CN116010767A - Method for improving zenith delay estimation precision of troposphere - Google Patents
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Abstract
The invention provides a method for improving the zenith delay estimation precision of a troposphere, and belongs to the technical field of navigation and positioning. The technical proposal is as follows: a method for improving the accuracy of the estimation of the zenith delay of a troposphere comprises taking the result of GNSS actual measurement signal calculation as a reference value of the zenith delay of the troposphere, and marking as ZTD GNSS The method comprises the steps of carrying out a first treatment on the surface of the Estimating zenith delay ZTD of troposphere based on GPT2w model GPT2w The method comprises the steps of carrying out a first treatment on the surface of the Calculating a troposphere zenith delay residual error dZTD according to the existing site data; after analyzing periodic signals in the troposphere zenith delay residual sequence, constructing a residual period model dZTD considering annual, semi-annual and seasonal period terms model The method comprises the steps of carrying out a first treatment on the surface of the Construction of troposphere zenith delay experience improved model ZTD model ：ZTD model ＝ZTD GPT2w +dZTD model . The beneficial effects of the invention are as follows: compared with a GPT2w model, the method effectively improves the calculation precision, can improve the positioning efficiency, and effectively reduces the estimated troposphere in the positioning processDelay-induced convergence time.
Description
Technical Field
The invention relates to the technical field of navigation positioning, in particular to a method for improving the zenith delay estimation precision of a troposphere.
Background
Troposphere zenith delay is one of key factors influencing GNSS high-precision positioning, and error of more than 2m is ignored to directly influence positioning results. In addition, the technologies of very long baseline interferometry, satellite-borne Doppler orbit determination positioning system, synthetic aperture radar interference and the like are also affected by troposphere delay, and the most widely applied method for weakening the troposphere delay error at present is to establish a high-precision troposphere zenith delay model.
Generally, the tropospheric zenith delay model is divided into a tropospheric zenith delay model based on measured meteorological parameters and a tropospheric zenith delay empirical model without measured meteorological parameters according to whether the model requires real-time meteorological parameters. For the troposphere zenith delay model based on the actually measured meteorological parameters, the temperature, the pressure, the steam pressure and the like are important parameters essential to the use process.
However, in actual work, meteorological parameters cannot be obtained in real time in many times, so that a model based on actual measurement cannot be widely applied; a number of regional empirical models have been developed that do not require measured meteorological parameters and are verified to be no less accurate than models based on measured meteorological parameters. However, the accuracy of the empirical model is not free from a lifting space, and how to improve the accuracy of the zenith delay estimation of the troposphere based on the empirical model is a key point for realizing quick positioning and improving positioning efficiency.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a method for improving the accuracy of the zenith delay estimation of a troposphere, which is improved on the basis of a GPT2w model, a high-accuracy single-site zenith delay empirical model is established, and the accuracy and the reliability of the empirical improvement model are ensured by combining millimeter-level zenith delay data of the troposphere calculated by GNSS actual measurement signals.
The invention is realized by the following technical scheme: a method for improving the accuracy of zenith delay estimation of a troposphere comprises the following steps:
s1, performing troposphere zenith delay calculation aiming at GNSS actually measured signals, taking a calculation result as a reference value of the troposphere zenith delay, and marking the reference value as ZTD GNSS ；
S2, calculating the zenith delay of a troposphere of a GPT2w model, wherein the GPT2w model provides gridding parameter information files with two resolutions of 1 DEG and 5 DEG, and the method is specifically as follows:
s21, calculating site position meteorological parameters according to a gridding parameter information file provided by a GPT2w model;
s22, combining a Saastamoinen model and a Askne and Nordius model, substituting the Saastamoinen model and the Askne and Nordius model into the site position meteorological parameters, and respectively calculating zenith dry delay ZHD and zenith wet delay ZWD;
s23, calculating the zenith delay ZTD of the troposphere of the GPT2w model GPT2w ，ZTD GPT2w ＝ZHD+ZWD；
S3, calculating a troposphere zenith delay residual error dZTD according to the existing site data based on the thought of model error compensation:
dZTD＝ZTD GNSS -ZTD GPT2w ；
s4, after analyzing periodic signals in the troposphere zenith delay residual sequence, constructing a residual error period model dZTD considering annual, semi-annual and seasonal period terms model Estimating unknown parameters in the model by using a least square method;
s5, constructing a troposphere zenith delay experience improved model ZTD model ：ZTD model ＝ZTD GPT2w +dZTD model 。
Further, the dZTD model The method comprises the following steps:
wherein: a, a 0 The average value of the residual error dZTD of the zenith delay of the troposphere; a, a 1 ～a 4 And
representing the annual, semi-annual and 120 and 90 day amplitude coefficients and initial phases, respectively.
