that the system embodiment provided by the present invention is used to implement the methods in the above method embodiment as well as the methods in other method embodiments provided by the present invention. The only difference is that the corresponding functional modules are set. The principle is basically the same as the principle of the above system embodiment provided by the present invention. As long as the technical personnel in this field refer to the specific technical solutions in other method embodiments on the basis of the above system embodiment, obtain the corresponding technical means and the technical solutions composed of these technical means by combining the technical features, and on the premise of ensuring the practicality of the technical solutions, improve the modules in the above system embodiment to obtain the corresponding system class embodiments, which are used to implement the methods in other method class embodiments. For example: Based on the content of the above system embodiment, as a preferred embodiment, in an embodiment of the present invention, a system for constructing an ionospheric mapping function taking into account the temporal and spatial distribution is provided, wherein the VTEC calculation module is further used to execute the following instructions: The thin ionosphere region is divided according to a 2′x2′ grid; The STEC that passes through the same grid within several minutes is taken as a set of data, and the data with elevation angle greater than 80° are selected for VTEC calculation; Based on the selected STEC data set, VTEC is calculated using the ionospheric mapping function MF, and the calculation results of the selected STEC data set are averaged as the VTEC reference result of the current grid.

[0061] Based on the content of the above system embodiment, as a preferred embodiment, in the embodiment of the present invention, a system for constructing an ionospheric mapping function taking into account the temporal and spatial distribution is provided, wherein the STEC calculation module is further used to execute the following instructions: Perform a non-difference non-combination estimation based on the observed data to obtain the carrier phase observation value, pseudo-range observation value and receiver differential code deviation; According to the carrier phase observation value, the pseudorange observation value and the receiver differential code deviation, combined with the position and clock error of the receiver, a secondary non-difference non-combined estimation is performed to obtain the ionospheric STEC.

[0062] Based on the content of the above system embodiment, as a preferred embodiment, a system for constructing an ionospheric mapping function taking into account the temporal and spatial distribution is provided in an embodiment of the present invention, wherein the model training module is further used to execute the following instructions: The number of neuron nodes in the hidden layer of the ionosphere model is determined using the a posteriori method; The VTEC grid data starting from the first day of the year, with a certain number of days as intervals and ending on the 365th day are selected as training samples to train the ionosphere model.

[0063] On the basis of the above-mentioned embodiments, an embodiment of the present invention further provides an ionospheric delay correction system, which is implemented based on the ionospheric model constructed in the above-mentioned embodiments. The system is used to execute an ionospheric delay correction method in the above-mentioned method embodiment.

[0064] See also Figure 4 The system includes: a first processing module for acquiring the ephemeris and position at the receiver; a second processing module for calculating the attribute parameters of the ionospheric piercing point according to the acquired ephemeris and position, including the altitude angle, azimuth angle, longitude and latitude; a third processing module for interpolating the calculated ionospheric piercing point in combination with the ionospheric delay at the receiver to calculate VTEC; a fourth processing module for sending the calculated altitude angle, azimuth angle, longitude, latitude and VTEC, together with the receiver time, into the trained ionospheric model to output the corrected STEC.

[0065] An ionospheric delay correction system provided by an embodiment of the present invention aims at the problem that most traditional ionospheric delay correction methods rely on simplified assumptions and averaged parameters and are not applicable to all geographical locations or times. Figure 4Several modules in it, through the constructed ionospheric model, take into account the geographical and temporal changes of the ionosphere, and can adapt to different geographical locations and times, including corrections when the ionospheric activity is abnormal (such as during solar storms).

[0066] Based on the same inventive concept as the aforementioned embodiment, an embodiment of the present invention also provides a device for constructing an ionospheric mapping function that takes into account the temporal and spatial distribution, including a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of a method for constructing an ionospheric mapping function that takes into account the temporal and spatial distribution.

[0067] Based on the same inventive concept as the aforementioned embodiment, an embodiment of the present invention further provides an ionospheric delay correction device, comprising a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of the ionospheric delay correction method.

[0068] In an embodiment of the present invention, the memory may be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), etc., or a volatile memory (volatile memory), such as a random-access memory (RAM). The memory is any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in an embodiment of the present invention may also be a circuit or any other device that can implement a storage function, for storing program instructions and / or data.

[0069] In the embodiments of the present invention, the processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiments of the present invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0070] Based on the same inventive concept as the aforementioned embodiment, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the steps of a method for constructing an ionospheric mapping function that takes into account the temporal and spatial distribution or to execute the steps of a method for correcting ionospheric delay.

[0071] In summary, the present invention aims at the problem that the error is difficult to be completely eliminated due to the complexity of the spatiotemporal changes of the ionosphere. By acquiring observation data, calculating STEC, gridding the thin ionosphere region, acquiring VTEC, constructing a BP neural network (BPNN) model, and selecting a sample training model, an ionosphere model and an ionosphere correction method based on the model are provided. The present invention can adapt to the differences in geographical locations, daily cycle changes, and seasonal changes, thereby providing users with more accurate and reliable positioning services.

