CN114384556B - Regional high-resolution ionosphere TEC map reconstruction method - Google Patents
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- G—PHYSICS
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- 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
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- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
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Abstract
The invention discloses a regional high-resolution ionosphere TEC map reconstruction method, which comprises the following steps: step A, downloading and preprocessing foundation GNSS observation data: step B, foundation GNSS inclination TEC solution: step C, projecting a GNSS vertical TEC of a plurality of stations in a region: and D, reconstructing a regional high-resolution ionosphere TEC map. According to the method disclosed by the invention, the regional very high time and space resolution TEC map reconstruction can be realized by utilizing the regional denser foundation GNSS monitoring data based on a discrete cosine transform-punishment least squares regression (DCT-PLS) algorithm.
Description
Technical Field
The invention belongs to the field of space weather report forecast, and particularly relates to a regional high-resolution ionosphere TEC map reconstruction method in the field.
Background
Ionosphere is one of the most dominant sources of error in many radio information systems such as satellite navigation, communications, radar, etc. The total electron content (Total Electron Content, TEC) is an important parameter for representing the number density of ionized layer plasmas, and has important significance in improving the systemicity of radio information, improving the scientific research of space and the capability of forecasting space weather by grasping the time-space change characteristics and rules of the ionized layer plasmas.
With the development of satellite technology, foundation GNSS has become the most important quantitative source of global TEC mapping. Since 1998, the International GNSS Service (IGS) began to release global TEC map (Global Ionospheric Map, GIM) data publicly. With the increase of the number of GNSS station networks and the development of data processing technologies, there are a variety of modeling strategies for generating GIMs, including spherical harmonic method, tomography (CT) method, kalman filter assimilation, and the like.
With the establishment of global dense GNSS stations, it becomes possible to acquire a high resolution area TEC map. In recent years, the united states MIT has issued a1 ° ×1 ° ×5 minute resolution scattered TEC data product with more than 2000 GNSS monitoring stations worldwide; the Royal astronomical station (ROB) in Belgium utilizes GNSS monitoring stations dense in European region EUREF to achieve on-line release (ftp:// GNSS. Oma. Be/GNSS/products/IONEX /) of the European region near real-time TEC map product of 0.5 ×0.5 ×15 minutes.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a regional high-resolution ionosphere TEC map reconstruction method aiming at the requirements of regional refined ionosphere monitoring and medium-small scale disturbance analysis.
The invention adopts the following technical scheme:
In the method for reconstructing the regional high-resolution ionosphere TEC map, the improvement comprises the following steps:
step A, downloading and preprocessing foundation GNSS observation data:
step A1, downloading GNSS satellite observation data and satellite ephemeris data files;
A2, reading a data file, and acquiring GNSS original double-frequency observation data comprising carrier phase observation data, pseudo-range observation data and navigation satellite ephemeris;
Step A3, detecting cycle slip and abnormal value of the GPS observation data in the file, smoothing the code pseudo range by adopting double-frequency carrier phase observation data, and finally outputting the observation data file after smoothing;
step B, foundation GNSS inclination TEC solution:
step B1, calculating carrier phase ionosphere delay observables based on the dual-frequency carrier phase observables The specific method comprises the following steps:
Wherein i and j represent the numbers of the receiver and satellite, respectively; c represents the speed of light in vacuum; and/> The hardware delays of the satellite and receiver at frequencies f 1 and f 2, respectively; lambda 1 and lambda 2 represent the wavelengths corresponding to frequencies f 1 and f 2, respectively; /(I)And/>The ambiguity of the carrier phase at frequencies f 1 and f 2, respectively; b i and B j are the inter-frequency offset of the receiver and satellite, respectively, α being a constant;
Step B2, calculating pseudo-range ionosphere delay observed quantity based on double-frequency pseudo-range observed quantity The specific method comprises the following steps:
