CN111323798A - GNSS occultation ionosphere error correction method and system based on ionosphere observation data - Google Patents
GNSS occultation ionosphere error correction method and system based on ionosphere observation data Download PDFInfo
- Publication number
- CN111323798A CN111323798A CN202010211937.9A CN202010211937A CN111323798A CN 111323798 A CN111323798 A CN 111323798A CN 202010211937 A CN202010211937 A CN 202010211937A CN 111323798 A CN111323798 A CN 111323798A
- Authority
- CN
- China
- Prior art keywords
- gnss
- occultation
- data
- profile
- ionosphere
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention discloses a GNSS occultation ionosphere error correction method and a GNSS occultation ionosphere error correction system based on ionosphere observation data, wherein the method comprises the following steps: acquiring GNSS occultation geometric data and ionosphere data; calculating an electron density profile at the occultation event tangent point position; calculating a dual-frequency bending angle difference profile based on the GNSS occultation geometric data and the electron density profile; judging whether the L2 signal data can be used for first-order non-ionized layer linear combination; if so, calculating an initial bending angle profile based on the L1 signal data and the L2 signal data, and correcting the initial bending angle profile by using a second-order term ionospheric residual error to obtain a corrected bending angle profile; otherwise, an initial bending angle profile is calculated based on the L1 signal data, and the initial bending angle profile is corrected by using the bending angle ionosphere error profile to obtain a corrected bending angle profile. The method can correct the GNSS atmospheric occultation second-order ionosphere residual error and improve the accuracy of the curve angle profile.
Description
Technical Field
The invention relates to the field of GNSS radio occultation atmosphere detection technology and meteorology, in particular to a GNSS occultation ionosphere error correction method and a GNSS occultation ionosphere error correction system based on ionosphere observation data.
Background
The GNSS (Global Navigation Satellite System) occultation detection technology can acquire the vertical profile of physical parameters such as neutral atmospheric refractive index, density, temperature, humidity, pressure and the like with high vertical resolution, high precision, no need of calibration, long-term stability and all weather, and provides a large amount of atmospheric detection data for global climate monitoring and numerical weather forecast. However, ionospheric errors have been a bottleneck limiting the high-precision application of GNSS atmospheric occultation data. At present, GNSS atmospheric occultation detection technology acquires L1 and L2 dual-frequency signal observed values, and ionospheric correction is carried out by a bending angle dual-frequency linear combination method, wherein the frequency of an L1 signal is greater than that of an L2 signal, so that the GNSS atmospheric occultation detection technology has strong atmospheric penetration capacity and is easy to capture and track. In the weather meteorological application of GNSS atmospheric occultation data, ionospheric error correction mainly has the following two problems: (1) in the lower atmosphere with complex physical environment and large water vapor, the L2 occultation signal is difficult to capture and track, so that the L2 occultation observation data quality of the lower atmosphere is poor or even lost, and the ionosphere error correction can not be carried out by using a bending angle double-frequency combination method. (2) The ionosphere residual error of the middle and high atmosphere (in the height range of 25-65 km) which is closer to the ionosphere is gradually increased, so that the atmospheric occultation data accuracy can not meet the requirements of climatological application.
With the development of the GNSS remote sensing technology, ground-based GNSS remote sensing and GNSS ionospheric occultation detection can provide ionospheric data products such as Global Ionosphere Maps (GIM) and ionospheric electron density profiles. In particular, with regard to masquerading programs compatible with both neutral atmosphere and ionosphere detection, such as CHAMP, COSMIC, and FY-3C/-3D GNOS, the same masker event can detect both neutral atmosphere and ionosphere electron density profiles. The correction of the GNSS neutral atmosphere ionosphere error based on the GNSS remote sensing ionosphere data product becomes possible.
In summary, the poor quality of the occultation observation data of the low-level atmosphere L2 makes the linear combination of the dual-frequency curved-angle deionization layer difficult to implement, and the residual error of the ionosphere of the middle-high level atmosphere is a major bottleneck limiting the high-precision application of the GNSS atmospheric occultation data. The improvement and application of GNSS remote sensing ionosphere data product quality brings opportunity for solving the problem of GNSS atmospheric occultation ionosphere.