[0072] It should be understood that parts not elaborated in detail in this specification belong to the prior art.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing an ionospheric mapping function taking into account both temporal and spatial distribution, characterized in that: include: Acquire multi-factor data taking into account the temporal and spatial distribution, including observation data at the receiver, position, clock error, ionosphere and differential code bias; Based on the acquired multi-factor data, non-difference and non-combination estimation is performed to calculate the altitude angle, azimuth, longitude, latitude and ionospheric STEC of the ionospheric puncture point; The thin ionosphere region at the receiver is divided into grids, and the VTEC of each grid is calculated in combination with the ionospheric STEC; Construct an ionospheric model, whose input layers are altitude, azimuth, longitude, latitude, time and VTEC, and whose output layer is the corrected ionospheric STEC; VTEC training samples are selected to train the constructed ionosphere model, and the trained ionosphere model is output for ionospheric delay correction.

2. The method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution according to claim 1, characterized in that: Based on the acquired multi-factor data, non-difference and non-combination estimation is performed, including: Perform a non-difference non-combination estimation based on the observed data to obtain the carrier phase observation value, pseudo-range observation value and receiver differential code deviation; According to the carrier phase observation value, the pseudorange observation value and the receiver differential code deviation, combined with the position and clock error of the receiver, a secondary non-difference non-combined estimation is performed to obtain the ionospheric STEC.

3. The method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution according to claim 1, characterized in that: The thin ionosphere region at the receiver is divided into grids, and the VTEC of each grid is calculated in combination with the ionosphere STEC, including: The thin ionosphere region is divided according to a 2′x2′ grid; The STEC that passes through the same grid within several minutes is taken as a set of data, and the data with elevation angle greater than 80° are selected for VTEC calculation; Based on the selected STEC data set, VTEC is calculated using the ionospheric mapping function MF, and the calculation results of the selected STEC data set are averaged as the VTEC reference result of the current grid.

4. The method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution according to claim 1, characterized in that: The training of the ionosphere model further includes: The number of neuron nodes in the hidden layer of the ionosphere model is determined using the a posteriori method; The VTEC grid data starting from the first day of the year, with a certain number of days as intervals and ending on the 365th day are selected as training samples to train the ionosphere model.

5. An ionospheric delay correction method, implemented based on the method for constructing an ionospheric mapping function taking into account the temporal and spatial distribution according to any one of claims 1 to 4, characterized in that: The method comprises: Get the ephemeris and position at the receiver; Calculate the attribute parameters of the ionospheric piercing point according to the acquired ephemeris and position, including altitude angle, azimuth angle, longitude and latitude; Based on the calculated ionospheric puncture point, VTEC is calculated by interpolation combined with the ionospheric delay at the receiver. The calculated altitude, azimuth, longitude, latitude and VTEC, together with the receiver time, are fed into the trained ionospheric model to output the corrected STEC.

6. A system for constructing an ionospheric mapping function taking into account both temporal and spatial distribution, characterized in that: include: The data acquisition module is used to acquire multi-factor data taking into account the temporal and spatial distribution, including the observation data, position, clock error, ionosphere and differential code deviation at the receiver; The STEC calculation module is used to perform non-difference and non-combination estimation based on the acquired multi-factor data to calculate the altitude angle, azimuth, longitude, latitude and ionospheric STEC of the ionospheric puncture point; The VTEC calculation module is used to grid the thin ionosphere area at the receiver and calculate the VTEC of each grid in combination with the ionosphere STEC; Model building module, used to build ionospheric model, whose input layers are altitude angle, azimuth, longitude, latitude, time and VTEC, and output layer is corrected ionospheric STEC; The model training module is used to select VTEC training samples, train the constructed ionospheric model, and output the trained ionospheric model for ionospheric delay correction.

7. An ionospheric delay correction system, implemented based on the ionospheric model constructed according to claim 6, characterized in that: The system comprises: A first processing module, used to obtain ephemeris and position at a receiver; The second processing module is used to calculate the attribute parameters of the ionospheric puncture point according to the acquired ephemeris and position, including altitude angle, azimuth angle, longitude and latitude; A third processing module is used to interpolate the calculated ionospheric puncture point in combination with the ionospheric delay at the receiver to calculate VTEC; The fourth processing module is used to send the calculated altitude angle, azimuth angle, longitude, latitude and VTEC, together with the receiver time, into the trained ionospheric model and output the corrected STEC.

8. A device for constructing an ionospheric mapping function taking into account both temporal and spatial distribution, characterized in that: It comprises a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of a method for constructing an ionospheric mapping function taking into account temporal and spatial distribution as described in any one of claims 1 to 4.

9. An ionospheric delay correction device, characterized in that: It comprises a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of the ionospheric delay correction method as claimed in claim 5.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the steps of a method for constructing an ionospheric mapping function that takes into account the temporal and spatial distribution as described in any one of claims 1 to 4, or execute the steps of an ionospheric delay correction method as described in claim 5.

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