Step B3, dividing the original observation data of a certain satellite in a continuous arc segment into N groups, respectively obtaining N groups of carrier phases and pseudo-range ionosphere delay observables according to the steps B1 and B2, and calculating the average value of the sum of the pseudo-range and carrier phase ionosphere delay observables, wherein the average value is specifically expressed as:
step B4, the average value of the sum of the carrier phase and the pseudo-range ionospheric delay observed quantity obtained in the step B3 is carried back to the carrier phase ionospheric delay observed quantity to obtain the satellite line-of-sight direction ionospheric delay observed quantity The concrete steps are as follows:
Step B5, repeating the steps B1 to B4, and solving the high-precision ionosphere delay observed quantity in the satellite sight direction of each reference station satellite by satellite;
And step B6, respectively calculating B i and B j by adopting a method proposed by Ciraolo L, and further calculating the ionized layer inclination TEC, wherein the calculation method is as follows:
Step C, projecting a GNSS vertical TEC of a plurality of stations in a region:
Step C1, projecting the inclined TEC in the same period as a vertical TEC value according to the corresponding puncture point position:
VTEC＝TEC/M(E,h)
Where VTEC represents the vertical TEC projected on the receiver and satellite link, M (E, h) represents the projection function between the tilted TEC and the vertical TEC, E is the elevation angle, For the elevation angle between receiver i and satellite j, R e represents the earth radius, h represents the ionospheric layer height;
Step C2, dividing according to longitude as intervals, taking 1 degree from the longitude intervals, and grouping vertical TEC data falling in the same area, wherein each group of TEC is expressed as IV;
step C3, linear fitting is carried out on the change of the vertical TECs of the same group in the same longitude interval along with the latitude, and a threshold value judging method is adopted to filter out the TECs corresponding to points with larger deviation than other data points in the curve, wherein judging conditions are as follows:
|IVk-μ|＞2σ,k＝1,2,...,K
wherein K represents the data number, K represents the number of samples of IV, mu is the mean value of the data sequence, sigma is the standard deviation of the data, if the judgment condition is met, the TEC value is considered to have a rough difference, and the data is rejected;
step C4, repeating the step C3 until all data points are within an acceptable range, so as to ensure that the curve fitted by the vertical TEC obtained by converting the inclined TEC after all the grouping is smooth;
step D, reconstructing a regional high-resolution ionosphere TEC map:
Step D1, setting X to represent a VTEC space-time data set with a blank gap, wherein W is an array with the same size as the dimension X and is used for identifying whether the X value is missing or not;
step D2, adopting discrete cosine transform-punishment least squares regression algorithm to seek minimization The cost function F is expressed as follows:
where is the euclidean norm, And/>Respectively representing the Laplace operator and Schur product, s is a scalar for controlling the smoothness degree;
Step D3, regional TEC map The implementation is realized through the step D2 and the inverse discrete cosine transform, and is expressed as follows:
where Γ is a filter tensor, specifically denoted as:
Where p t represents the p-th element along the t-th dimension and n t represents the size along this dimension X.
The beneficial effects of the invention are as follows:
According to the method disclosed by the invention, the regional very high time and space resolution TEC map reconstruction can be realized by utilizing the regional denser foundation GNSS monitoring data based on a discrete cosine transform-punishment least squares regression (DCT-PLS) algorithm. The method can provide technical support for realizing regional high-resolution ionosphere monitoring and disturbance analysis.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a view of the projection effect of a GNSS vertical TEC of a plurality of stations in a region;
fig. 3 is a view of the effect of regional high resolution ionosphere TEC map reconstruction.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Events such as earthquake, tsunami, typhoon, rocket launch, etc. may cause small and obvious ionospheric disturbances; in spatial weather events such as solar flare and coronal mass projection (CME), severe disturbance changes in the ionosphere occur frequently in a short period of time. Analysis and modeling of smaller scale ionospheric disturbances requires ionospheric TEC map products of high temporal and spatial resolution. Currently, most GIM data products have a time resolution of usually 1-2 hours, the size of a geographic latitude and longitude grid is 2.5 degrees multiplied by 5 degrees, and TEC maps with the resolution cannot meet the requirements of fine ionosphere monitoring and small-medium-scale disturbance analysis.