Disclosure of Invention
The invention aims to solve the problems of poor quality or missing of low-level atmosphere L2 occultation observation data, large ionospheric residual error of middle-level and high-level atmosphere and the like, so that the potential application value of a GNSS atmospheric occultation data product is mined, and the ionospheric residual error correction method of the GNSS atmospheric occultation detection data of the ionospheric data product based on ground-based GNSS remote sensing and GNSS occultation detection is provided.
In order to achieve the above object, the present invention provides a GNSS occultation ionosphere error correction method based on ionosphere observation data, the method comprising:
preprocessing GNSS atmospheric occultation original observation data, ground-based GNSS remote sensing and GNSS ionosphere occultation observation data to obtain GNSS occultation geometric data and ionosphere data;
calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ionosphere observation data; or calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ground-based GNSS ionosphere remote sensing data by combining an ionosphere mode;
calculating a dual-frequency bending angle difference profile based on the GNSS occultation geometric data and the electron density profile;
judging whether the L2 signal data can be used for first-order non-ionized layer linear combination or not based on the double-frequency bending angle difference profile; if so, calculating an initial bending angle profile based on the L1 signal data and the L2 signal data, and correcting the initial bending angle profile by using a second-order term ionospheric residual error to obtain a corrected bending angle profile;
otherwise, an initial bending angle profile is calculated based on the L1 signal data, and the initial bending angle profile is corrected by using the bending angle ionosphere error profile to obtain a corrected bending angle profile.
As an improvement of the above method, the GNSS occultation geometry data comprises: the occurence position of a occultation event, the curvature radius of a occultation tangent point, the difference of a ground level plane, an influence parameter, a GNSS satellite position vector and a LEO satellite position vector; the ionospheric data includes: vertical total electron content vTEC obtained through ground-based GNSS remote sensing data product at occultation event tangent point positionGroundAnd the vertical total electron content vTEC obtained through GNSS ionosphere occultation data informationROAnd electron density profile NeRO(a)。
As an improvement of the above method, the calculating of the electron density profile at the position of the occultation event tangent point based on the GNSS occultation geometric data and ionosphere observation data; the method specifically comprises the following steps:
calculating the vertical total electron content vTEC at the cut point position of the occultation event by adopting GNSS occultation geometric data and ground-based GNSS remote sensing dataGround；
Calculating an ionospheric electron density profile Ne at a occultation event tangent point position using GNSS occultation geometry data and GNSS ionospheric occultation dataRO(a) And vertical total electron content vTECROA is an influence parameter;
the electron density profile ne (a) at the occultation event tangent point position is calculated by the following weighted average formula:
wherein, WGroundAnd WROAre all weight coefficients.
As an improvement of the above method, the electron density profile at the occultation point position of the occultation event is calculated based on the GNSS occultation geometric data and the ground-based GNSS ionosphere remote sensing data, in combination with the ionosphere mode; the method specifically comprises the following steps:
calculating the vertical total electron content vTEC at the cut point position of the occultation event by adopting GNSS occultation geometric data and IGS station vTEC maps dataGround；
Calculating the ionospheric electron density profile Ne at the occultation point position of the occultation event by adopting GNSS occultation geometric data and ionospheric modeModel(a) And vertical total electron content vTECModelA is an influence parameter;
calculating the electron density profile ne (a) at the occultation event tangent point position:
Ne(a)＝(vTECGround/vTECModel)×NeModel(a)。
as an improvement of the above method, the dual-frequency bending angle difference profile is calculated based on the GNSS occultation geometric data and the electron density profile; the method specifically comprises the following steps:
calculating the cumulative influence value F (a) of the electron density of the ionized layer along the GNSS occultation electric wave signal path and the low-orbit satellite:
wherein the content of the first and second substances,a is an influence parameter, rGAnd rLThe distances from the geocentric to the GNSS and LEO satellites respectively;
calculating the two-frequency bending angle difference profile Delta α of the L1 and L2 signals1,2(a)：
Wherein C is a constant 40.308, f1And f2The L1 signal frequency and the L2 signal frequency.
As an improvement of the above method, the determining whether the L2 signal data can be used for the first-order ionosphere-free linear combination based on the dual-frequency bending angle difference profile specifically includes:
firstly, judging whether the L2 signal is unlocked below 10km or not, and if the L2 signal is unlocked, judging whether the L2 signal is unlocked or not; if not, determining whether the quality of the L2 signal data is suitable for the first-order non-ionosphere linear combination, specifically:
observed dual-frequency bending angle difference profile α is calculated from L1 signal and L2 signal observation dataL1(a)-αL2(a)；αL1(a) Is a bending angle profile calculated by original observation data of a GNSS atmospheric occultation L1 frequency band, αL2(a) The curve angle profile is calculated by original observation data of a GNSS atmospheric occultation L2 frequency band;
judgment of
Whether the difference is between 0.7 and 1.3, if so, judging that the result is yes, otherwise, judging that the result is no.