Further, the S1 specifically includes: the tropospheric delay is resolved by high-precision resolving software, real-time/post PPP processing is simulated for the actual received signal observed by GNSS, namely, the track and clock products recorded by IGS are used, and the estimated tropospheric zenith delay is used as a reference value ZTD of the tropospheric delay GNSS The specific processing strategy can be based on actual observations.
Further, the step S21 specifically includes:
s211, firstly, determining four grid points around the site position, and acquiring weather parameters of the grid point height according to the grid parameter information file;
s212, vertically correcting the meteorological parameters of the grid point height to the site height through calculation;
s213, interpolating weather parameters of the four network point heights to the site position in the horizontal direction by using a bilinear interpolation method;
s214, obtaining the meteorological parameters of the site position after calculation, wherein the meteorological parameters comprise P, e and T m Lambda represents the air pressure, the water vapor pressure, the weighted average temperature and the water vapor reduction factor, respectively.
Further, the specific calculation formula of S212 is:
T V ＝T 0 *(1+0.6077Q)
e 0 ＝Q*P 0 /(0.622+0.378*Q)
T＝T 0 +dT*(h-h 0 )
e＝e 0 (P*100/P 0 ) λ+1
wherein P is 0 、e 0 、T 0 The air pressure, the water vapor pressure and the temperature of the grid point height are respectively expressed, and Q is the specific humidity; p, T and e respectively represent the air pressure, temperature and water vapor pressure of the site height; dT represents the temperature decrease rate; g m Represents gravity and takes the value of 9.80665m/s 2 ；T v Representing the deficiency temperature; dM and R g Respectively represent the molar mass of dry air, and the values are 28.965 ×10 respectively -3 kg/mol and 8.3143J/K/mol.
Further, the zenith dry delay ZHD is calculated based on the Saastamoinen model, as follows:
wherein:
h represents site latitude and ground height, respectively; p represents the surface air pressure.
Further, the zenith wet delay ZWD is calculated according to the Askne and Nordius model as follows:
wherein: k' 2 、k 3 、R d Are constants in the model formula.
A high-precision troposphere zenith delay measurement system, comprising a troposphere zenith delay experience improvement model ZTD constructed based on the method for improving the estimation precision of the troposphere zenith delay according to any one of claims 1 to 7 model 。
The beneficial effects of the invention are as follows: according to the invention, a high-precision single-site troposphere zenith delay empirical model is constructed, and the precision and reliability of the empirical improvement model are ensured through millimeter-level troposphere zenith delay data calculated by combining GNSS actual measurement signals; compared with a GPT2w model, the method effectively improves the calculation precision, and has important practical engineering application value for improving the GNSS positioning precision, especially the positioning precision in the elevation direction; the positioning efficiency can be improved, and the convergence time caused by the estimated troposphere delay in the positioning process can be effectively reduced.
Drawings
FIG. 1 is a flow chart of the method steps of the present invention.
Fig. 2 is a comparison of ZTD estimates for several methods of the present invention.
FIG. 3 shows the fitting effect of the residual periodic model in the present invention.
Detailed Description
In order to clearly illustrate the technical characteristics of the scheme, the scheme is explained below through a specific embodiment.