Embodiment 1, this embodiment discloses a regional high resolution ionosphere TEC map reconstruction method, as shown in fig. 1, comprising the following steps:
step A, downloading and preprocessing foundation GNSS observation data:
step A1, downloading GNSS satellite observation data and satellite ephemeris data files;
A2, reading a data file, and acquiring GNSS original double-frequency observation data comprising carrier phase observation data, pseudo-range observation data and navigation satellite ephemeris;
Step A3, detecting cycle slip and abnormal values of the GPS observation data in the RINEX format file by adopting Bernese software, smoothing the code pseudo range by adopting the double-frequency carrier phase observation data, and finally outputting the smoothed observation data in the RINEX format file;
step B, foundation GNSS inclination TEC solution:
step B1, calculating carrier phase ionosphere delay observables based on the dual-frequency carrier phase observables The specific method comprises the following steps:
Wherein i and j represent the numbers of the receiver and satellite, respectively; c represents the speed of light in vacuum; and/> The hardware delays of the satellite and receiver at frequencies f 1 and f 2, respectively; lambda 1 and lambda 2 represent the wavelengths corresponding to frequencies f 1 and f 2, respectively; /(I)And/>The ambiguity of the carrier phase at frequencies f 1 and f 2, respectively; b i and B j are the frequency offset between the receiver and the satellite, respectively, and α is a constant, and the typical value is 40.31;
Step B2, calculating pseudo-range ionosphere delay observed quantity based on double-frequency pseudo-range observed quantity The specific method comprises the following steps:
wherein A, B i and B j have the same meaning as in step B1;
Step B3, dividing the original observation data of a certain satellite in a continuous arc segment into N groups, respectively obtaining N groups of carrier phases and pseudo-range ionosphere delay observables according to the steps B1 and B2, and calculating the average value of the sum of the pseudo-range and carrier phase ionosphere delay observables, wherein the average value is specifically expressed as:
the meanings of the variables in the above formula are the same as those in the steps B1 and B2;
step B4, the average value of the sum of the carrier phase and the pseudo-range ionospheric delay observed quantity obtained in the step B3 is carried back to the carrier phase ionospheric delay observed quantity, and the satellite line-of-sight direction ionospheric delay observed quantity can be obtained The concrete steps are as follows:
Step B5, repeating the steps B1 to B4, and solving the high-precision ionosphere delay observed quantity in the satellite sight direction of each reference station satellite by satellite;
Step B6, adopting the method proposed by Ciraolo L (specifically referring to Ciraolo L,Azpilicueta F,Brunini C,et al.Calibration errors on experimental slant total electron content(TEC)determined with GPS[J].J.Geod.,2007,81(2):111–120),, calculating B i and B j respectively, and further calculating the ionospheric tilt TEC, the calculation method is as follows:
Step C, projecting a GNSS vertical TEC of a plurality of stations in a region:
Step C1, projecting the inclined TEC in the same period as a vertical TEC value according to the corresponding puncture point position:
VTEC＝TEC/M(E,h)
Where VTEC represents the vertical TEC projected on the receiver and satellite link, M (E, h) represents the projection function between the tilted TEC and the vertical TEC, E is the elevation angle, For the elevation angle between receiver i and satellite j, R e represents the earth radius, h represents the ionosphere thin-layer altitude, typically taken at 350 km;
Step C2, dividing according to longitude as intervals, taking 1 degree from the longitude intervals, and grouping vertical TEC data falling in the same area, wherein each group of TEC is expressed as IV;
step C3, linear fitting is carried out on the change of the vertical TECs of the same group in the same longitude interval along with the latitude, and a threshold value judging method is adopted to filter out the TECs corresponding to points with larger deviation than other data points in the curve, wherein judging conditions are as follows:
|IVk-μ|＞2σ,k＝1,2,...,K
wherein K represents the data number, K represents the number of samples of IV, mu is the mean value of the data sequence, sigma is the standard deviation of the data, if the judgment condition is met, the TEC value is considered to have a rough difference, and the data is rejected;
And C4, repeating the step C3 until all data points are within an acceptable range, so as to ensure that the curve fitted by the vertical TEC obtained by converting the inclined TEC after all grouping is smoother, and the processing result is shown in figure 2.
Step D, reconstructing a regional high-resolution ionosphere TEC map:
Step D1, setting X to represent a VTEC space-time data set with a blank gap, wherein W is an array with the same size as the dimension X and is used for identifying whether the X value is missing or not;
Step D2, employing discrete cosine transform-penalty least squares regression algorithm (DCT-PLS) to seek minimization The reconstruction of the TEC map is realized, and the cost function F is expressed as follows:
where is the euclidean norm, And/>Representing the Laplace operator and Schur product, respectively, s being a scalar controlling the degree of smoothness;
Step D3, regional TEC map By step D2 and the Inverse Discrete Cosine Transform (IDCT), expressed as:
where Γ is a filter tensor, specifically denoted as:
Where p t represents the p-th element along the t-th dimension and n t represents the size along this dimension X. Fig. 3 shows a regional high resolution ionosphere TEC map reconstruction effect diagram.