As an improvement of the above method, the calculating an initial bending angle profile based on the L1 signal data and the L2 signal data, and correcting the initial bending angle profile by using the second-order ionospheric residual error to obtain a corrected bending angle profile specifically includes:
initial bend angle profile α was calculated using a dual-frequency first-order-term ionosphere-free linear combination method based on L1 signal data and L2 signal dataC(a)：
Calculating a second-order ionospheric residual error δ α (a):
δα(a)＝-k·[Δα1,2(a)]2
wherein k is an empirical parameter;
calculate the corrected bend angle profile α (a):
α(a)＝αC(a)+δα(a)。
as an improvement of the above method, the calculating an initial bending angle profile based on the L1 signal data, and correcting the initial bending angle profile by using the bending angle ionospheric error profile to obtain a corrected bending angle profile specifically includes:
calculating an ionospheric error Δ α (a) comprising first and second order terms:
wherein k is an empirical parameter;
calculate the corrected bend angle profile α (a):
α(a)＝αL1(a)+Δα(a)；
wherein the initial bend angle profile is αL1(a)。
The invention also provides a GNSS occultation ionosphere error correction system based on ionosphere observation data, which comprises:
the preprocessing module is used for preprocessing GNSS atmospheric occultation original observation data, ground-based GNSS remote sensing and GNSS ionosphere occultation data to acquire GNSS occultation geometric data and ionosphere data;
the electronic density profile calculation module is used for calculating the electronic density profile at the occultation event tangent point position based on GNSS occultation geometric data and ionosphere observation data; or calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ground-based GNSS ionosphere remote sensing data by combining an ionosphere mode;
the double-frequency bending angle difference profile calculation module is used for calculating a double-frequency bending angle difference profile based on GNSS occultation geometric data and the electron density profile;
the judging module is used for judging whether the L2 signal data can be used for first-order non-ionized layer linear combination or not based on the double-frequency bending angle difference profile;
the bending angle ionospheric error correction module is used for calculating an initial bending angle profile based on the L1 signal data and the L2 signal data and correcting the initial bending angle profile by using a second-order ionospheric residual error to obtain a corrected bending angle profile if the output result of the judgment module is yes; otherwise, an initial bending angle profile is calculated based on the L1 signal data, and the initial bending angle profile is corrected by using the bending angle ionosphere error profile to obtain a corrected bending angle profile.
The invention has the advantages that:
1. the method comprehensively uses ground GNSS remote sensing, GNSS ionosphere occultation detection data and ionosphere mode data, and fully considers the near-real ionosphere environment of GNSS occultation events;
2. the method can be used for occultation events that the L2 signal is unlocked or the observed data quality is poor;
3. the method can correct the GNSS atmospheric occultation second-order ionosphere residual error and improve the accuracy of the curve angle profile.
Drawings
FIG. 1 is a flowchart of a GNSS atmospheric masker ionosphere error correction method based on ionosphere observation data according to embodiment 1 of the present invention;
FIG. 2 is a curved angle ionosphere error profile and a second order residual error profile of a 7/15/7/M MetOp-B full-day occultation event in 2013 obtained by the method of the present invention;
fig. 3 is a schematic diagram of a GNSS atmospheric masquerading ionosphere error correction system based on ionosphere observation data according to embodiment 2 of the present invention.
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.
The invention provides a GNSS atmospheric occultation ionosphere error correction method of ionosphere data products based on ground-based GNSS remote sensing and GNSS occultation detection, aiming at the problems of low-level atmosphere L2 occultation signal lock loss or poor observation data quality in GNSS atmospheric occultation detection, and ionosphere error correction problems such as large ionosphere residual error of middle and high-level atmosphere, and the like, and comprising the following steps: the GNSS occultation geometric data and the ionosphere space environment data are obtained by interpreting and analyzing GNSS atmospheric occultation observation data and preprocessing related GNSS remote sensing ionosphere data products; determining ionospheric input parameters by combining an ionospheric mode according to the preprocessed data; establishing GNSS occultation bending angle ionosphere error models aiming at different situations according to the GNSS occultation geometry and the ionosphere input parameters; and acquiring the ionosphere error profile of the GNSS occultation bending angle according to the ionosphere error model. The method effectively utilizes GNSS remote sensing ionosphere data products, solves the problems of low-level atmosphere L2 occultation signal lock losing and medium-high-level atmosphere ionosphere residual error larger in GNSS atmospheric occultation data inversion, and accordingly obtains the GNSS occultation bending angle profile with higher accuracy.
