CN110275183B - GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density - Google Patents

GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density Download PDF

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CN110275183B
CN110275183B CN201910526514.3A CN201910526514A CN110275183B CN 110275183 B CN110275183 B CN 110275183B CN 201910526514 A CN201910526514 A CN 201910526514A CN 110275183 B CN110275183 B CN 110275183B
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柳聪亮
孙越强
杜起飞
白伟华
王先毅
蔡跃荣
孟祥广
夏俊明
王冬伟
李伟
吴春俊
刘成
赵丹阳
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Abstract

The invention provides a GNSS occultation ionosphere residual error correction method and a GNSS occultation ionosphere residual error correction system based on ionosphere electron density, wherein the method comprises the following steps: preprocessing GNSS occultation original observation data and ionosphere vTEC maps data to obtain GNSS occultation geometric data and ionosphere data; calculating electron density profiles of ionosphere puncture point positions on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode; and calculating a bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile. The GNSS occultation ionosphere residual error correction method and the GNSS occultation ionosphere residual error correction system can be used for single GNSS occultation event atmospheric parameter inversion to weaken the influence of ionosphere residual error, so that a GNSS occultation bending angle profile with higher precision is obtained, and the method and the system are efficient and reliable.

Description

GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density
Technical Field
The invention relates to the field of GNSS radio occultation atmosphere detection technology and meteorology, in particular to a GNSS occultation ionosphere residual error correction method and a GNSS occultation ionosphere residual error correction system based on ionosphere electron density.
Background
The GNSS occultation detection technology can obtain the vertical profiles of physical parameters such as high vertical resolution, high precision, no calibration, long-term stability, all-weather atmospheric refractive index, density, temperature, humidity, pressure and the like.
The sequential implementation of the GNSS masquerading plan provides a completely new data source for global climate monitoring and numerical weather forecast. The GNSS masquerading data product is applied to the climate analysis of a twenty-year time scale, and the analysis result shows that: the temperature precision of a single occultation observation profile is superior to 1K, the monthly average temperature precision is superior to 0.2K, and the requirement of a global climate monitoring system on the temperature precision can be met. Studies by the european mid-term weather forecast center show that: after the GNSS occultation observation data are assimilated, the numerical weather forecast precision is obviously improved.
Along with the rise of the height, the influence of an ionized layer is larger and larger, the accuracy of inversion atmospheric parameters is gradually reduced, and the occultation data accuracy of the top of an stratosphere and the bottom of an intermediate layer (within the height range of 25-60 km) can not meet the requirements of climatological application. At present, in the course of initializing the ionospheric residuals at the upper boundary by each large GNSS occultation data processing center in the world, the background atmosphere mode information is used for correcting or replacing the ionospheric residuals by a statistical optimization method, but the quality of GNSS occultation observation data is not substantially improved to reflect the physical state of the real atmosphere.
At present, a bending angle dual-frequency linear combination method is the most commonly used ionosphere correction method in GNSS occultation data processing. However, the curved angle corrected by the dual-frequency linear combination method still contains ionospheric residuals, which are the main bottleneck limiting the exploration of the upper atmosphere in the GNSS masker.
In order to attenuate the influence of ionospheric residuals, researchers have proposed "statistical characterization" and Kappa bend angle ionospheric residual correction methods. The 'statistical properties' and Kappa correction methods rely on statistical properties such as solar activity periods and diurnal variations of the bending angle ionospheric residuals or ionospheric prior statistical information. Therefore, they are suitable for analysis of climate change trend on a large spatio-temporal scale, but not for ionospheric residual correction and short-term local weather observation analysis of single occultation events. At present, the more advanced Kappa correction method is based on the assumption of symmetry of neutral atmosphere and ionized layer spheres, ignores the influence of uneven distribution of electron density along the masker signal path, and has poor reliability and accuracy.
