A method for constructing a hybrid order regional ionospheric model

Abstract

The application discloses a mixed order regional ionospheric model construction method, which comprises the following steps: establishing a mixed order regional ionospheric model based on observation data; according to whether the ionosphere is in a quiet period or an active period, using different orders and model parameter update intervals to establish corresponding regional ionospheric models; designing a model order self-adaptive adjustment strategy to realize switching of the mixed order regional ionospheric model to a first-order polynomial model or a second-order polynomial model; and unifying generation approaches of mixed order regional ionospheric model parameters to realize estimation of first-order / second-order polynomial model parameters. The mixed order regional ionospheric model has the advantages that, compared with the first-order polynomial method, the problem of low modeling accuracy in the ionosphere active period is overcome; compared with the second-order polynomial method, the limitations of model overfitting and modeling instability in the ionosphere quiet period are avoided; and in terms of parameter generation and modeling accuracy, the mixed order regional ionospheric model combines the advantages of the second-order model and the first-order model, thereby ensuring the accuracy and applicability of regional ionospheric modeling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ionosphere model construction, and particularly relates to a mixed order regional ionosphere model construction method. BACKGROUND

[0002] Global Navigation Satellite System (GNSS) sends navigation signals to provide real-time, continuous, all-weather positioning, navigation, and timing services for global users. After the GNSS signal enters the atmosphere, it is affected by the refraction of the ionosphere, the propagation speed of the navigation signal changes, and the ionospheric delay effect is produced. Using GNSS multi-frequency observation values, the total electron content (TEC) of the observation line of sight from the station to the satellite can be extracted. Through the projection function, the line-of-sight TEC is projected to the zenith direction to obtain the zenith direction total electron content (VTEC). Using the VTEC observation values in the region, regional ionosphere modeling can be completed. According to the regional ionosphere model, the VTEC at any position in the region can be calculated, the ionosphere change monitoring can be realized, and the ionosphere delay can be corrected to expand the GNSS service field and improve the GNSS positioning accuracy. Therefore, a simple and high-precision regional ionosphere model is of great significance in the fields of space weather monitoring and forecasting, GNSS local area enhancement, and continuous operation reference station (CORS) services.

[0003] Using a polynomial model with fixed order, regional ionosphere modeling can be completed. A first-order polynomial model is usually used to establish a VTEC observation equation, calculate the first-order polynomial coefficients, and obtain a regional ionosphere model. Although the first-order model method is simple to calculate, the modeling accuracy is low during the active period of the ionosphere. In order to obtain a high-precision ionosphere model, the current method mainly uses a high-order model to establish a VTEC observation equation and estimate the regional ionosphere model parameters. A second-order polynomial model can accurately represent the regional ionosphere electron content and its changes. However, during the quiet period of the ionosphere, the second-order polynomial model is prone to model overfitting problems, and the modeling stability needs to be improved. During the active period of the ionosphere, if the model parameters are still updated at a fixed large interval, the regional ionosphere model will be difficult to adapt to the severe changes of the ionosphere, and the modeling effect needs to be improved.

[0004] Existing research uses a single order and a fixed update interval for regional ionosphere modeling. Because the regional ionosphere changes significantly during the quiet period and the active period, a single order model is difficult to adapt to the modeling of the regional ionosphere under different change characteristics. A fixed parameter update interval is prone to problems of poor ionosphere modeling accuracy during the active period of the ionosphere.

[0005] Therefore, in order to overcome the limitations of the traditional single order model in regional ionosphere modeling and improve the regional ionosphere modeling accuracy and adaptability, the present application provides a flexible and practical mixed order regional ionosphere model construction method. SUMMARY

[0006] The application aims to provide a hybrid order regional ionospheric model construction method, thereby solving the aforementioned problems in the prior art.

[0007] To achieve the above-mentioned purpose, the technical solution adopted by the application is as follows:

[0008] A hybrid order regional ionospheric model construction method comprises the following steps,

[0009] S1, establishing a hybrid order regional ionospheric model based on observation data:

[0010] Based on the obtained VTEC of the ionosphere at the piercing points in the region, a hybrid order regional ionospheric model is established.