Example 1
As shown in fig. 1, an ionosphere data product based on ground-based GNSS remote sensing and GNSS occultation detection, embodiment 1 of the present invention provides a method for correcting an ionosphere error of GNSS occultation based on ionosphere observation data, which can comprehensively utilize ionosphere remote sensing products and ionosphere mode data, and includes the following steps:
s101, reading GNSS atmospheric occultation double-frequency observation data, geometric data and a GNSS remote sensing ionosphere product;
the embodiment adopts GPS-CHAMP and GPS-MetOp atmospheric occultation data, and vTEC maps data products and GPS-CHAMP occultation ionosphere data products issued by an IGS station to perform data processing and model verification;
s102, obtaining GNSS occultation geometric input parameters through data preprocessing;
the main GNSS occultation geometry input parameters of this embodiment include: the method comprises the following steps of (1) occultation event tangent point position, occultation tangent point curvature radius, large ground level plane gap, influence parameters, GNSS satellite position vector and LEO satellite position vector;
s103, determining ionospheric input parameters according to the ionospheric data product of S101, the GNSS occultation geometric input parameters of S102 and the ionospheric climate pattern;
the main ionospheric input parameters of this embodiment are ionospheric electron density profiles at the occultation tangent point position, and the calculation specifically includes the following steps:
step S103-1) calculating the vertical total electron content vTEC at the occultation point position of the occultation event by adopting GPS-CHAMP occultation geometric data and IGS station vTEC maps dataGround；
Step S103-2) calculating the ionosphere electron density profile Ne at the occultation point position of the occultation event by adopting GPS-CHAMP occultation geometric data and GPS-CHAMP occultation ionosphere productRO(a) And vertical total electron content vTECRO；
Step S103-3) calculating an electron density profile at the occultation tangent point position according to the ionosphere data obtained by the calculation in the steps S103-1) and S103-2) by using the following weighted average formula:
weight coefficient W in the formulaGroundAnd WROMainly related to the position of the GNSS occultation tangent point, in inland areas W with more dense foundation stationsGroundGreater than WROAnd in deep sea or desert areas W lacking a ground observation stationROGreater than WGround；
When the metalp masker plan does not have an ionospheric sounding data product, its masker geometry data and NeUoG ionospheric model are used for the metalp masker event, S103 includes:
step S103-1') calculating the vertical total electron content vTEC at the position of the tangent point of the occultation event by adopting GPS-MetOp occultation geometric data and IGS station vTEC maps dataGround；
Step S103-2') calculating an ionospheric electron density profile Ne at the occultation event tangent pointModel(a) And vertical total electron content vTECModel；
Step S103-3') calculating an electron density profile at the occultation tangent point position:
Ne(a)＝(vTECGround/vTECModel)×NeModel(a)；
s104, establishing a model for simulation calculation of the dual-frequency bending angle difference profile according to the GNSS geometry in the S102 and the ionosphere input parameters in the S103; the method comprises the following specific steps:
step S104-1) calculating the cumulative influence value F (a) of the electron density of the ionized layer along the GNSS masquerade radio wave signal path and the low-orbit satellite:
in which a is an influencing parameter, rGAnd rLThe distance from the geocentric to the GNSS and LEO satellites, respectively.
Step S104-2) simulation calculation of the dual-frequency bending angle difference delta α1,2(a)：
Wherein C is a constant 40.308, f1,2The L1 and L2 signal frequencies.
