CN112444825A - Ionized layer TEC assimilation modeling method based on Beidou GEO - Google Patents

Ionized layer TEC assimilation modeling method based on Beidou GEO Download PDF

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CN112444825A
CN112444825A CN202011365483.7A CN202011365483A CN112444825A CN 112444825 A CN112444825 A CN 112444825A CN 202011365483 A CN202011365483 A CN 202011365483A CN 112444825 A CN112444825 A CN 112444825A
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assimilation
tec
ionosphere
model
beidou geo
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汤俊
刘淑琼
李垠健
高鑫
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East China Jiaotong University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
    • G01S19/072—Ionosphere corrections

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Abstract

The invention discloses an ionized layer TEC assimilation modeling method based on Beidou GEO, which comprises the following steps: an assimilation method: carrying out a data assimilation experiment by using a gradual correction method, taking an IRI model as prior information, and gradually correcting by using Beidou GEO ionized layer TEC data; extracting the Beidou GEO ionized layer TEC; extracting a TEC grid value of an international reference ionosphere model IRI, and assimilating the Beidou GEO ionosphere TEC value into the IRI model by using an improved stepwise correction method; and (5) evaluating the accuracy of the assimilation model. The method assimilates the ionized layer into an international reference ionosphere model IRI by an improved gradual correction method, and carries out comparative analysis with a global ionosphere map GIM and Beidou GEO ionosphere TEC values which do not participate in modeling to evaluate the precision of the ionized layer IRI. The method has important application value in GNSS navigation positioning accuracy improvement and disaster reduction and prevention capability in space environment.

Description

Ionized layer TEC assimilation modeling method based on Beidou GEO
Technical Field
The invention relates to an ionized layer technology, in particular to an ionized layer TEC assimilation modeling method based on Beidou GEO.
Background
Currently, the ionosphere is a complex system that exhibits not only significant climate change, but also significant weather disturbances after exposure to solar, geomagnetic, and meteorological effects. Ionospheric disturbances can have a severe impact on navigation positioning, short-wave communication, power grids, and the like. In order to correct ionospheric errors in satellite navigation and orbital positioning and to mitigate the effects of the errors on military and civilian systems, it is important to provide accurate and reliable ionospheric products as much as possible in practical applications. The Global Navigation Satellite System (GNSS) technology has greatly promoted the development of Global ionosphere modeling and regional ionosphere modeling, and plays an important role in determining the dynamic characteristics of the ionosphere. In addition, a plurality of modeling technologies such as empirical models, analytical and parametric models, and numerical models can reproduce the large-scale morphological characteristics of the ionosphere and perform ionosphere prediction. However, these ionospheric modeling techniques do not reproduce the ionospheric disturbance morphology well due to the mere interpolation of discrete ionospheric measurements and the lack of reliable estimates of the ionosphere. The above is a key problem faced by ionosphere modeling, and in recent years, a data assimilation technology has become a common method for improving the accuracy of a monitoring and forecasting system by assimilating observation values into an ionosphere model. Data assimilation techniques project observations through some analytical algorithm onto a suitable scale or suitable global or regional grid, and then combine with background model values to make predictions. Data assimilation methods have been successful in meteorology and oceanology, and many experiences and mature assimilation algorithms such as variational method and Kalman filtering method are accumulated. The key of the ionosphere assimilation model is an assimilation method and an assimilation data source, and the precision of the ionosphere model is improved by utilizing Beidou GEO (Geostationary Earth Orbit) ionosphere TEC in a few documents.
In the prior art:
(1) an assimilation method: the progressive Correction Method (SCM) is an iterative empirical Method. And performing a data assimilation experiment by using a gradual correction method, taking the IRI model as prior information, and performing gradual correction by using Beidou GEO ionosphere TEC data.