[0011] S2, model order switching strategy:

[0012] According to the size relationship between all VTEC in the region and the preset threshold, it is determined whether the ionosphere belongs to a quiet period or an active period, and according to the determination result, it is determined whether the hybrid order regional ionospheric model needs to be switched to a first-order polynomial model or a second-order polynomial model.

[0013] S3, model parameter unification:

[0014] According to whether the ionosphere belongs to a quiet period or an active period, the corresponding regional ionospheric model parameters are estimated by using the least square method, and when the ionosphere is in a quiet period, a constraint condition is added to it, all polynomial model coefficients are determined, and finally the regional ionospheric model parameters are obtained.

[0015] Preferably, step S1 is specifically setting the central latitude and longitude of the region, and based on the VTEC of the ionosphere at the piercing points, a hybrid order regional ionospheric model is established by using a second-order polynomial.

[0016]

[0017] Wherein, (φ, λ) is the piercing point latitude and longitude; (φ0, λ0) is the central latitude and longitude of the region, subscript i is the receiver number, and superscript j is the satellite number; is the zenith electron content of receiver i to satellite j at piercing point (φ, λ); DCB i is the hardware delay of receiver i; DCB j is the hardware delay of satellite j; A 00 , A 10 , A 01 , A 11 is the first-order polynomial model coefficient; A 20 , A 21 is the second-order polynomial model coefficient.

[0018] Preferably, by using the least squares method to estimate the parameters of the regional ionospheric model, the estimated values ​​of each polynomial coefficient and the receiver and satellite hardware delay can be obtained; based on the polynomial coefficients, the VTEC at any location in the region can be calculated, thereby obtaining the ionospheric delay correction value in the region.

[0019] Preferably, step S2 specifically includes the following:

[0020] S21. When all VTEC values ​​in the region are less than the preset threshold, the ionosphere is considered to be in a quiescent period. The mixed-order region ionosphere model needs to be switched to a first-order polynomial model, and the model parameter update interval is set to the first time period.

[0021] S22. When at least one VTEC in the region is greater than or equal to a preset threshold, the ionosphere is considered to be in an active period. The mixed-order region ionosphere model needs to be switched to a second-order polynomial model, and the model parameter update interval is set to the second time period.

[0022] Preferably, the duration of the first time period is greater than the duration of the second time period.

[0023] Preferably, step S3 specifically includes the following:

[0024] S31. If the ionosphere is in an active period, then establish a regional ionosphere model according to formula (1); use the least squares method to estimate the parameters of the regional ionosphere model, obtain all polynomial coefficients and the estimated values ​​of receiver and satellite hardware delay, and then obtain the final regional ionosphere model parameters.

[0025] S32. If the ionosphere is in a quiescent period, establish a regional ionosphere model according to formula (1) and add constraints. The constraint equation is as shown in formula (2), and the mean square error of the constraint equation is as shown in formula (3). Use the least squares method to estimate the parameters of the regional ionosphere model with constraints, obtain all polynomial coefficients and the estimated values ​​of receiver and satellite hardware delay, and then obtain the final regional ionosphere model parameters.

[0026] The constraint equations are:

[0027]

[0028] The mean square error of the constraint equations is:

[0029]

[0030] Where, σ 20 For A 20 The prior mean square error of the coefficients; σ 21 For A 21The prior mean error of the coefficient.

[0031] Preferably, before step S1, there is also step S0, observation data preparation:

[0032] S01, in the same observation period, a plurality of GNSS continuous tracking observation stations are set in the region, and multi-frequency observation data of a plurality of GNSS satellites are continuously collected;

[0033] S02, the multi-frequency observation data of the plurality of GNSS satellites are processed by using a mature phase smoothing pseudo-range method or a precise point positioning model to obtain a plurality of groups of ionospheric delays of the line of sight direction from the observation station to the navigation satellite;

[0034] S03, according to the classic ionospheric thin layer model, the longitude and latitude of the piercing point of the observation line on the thin layer are calculated;

[0035] S04, according to the zenith angle at the piercing point, the projection function is calculated;

[0036] S05, the projection function is used to project the direction ionospheric delay to the zenith direction to obtain a plurality of groups of zenith direction ionospheric electron total content VTEC at the piercing point.