S105, detecting whether the L2 signal data can be used for first-order non-ionosphere linear combination;
step S105-1) preliminarily judging whether the L2 signal is unlocked at 10km, and judging that the detection is failed if the signal is unlocked; if the lock is not lost, the next judging step is carried out;
step S105-2) determining whether the quality of the L2 data is suitable for the first-order non-ionospheric linear combination, if calculated using the observed data, αL1(a)-αL2(a) Satisfy inequality
α, judging the result is passed, otherwise, judging the result is not passedL1(a) Is a bending angle profile calculated by original observation data of a GNSS atmospheric occultation L1 frequency band, αL2(a) The curve angle profile is calculated by original observation data of a GNSS atmospheric occultation L2 frequency band;
if the L2 data product passes the detection in S105, the following steps are executed to obtain the ionospheric error corrected curve angle profile:
s106, calculating an initial bending angle profile α by using a dual-frequency first-order non-ionosphere linear combination methodC(a)
S107, calculating a second-order ionospheric residual error profile of a bending angle according to the model
δα(a)＝-k·[Δα1,2(a)]2
Where k is an empirical parameter, and in this embodiment k is equal to 16.
S110, obtaining the corrected bending angle profile
α(a)＝αC(a)+δα(a)
If the L2 data product fails to pass the detection in S105, the following steps are executed to obtain the ionospheric error corrected curve angle profile:
s108, calculating an initial bending angle profile α by using L1 signal dataL1(a)；
S109, calculating α a bending angle profile according to the modelL1(a) Error profile of (a):
where k is an empirical parameter, and in this embodiment k is equal to 16.
S110, obtaining the corrected bending angle profile
α(a)＝αL1(a)+Δα(a)
Fig. 2 shows the curve angle error profile and the second-order term residual error profile calculated by the above method, as an example of a 7/15/7/2013 day metalp-B occultation event, indicating that the method of the present invention is feasible.
Example 2
As shown in fig. 3, an embodiment 2 of the present invention provides a GNSS masquerading ionosphere error correction system based on ionosphere observation data, the system including:
the preprocessing module 201 is configured to preprocess GNSS atmospheric occultation original observation data, ground-based GNSS remote sensing and GNSS ionosphere occultation data, and acquire GNSS occultation geometric data and ionosphere data;
the electronic density profile calculation module 202 is configured to calculate an electronic density profile at a occultation event tangent point position based on GNSS occultation geometric data and ionosphere observation data; or calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ground-based GNSS ionosphere remote sensing data by combining an ionosphere mode;
a dual-frequency bending angle difference profile calculation module 203, configured to calculate a dual-frequency bending angle difference profile based on the GNSS occultation geometric data and the electron density profile;
a judging module 204, configured to judge whether the L2 signal data can be used for first-order ionosphere-free linear combination based on the dual-frequency bending angle difference profile;
a bending angle ionospheric error correction module 205, configured to, if the output result of the determination module is yes, calculate an initial bending angle profile based on the L1 signal data and the L2 signal data, and correct the initial bending angle profile by using a second-order term ionospheric residual error, to obtain a corrected bending angle profile; otherwise, an initial bending angle profile is calculated based on the L1 signal data, and the initial bending angle profile is corrected by using the bending angle ionosphere error profile to obtain a corrected bending angle 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 (9)
1. A GNSS masquerading ionosphere error correction method based on ionosphere observation data, the method comprising:
preprocessing GNSS atmospheric occultation original observation data, ground-based GNSS remote sensing and GNSS ionosphere occultation observation data to obtain GNSS occultation geometric data and ionosphere data;
calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ionosphere observation data; or calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ground-based GNSS ionosphere remote sensing data by combining an ionosphere mode;
calculating a dual-frequency bending angle difference profile based on the GNSS occultation geometric data and the electron density profile;
judging whether the L2 signal data can be used for first-order non-ionized layer linear combination or not based on the double-frequency bending angle difference profile; if so, calculating an initial bending angle profile based on the L1 signal data and the L2 signal data, and correcting the initial bending angle profile by using a second-order term ionospheric residual error to obtain a corrected bending angle profile;
otherwise, an initial bending angle profile is calculated based on the L1 signal data, and the initial bending angle profile is corrected by using the bending angle ionosphere error profile to obtain a corrected bending angle profile.
