阅读说明：本技术 一种gnss实时全球电离层tec建模方法 (GNSS real-time global ionized layer TEC modeling method ) 是由 张强 赵齐乐 王坤石 于 2019-10-29 设计创作，主要内容包括：本发明涉及一种电离层建模方法,尤其是涉及一种GNSS实时全球电离层TEC建模方法；该方法主要采用了两种数据源建立实时全球电离层TEC模型,其中预报全球电离层TEC模型作为背景场描述全球电离层TEC的整体趋势,GNSS实时观测数据能够反映各个观测站附近电离层TEC的实时变化和局部变化；结合两种数据源既能够保证全球范围反演电离层TEC的可靠性,又能提高GNSS实时观测数据覆盖地区的模型精度。(The invention relates to an ionized layer modeling method, in particular to a GNSS real-time global ionized layer TEC modeling method; the method mainly adopts two data sources to establish a real-time global ionized layer TEC model, wherein the predicted global ionized layer TEC model is used as a background field to describe the overall trend of the global ionized layer TEC, and GNSS real-time observation data can reflect the real-time change and the local change of the ionized layer TEC near each observation station; by combining the two data sources, the reliability of global inversion ionosphere TEC can be guaranteed, and the model precision of a GNSS real-time observation data coverage area can be improved.)

1. A GNSS real-time global ionized layer TEC modeling method is characterized in that: establishing a post global ionized layer TEC model by utilizing the post observation data of the GNSS distributed in the global domain, and establishing a forecast global ionized layer TEC model according to a post global ionized layer TEC model database; the ionosphere observation information at an ionosphere puncture point is extracted by utilizing GNSS real-time data flow with global finite distribution, and a real-time global ionosphere TEC model of a current epoch is generated by combining a generated forecast global ionosphere TEC model, wherein the whole calculation step is as follows:

step 1, extracting smooth ionospheric observation information according to GNSS post-event double-frequency carrier and pseudo-range observation data, establishing a post-event GNSS global ionospheric TEC model by using a spherical harmonic function, and simultaneously solving a spherical harmonic function coefficient and a difference code deviation between a satellite and a receiver end; step 2, establishing a model coefficient database according to the spherical harmonic model coefficients before the current time, and forecasting the global ionized layer TEC model by adopting a least square configuration method; step 3, interpolating the spherical harmonic model coefficient of the current epoch according to the forecast spherical harmonic model coefficient time; step 4, extracting ionosphere observation information according to GNSS real-time data flow, wherein differential code deviation between a satellite and a receiver directly adopts a differential code deviation product generated two days ago; and 5, establishing a real-time global ionized layer TEC model by adopting a least square parameter estimation method by combining the forecast spherical harmonic coefficient and the real-time observation data with the differential code deviation eliminated.

2. The GNSS real-time global ionosphere TEC modeling method according to claim 1, characterized in that in step 2, the periodic variation law of the ionosphere TEC is used to predict the spherical harmonic model coefficients for 2 days in the future by using the least square configuration method; the sliding window of the spherical harmonic coefficient database is set to be 30 days, the period items are significant day and sub-day period items, and the forecasted spherical harmonic coefficients comprise trend items and random items.

3. The method for modeling the TEC of the GNSS real-time global ionized layer (GNSS TEC) of claim 1, wherein in step 4, the differential code bias between the GNSS real-time observation data and the receiver directly adopts the differential code bias product estimated 2 days ago.

4. The GNSS real-time global ionosphere TEC modeling method of claim 1, wherein in step 5, the time resolution of the model is set to 5 minutes, wherein the real-time observation data is stored every 5 minutes, and the real-time observation data participating in modeling adopts a sliding window of 15 minutes.

Technical Field

The invention relates to an ionosphere modeling method, in particular to a GNSS real-time global ionosphere TEC modeling method.

Background

The ionospheric delay error is one of the main errors of real-time single-frequency single-point positioning, the influence of the ionospheric delay error on the frequency of GPS L1 in the zenith direction can reach 29.2m, and even exceeds 87.6m when the satellite altitude angle is low, the current model for real-time ionospheric delay correction is mainly a broadcast ionospheric model, however, the model is usually an empirical model, such as Klobuchar model, nequickk model, IRI model, etc., and the ionospheric delay correction rate of these models is generally only 50% to 70%.

Based on hundreds of GNSS observation stations distributed in the world, a high-precision global ionized layer TEC model can be obtained through inversion, wherein the final ionized layer product generally lags behind 6 to 9 days, the rapid ionized layer product generally lags behind 1 to 2 days, and a global ionized layer TEC forecast product is issued by part of ionized layer analysis centers.

The broadcast ionosphere model and the GNSS after or forecast the global ionosphere model do not meet the increasing high-precision positioning requirement, so that the establishment of a real-time, high-precision, stable and reliable global ionosphere delay correction model is a current research hotspot, an IGS real-time working group is established in 2002, an IGS real-time test plan is developed in 2007 6 months, real-time data and product services are formed in early 2013, a real-time ionosphere monitoring working group is established in 2016 by the international geodetic society, and at present, each analysis center of the IGS is performing real-time global ionosphere TEC model algorithm research and precision verification, and some preliminary progress is achieved.