Claims (1)
1. The regional high-resolution ionosphere TEC map reconstruction method is characterized by comprising the following steps of:
step A, downloading and preprocessing foundation GNSS observation data:
step A1, downloading GNSS satellite observation data and satellite ephemeris data files;
A2, reading a data file, and acquiring GNSS original double-frequency observation data comprising carrier phase observation data, pseudo-range observation data and navigation satellite ephemeris;
Step A3, detecting cycle slip and abnormal value of the GPS observation data in the file, smoothing the code pseudo range by adopting double-frequency carrier phase observation data, and finally outputting the observation data file after smoothing;
step B, foundation GNSS inclination TEC solution:
step B1, calculating carrier phase ionosphere delay observables based on the dual-frequency carrier phase observables The specific method comprises the following steps:
Wherein i and j represent the numbers of the receiver and satellite, respectively; c represents the speed of light in vacuum; and/> The hardware delays of the satellite and receiver at frequencies f 1 and f 2, respectively; lambda 1 and lambda 2 represent the wavelengths corresponding to frequencies f 1 and f 2, respectively; /(I)And/>The ambiguity of the carrier phase at frequencies f 1 and f 2, respectively; b i and B j are the inter-frequency offset of the receiver and satellite, respectively, α being a constant;
Step B2, calculating pseudo-range ionosphere delay observed quantity based on double-frequency pseudo-range observed quantity The specific method comprises the following steps:
Step B3, dividing the original observation data of a certain satellite in a continuous arc segment into N groups, respectively obtaining N groups of carrier phases and pseudo-range ionosphere delay observables according to the steps B1 and B2, and calculating the average value of the sum of the pseudo-range and carrier phase ionosphere delay observables, wherein the average value is specifically expressed as:
step B4, the average value of the sum of the carrier phase and the pseudo-range ionospheric delay observed quantity obtained in the step B3 is carried back to the carrier phase ionospheric delay observed quantity to obtain the satellite line-of-sight direction ionospheric delay observed quantity The concrete steps are as follows:
Step B5, repeating the steps B1 to B4, and solving the high-precision ionosphere delay observed quantity in the satellite sight direction of each reference station satellite by satellite;
And step B6, respectively calculating B i and B j by adopting a method proposed by Ciraolo L, and further calculating the ionized layer inclination TEC, wherein the calculation method is as follows:
Step C, projecting a GNSS vertical TEC of a plurality of stations in a region:
Step C1, projecting the inclined TEC in the same period as a vertical TEC value according to the corresponding puncture point position:
VTEC＝TEC/M(E,h)
Where VTEC represents the vertical TEC projected on the receiver and satellite link, M (E, h) represents the projection function between the tilted TEC and the vertical TEC, E is the elevation angle, For the elevation angle between receiver i and satellite j, R e represents the earth radius, h represents the ionospheric layer height;
Step C2, dividing according to longitude as intervals, taking 1 degree from the longitude intervals, and grouping vertical TEC data falling in the same area, wherein each group of TEC is expressed as IV;
step C3, linear fitting is carried out on the change of the vertical TECs of the same group in the same longitude interval along with the latitude, and a threshold value judging method is adopted to filter out the TECs corresponding to points with larger deviation than other data points in the curve, wherein judging conditions are as follows:
|IVk-μ|＞2σ,k＝1,2,...,K
wherein K represents the data number, K represents the number of samples of IV, mu is the mean value of the data sequence, sigma is the standard deviation of the data, if the judgment condition is met, the TEC value is considered to have a rough difference, and the data is rejected;
step C4, repeating the step C3 until all data points are within an acceptable range, so as to ensure that the curve fitted by the vertical TEC obtained by converting the inclined TEC after all the grouping is smooth;
step D, reconstructing a regional high-resolution ionosphere TEC map:
Step D1, setting X to represent a VTEC space-time data set with a blank gap, wherein W is an array with the same size as the dimension X and is used for identifying whether the X value is missing or not;
step D2, adopting discrete cosine transform-punishment least squares regression algorithm to seek minimization The cost function F is expressed as follows:
where is the euclidean norm, And/>Respectively representing the Laplace operator and Schur product, s is a scalar for controlling the smoothness degree;
Step D3, regional TEC map The implementation is realized through the step D2 and the inverse discrete cosine transform, and is expressed as follows:
where Γ is a filter tensor, specifically denoted as:
Where p t represents the p-th element along the t-th dimension and n t represents the size along this dimension X.
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| CN111273335A (en) * | 2019-12-20 | 2020-06-12 | 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 tomography method based on vertical measurement data constraint |
| KR20200084651A (en) * | 2019-01-03 | 2020-07-13 | 서울대학교산학협력단 | System and method for ionospheric correction using pseudorange and double-difference carrier phase measurement |
| CN113109840A (en) * | 2021-03-19 | 2021-07-13 | 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 TEC real-time measurement method based on GNSS receiver |
| CN113625356A (en) * | 2021-07-05 | 2021-11-09 | 江苏师范大学 | Real-time anomaly monitoring method suitable for single-station ionized layer TEC |
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| CN111273335A (en) * | 2019-12-20 | 2020-06-12 | 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 tomography method based on vertical measurement data constraint |
| CN113109840A (en) * | 2021-03-19 | 2021-07-13 | 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 TEC real-time measurement method based on GNSS receiver |
| CN113625356A (en) * | 2021-07-05 | 2021-11-09 | 江苏师范大学 | Real-time anomaly monitoring method suitable for single-station ionized layer TEC |
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