2. The ionospheric observation data-based GNSS occultation ionospheric error correction method of claim 1, wherein the GNSS occultation geometry data comprises: the occurence position of a occultation event, the curvature radius of a occultation tangent point, the difference of a ground level plane, an influence parameter, a GNSS satellite position vector and a LEO satellite position vector; the ionospheric data includes: vertical total electron content vTEC obtained through ground-based GNSS remote sensing data product at occultation event tangent point positionGroundAnd the vertical total electron content vTEC obtained through GNSS ionosphere occultation data informationROAnd electron density profile NeRO(a)。
3. The method of claim 2, wherein the calculating of the electron density profile at the occultation point of the occultation event based on the GNSS occultation geometry data and the ionosphere observation data; the method specifically comprises the following steps:
calculating the vertical total electron content vTEC at the cut point position of the occultation event by adopting GNSS occultation geometric data and ground-based GNSS remote sensing dataGround；
Calculating an ionospheric electron density profile Ne at a occultation event tangent point position using GNSS occultation geometry data and GNSS ionospheric occultation dataRO(a) And vertical total electron content vTECROA is an influence parameter;
the electron density profile ne (a) at the occultation event tangent point position is calculated by the following weighted average formula:
wherein, WGroundAnd WROAre all weight coefficients.
4. The method for correcting the ionospheric-observation-data-based GNSS masquerading ionosphere error of claim 2, wherein the method for correcting the ionospheric-observation-data-based GNSS masquerading ionosphere error of the ionospheric-observation-data-based GNSS is characterized in that an electron density profile at a position of a occultation event tangent point is calculated based on GNSS masquerading geometric data and ground-based GNSS ionospheric remote sensing data in combination with an ionospheric model; the method specifically comprises the following steps:
calculating the vertical total electron content vTEC at the tangent point position of the occultation event by adopting GNSS occultation geometric data and ground-based GNSS ionosphere remote sensing dataGround；
Calculating the ionospheric electron density profile Ne at the occultation point position of the occultation event by adopting GNSS occultation geometric data and ionospheric modeModel(a) And vertical total electron content vTECModelA is an influence parameter;
calculating the electron density profile ne (a) at the occultation event tangent point position:
Ne(a)＝(vTECGround/vTECModel)×NeModel(a)。
5. the method of ionospheric observation data-based GNSS masquerade ionospheric error correction based on claim 3 or 4, wherein the dual-frequency curved angle difference profile is calculated based on GNSS masquerade geometric data and an electron density profile; the method specifically comprises the following steps:
calculating the cumulative influence value F (a) of the electron density of the ionized layer along the GNSS occultation electric wave signal path and the low-orbit satellite:
wherein a is an influence parameter, rGAnd rLThe distances from the geocentric to the GNSS and LEO satellites respectively;
calculating the two-frequency bending angle difference profile Delta α of the L1 and L2 signals1,2(a)：
Wherein C is a constant 40.308, f1And f2The L1 signal frequency and the L2 signal frequency.
6. The method as claimed in claim 5, wherein the determining whether the L2 signal data can be used for ionospheric-free first-order linear combination based on the dual-frequency curved angular difference profile comprises:
firstly, judging whether the L2 signal is unlocked below 10km or not, and if the L2 signal is unlocked, judging whether the L2 signal is unlocked or not; if not, determining whether the quality of the L2 signal data is suitable for the first-order non-ionosphere linear combination, specifically:
observed dual-frequency bending angle difference profile α is calculated from L1 signal and L2 signal observation dataL1(a)-αL2(a)；αL1(a) Is a bending angle profile calculated by original observation data of a GNSS atmospheric occultation L1 frequency band, αL2(a) The curve angle profile is calculated by original observation data of a GNSS atmospheric occultation L2 frequency band;
judgment of
Whether the difference is between 0.7 and 1.3, if so, judging that the result is yes, otherwise, judging that the result is no.