[0037] The beneficial effects of the present application are: 1. The present application uses different order models to model the regional ionosphere in different periods according to the change characteristics of the regional ionosphere in the calm period and the active period, which takes advantage of different order models in the calm period and the active period of the ionosphere, and improves the accuracy of the regional ionosphere modeling in the whole period. 2. The present application designs a model order switching strategy, judges the ionospheric characteristics according to the measured VTEC, adaptively selects the model order, adaptively adjusts the model parameter update interval, and completes the adaptive switching of the model order and the update interval, which improves the adaptability of the regional ionosphere modeling method. In the active period, by increasing the model order and reducing the model parameter update interval, the effect of regional ionosphere modeling is guaranteed. 3. The present application uses a consistent observation model and estimation method to realize the unified generation and compatible application of mixed order model parameters. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 It is the principle flow chart of the model construction method in the embodiment of the present application. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical scheme and advantages of the present application clearer, further detailed description of the present application will be made in combination with the drawings. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0040] As Figure 1As shown, in this embodiment, a hybrid order regional ionospheric model construction method is provided, mainly including three parts, which are respectively based on observation data to establish a hybrid order regional ionospheric model, a model order switching strategy, and model parameter unification; before the execution of the three parts, the preparation of the observation data is needed. The following will be described with respect to the four parts:

[0041] I. Observation data preparation

[0042] This part corresponds to step S0, specifically:

[0043] In the same period, a plurality of GNSS continuous tracking observation stations are set in the region, and the multi-frequency observation data of a plurality of GNSS satellites are continuously collected; the mature phase smoothing pseudo-range method or the precise point positioning model is used to process the multi-frequency observation data of the plurality of GNSS satellites, to obtain the ionospheric delay of the line of sight direction from the station to the navigation satellite; according to the classic ionospheric thin layer model, the piercing point longitude and latitude of the observation line of sight on the thin layer are calculated; according to the zenith angle at the piercing point, the projection function is calculated; the projection function is used to project the line of sight direction ionospheric delay to the zenith direction, to obtain a plurality of groups of zenith direction ionospheric electron content VTEC at the piercing point.

[0044] II. Based on observation data to establish a hybrid order regional ionospheric model

[0045] This part corresponds to step S1, and a hybrid order regional ionospheric model is established based on the obtained VTEC at the piercing point in the region.

[0046] Specifically, in an observation period, a plurality of observation stations are set in the region, and the multi-frequency observation values of a plurality of GNSS satellites are observed to obtain a plurality of groups of VTEC observation values. Then, by setting the central longitude and latitude of the region, a hybrid order regional ionospheric model is established based on the VTEC at the piercing point and using a second-order polynomial;

[0047]

[0048] Wherein, (φ, λ) is the piercing point longitude and latitude; (φ0, λ0) is the central longitude and latitude of the region, subscript i is the receiver number, and superscript j is the satellite number; is the zenith electron content of receiver i to satellite j at the piercing point (φ, λ); DCB i is the hardware delay of receiver i; DCB j is the hardware delay of satellite j; A 00 , A 10 , A 01 , A 11 is the first-order polynomial model coefficient; A 20 , A 21 is the second-order polynomial model coefficient.

[0049] In formula (1), since the ionosphere changes significantly in the latitude direction, the coefficients related to the latitude term include the first-order term coefficients A 10 、A 11 and the second-order term coefficients A 20 、A 21 . Since the ionosphere changes gently in the longitude direction, the coefficients related to the longitude term only include the first-order term coefficients A 01 、A 11 .