Figure 692580DEST_PATH_IMAGE001
Is a given grid point
Figure 521865DEST_PATH_IMAGE003
Given by the IRI model, the specific iteration is as follows:
Figure 204650DEST_PATH_IMAGE004
(1)
in the formula (I), the compound is shown in the specification,
Figure 969344DEST_PATH_IMAGE006
in order to correct the number of times,
Figure 721268DEST_PATH_IMAGE008
to affect the total number of grid points within a radius,
Figure 698451DEST_PATH_IMAGE009
is as follows
Figure 501322DEST_PATH_IMAGE010
The secondary observation points are used for observing the secondary observation points,
Figure 295972DEST_PATH_IMAGE011
to observe
Figure 410558DEST_PATH_IMAGE012
At a point of
Figure 66799DEST_PATH_IMAGE014
The sub-estimation is carried out in such a way that,
Figure DEST_PATH_IMAGE016
is as follows
Figure 848810DEST_PATH_IMAGE017
Passing over the grid point
Figure 814361DEST_PATH_IMAGE019
The value after the second iteration is,
Figure 416243DEST_PATH_IMAGE020
to measureAn estimate of the ratio of the magnitude error variance to the a priori error variance,
Figure 610595DEST_PATH_IMAGE021
is as follows
Figure 981534DEST_PATH_IMAGE022
At the time of the next iteration, the
Figure 117986DEST_PATH_IMAGE024
A weighting factor for each observation; weighting factor
Figure DEST_PATH_IMAGE025
The distance between the observation point and the grid point is defined as the reduction of inverse proportion to the square or inverse proportion to the index of the square distance, the Beidou GEO ionosphere TEC value is fused, and the weighting factor is defined as follows:
Figure 207165DEST_PATH_IMAGE026
(2)
in the formula (I), the compound is shown in the specification,
Figure 470787DEST_PATH_IMAGE027
is a large circle radius inner grid point
Figure 430653DEST_PATH_IMAGE029
And
Figure 738006DEST_PATH_IMAGE031
the distance of (a) to (b),
Figure 314481DEST_PATH_IMAGE032
for the planar correlation length between grid points,
Figure 975270DEST_PATH_IMAGE033
is the iteration radius of the influence of a grid point on its neighborhood.
(2) Assimilation of data sources: taking an International Reference Ionosphere model IRI (International Reference Ionosphere) as a prior model, acquiring the Ionosphere TEC by utilizing a GNSS middle Orbit (MEO) satellite, and assimilating the Ionosphere TEC into the IRI prior model.
(1) The SCM corrects the previous guess by the difference between the observed data and the prior information, and the function weight of the method is constant in the iterative process.
(2) The ionospheric IRI prior model is assimilated with TEC data for MEO satellites (e.g., GPS or GLONASS satellites), however, these TEC data are affected by changes in spatial gradients caused by satellite movement.
The Ionosphere assimilation model is constructed by utilizing the Beidou GEO satellite Ionosphere TEC and an International Reference Ionosphere model IRI (International Reference Ionosphere) based on an improved gradual correction method.
Disclosure of Invention
The invention mainly aims to provide an ionized layer TEC assimilation modeling method based on Beidou GEO, and an SCM is improved by selecting an appropriate estimation value of a ratio of a measurement error variance to a prior error variance.
The technical scheme adopted by the invention is as follows: an ionized layer TEC assimilation modeling method based on Beidou GEO comprises the following steps:
an assimilation method: carrying out a data assimilation experiment by using a gradual correction method, taking an IRI model as prior information, and gradually correcting by using Beidou GEO ionized layer TEC data;
extracting the Beidou GEO ionized layer TEC;
extracting a TEC grid value of an international reference ionosphere model IRI, and assimilating the Beidou GEO ionosphere TEC value into the IRI model by using an improved stepwise correction method;
and (5) evaluating the accuracy of the assimilation model.