7. The method as claimed in claim 6, wherein the method for correcting the GNSS occultation ionosphere error based on ionosphere observation data comprises calculating an initial bending angle profile based on L1 signal data and L2 signal data, and correcting the initial bending angle profile by using the ionosphere residual error of the second order term to obtain a corrected bending angle profile, and specifically comprises:
initial bend angle profile α was calculated using a dual-frequency first-order-term ionosphere-free linear combination method based on L1 signal data and L2 signal dataC(a)：
Calculating a second-order ionospheric residual error δ α (a):
δα(a)＝-k·[Δα1,2(a)]2
wherein k is an empirical parameter;
calculate the corrected bend angle profile α (a):
α(a)＝αC(a)+δα(a)。
8. the method as claimed in claim 6, wherein the method for correcting the ionospheric error of GNSS masquerading based on ionospheric observation data comprises calculating an initial bending angle profile based on L1 signal data, and correcting the initial bending angle profile by using the bending angle ionospheric error profile to obtain a corrected bending angle profile, and specifically comprises:
calculating an ionospheric error Δ α (a) comprising first and second order terms:
wherein k is an empirical parameter;
calculate the corrected bend angle profile α (a):
α(a)＝αL1(a)+Δα(a)；
wherein the initial bend angle profile is αL1(a)。
9. A GNSS masquerading ionosphere error correction system based on ionosphere observation data, the system comprising:
the preprocessing module is used for preprocessing GNSS atmospheric occultation original observation data, ground-based GNSS remote sensing and GNSS ionosphere occultation data to acquire GNSS occultation geometric data and ionosphere data;
the electronic density profile calculation module is used for calculating the electronic density profile at the occultation event tangent point position based on GNSS occultation geometric data and ionosphere observation data; or calculating an electron density profile at the occultation event tangent point position based on GNSS occultation geometric data and ground-based GNSS ionosphere remote sensing data by combining an ionosphere mode;
the double-frequency bending angle difference profile calculation module is used for calculating a double-frequency bending angle difference profile based on GNSS occultation geometric data and the electron density profile;
the judging module is used for judging whether the L2 signal data can be used for first-order non-ionized layer linear combination or not based on the double-frequency bending angle difference profile;
the bending angle ionospheric error correction module is used for calculating an initial bending angle profile based on the L1 signal data and the L2 signal data and correcting the initial bending angle profile by using a second-order ionospheric residual error to obtain a corrected bending angle profile if the output result of the judgment module is yes; otherwise, an initial bending angle profile is calculated based on the L1 signal data, and the initial bending angle profile is corrected by using the bending angle ionosphere error profile to obtain a corrected bending angle profile.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010211937.9A CN111323798B (en) | 2020-03-24 | 2020-03-24 | GNSS occultation ionosphere error correction method and system based on ionosphere observation data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010211937.9A CN111323798B (en) | 2020-03-24 | 2020-03-24 | GNSS occultation ionosphere error correction method and system based on ionosphere observation data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111323798A true CN111323798A (en) | 2020-06-23 |
| CN111323798B CN111323798B (en) | 2021-04-09 |
Family
ID=71171669
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010211937.9A Active CN111323798B (en) | 2020-03-24 | 2020-03-24 | GNSS occultation ionosphere error correction method and system based on ionosphere observation data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111323798B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113189620A (en) * | 2021-04-13 | 2021-07-30 | 中国科学院国家空间科学中心 | GNSS occultation near space climate data inversion method and system |
| CN113220739A (en) * | 2021-04-13 | 2021-08-06 | 中国科学院国家空间科学中心 | Multi-source GNSS occultation data fusion-based climate data inversion method and system |
| CN114114467A (en) * | 2021-11-20 | 2022-03-01 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | Ionospheric data assimilation observation matrix construction method compatible with foundation GNSS and occultation data |
| CN114545447A (en) * | 2022-02-22 | 2022-05-27 | 应急管理部国家自然灾害防治研究院 | Method for correcting GNSS occultation ionization layer data |
| CN117194856A (en) * | 2023-11-07 | 2023-12-08 | 天津云遥宇航科技有限公司 | ERA5 and CIRA-based star-masking bending angle optimization method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150054686A1 (en) * | 2013-08-21 | 2015-02-26 | Samsung Electronics Co., Ltd. | System, method, and apparatus for compensating for ionospheric delay in a multi constellation single radio frequency path gnss receiver |
| CN110082791A (en) * | 2019-04-19 | 2019-08-02 | 中国科学院国家授时中心 | A kind of satellite navigation signals pseudorange biases accurate measurement and effectively eliminate method |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103163542B (en) * | 2013-03-26 | 2014-12-10 | 东南大学 | Observation constant based method for detecting gross error in global navigation satellite system (GNSS) baseline solution |