With the starting of the IAG/IGS real-time test plan, more and more IGS observation stations can provide real-time data service, and the establishment of the GNSS real-time global ionized layer TEC model becomes possible based on the GNSS real-time observation stations distributed in the global. However, because the number of the IGS real-time observation stations is insufficient and the IGS real-time observation stations are not uniformly distributed at present, the high-precision global ionized layer TEC modeling is difficult to realize only by relying on GNSS real-time observation data, and obvious model errors can be generated in areas lacking ionized layer observation information; the currently known real-time global ionosphere TEC model algorithms are not mature and still require a lot of research work.

Disclosure of Invention

The invention mainly provides a method for establishing a high-precision global ionized layer TEC model in real time based on GNSS observation data, and aims to solve the problem that the real-time high-precision global ionized layer TEC model cannot be solved only by means of GNSS real-time observation data due to the fact that the number of current GNSS real-time observation stations is limited and the distribution is uneven.

The technical problem of the invention is mainly solved by the following technical scheme:

a GNSS real-time global ionized layer TEC modeling method is characterized in that: establishing a post global ionized layer TEC model by utilizing the post observation data of the GNSS distributed in the global domain, and establishing a forecast global ionized layer TEC model according to a post global ionized layer TEC model database; extracting ionosphere observation information at an ionosphere puncture point by utilizing GNSS real-time data flow with global finite distribution, and generating a real-time global ionosphere TEC model of a current epoch by combining with a generated forecast global ionosphere TEC model; the whole calculation steps are as follows:

step 1, extracting smooth ionospheric observation information according to GNSS post-event double-frequency carrier and pseudo-range observation data, establishing a post-event GNSS global ionospheric TEC model by using a spherical harmonic function, and simultaneously solving a spherical harmonic function coefficient and a difference code deviation between a satellite and a receiver end; step 2, establishing a model coefficient database according to the spherical harmonic model coefficients before the current time, and forecasting the global ionized layer TEC model by adopting a least square configuration method; step 3, interpolating the spherical harmonic model coefficient of the current epoch according to the forecast spherical harmonic model coefficient time; step 4, extracting ionosphere observation information according to GNSS real-time data flow, wherein differential code deviation between a satellite and a receiver directly adopts a differential code deviation product generated 2 days ago; and 5, establishing a real-time global ionized layer TEC model by adopting a least square parameter estimation method by combining the forecast spherical harmonic coefficient and the real-time observation data with the differential code deviation eliminated.

The step 2 comprises the following information in more detail: forecasting a spherical harmonic model coefficient of 2 days in the future by adopting a least square configuration method; setting a sliding window of a spherical harmonic coefficient database to be 30 days; selecting obvious day and sub-day period items from the period items; the spherical harmonic coefficients of the forecast include a trend term and a random term.

The step 3 comprises the following information in more detail: the forecasting spherical harmonic coefficients are directly adopted to participate in real-time global ionized layer TEC model parameter calculation, so that calculation errors caused by calculation of grid point ionized layer VTEC according to the forecasting spherical harmonic coefficients are avoided, and only weight distribution of the forecasting spherical harmonic coefficients and real-time observation data streams needs to be determined.

The step 4 comprises the following information in more detail: the differential code deviation between the satellite of the GNSS real-time data stream and the receiver directly adopts a differential code deviation product estimated 2 days ago; for the newly added GNSS real-time observation station, the post differential code deviation product does not comprise the corresponding satellite and receiver end differential code deviation product, relevant data is removed from the current real-time global ionized layer TEC modeling, the newly added observation station is added into the post global ionized layer TEC modeling, and the generated differential code deviation product is used for the next day real-time global ionized layer TEC modeling.

The step 5 comprises the following information in more detail: estimating real-time global ionized layer TEC model coefficients by adopting a least square method, wherein the time resolution of the model is 5 minutes; the real-time observation data is stored every 5 minutes, and a sliding window of 15 minutes is adopted for the real-time observation data participating in modeling.

In the GNSS real-time global ionized layer TEC modeling method, two data sources are mainly adopted to establish a real-time global ionized layer TEC model, wherein the global ionized layer TEC model is forecasted to serve as a background field to describe the overall trend of the global ionized layer TEC, and GNSS real-time observation data can reflect real-time changes and local changes of the ionized layer TEC near each observation station; by combining the two data sources, the reliability of global inversion ionosphere TEC can be guaranteed, and the model precision of a GNSS real-time observation data coverage area can be improved.

Therefore, the invention has the following advantages: 1. the forecasting global ionized layer TEC model is used as a background field, so that the defect that the high-precision global ionized layer TEC model cannot be solved in real time due to the fact that the number of current GNSS real-time observation stations is limited and the distribution is uneven is overcome; 2. in the real-time global ionized layer TEC modeling, a difference code deviation of a satellite and a receiver estimated in advance is introduced, the influence of the difference code deviation is eliminated in the real-time data stream preprocessing stage, and the mutual influence of the simultaneous resolving of the spherical harmonic function model coefficient and the difference code deviation parameter estimation is avoided; 3. the real-time global ionized layer TEC model coefficient is estimated by adopting weighted least square, the weight of the forecast ionized layer background field and the real-time observation data can be optimally determined based on a variance component estimation method, and the reliability and the time variability of the ionized layer TEC model are ensured.

Drawings

FIG. 1 is a data processing flow diagram of the present invention;

FIG. 2 is a flow chart of spherical harmonic model coefficient prediction;

FIG. 3 is a flow chart of real-time observation data ionosphere TEC extraction;

fig. 4 is a flow chart of real-time global ionospheric model parameter estimation.

Detailed Description

The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.