Further, the assimilation method includes:
Figure 930587DEST_PATH_IMAGE001
is a given grid point
Figure 549787DEST_PATH_IMAGE003
Given by the IRI model, the specific iteration is as follows:
Figure 207034DEST_PATH_IMAGE004
(1)
in the formula (I), the compound is shown in the specification,
Figure 671513DEST_PATH_IMAGE006
in order to correct the number of times,
Figure 746916DEST_PATH_IMAGE008
to affect the total number of grid points within a radius,
Figure 271439DEST_PATH_IMAGE009
is as follows
Figure 291347DEST_PATH_IMAGE010
The secondary observation points are used for observing the secondary observation points,
Figure 949731DEST_PATH_IMAGE011
to observe
Figure 738695DEST_PATH_IMAGE012
At a point of
Figure 309485DEST_PATH_IMAGE014
The sub-estimation is carried out in such a way that,
Figure 82269DEST_PATH_IMAGE016
is as follows
Figure 888551DEST_PATH_IMAGE017
Passing over the grid point
Figure 922235DEST_PATH_IMAGE019
The value after the second iteration is,
Figure 54139DEST_PATH_IMAGE020
to estimate the ratio of the measurement error variance to the a priori error variance,
Figure 924006DEST_PATH_IMAGE021
is as follows
Figure 533979DEST_PATH_IMAGE022
At the time of the next iteration, the
Figure 687748DEST_PATH_IMAGE024
A weighting factor for each observation; weighting factor
Figure 459395DEST_PATH_IMAGE025
The distance between the observation point and the grid point is defined as the reduction of inverse proportion to the square or inverse proportion to the index of the square distance, the Beidou GEO ionosphere TEC value is fused, and the weighting factor is defined as follows:
Figure 206771DEST_PATH_IMAGE026
(2)
in the formula (I), the compound is shown in the specification,
Figure 230222DEST_PATH_IMAGE027
is a large circle radius inner grid point
Figure 113865DEST_PATH_IMAGE029
And
Figure 446626DEST_PATH_IMAGE034
the distance of (a) to (b),
Figure 415719DEST_PATH_IMAGE032
for the planar correlation length between grid points,
Figure 367494DEST_PATH_IMAGE033
is the iteration radius of the influence of a grid point on its neighborhood.
Still further, the assimilation method further includes:
the ionized layer TEC assimilation is carried out by using an improved step-by-step correction method ISCM, and the method comprises the following steps:
Figure 981009DEST_PATH_IMAGE035
(3)
in the formula (I), the compound is shown in the specification,
Figure 625617DEST_PATH_IMAGE036
in order to correct the number of times,
Figure 964499DEST_PATH_IMAGE038
to affect the total number of grid points within a radius,
Figure 719965DEST_PATH_IMAGE039
is as follows
Figure 453566DEST_PATH_IMAGE040
The last iteration of each lattice point
Figure 3496DEST_PATH_IMAGE042
The latter value is then used to determine the value,
Figure 100002_DEST_PATH_IMAGE044
is as follows
Figure 100002_DEST_PATH_IMAGE046
The secondary observation points are used for observing the secondary observation points,
Figure 100002_DEST_PATH_IMAGE047
to observe
Figure 100002_DEST_PATH_IMAGE049
At a point of
Figure 100002_DEST_PATH_IMAGE050
The sub-estimation is carried out in such a way that,
Figure 100002_DEST_PATH_IMAGE051
is as follows
Figure 100002_DEST_PATH_IMAGE052
At the time of the next iteration, the
Figure 100002_DEST_PATH_IMAGE053
The weight factor of each of the observations is,
Figure 100002_DEST_PATH_IMAGE055
in order to be the variance of the model,
Figure DEST_PATH_IMAGE057
measuring error variance of the Beidou GEO ionized layer TEC value; and assimilating the Beidou GEO ionosphere TEC value into the IRI model through ISCM.
Still further, the accuracy assessment of the assimilation model includes:
and comparing and analyzing the data with the global ionosphere pattern GIM, and simultaneously evaluating the precision of the data with the Beidou GEO ionosphere TEC value which does not participate in modeling.
The invention has the advantages that:
according to the ionized layer TEC assimilation modeling method based on the Beidou GEO, the TEC of the fixed puncture point obtained by Beidou GEO satellite estimation is assimilated into an international reference ionized layer model IRI by an improved gradual correction method, and compared with a global ionized layer diagram GIM and a Beidou GEO ionized layer TEC value which does not participate in modeling are analyzed to evaluate the precision of the TEC.
The method has important application value in GNSS navigation positioning accuracy improvement and disaster reduction and prevention capability in space environment.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention.
FIG. 1 is a Beidou survey station profile of the assimilation modeling of the present invention;
FIG. 2 is an ionosphere TEC profile for a Beidou GEO satellite of the present invention;
fig. 3 is a comparison graph of the ISCM and SCM assimilation modeling results of the present invention and beidou GEO satellite TEC and GIM-TEC, wherein (a) is an ionospheric VTEC value in 2017, 5 months and 8 days obtained by resolving after a C01 satellite signal is received by CHBT and (b) is an ionospheric VTEC value in 2017, 5 months and 8 days obtained by resolving after a C01 satellite signal is received by QXSZ and is used as a reference value graph.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The ionized layer TEC assimilation modeling method based on the Beidou GEO comprises the following steps:
(1) an assimilation method: the progressive Correction Method (SCM) is an iterative empirical Method. And performing a data assimilation experiment by using a gradual correction method, taking the IRI model as prior information, and performing gradual correction by using Beidou GEO ionosphere TEC data.
Figure 321082DEST_PATH_IMAGE001
Is a given grid point
Figure 880240DEST_PATH_IMAGE003
Given by the IRI model, the specific iteration is as follows:
Figure 468347DEST_PATH_IMAGE004
(1)
in the formula (I), the compound is shown in the specification,
Figure 189178DEST_PATH_IMAGE006
in order to correct the number of times,
Figure 620160DEST_PATH_IMAGE008
to affect the total number of grid points within a radius,
Figure 842062DEST_PATH_IMAGE009
is as follows
Figure 143731DEST_PATH_IMAGE010
The secondary observation points are used for observing the secondary observation points,
Figure 176409DEST_PATH_IMAGE011
to observe
Figure 829107DEST_PATH_IMAGE012
At a point of
Figure 464488DEST_PATH_IMAGE014
The sub-estimation is carried out in such a way that,
Figure 276455DEST_PATH_IMAGE016
is as follows
Figure 604668DEST_PATH_IMAGE017
Passing over the grid point
Figure 354449DEST_PATH_IMAGE019
The value after the second iteration is,
Figure 793521DEST_PATH_IMAGE020
to estimate the ratio of the measurement error variance to the a priori error variance,
Figure 69781DEST_PATH_IMAGE021
is as follows
Figure 693530DEST_PATH_IMAGE022
At the time of the next iteration, the
Figure 55241DEST_PATH_IMAGE024
A weighting factor for each observation; weighting factor
Figure 173370DEST_PATH_IMAGE025
Defined as the decrease in inverse square of the distance between the observation point and the grid point or in inverse proportion to the exponent of the squared distance. The Beidou GEO ionized layer TEC value is fused, and the weight factors are defined as follows:
Figure 835295DEST_PATH_IMAGE026
(2)
in the formula (I), the compound is shown in the specification,
Figure 629945DEST_PATH_IMAGE027
is a large circle radius inner grid point
Figure 213373DEST_PATH_IMAGE029
And
Figure 259826DEST_PATH_IMAGE034
the distance of (a) to (b),
Figure 651624DEST_PATH_IMAGE032
for the planar correlation length between grid points,
Figure 492541DEST_PATH_IMAGE033
is the iteration radius of the influence of a grid point on its neighborhood.
SCM is improved by choosing an appropriate estimate of the ratio of the measurement error variance to the a priori error variance, and correcting the previous estimate by observing the difference between the data and the a priori information, the functional weight of the method being constant during the iteration. The invention provides a Method for assimilating ionized layer TEC by using an Improved progressive successful Correction Method (ISCM) based on Beidou GEO ionized layer TEC value and prior model IRI information. The improved method comprises the following steps:
Figure 687899DEST_PATH_IMAGE035
(3)
in the formula (I), the compound is shown in the specification,
Figure 272465DEST_PATH_IMAGE036
in order to correct the number of times,
Figure 518769DEST_PATH_IMAGE038
to affect the total number of grid points within a radius,
Figure 265008DEST_PATH_IMAGE039
is as follows
Figure 354187DEST_PATH_IMAGE040
The last iteration of each lattice point
Figure 601498DEST_PATH_IMAGE042
The latter value is then used to determine the value,
Figure 826943DEST_PATH_IMAGE044
is as follows
Figure 885028DEST_PATH_IMAGE046
The secondary observation points are used for observing the secondary observation points,
Figure 195924DEST_PATH_IMAGE047
to observe
Figure 246926DEST_PATH_IMAGE049
At a point of
Figure 326877DEST_PATH_IMAGE050
The sub-estimation is carried out in such a way that,
Figure 680498DEST_PATH_IMAGE051
is as follows
Figure 354056DEST_PATH_IMAGE052
At the time of the next iteration, the
Figure 818535DEST_PATH_IMAGE053
The weight factor of each of the observations is,
Figure 143206DEST_PATH_IMAGE055
in order to be the variance of the model,
Figure 667729DEST_PATH_IMAGE057
measuring error variance of the Beidou GEO ionized layer TEC value; and assimilating the Beidou GEO ionosphere TEC value into the IRI model through ISCM.