| KR20190135099A (en) * | 2018-05-28 | 2019-12-06 | 부산대학교 산학협력단 | Improvement of gnss-ro refraction angle calculation algorithm using geometric optics |
| CN110275183B (en) * | 2019-06-18 | 2021-03-09 | 中国科学院国家空间科学中心 | GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density |
-
2020
- 2020-03-24 CN CN202010211937.9A patent/CN111323798B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150054686A1 (en) * | 2013-08-21 | 2015-02-26 | Samsung Electronics Co., Ltd. | System, method, and apparatus for compensating for ionospheric delay in a multi constellation single radio frequency path gnss receiver |
| CN110082791A (en) * | 2019-04-19 | 2019-08-02 | 中国科学院国家授时中心 | A kind of satellite navigation signals pseudorange biases accurate measurement and effectively eliminate method |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113189620A (en) * | 2021-04-13 | 2021-07-30 | 中国科学院国家空间科学中心 | GNSS occultation near space climate data inversion method and system |
| CN113220739A (en) * | 2021-04-13 | 2021-08-06 | 中国科学院国家空间科学中心 | Multi-source GNSS occultation data fusion-based climate data inversion method and system |
| CN113189620B (en) * | 2021-04-13 | 2021-11-09 | 中国科学院国家空间科学中心 | GNSS occultation near space climate data inversion method and system |
| CN113220739B (en) * | 2021-04-13 | 2021-12-07 | 中国科学院国家空间科学中心 | Multi-source GNSS occultation data fusion-based climate data inversion method and system |
| CN114114467A (en) * | 2021-11-20 | 2022-03-01 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | Ionospheric data assimilation observation matrix construction method compatible with foundation GNSS and occultation data |
| CN114114467B (en) * | 2021-11-20 | 2023-04-25 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | Ionosphere data assimilation observation matrix construction method compatible with foundation GNSS and occultation data |
| CN114545447A (en) * | 2022-02-22 | 2022-05-27 | 应急管理部国家自然灾害防治研究院 | Method for correcting GNSS occultation ionization layer data |
| CN114545447B (en) * | 2022-02-22 | 2023-01-03 | 应急管理部国家自然灾害防治研究院 | GNSS occultation ionization layer data correction method |
| CN117194856A (en) * | 2023-11-07 | 2023-12-08 | 天津云遥宇航科技有限公司 | ERA5 and CIRA-based star-masking bending angle optimization method |
| CN117194856B (en) * | 2023-11-07 | 2024-01-26 | 天津云遥宇航科技有限公司 | ERA5 and CIRA-based star-masking bending angle optimization method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111323798B (en) | 2021-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111323798B (en) | GNSS occultation ionosphere error correction method and system based on ionosphere observation data | |
| US20220283320A1 (en) | Systems and methods for high-integrity satellite positioning | |
| CN110275184B (en) | GNSS occultation ionosphere residual error correction method, system, equipment and storage medium | |
| Syndergaard | On the ionosphere calibration in GPS radio occultation measurements | |
| EP2400268B1 (en) | Track information generating device, track information generating method, and computer-readable storage medium | |
| CN101971047B (en) | Device and method for the real-time monitoring of the integrity of a satellite navigation system | |
| CN101846735B (en) | Method and apparatus for precise relative positioning in multiple vehicles | |
| CN110275183B (en) | GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density | |
| AU2012203766A1 (en) | Satellite navigation system fault detection based on biased measurements | |
| US20240142637A1 (en) | System and method for gaussian process enhanced gnss corrections generation | |
| CN110988942B (en) | Satellite-borne GNSS-R mirror reflection point position accurate calculation method | |
| CN113189620B (en) | GNSS occultation near space climate data inversion method and system | |
| CN110456388B (en) | Device and method for calibrating satellite-borne GNSS-R sea surface height factors | |
| CN115267855B (en) | Abnormal value detection method and differential positioning method in GNSS-INS tight combination | |
| CN109613582B (en) | Vehicle-mounted real-time single-frequency meter-level pseudo-range positioning method | |
| CN110207721B (en) | Invalid terrain matching result identification method considering residual distribution | |
| CN110426717B (en) | Cooperative positioning method and system, positioning device and storage medium | |
| CN115902963A (en) | Single-point positioning data processing method and device, electronic equipment and storage medium | |
| CN115657097A (en) | Orbit constraint-based rapid reconvergence method for orbit determination ambiguity of LEO geometric method | |
| JP2008039691A (en) | Carrier-wave phase type position measuring instrument | |
| US20210181357A1 (en) | System and method for validating gnss ambiguities | |
| CN115980317B (en) | Foundation GNSS-R data soil moisture estimation method based on corrected phase | |
| CN116358566B (en) | Coarse detection combined navigation method based on robust adaptive factor | |
| JP4901365B2 (en) | Positioning system, positioning method and positioning program | |
| CN116224390A (en) | Multi-frequency GNSS occultation processing method, device, equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |