A method for ionospheric TEC assimilation modeling based on BeiDou GEO

Abstract

The invention discloses an ionospheric TEC assimilation modeling method based on Beidou GEO, comprising: an assimilation method: using a stepwise correction method to conduct a data assimilation experiment, taking an IRI model as prior information, and using Beidou GEO ionospheric TEC data for stepwise correction; Beidou GEO ionospheric TEC extraction; extracting the TEC grid value of the international reference ionospheric model IRI, and using an improved stepwise correction method to assimilate the Beidou GEO ionospheric TEC value into the IRI model; and evaluating the accuracy of the assimilated model. The method of the invention uses an improved stepwise correction method to assimilate it into the international reference ionospheric model IRI, and compares and analyzes it with a global ionospheric map GIM and Beidou GEO ionospheric TEC values ​​that are not involved in the modeling to evaluate its accuracy. It has important application value in improving the accuracy of GNSS navigation positioning and the disaster reduction and prevention capabilities of the space environment.

Description

Technical Field

[0001] The present invention relates to ionospheric technology, and in particular to an ionospheric TEC assimilation modeling method based on BeiDou GEO. Background Art

[0002] The ionosphere is a complex and dynamic system, exhibiting not only significant climate variability but also significant weather disturbances influenced by solar, geomagnetic, and meteorological factors. Ionospheric disturbances can severely impact navigation, shortwave communications, power grids, and other applications. To correct ionospheric errors in satellite navigation and orbital positioning and mitigate their impact on military and civilian systems, providing accurate and reliable ionospheric products is crucial for practical applications. Global Navigation Satellite System (GNSS) technology has significantly advanced global and regional ionospheric modeling, playing a crucial role in determining the dynamic characteristics of the ionosphere. Furthermore, various modeling techniques, including empirical, analytical, parameterized, and numerical models, can reproduce large-scale ionospheric morphologies and enable ionospheric predictions. However, these ionospheric modeling techniques are unable to accurately reproduce the morphology of ionospheric disturbances due to the interpolation of discrete ionospheric measurements and the lack of reliable ionospheric estimates. The above are the key challenges facing ionospheric modeling. In recent years, data assimilation technology has become a common method to improve the accuracy of monitoring and forecasting systems by assimilating observations into ionospheric models. Data assimilation technology uses an analytical algorithm to project observations onto an appropriate scale or a suitable global or regional grid, and then combines them with background model values ​​for prediction. Data assimilation methods have achieved great success in meteorology and oceanography, accumulating extensive experience and mature assimilation algorithms such as variational methods and Kalman filtering. In recent years, these assimilation methods have been widely used in ionospheric model construction. The key to ionospheric assimilation models lies in the assimilation method and the assimilation data source. Few literature has used BeiDou GEO (Geostationary Earth Orbit) ionospheric TEC to improve ionospheric model accuracy.

[0003] In the prior art:

[0004] (1) Assimilation method: The Successive Correction Method (SCM) is an iterative empirical method. The data assimilation experiment was conducted using the Successive Correction Method, which uses the IRI model as prior information and performs a gradual correction using BeiDou GEO ionospheric TEC data. is a given grid point The initial information is given by the IRI model, and the specific iteration is as follows:

[0005] (1)

[0006] Where, is the number of corrections, is the total number of grid points within the impact radius, For the Secondary observation point, For observation The first point Second estimate, For the Grid points passing through The value after iterations, is an estimate of the ratio of the measurement error variance to the prior error variance, For the At the first iteration, The weight factor of the observation value; the weight factor It is defined as a decrease in inverse proportion to the square of the distance between the observation point and the grid point or inversely proportional to the exponential of the squared distance. The weight factor is integrated with the BeiDou GEO ionospheric TEC value and is defined as follows:

[0007] (2)

[0008] Where, Grid points within the radius of the great circle and distance, is the plane correlation length between grid points, is the iterative radius of influence of a grid point on its neighborhood.

[0009] (2) Assimilated data source: Taking the International Reference Ionosphere (IRI) as the prior model, the ionospheric TEC is obtained using GNSS medium Earth Orbit (MEO) satellites and assimilated into the IRI prior model.

[0010] (1) SCM corrects the previous estimated value by the difference between the observed data and the prior information. The function weight of this method remains constant during the iteration process.

[0011] (2) The ionospheric IRI prior model is assimilated using TEC data from MEO satellites (e.g., GPS or GLONASS satellites). However, these TEC data are affected by the spatial gradient changes caused by satellite motion.

[0012] The present invention is based on an improved step-by-step correction method and utilizes the BeiDou GEO satellite ionospheric TEC and the International Reference Ionosphere model (IRI) to construct an ionospheric assimilation model. Summary of the Invention

[0013] The main purpose of the present invention is to provide an ionospheric TEC assimilation modeling method based on BeiDou GEO, which improves the SCM by selecting a suitable estimate of the ratio of the measurement error variance to the prior error variance.

[0014] The technical solution adopted by the present invention is: a BeiDou GEO-based ionospheric TEC assimilation modeling method, comprising:

[0015] Assimilation method: A data assimilation experiment was conducted using the stepwise correction method, with the IRI model as prior information and BeiDou GEO ionospheric TEC data used for stepwise correction.

[0016] BeiDou GEO ionospheric TEC extraction;

[0017] Extract the TEC grid values ​​of the International Reference Ionospheric Model (IRI) and assimilate the BeiDou GEO ionospheric TEC values ​​into the IRI model using an improved stepwise correction method.

[0018] Accuracy assessment of assimilation models.

[0019] Furthermore, the assimilation method comprises:

[0020] is a given grid point The initial information is given by the IRI model, and the specific iteration is as follows:

[0021] (1)

[0022] Where, is the number of corrections, is the total number of grid points within the impact radius, For the Secondary observation point, For observation The first point Second estimate, For the Grid points passing through The value after iterations, is an estimate of the ratio of the measurement error variance to the prior error variance, For the At the first iteration, The weight factor of the observation value; the weight factor It is defined as a decrease in inverse proportion to the square of the distance between the observation point and the grid point or inversely proportional to the exponential of the squared distance. The weight factor is integrated with the BeiDou GEO ionospheric TEC value and is defined as follows:

[0023] (2)

[0024] Where, Grid points within the radius of the great circle and distance, is the plane correlation length between grid points, is the iterative radius of influence of a grid point on its neighborhood.

[0025] Furthermore, the assimilation method further comprises:

[0026] The improved stepwise correction method (ISCM) is used to perform ionospheric TEC assimilation as follows:

[0027] (3)

[0028] Where, is the number of corrections, is the total number of grid points within the impact radius, For the After iterations on the grid points The value after For the Secondary observation point, For observation The first point Second estimate, For the At the first iteration, The weight factor for each observation, is the model variance, is the measurement error variance of the BeiDou GEO ionospheric TEC value; the BeiDou GEO ionospheric TEC value is assimilated into the IRI model through the ISCM.

[0029] Furthermore, the accuracy assessment of the assimilation model includes:

[0030] A comparative analysis is performed with the Global Ionospheric Map (GIM), and the accuracy of the ionospheric TEC values ​​is evaluated with the BeiDou GEO ionospheric TEC values ​​that are not modeled.

[0031] Advantages of the present invention:

[0032] The ionospheric TEC assimilation modeling method based on BeiDou GEO of the present invention assimilates the TEC of a fixed puncture point estimated by BeiDou GEO satellite into the International Reference Ionospheric Model (IRI) using an improved stepwise correction method, and compares and analyzes the ionospheric TEC values ​​of BeiDou GEO that are not involved in the modeling to evaluate their accuracy.

[0033] It has important application value in improving the accuracy of GNSS navigation and positioning and the disaster reduction and prevention capabilities of the space environment.

[0034] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0036] Figure 1 is a BeiDou station distribution map of the assimilation modeling of the present invention;

[0037] Figure 2 It is the ionospheric TEC distribution map of the BeiDou GEO satellite of the present invention;

[0038] Figure 3 1 is a comparison diagram of the ISCM and SCM assimilation modeling results of the present invention and the BeiDou GEO-1 satellite TEC and GIM-TEC, wherein (a) is the ionospheric VTEC value of May 8, 2017, calculated by CHBT after receiving the C01 satellite signal as a reference value diagram, and (b) is the ionospheric VTEC value of May 8, 2017, calculated by QXSZ after receiving the C01 satellite signal as a reference value diagram. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0040] The ionospheric TEC assimilation modeling method based on BeiDou GEO of the present invention includes:

[0041] (1) Assimilation method: The Successive Correction Method (SCM) is an iterative empirical method. The data assimilation experiment was conducted using the Successive Correction Method, which uses the IRI model as prior information and performs a gradual correction using BeiDou GEO ionospheric TEC data. is a given grid point The initial information is given by the IRI model, and the specific iteration is as follows:

[0042] (1)

[0043] Where, is the number of corrections, is the total number of grid points within the impact radius, For the Secondary observation point, For observation The first point Second estimate, For the Grid points passing through The value after iterations, is an estimate of the ratio of the measurement error variance to the prior error variance, For the At the first iteration, The weight factor of the observation value; the weight factor It is defined as a decrease in inverse proportion to the square of the distance between the observation point and the grid point or inversely proportional to the exponential of the square distance. Integrating the BeiDou GEO ionospheric TEC value, the weight factor is defined as follows:

[0044] (2)

[0045] Where, Grid points within the radius of the great circle and distance, is the plane correlation length between grid points, is the iterative radius of influence of a grid point on its neighborhood.

[0046] The SCM uses the difference between observed data and prior information to correct the previous estimate. The function weight of this method remains constant during the iteration process. To this end, the SCM is improved by selecting an appropriate estimate of the ratio of the measurement error variance to the prior error variance. Based on BeiDou GEO ionospheric TEC values ​​and prior model IRI information, this paper proposes an improved successive correction method (ISCM) for ionospheric TEC assimilation. The improved method is as follows:

[0047] (3)

[0048] Where, is the number of corrections, is the total number of grid points within the impact radius, For the After iterations on the grid points The value after For the Secondary observation point, For observation The first point Second estimate, For the At the first iteration, The weight factor for each observation, is the model variance, is the measurement error variance of the BeiDou GEO ionospheric TEC value; the BeiDou GEO ionospheric TEC value is assimilated into the IRI model through the ISCM.