In an embodiment, referring to fig. 1, the present invention is implemented by the following technical scheme: a method for improving the accuracy of zenith delay estimation of a troposphere comprises the following steps:
s1, performing troposphere zenith delay calculation aiming at GNSS actually measured signals, taking a calculation result as a reference value of the troposphere zenith delay, and marking the reference value as ZTD GNSS ；
S2, calculating the zenith delay of a troposphere of a GPT2w model, wherein the GPT2w model provides gridding parameter information files with two resolutions of 1 DEG and 5 DEG, and the method is specifically as follows:
s21, calculating site position meteorological parameters according to a gridding parameter information file provided by a GPT2w model;
s22, combining a Saastamoinen model and a Askne and Nordius model, substituting the Saastamoinen model and the Askne and Nordius model into the site position meteorological parameters, and respectively calculating zenith dry delay ZHD and zenith wet delay ZWD;
s23, calculating the zenith delay ZTD of the troposphere of the GPT2w model GPT2w ，ZTD GPT2w ＝ZHD+ZWD；
S3, calculating a troposphere zenith delay residual error dZTD according to the existing site data based on the thought of model error compensation:
dZTD＝ZTD GNSS -ZTD GPT2w ；
s4, after analyzing periodic signals in the troposphere zenith delay residual sequence, constructing a residual error period model dZTD considering annual, semi-annual and seasonal period terms model Estimating unknown parameters in the model by using a least square method;
s5, constructing a troposphere zenith delay experience improved model ZTD model ：ZTD model ＝ZTD GPT2w +dZTD model 。
The dZTD model The method comprises the following steps:
wherein: a, a 0 The average value of the residual error dZTD of the zenith delay of the troposphere; a, a 1 ～a 4 And
amplitude coefficients and initial phases representing years, half-years, and 120 days and 90 days, respectivelyBits.
In a second embodiment, referring to fig. 1 to 3, a method for improving accuracy of zenith delay estimation of a troposphere includes the following steps:
s1, calculating tropospheric delay by high-precision resolving software such as Bernese or GAMIT, and regarding an actual received signal observed by GNSS, performing PPP processing in real-time/post-hoc mode by using an IGS recorded track and clock product, wherein the estimated tropospheric zenith delay is used as a reference value ZTD of the tropospheric delay GNSS The specific processing strategy can be based on actual observation, as shown in FIG. 2, and the calculated result is used as reference value of the zenith delay of the troposphere and recorded as ZTD GNSS ；
S2, calculating the zenith delay of a troposphere of a GPT2w model, wherein the GPT2w model provides gridding parameter information files with two resolutions of 1 DEG and 5 DEG, and the method is specifically as follows:
s21, calculating site position meteorological parameters according to a gridding parameter information file provided by a GPT2w model;
s211, firstly, determining four grid points around the site position, and acquiring weather parameters of the grid point height according to the grid parameter information file;
s212, vertically correcting the meteorological parameters of the grid point height to the site height through calculation, wherein a specific calculation formula is as follows:
T V ＝T 0 *(1+0.6077Q)
e 0 ＝Q*P 0 /(0.622+0.378*Q)
T＝T 0 +dT*(h-h 0 )
e＝e 0 (P*100/P 0 ) λ+1
wherein P is 0 、e 0 、T 0 The air pressure, the water vapor pressure and the temperature of the grid point height are respectively expressed, and Q is the specific humidity; p, T and e respectively represent the air pressure, temperature and water vapor pressure of the site height; dT represents the temperature decrease rate; g m Indicating gravity, takingA value of 9.80665m/s 2 ；T v Representing the deficiency temperature; dM and R g Respectively represent the molar mass of dry air, and the values are 28.965 ×10 respectively -3 kg/mol and 8.3143J/K/mol;
s213, interpolating weather parameters of the four network point heights to the site position in the horizontal direction by using a bilinear interpolation method;
s214, obtaining the meteorological parameters of the site position after calculation, wherein the meteorological parameters comprise P, e and T m Lambda represents the air pressure, the water vapor pressure, the weighted average temperature and the water vapor decrement factor respectively;
s22, combining a Saastamoinen model and a Askne and Nordius model, substituting the Saastamoinen model and the Askne and Nordius model into the site position meteorological parameters, and respectively calculating zenith dry delay ZHD and zenith wet delay ZWD;
the zenith dry delay ZHD is calculated based on the Saastamoinen model, and the formula is as follows:
wherein:
h represents site latitude and ground height, respectively; p represents the surface air pressure;
the zenith wet delay ZWD is calculated according to the Askne and Nordius model as follows:
wherein: k' 2 、k 3 、R d Are constants in the model formula;
s23, calculating the zenith delay ZTD of the troposphere of the GPT2w model GPT2w ，ZTD GPT2w ＝ZHD+ZWD；
S3, calculating a troposphere zenith delay residual error dZTD according to the existing site data based on the thought of model error compensation:
dZTD＝ZTD GNSS -ZTD GPT2w ；
s4, after analyzing periodic signals in the troposphere zenith delay residual sequence, constructing a residual error period model dZTD considering annual, semi-annual and seasonal period terms model Estimating unknown parameters in the model by using a least square method;
s5, constructing a troposphere zenith delay experience improved model ZTD model ：ZTD model ＝ZTD GPT2w +dZTD model 。
The dZTD model The method comprises the following steps:
wherein: a, a 0 The average value of the residual error dZTD of the zenith delay of the troposphere; a, a 1 ～a 4 And
representing the annual, semi-annual and 120 and 90 day amplitude coefficients and initial phases, respectively.
As shown in fig. 2, it is obvious that the correlation of the estimated zenith delay values of the troposphere in several methods according to the present invention: the method is superior to GPT2w in performance of zenith delay estimation of the troposphere, has better precision, can further improve positioning efficiency, and effectively reduces convergence time caused by estimated troposphere delay in the positioning process.
As shown in fig. 3, the black dispersion point represents the troposphere zenith delay residual dZTD of the month resolution, the light thin line segment is a linear line of the troposphere zenith delay residual dZTD for indicating the variation trend of dZTD, and the dark thick line segment is the model value dZTD of the residual period model established based on the troposphere zenith delay residual dZTD model It can be seen that: residual error period model dZTD model Is a very good empirical expression method of the troposphere zenith delay residual error dZTD.
The third embodiment of the invention provides a high-precision troposphere zenith delay measurement system, which comprises the troposphere zenith delay constructed based on the method for improving the estimation precision of the troposphere zenith delay in the second embodimentLate experience improved model ZTD model 。
In the description of the invention, the foregoing detailed description has set forth various embodiments of the devices and/or processes via the use of block diagrams, flowcharts, and/or examples. To the extent that such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood by those within the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of different hardware, software, firmware, or virtually any combination thereof.
The technical features of the present invention that are not described in the present invention may be implemented by or using the prior art, and are not described in detail herein, but the above description is not intended to limit the present invention, and the present invention is not limited to the above examples, but is also intended to be within the scope of the present invention by those skilled in the art.
Claims (8)
1. The method for improving the accuracy of the zenith delay estimation of the troposphere is characterized by comprising the following steps:
s1, performing troposphere zenith delay calculation aiming at GNSS actually measured signals, taking a calculation result as a reference value of the troposphere zenith delay, and marking the reference value as ZTD GNSS ；
And S2, calculating the zenith delay of the troposphere of the GPT2w model, wherein the zenith delay is specifically as follows:
s21, calculating site position meteorological parameters according to a gridding parameter information file provided by a GPT2w model;
s22, combining a Saastamoinen model and a Askne and Nordius model, substituting site position meteorological parameters, and respectively calculating zenith dry delay ZHD and zenith wet delay ZWD;
s23, calculating the zenith delay ZTD of the troposphere of the GPT2w model GPT2w ，ZTD GPT2w ＝ZHD+ZWD；
S3, calculating a troposphere zenith delay residual error dZTD according to the existing site data:
dZTD＝ZTD GNSS -ZTD GPT2w ；
s4, after analyzing periodic signals in the troposphere zenith delay residual sequence, constructing a residual error period model dZTD considering annual, semi-annual and seasonal period terms model ；
S5, constructing a troposphere zenith delay experience improved model ZTD model ：ZTD model ＝ZTD GPT2w +dZTD model 。
2. The method for improving accuracy of zenith delay estimation of troposphere according to claim 1, wherein the dZTD model The method comprises the following steps:
wherein: a, a 0 The average value of the residual error dZTD of the zenith delay of the troposphere; a, a 1 ～a 4 And
representing the annual, semi-annual and 120 and 90 day amplitude coefficients and initial phases, respectively.
3. The method for improving accuracy of zenith delay estimation of troposphere according to claim 1, wherein S1 is specifically: the tropospheric delay is resolved by high-precision resolving software, real-time/post PPP processing is simulated for the actual received signal observed by GNSS, and the estimated tropospheric zenith delay is used as a reference value ZTD of the tropospheric delay GNSS 。
4. The method for improving accuracy of zenith delay estimation of troposphere according to claim 1, wherein S21 is specifically:
s211, firstly, determining four grid points around the site position, and acquiring weather parameters of the grid point height according to the grid parameter information file;
s212, vertically correcting the meteorological parameters of the grid point height to the site height through calculation;
s213, interpolating weather parameters of the four network point heights to the site position in the horizontal direction by using a bilinear interpolation method;
s214, obtaining the meteorological parameters of the site position after calculation, wherein the meteorological parameters comprise P, e and T m Lambda represents the air pressure, the water vapor pressure, the weighted average temperature and the water vapor reduction factor, respectively.
5. The method for improving accuracy of zenith delay estimation of troposphere according to claim 4, wherein the specific calculation formula of S212 is:
T V ＝T 0 *(1+0.6077Q)
e 0 ＝Q*P 0 /(0.622+0.378*Q)
T＝T 0 +dT*(h-h 0 )
e＝e 0 (P*100/P 0 ) λ+1
wherein P is 0 、e 0 、T 0 The air pressure, the water vapor pressure and the temperature of the grid point height are respectively expressed, and Q is the specific humidity; p, T and e respectively represent the air pressure, temperature and water vapor pressure of the site height; dT represents the temperature decrease rate; g m Represents gravity and takes the value of 9.80665m/s 2 ；T v Representing the deficiency temperature; dM and R g Respectively represent the molar mass of dry air, and the values are 28.965 ×10 respectively -3 kg/mol and 8.3143J/K/mol.
6. The method for improving accuracy of zenith delay estimation of troposphere according to claim 4, wherein said zenith delay ZHD is calculated based on the Saastamoinen model as follows:
wherein:
h represents site latitude and ground height, respectively; p represents the surface air pressure.
7. The method for improving accuracy of zenith delay estimation of troposphere according to claim 4, wherein the zenith wet delay ZWD is calculated according to a model Askne and Nordius as follows:
wherein: k' 2 、k 3 、R d Are constants in the model formula.
8. A high-precision troposphere zenith delay measurement system, which is characterized by comprising a troposphere zenith delay experience improvement model ZTD constructed based on the method for improving the estimation precision of the troposphere zenith delay according to any one of claims 1 to 7 model 。
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117933145A (en) * | 2024-03-22 | 2024-04-26 | 长江三峡集团实业发展(北京)有限公司 | GNSS-based troposphere delay modeling method for Sha Gehuang equal drought areas |
| CN117992706A (en) * | 2024-04-07 | 2024-05-07 | 武汉大学 | Point-to-plane conversion method and system for real-time troposphere zenith delay |
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2021
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117933145A (en) * | 2024-03-22 | 2024-04-26 | 长江三峡集团实业发展(北京)有限公司 | GNSS-based troposphere delay modeling method for Sha Gehuang equal drought areas |
| CN117933145B (en) * | 2024-03-22 | 2024-05-24 | 长江三峡集团实业发展(北京)有限公司 | GNSS-based troposphere delay modeling method for Sha Gehuang drought region |
| CN117992706A (en) * | 2024-04-07 | 2024-05-07 | 武汉大学 | Point-to-plane conversion method and system for real-time troposphere zenith delay |
| CN117992706B (en) * | 2024-04-07 | 2024-06-11 | 武汉大学 | Point-to-plane conversion method and system for real-time troposphere zenith delay |
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