[0050] For the VTEC observation values of all stations in a period, the observation equation (regional ionosphere model) is established according to formula (1). Under the reference that the sum of all satellite hardware delays is 0, the observation equation is estimated by using the least square method to obtain the estimated values of the polynomial coefficients and the receiver and satellite hardware delays. According to the polynomial coefficients, the VTEC at any position in the region can be calculated to obtain the ionosphere delay correction value in the region.

[0051] III. Model order switching strategy

[0052] According to the change rule of the regional ionosphere, the ionosphere change is divided into a quiet period and an active period. At 10-16 o'clock local time, the sun radiates and acts on the local atmosphere strongly, resulting in a relatively active ionosphere. From 16 o'clock local time to 10 o'clock of the next day, the sun radiates and acts on the local atmosphere weakly, and the ionosphere enters the quiet period. However, if the quiet period and the active period of the ionosphere are only determined according to the local time, there is a great limitation, and it is difficult to realize quantitative and accurate determination of the active period.

[0053] Since the GNSS reference station can collect multi-frequency observation data in real time, the zenith ionosphere delay and VTEC can be generated. According to the measured VTEC, whether the ionosphere is in the active period is determined, which can effectively improve the adaptability of the model and ensure the reliability of the ionosphere state determination.

[0054] This part corresponds to step S2. According to the size relationship between all VTECs in the region and the preset threshold, it is determined whether the ionosphere belongs to the quiet period or the active period, and according to the determination result, it is determined whether the mixed order regional ionosphere model needs to be switched to the first-order polynomial model or the second-order polynomial model.

[0055] Specifically, this part includes the following contents,

[0056] 1. When all VTECs in the region are less than the preset threshold, it is considered that the ionosphere is in the quiet period, and the mixed order regional ionosphere model needs to be switched to the first-order polynomial model, and the model parameter update interval is set to the first period.

[0057] 2. When at least one VTEC in the region is greater than or equal to the preset threshold value, it is considered that the ionosphere is in an active period, the mixed order regional ionosphere model needs to be switched to a second order polynomial model, and the model parameter update interval is set to a second time period.

[0058] The preset threshold value can be set according to actual conditions to better meet actual requirements. In the embodiment, the preset threshold value is 30 TECU. The lengths of the first time period and the second time period can also be set according to actual conditions to better meet actual requirements, and the length of the first time period is greater than the length of the second time period. In the embodiment, the length of the first time period is 1 hour, and the length of the second time period is 0.5 hour.

[0059] In the embodiment, the VTEC values obtained are used as the basis to judge and select the model order suitable for the change characteristics of the regional ionosphere. When the ionosphere is in a calm period, the ionosphere change and distribution are close to linear at this time, and a first order polynomial is selected for regional ionosphere modeling. Since the first order model changes gently, the model parameter update interval can refer to the ionosphere grid model parameter update interval, and 1 hour can be selected. When the ionosphere is in an active period, the ionosphere change and distribution have surface characteristics at this time, and a second order polynomial is selected for regional ionosphere modeling. Since the second order model changes significantly, the accuracy and adaptability of regional ionosphere modeling can be further improved by reducing the model parameter update interval, and the second order model parameter update interval is selected to be 0.5 hour.

[0060] According to the model order switching strategy, the mixed order regional ionosphere model is switched to a first order polynomial model or a second order polynomial model.

[0061] Four, model parameter unification

[0062] This part corresponds to step S3. According to whether the ionosphere belongs to a calm period or an active period, the least square method is used to estimate the corresponding regional ionosphere model parameters, and a constraint condition is added to the ionosphere in the calm period to determine all polynomial model coefficients, and then the final regional ionosphere model parameters are obtained.