In conclusion, bending angle ionosphere residual errors are main factors for restricting high-precision inversion of GNSS occultation data in the height range of 25-60 km; the Kappa bending angle ionosphere residual error correction method is based on the assumption of neutral atmosphere and ionosphere symmetry, neglects the influence of uneven distribution of electron density along a occultation signal path, is a simple statistical empirical model, and is poor in reliability and accuracy.
Disclosure of Invention
The invention aims to break through the limitation of the existing ionosphere residual error correction method, realize high-precision inversion of GNSS occultation data in a height range of 25-60 km, and provide the GNSS occultation ionosphere residual error correction method considering the asymmetry of the ionosphere electron density.
In order to achieve the above object, the present invention provides a GNSS masquerading ionosphere residual error correction method based on ionosphere electron density, the method comprising:
preprocessing GNSS occultation original observation data and ionosphere vTEC maps data to obtain GNSS occultation geometric data and ionosphere data;
calculating electron density profiles of ionosphere puncture point positions on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode;
and calculating a bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile.
As an improvement of the above method, the GNSS occultation geometry data comprises: occurence position of a occultation event, curvature radius of occultation tangent point, ground level surface difference, influence parameters, GNSS satellite position vector, LEO satellite position vector, incident ray side ionospheric puncture point position vector and emergent ray side ionospheric puncture point position vector; the ionospheric data includes: the solar activity intensity is F10.7 index, vTEC at the puncture point position of the side ionosphere of the 'incident ray' and vTEC at the puncture point position of the side ionosphere of the 'emergent ray'.
As an improvement of the above method, the electron density profiles of ionosphere puncture point positions on the sides of an incident line and an emergent line are calculated based on the GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere pattern; the method specifically comprises the following steps:
step 2-1) calculating the electron density profile of the ionosphere at the side ionosphere puncture point positions of an incident line and an emergent line of a occultation event by adopting GNSS occultation geometric data and a three-dimensional NeUoG ionosphere mode
Figure BDA0002098405760000021
And
Figure BDA0002098405760000022
and value of vTEC
Figure BDA0002098405760000023
And
Figure BDA0002098405760000024
step 2-2) calculating the vTEC values at the positions of the ionosphere puncture points on the sides of the incident ray and the emergent ray by adopting GNSS occultation geometric data and ionosphere data
Figure BDA0002098405760000025
And
Figure BDA0002098405760000026
step 2-3) respectively calculating electron density profiles Ne at the positions of the ionosphere puncture points on the sides of the incident ray and the emergent rayI350TAnd NeI350R：
Figure BDA0002098405760000027
Figure BDA0002098405760000031
As an improvement of the above method, the calculating a bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile specifically includes:
step 3-1), calculating an accumulated influence value F (a) of an ionosphere electron density square term along a GNSS occultation electric wave signal path and a low-orbit satellite:
Figure BDA0002098405760000032
wherein, NeI350R(rL) Is the ionospheric electron density value at the LEO satellite, a is the influence parameter, rGAnd rLPosition vectors for GNSS and LEO satellites, respectively;
step 3-2), calculating a bending angle ionosphere residual error profile delta alpha (a):
Figure BDA0002098405760000033
wherein C is a constant 40.308, f1And f2The frequencies of the dual frequency signals L1 and L2 of GPS.
The invention also provides a GNSS occultation ionosphere residual error correction system based on the ionosphere electron density, which comprises:
the preprocessing module is used for preprocessing GNSS occultation original observation data and ionosphere vTEC maps data to obtain GNSS occultation geometric data and ionosphere data;
the electron density calculation module is used for calculating electron density profiles of ionosphere puncture points on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode;
and the residual error correction module is used for calculating the bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile.
The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the computer program.
The invention also provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, causes the processor to perform the above-mentioned method.