[0049] (2) BeiDou GEO ionospheric TEC extraction. Because GEO satellites rotate synchronously with the Earth and are relatively stationary relative to the Earth, the signal propagation path between the GEO satellite and ground receivers remains virtually unchanged. Therefore, BeiDou GEO ionospheric TEC is unaffected by changes in the spatial and temporal gradients of the ionosphere. This paper utilizes undifferenced, non-combined, precise point positioning technology to extract ionospheric TEC.

[0050] (3) Extract the TEC grid values ​​of the International Reference Ionospheric Model (IRI) and assimilate the BeiDou GEO ionospheric TEC values ​​into the IRI model using an improved stepwise correction method.

[0051] (4) Accuracy assessment of the assimilated model. Comparison and analysis are performed with the Global Ionosphere Map (GIM), and the accuracy of the ionospheric TEC values ​​of the BeiDou GEO, which is not included in the modeling, is also evaluated.

[0052] The SCM method uses the difference between observed data and prior information to correct the previous estimate. The function weight of this method remains constant during the iteration process. To this end, the SCM is improved by selecting an appropriate estimate of the ratio of the measurement error variance to the prior error variance. Based on BeiDou GEO ionospheric TEC values ​​and prior model IRI information, this paper proposes an improved successive correction method (ISCM) for ionospheric TEC assimilation.

[0053] Because GEO satellites rotate synchronously with the Earth, their relative stationary nature ensures that the signal propagation path between GEO satellites and ground receivers remains virtually unchanged. Therefore, BeiDou GEO's ionospheric TEC is unaffected by variations in the spatial and temporal gradients of the ionosphere. This paper assimilates BeiDou GEO ionospheric TEC values ​​into the International Reference Ionosphere Model (IRI).

[0054] Attachment Figure 1 The distribution of Beidou stations involved in assimilation modeling is shown. In the figure, ▲ represents the stations participating in assimilation modeling, and ★ represents the stations not participating in assimilation modeling, namely CHBT and QXSZ stations.

[0055] Attachment Figure 2 The ionospheric TEC distribution of the BeiDou GEO satellite UT12 on May 8, 2017 is shown.

[0056] Attachment Figure 3 This figure shows a comparison of ISCM and SCM assimilation modeling results with BeiDou GEO-1 satellite TEC and GIM-TEC. (a) shows the ionospheric VTEC values ​​calculated by CHBT after receiving the C01 satellite signal on May 8, 2017, as a reference value. (b) shows the ionospheric VTEC values ​​calculated by QXSZ after receiving the C01 satellite signal on May 8, 2017, as a reference value. It can be seen that the results of ISCM assimilation modeling are closer to the ionospheric TEC values ​​of the BeiDou GEO satellite, indicating that ISCM assimilation modeling results are superior to SCM assimilation modeling results.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An ionospheric TEC assimilation modeling method based on BeiDou GEO, characterized in that: include: Assimilation method: The improved step-by-step correction method is used to perform data assimilation experiments. The IRI model is used as prior information and the BeiDou GEO ionospheric TEC data is used for step-by-step correction: BeiDou GEO ionospheric TEC extraction; Extract the TEC grid value of the International Reference Ionospheric Model (IRI), and use the improved stepwise correction method to assimilate the BeiDou GEO ionospheric TEC value into the IRI model; Accuracy assessment of assimilation models; The assimilation method comprises: is the initial information of a given grid point a, given by the IRI model, and the specific iteration is as follows: Where n is the number of corrections, N is the total number of grid points within the impact radius, and u b is the b-th observation point, is the nth estimate of the observation point b, is the value after n iterations at the a-th grid point, ε 2 is an estimate of the ratio of the measurement error variance to the prior error variance, is the weight factor of the bth observation at the nth iteration; the weight factor It is defined as a decrease inversely proportional to the square of the distance between the observation point and the grid point or inversely proportional to the exponential of the square distance. The weight factor is defined as follows when integrating the BeiDou GEO ionospheric TEC value: Where, d aj is the distance between grid points a and j within the radius of the great circle, cor is the plane correlation length between grid points, and R is the iterative radius of the influence of a grid point on its neighborhood; The assimilation method further comprises: The improved stepwise correction method ISCM is used to perform ionospheric TEC assimilation as follows: Where n is the number of corrections, N is the total number of grid points within the impact radius, is the value after n iterations at the a-th grid point, u b is the b-th observation point, is the nth estimate of the observation point b, is the weight factor of the bth observation at the nth iteration, std 2 is the model variance, is the measurement error variance of the BeiDou GEO ionospheric TEC value; the BeiDou GEO ionospheric TEC value is assimilated into the IRI model through ISCM; The accuracy assessment of the assimilation model includes: A comparative analysis is performed with the global ionosphere map GIM, and the accuracy of the ionosphere TEC values ​​of BeiDou GEO, which is not involved in the modeling, is also evaluated.

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