(2) And (4) extracting the Beidou GEO ionized layer TEC. Because the GEO satellite keeps synchronous with the earth rotation and the signal propagation path of the GEO satellite and the ground receiver is almost kept unchanged due to the characteristic that the satellite and the earth are relatively static, the ionized layer TEC of the Beidou GEO cannot be influenced by the change of the ionized layer space and time gradient. The invention utilizes a non-differential non-combination precise single-point positioning technology to extract the ionized layer TEC.
(3) And extracting a TEC grid value of the international reference ionosphere model IRI, and assimilating the Beidou GEO ionosphere TEC value into the IRI model by using an improved gradual correction method.
(4) And (5) evaluating the accuracy of the assimilation model. And carrying out comparative analysis with a Global Ionosphere Map (GIM) and simultaneously carrying out precision evaluation with Beidou GEO Ionosphere TEC values which do not participate in modeling.
Wherein the SCM is refined by selecting an appropriate estimate of the ratio of the measurement error variance to the a priori error variance, wherein the SCM corrects the previous estimate by the difference between the observed data and the a priori information, and the functional weight of the method is constant during the iteration. The invention provides a Method for assimilating ionized layer TEC by using an Improved progressive successful Correction Method (ISCM) based on Beidou GEO ionized layer TEC value and prior model IRI information.
Because the GEO satellite keeps synchronous with the earth rotation and the signal propagation path of the GEO satellite and the ground receiver is almost kept unchanged due to the characteristic that the satellite and the earth are relatively static, the ionized layer TEC of the Beidou GEO cannot be influenced by the change of the space and the time gradient of the ionized layer. According to the invention, the Beidou GEO ionized layer TEC value is assimilated into an international reference ionized layer model IRI model.
Fig. 1 shows the distribution of the Beidou test stations for assimilation modeling, wherein ^ x represents a test station participating in assimilation modeling and ^ x represents a test station not participating in assimilation modeling, namely a CHBT test station and a QXSZ test station.
FIG. 2 shows the ionosphere TEC distribution of UT12 Beidou GEO satellite 5/8/2017.
Fig. 3 shows comparison of the ISCM and SCM assimilation modeling results with the TECs and GIM-TECs of beidou GEO satellite No. one, (a) the diagram shows the ionospheric VTEC value of 2017, 5 months and 8 days obtained by resolving after the CHBT receives the C01 satellite signal as a reference value, and (b) the diagram shows the ionospheric VTEC value of 2017, 5 months and 8 days obtained by resolving after the QXSZ receives the C01 satellite signal as a reference value. It can be seen that the result of the ISCM assimilation modeling is closer to the ionosphere TEC value of the Beidou GEO satellite, so that the ISCM assimilation modeling result is better than the SCM assimilation modeling result.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (4)

1. The ionized layer TEC assimilation modeling method based on Beidou GEO is characterized by comprising the following steps of:
an assimilation method: carrying out a data assimilation experiment by using a gradual correction method, taking an IRI model as prior information, and gradually correcting by using Beidou GEO ionized layer TEC data;
extracting the Beidou GEO ionized layer TEC;
extracting a TEC grid value of an international reference ionosphere model IRI, and assimilating the Beidou GEO ionosphere TEC value into the IRI model by using an improved stepwise correction method;
and (5) evaluating the accuracy of the assimilation model.