[0063] Specifically, this part includes the following contents,

[0064] 1. If the ionosphere is in an active period, a regional ionosphere model is established according to formula (1); the least square method is used to estimate the regional ionosphere model parameters, all polynomial coefficients and the estimated value of the receiver and satellite hardware delay are obtained, and then the final regional ionosphere model parameters are obtained;

[0065] 2. If the ionosphere is in a quiet period, a regional ionospheric model is established according to formula (1), and a constraint condition is added, the constraint condition equation is formula (2), and the mean error of the constraint condition equation is formula (3); the least square method is used to estimate the regional ionospheric model parameters with the constraint condition, to obtain all polynomial coefficients and the estimated value of the receiver and satellite hardware delay, and to further obtain the final regional ionospheric model parameters;

[0066] The constraint condition equation is:

[0067]

[0068] The mean error of the constraint condition equation is:

[0069]

[0070] wherein, σ 20 is the prior mean error of the A 20 coefficient; σ 21 is the prior mean error of the A 21 coefficient. Formula (2) can be used as an observation equation in the least square method, and formula (3) can be used as the mean error of the observation equation in the least square method, so that the constraint condition is included in the least square observation equation, and the regional ionospheric model parameters with the constraint condition are estimated by using the least square method.

[0071] After the model parameters of the mixed model are uniformly processed, the model parameters generated by the mixed model and the number of second-order model coefficients are the same, and the types are consistent, so that the mixed model observation equation and the estimated parameters are unified. By adding the constraint condition equation, the smooth switching of the second-order model to the first-order model is realized, and the adaptability of the regional ionospheric modeling is improved.

[0072] In this embodiment, for the VTEC observation data in the regional GNSS tracking observation network, the regional ionospheric modeling is carried out. First, the measured VTEC within 1 hour is taken as the judgment condition, and the model order and the update interval are selected according to the model order switching strategy. Secondly, for all the measured VTEC within the update interval, the observation equation is established according to formula (1). If the model order is one order, formula (2) and formula (3) are added as constraint condition observation equations. Finally, the model parameters are generated according to the model parameter generation method, and the regional ionospheric modeling is completed. Through the above process, the method of the application makes full use of the representation ability of the first-order polynomial model to linearly and gently change the characteristics, and carries out the regional ionospheric modeling in the calm period. The representation ability of the second-order polynomial to the surface characteristics in the short update interval is utilized, and the regional ionospheric modeling in the active period is carried out. The model order switching strategy is designed based on the measured ionospheric VTEC, and the adaptive selection of the ionospheric model order and the setting of the model parameter update interval are completed. The unified generation method of the mixed model parameters is provided, and based on the second-order model, the switching from the second-order model to the first-order model is completed by selecting and adding the constraint condition equation, and the model parameter generation is realized uniformly according to the same model parameter and estimation method. The method of the application breaks through the shortcomings of a single ionospheric model, overcomes the limitation of fixed ionospheric model parameter update interval, and guarantees the accuracy and adaptability of the regional ionospheric modeling.

[0073] By adopting the above technical solutions disclosed in the application, the following beneficial effects are obtained:

[0074] The application provides a mixed-order regional ionospheric model construction method. According to the change characteristics of the regional ionosphere in the calm period and the active period, different order models are used to model the regional ionosphere in different periods, the modeling advantages of different order models in the calm period and the active period of the ionosphere are given play to, and the accuracy of the regional ionosphere modeling in the whole period is improved. The application designs a model order switching strategy, judges the ionospheric characteristics according to the measured VTEC, adaptively selects the model order, adaptively adjusts the model parameter update interval, completes the adaptive switching of the model order and the update interval, and improves the adaptability of the regional ionosphere modeling method. In the active period, the model order is increased and the model parameter update interval is reduced, so that the effect of the regional ionosphere modeling is guaranteed. The application uses the same observation model and estimation method to realize the unified generation and compatible application of the mixed-order model parameters.

[0075] The above only describes the preferred embodiments of the application, and it should be noted that those skilled in the art can make several improvements and refinements without departing from the principles of the application, and these improvements and refinements should also be regarded as the protection scope of the application.