The invention has the advantages that:
1. the GNSS occultation ionosphere residual error correction method and system based on the ionosphere electron density can comprehensively use ionosphere observation data and ionosphere mode data and fully consider the asymmetry of the ionosphere electron density along a signal path;
2. the GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density can be used in the atmospheric parameter inversion of a single GNSS occultation event to weaken the influence of ionosphere residual error, so that a GNSS occultation bending angle profile with higher precision is obtained, and the method and system are efficient and reliable;
3. the GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density can weaken the influence of ionosphere refraction effect on GNSS occultation neutral atmosphere bending angle profile and improve the accuracy of the bending angle profile.
Drawings
Fig. 1 is a flowchart of a GNSS masquerading ionosphere residual error correction method based on ionosphere electron density according to embodiment 1 of the present invention;
FIG. 2 is a schematic diagram of a curved angle ionosphere residual error profile and its statistical analysis results of a GPS/MetOp-A whole-day occultation event of 7, month and 15 days in 2008 in the embodiment of the present invention;
fig. 3 is a schematic diagram of a curved angle ionosphere residual error profile of a GPS/metap-a whole-day occultation event of 7/15/7/2013 in the embodiment of the present invention and a statistical analysis result thereof.
Detailed Description
In order to make the purpose and technical solution of the present invention clearer, the technical solution of the present invention will be described in detail below with reference to the accompanying drawings and examples.
In view of relevant theories and technologies, if the ionospheric residual profile of the dual-frequency curved angle linear combination method can be estimated, the influence of the ionospheric refraction effect on the accuracy of the neutral atmosphere curved angle profile can be further weakened in the GNSS occultation atmosphere parameter inversion, and then the high-accuracy GNSS occultation atmosphere data product can be obtained through the inversion.
Example 1
As shown in fig. 1, an embodiment 1 of the present invention provides a GNSS masquerading ionosphere residual error correction method based on ionosphere electron density, where the method considers ionosphere electron density asymmetry, and includes the following steps:
s11, GNSS occultation geometric data and ionosphere data are obtained through data preprocessing;
in this embodiment, GPS-metalop occultation observation data and the vTEC maps data product issued by the IGS station are used for data processing and model verification, and a basic input parameter mainly including a GNSS occultation geometric input parameter is shown in table 1:
TABLE 1 bending angle ionosphere residual correction model basic input parameters
Figure BDA0002098405760000059
S12, determining ionospheric input parameters according to the observation data and the ionospheric mode;
comprehensively using the model basic input parameters and the ionized layer mode data to determine ionized layer input parameters of an ionized layer residual error correction model;
in the embodiment, the ionosphere electron density profile at the position of the ionosphere puncture point on the sides of the incident line and the emergent line of the occultation event is calculated by adopting three-dimensional NeUoG ionosphere mode data and the occultation geometric parameters
Figure BDA0002098405760000051
And
Figure BDA0002098405760000052
and value of vTEC
Figure BDA0002098405760000053
And
Figure BDA0002098405760000054
calculating the vTEC values at the positions of the ionosphere puncture points on the sides of the 'incident ray' and the 'emergent ray' by adopting the vTEC maps data product issued by IGS and the occultation geometric parameters
Figure BDA0002098405760000055
And
Figure BDA0002098405760000056
calculating the normalized electron density profile Ne at the side ionosphere puncture point positions of the incidence line and the emergent line by a normalization method through the following formulaI350TAnd NeI350R。
Figure BDA0002098405760000057
Figure BDA0002098405760000058
Due to ionospheric electron density asymmetry, NeI350TAnd NeI350RAre not identical.
S13, establishing a GNSS occultation bending angle ionosphere residual error model according to the GNSS occultation geometry and ionosphere input parameters;
the cumulative effect along the GNSS masquerading wave signal path and at low earth orbit satellites is calculated by the equation:
Figure BDA0002098405760000061
wherein, NeI350TIonospheric electron density profile, Ne, on the "incident ray" sideI350RIonospheric electron density profile, Ne, on the "emergent ray" sideI350R(rL) Is the ionospheric electron density value at the LEO satellite, a is the influence parameter, rGAnd rLPosition vectors for GNSS and LEO satellites, respectively;
establishing the ionospheric residual model by the following formula, thereby calculating a curved angle ionospheric residual profile:
Figure BDA0002098405760000062
wherein C is a constant 40.308, f1And f2The frequencies of the dual-frequency signals L1 and L2 of GPS, a is high influence, alphaC(a) The curve angle profile after the error of the dual-frequency linear combination deionization layer is obtained, alpha (a) is the original curve angle profile, and delta alpha (a) is the curve angle ionosphere residual error profile.
And S14, acquiring the GNSS occultation bending angle ionosphere residual error profile according to the ionosphere residual error model.
Fig. 2 and 3 are the curved angle ionospheric residual profiles and their statistical analysis results for the GPS-MetOp occultation event all day for 2008 year 7 and 15 days (representing low solar activity) and 2013 year 7 and 15 days (representing high solar activity), respectively. It can be seen that the mean deviation and standard deviation of the solar activity low-age ionospheric residual profiles are smaller than those of the solar activity high-age. The curve angle ionospheric residual profile and statistics presented in figures 2 and 3 are close to the results of the Kappa curve angle ionospheric residual correction model. Moreover, the ionospheric residual error correction method of the GNSS occultation bending angle can be used for ionospheric residual error correction of a single occultation event, and the residual error profile is more accurate and reliable. The simulation results prove the reliability and superiority of the method provided by the invention.
Example 2
An embodiment 2 of the present invention provides a GNSS masquerading ionosphere residual error correction system based on ionosphere electron density, including:
the preprocessing module is used for preprocessing GNSS occultation original observation data and ionosphere vTEC maps data to obtain GNSS occultation geometric data and ionosphere data;
the electron density calculation module is used for calculating electron density profiles of ionosphere puncture points on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode;
and the residual error correction module is used for calculating the bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile.
Example 3
Embodiment 3 of the present invention provides a computer apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of embodiment 1 when executing the computer program.
Example 4
Embodiment 4 of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the method of embodiment 1.
It will be understood by those skilled in the art that all or part of the steps of the above methods may be implemented by instructing the relevant hardware through a program, and the program may be stored in a computer readable storage medium, such as a read-only memory, a magnetic or optical disk, and the like. Alternatively, all or part of the steps of the above embodiments may be implemented using one or more integrated circuits. Accordingly, each module/unit in the above embodiments may be implemented in the form of hardware, and may also be implemented in the form of a software functional module. The present invention is not limited to any specific form of combination of hardware and software.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (4)

1. A GNSS occultation ionosphere residual error correction method based on ionosphere electron density comprises the following steps:
preprocessing GNSS occultation original observation data and ionosphere vTEC maps data to obtain GNSS occultation geometric data and ionosphere data;
calculating electron density profiles of ionosphere puncture point positions on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode;
calculating a bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile;
the GNSS occultation geometry data comprises: occurence position of a occultation event, curvature radius of occultation tangent point, ground level surface difference, influence parameters, GNSS satellite position vector, LEO satellite position vector, incident ray side ionospheric puncture point position vector and emergent ray side ionospheric puncture point position vector; the ionospheric data includes: the solar activity intensity is F10.7 index, the vTEC is positioned at the puncture point of the side ionized layer of the incident ray and the vTEC is positioned at the puncture point of the side ionized layer of the emergent ray;
calculating electron density profiles of ionosphere puncture point positions on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode; the method specifically comprises the following steps:
step 2-1) calculating the electron density profile of the ionosphere at the side ionosphere puncture point positions of an incident line and an emergent line of a occultation event by adopting GNSS occultation geometric data and a three-dimensional NeUoG ionosphere mode
Figure FDA0002749671830000011
And
Figure FDA0002749671830000012
and value of vTEC
Figure FDA0002749671830000013
And
Figure FDA0002749671830000014
step 2-2) calculating the vTEC values at the positions of the ionosphere puncture points on the sides of the incident ray and the emergent ray by adopting GNSS occultation geometric data and ionosphere data
Figure FDA0002749671830000015
And
Figure FDA0002749671830000016
step 2-3) calculating the electron density profiles Ne at the ionospheric puncture site locations on the "incident" and "emergent" sides, respectivelyI350TAnd NeI350R：
Figure FDA0002749671830000017
Figure FDA0002749671830000018
The calculating of the bending angle ionosphere residual error profile based on the GNSS occultation geometric data and the electron density profile specifically comprises:
step 3-1), calculating an accumulated influence value F (a) of an ionosphere electron density square term along a GNSS occultation electric wave signal path and a low-orbit satellite:
Figure FDA0002749671830000021
wherein, NeI350R(rL) Is the ionospheric electron density value at the LEO satellite, a is the influence parameter, rGAnd rLPosition vectors for GNSS and LEO satellites, respectively;
step 3-2), calculating a bending angle ionosphere residual error profile delta alpha (a):
Figure FDA0002749671830000022
wherein C is a constant 40.308, f1And f2The frequencies of the dual frequency signals L1 and L2 of GPS.
2. A GNSS masquerading ionosphere residual correction system based on ionosphere electron density, the system comprising:
the preprocessing module is used for preprocessing GNSS occultation original observation data and ionosphere vTEC maps data to obtain GNSS occultation geometric data and ionosphere data;
the GNSS occultation geometry data comprises: occurence position of a occultation event, curvature radius of occultation tangent point, ground level surface difference, influence parameters, GNSS satellite position vector, LEO satellite position vector, incident ray side ionospheric puncture point position vector and emergent ray side ionospheric puncture point position vector; the ionospheric data includes: the solar activity intensity is F10.7 index, the vTEC is positioned at the puncture point of the side ionized layer of the incident ray and the vTEC is positioned at the puncture point of the side ionized layer of the emergent ray;
the electron density calculation module is used for calculating electron density profiles of ionosphere puncture points on the sides of an incident line and an emergent line based on GNSS occultation geometric data, ionosphere data and a three-dimensional NeUoG ionosphere mode; the method specifically comprises the following steps:
step 2-1) calculating the electron density profile of the ionosphere at the side ionosphere puncture point positions of an incident line and an emergent line of a occultation event by adopting GNSS occultation geometric data and a three-dimensional NeUoG ionosphere mode
Figure FDA0002749671830000023
And
Figure FDA0002749671830000024
and value of vTEC
Figure FDA0002749671830000025
And
Figure FDA0002749671830000026
step 2-2) calculating the vTEC values at the positions of the ionosphere puncture points on the sides of the incident ray and the emergent ray by adopting GNSS occultation geometric data and ionosphere data
Figure FDA0002749671830000027
And
Figure FDA0002749671830000028
step 2-3) respectively calculating electron density profiles Ne at the positions of the ionosphere puncture points on the sides of the incident ray and the emergent rayI350TAnd NeI350R：
Figure FDA0002749671830000031
Figure FDA0002749671830000032
The residual error correction module is used for calculating a bending angle ionosphere residual error profile based on GNSS occultation geometric data and an electron density profile, and specifically comprises the following steps:
step 3-1), calculating an accumulated influence value F (a) of an ionosphere electron density square term along a GNSS occultation electric wave signal path and a low-orbit satellite:
Figure FDA0002749671830000033
wherein, NeI350R(rL) Is the ionospheric electron density value at the LEO satellite, a is the influence parameter, rGAnd rLPosition vectors for GNSS and LEO satellites, respectively;
step 3-2), calculating a bending angle ionosphere residual error profile delta alpha (a):
Figure FDA0002749671830000034
wherein C is a constant 40.308, f1And f2The frequencies of the dual frequency signals L1 and L2 of GPS.
3. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of claim 1 when executing the computer program.
4. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to carry out the method of claim 1.
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