2. The ionosphere TEC assimilation modeling method based on Beidou GEO according to claim 1,
characterized in that the assimilation method comprises:
Figure 535107DEST_PATH_IMAGE001
is a given grid point
Figure 670554DEST_PATH_IMAGE003
Given by the IRI model, the specific iteration is as follows:
Figure 14947DEST_PATH_IMAGE004
(1)
in the formula (I), the compound is shown in the specification,
Figure 168717DEST_PATH_IMAGE006
in order to correct the number of times,
Figure 940364DEST_PATH_IMAGE008
to affect the total number of grid points within a radius,
Figure 422161DEST_PATH_IMAGE009
is as follows
Figure 711191DEST_PATH_IMAGE010
The secondary observation points are used for observing the secondary observation points,
Figure 594833DEST_PATH_IMAGE011
to observe
Figure 802961DEST_PATH_IMAGE012
At a point of
Figure 631108DEST_PATH_IMAGE014
The sub-estimation is carried out in such a way that,
Figure 582884DEST_PATH_IMAGE016
is as follows
Figure 321032DEST_PATH_IMAGE017
Passing over the grid point
Figure 575427DEST_PATH_IMAGE019
The value after the second iteration is,
Figure 766237DEST_PATH_IMAGE020
to estimate the ratio of the measurement error variance to the a priori error variance,
Figure 256124DEST_PATH_IMAGE021
is as follows
Figure 238993DEST_PATH_IMAGE023
At the time of the next iteration, the
Figure 54502DEST_PATH_IMAGE025
A weighting factor for each observation; weighting factor
Figure 607974DEST_PATH_IMAGE026
The distance between the observation point and the grid point is defined as the reduction of inverse proportion to the square or inverse proportion to the index of the square distance, the Beidou GEO ionosphere TEC value is fused, and the weighting factor is defined as follows:
Figure 901552DEST_PATH_IMAGE027
(2)
in the formula (I), the compound is shown in the specification,
Figure 348714DEST_PATH_IMAGE028
is a large circle radius inner grid point
Figure 459759DEST_PATH_IMAGE030
And
Figure 625161DEST_PATH_IMAGE032
the distance of (a) to (b),
Figure 597796DEST_PATH_IMAGE033
for the planar correlation length between grid points,
Figure 899464DEST_PATH_IMAGE034
is the iteration radius of the influence of a grid point on its neighborhood.
3. The ionosphere TEC assimilation modeling method based on Beidou GEO according to claim 1,
characterized in that the assimilation method further comprises:
the ionized layer TEC assimilation is carried out by using an improved step-by-step correction method ISCM, and the method comprises the following steps:
Figure 791197DEST_PATH_IMAGE035
(3)
in the formula (I), the compound is shown in the specification,
Figure 834108DEST_PATH_IMAGE036
in order to correct the number of times,
Figure 203910DEST_PATH_IMAGE038
to affect the total number of grid points within a radius,
Figure 891243DEST_PATH_IMAGE039
is as follows
Figure 829243DEST_PATH_IMAGE040
The last iteration of each lattice point
Figure DEST_PATH_IMAGE042
The latter value is then used to determine the value,
Figure DEST_PATH_IMAGE044
is as follows
Figure DEST_PATH_IMAGE046
The secondary observation points are used for observing the secondary observation points,
Figure DEST_PATH_IMAGE047
to observe
Figure DEST_PATH_IMAGE049
At a point of
Figure DEST_PATH_IMAGE050
The sub-estimation is carried out in such a way that,
Figure DEST_PATH_IMAGE051
is as follows
Figure DEST_PATH_IMAGE052
At the time of the next iteration, the
Figure DEST_PATH_IMAGE053
The weight factor of each of the observations is,
Figure DEST_PATH_IMAGE055
in order to be the variance of the model,
Figure DEST_PATH_IMAGE056
measuring error variance of the Beidou GEO ionized layer TEC value; and assimilating the Beidou GEO ionosphere TEC value into the IRI model through ISCM.
4. The ionosphere TEC assimilation modeling method based on Beidou GEO according to claim 1,
wherein the accuracy assessment of the assimilation model comprises:
and comparing and analyzing the data with the global ionosphere pattern GIM, and simultaneously evaluating the precision of the data with the Beidou GEO ionosphere TEC value which does not participate in modeling.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115792963A (en) * 2023-02-13 2023-03-14 天津云遥宇航科技有限公司 Ionized layer correction method based on GIM (global information model), electronic equipment and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115792963A (en) * 2023-02-13 2023-03-14 天津云遥宇航科技有限公司 Ionized layer correction method based on GIM (global information model), electronic equipment and storage medium

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