Claims

1. A method for constructing a mixed-order region ionospheric model, characterized in that: Includes the following steps, S1. Establish a mixed-order region ionospheric model based on observation data: A mixed-order regional ionospheric model was established based on the total ionospheric electron volume (VTEC) at multiple puncture points within the region in the zenith direction. S2, Model Order Switching Strategy: Based on the relationship between all VTEC values ​​in the region and the preset threshold, the ionosphere is determined to be in a quiescent or active phase. Based on the determination results, it is determined whether the ionosphere model in the mixed-order region needs to be switched to a first-order polynomial model or a second-order polynomial model. S3. Model parameters are unified: Based on whether the ionosphere is in a quiescent or active phase, the least squares method is used to estimate the corresponding regional ionosphere model parameters. When the ionosphere is in a quiescent phase, constraints are added to determine all polynomial model coefficients, and the final regional ionosphere model parameters are obtained. Step S1 specifically involves setting the latitude and longitude of the region center, and establishing a mixed-order regional ionospheric model based on the total ionospheric electron volume VTEC at multiple puncture points in the zenith direction using a second-order polynomial. （1） in, The latitude and longitude of the puncture point; The latitude and longitude of the regional center, subscript For receiver number, superscript Number the satellite; For receiver For satellite At the puncture point The total number of zenith electrons at that location; For receiver Hardware latency; For satellite Hardware latency; , , , These are the coefficients of the first-order polynomial model. , These are the coefficients of the second-order polynomial model; Step S2 specifically includes the following: S21. When all VTEC values ​​in the region are less than the preset threshold, the ionosphere is considered to be in a quiescent period. The mixed-order region ionosphere model needs to be switched to a first-order polynomial model, and the model parameter update interval is set to the first time period. S22. When at least one VTEC in the region is greater than or equal to a preset threshold, the ionosphere is considered to be in an active period. The mixed-order region ionosphere model needs to be switched to a second-order polynomial model, and the model parameter update interval is set to the second time period. The duration of the first time period is greater than the duration of the second time period; Step S3 specifically includes the following: S31. If the ionosphere is in an active period, then establish a regional ionosphere model according to formula (1); use the least squares method to estimate the parameters of the regional ionosphere model, obtain all polynomial coefficients and the estimated values ​​of receiver and satellite hardware delay, and then obtain the final regional ionosphere model parameters. S32. If the ionosphere is in a quiet period, then establish a regional ionosphere model according to formula (1) and add constraints. The constraint equation is as shown in formula (2), and the mean square error of the constraint equation is as shown in formula (3). Use the least squares method to estimate the parameters of the regional ionosphere model with constraints, obtain all the polynomial coefficients and the estimated values ​​of receiver and satellite hardware delay, and then obtain the final regional ionosphere model parameters. The constraint equations are: （2） The mean square error of the constraint equations is: （3） in, for The prior mean square error of the coefficients; for The prior mean square error of the coefficients.

2. The method for constructing a mixed-order region ionosphere model according to claim 1, characterized in that: By using the least squares method to estimate the parameters of the regional ionospheric model, we can obtain the estimates of the polynomial coefficients and the hardware delays of the receiver and satellite. Based on the polynomial coefficients, we can calculate the VTEC at any location within the region, and thus obtain the ionospheric delay correction value within the region.

3. The method for constructing a mixed-order region ionosphere model according to claim 2, characterized in that: Before step S1, there is also S0, observation data preparation: S01. During the same observation period, multiple GNSS continuous tracking observation stations are set up in the area to continuously collect multi-frequency observation data from multiple GNSS satellites. S02. Utilize mature phase smoothing pseudorange methods or precise single-point positioning models to process multi-frequency observation data from multiple GNSS satellites and obtain multiple sets of ionospheric delays in the line-of-sight direction from observation stations to navigation satellites. S03. Based on the classic thin-layer ionospheric model, calculate the latitude and longitude of the piercing point of the observation line on the thin layer; S04. Calculate the projection function based on the zenith angle at the puncture point; S05. Using the projection function, the ionospheric delay is projected to the zenith direction to obtain the total ionospheric electrons VTEC at the zenith direction at multiple puncture points.

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