A piecewise fitting inversion method and system for detecting mid- and high-level atmospheric density

Abstract

The invention discloses a piecewise fitting inversion method and system for detecting the atmospheric density of the middle and high layers, the method comprising: uniformly stratifying the atmospheric layer, generating a fine grid, calculating the atmospheric density of each layer in the fine grid using an atmospheric model, setting the initial value of the atmospheric density correction factor to 1; uniformly segmenting the atmospheric layer into a plurality of sub-regions, with adjacent sub-regions overlapping; traversing each sub-region, screening out the satellite measured data points whose tangent point height is located in the sub-region, dividing the sub-region into a coarse grid, using the atmospheric density correction factor at the coarse grid vertex as the atmospheric density fitting inversion parameter of the sub-region, generating and replacing the atmospheric density correction factor of the fine grid by interpolation, fitting and solving the atmospheric density of the sub-region; respectively completing the atmospheric density solution of each sub-region, and obtaining the density profile of the entire atmospheric layer. The advantages of the invention are: being able to improve the calculation speed, realizing the dynamic adjustment of the resolution, and ensuring the continuity of the inversion result at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of space environment detection, and in particular to a piecewise fitting inversion method and system for detecting middle and upper atmospheric density. Background Art

[0002] The global detection of the atmospheric density in the middle and upper layers of 60-250km is of great value for the study of the energy transfer mechanism of the coupled earth spheres, as well as the design and flight control of aerospace vehicles. In recent years, the National Space Science Center of the Chinese Academy of Sciences has made breakthroughs in the tomographic detection technology of the atmospheric density in the middle and upper layers using X-ray occultation / solar occultation. This detection technology uses the characteristics of the absorption and attenuation of celestial X-rays by the atmospheric density in near-space to achieve global near-space atmospheric density detection through satellite platforms and occultation / sun occultation detection. During the implementation of this technology, the atmospheric density needs to be inverted through fitting. The fitting process usually faces the following problems: there are many fitting parameters and the time complexity is large; the vertical resolution at different altitudes needs to be adjusted according to the sampling interval of the satellite; the results of the atmospheric density inversion need to be continuous. Summary of the invention

[0003] The purpose of the present invention is to overcome the defects of the prior art that the fitting parameters are too many and the time complexity is large.

[0004] In order to achieve the above purpose, the present application proposes a segmented fitting inversion method for detecting the density of the middle and upper atmosphere, including:

[0005] Step 1) The atmosphere is evenly layered to generate a fine grid, the atmospheric density of each layer in the fine grid is calculated using the atmospheric model, and the initial value of the atmospheric density correction factor is set to 1;

[0006] Step 2) Evenly segment the atmosphere to generate a number of sub-areas, with the altitudes of adjacent sub-areas overlapping;

[0007] Step 3) traverse each sub-region, filter out the satellite measured data points whose tangent point height is within the sub-region, divide the sub-region into coarse grids, use the atmospheric density correction factor at the vertex of the coarse grid as the atmospheric density fitting inversion parameter of the sub-region, generate and replace the atmospheric density correction factor of the fine grid by interpolation, and fit and solve the atmospheric density of the sub-region;

[0008] Step 4) After the traversal is completed, the atmospheric density of each sub-region is solved respectively, so as to obtain the density profile of the entire atmosphere.

[0009] As an improvement to the above method, the upper and lower limits of the ith sub-region in step 2) are h upi and h downi , the heights of the adjacent i-th sub-region and i+1-th sub-region partially overlap, that is, hupi >h upi+1 ,h downi <h upi+1 .

[0010] As an improvement of the above method, in step 3), the satellite measured data points whose tangent point height is within the sub-area are screened out, and the tangent point height H j The following conditions are met: downi ≤H j ≤h upi .

[0011] As an improvement to the above method, in step 3), the spacing of the coarse grid is the expected vertical resolution, which is determined by the height interval of the satellite measured data points in the sub-area.

[0012] As an improvement to the above method, the division interval of the fine grid is determined by the expected vertical resolution and is one order of magnitude smaller than the expected vertical resolution.

[0013] As an improvement of the above method, in step 3), the atmospheric density correction factor at the vertex of the coarse grid is used as the atmospheric density fitting inversion parameter of the sub-region, and the atmospheric density correction factor of the fine grid is generated and replaced by interpolation to fit and solve the atmospheric density of the sub-region; comprising:

[0014] Step S1) using the atmospheric density correction factor at the vertex coarse grid as the atmospheric density fitting inversion parameter of the sub-region;

[0015] Step S2) Linear interpolation is performed on the coarse grid to generate and replace the atmospheric density correction factor γ of the corresponding sub-region in the fine grid k ;

[0016] Step S3) Calculate the transmittance of the satellite measured data point, combine it with the tangent point height H, and calculate the model calculated value t0(H) by the occultation rate function:

[0017] t0(H)=e -τ(H)

[0018]

[0019] Among them, l k (H) represents the distance that the light propagates in the kth layer of fine grid atmosphere, n s0 (h k ) represents the number density of the s component in the kth layer of fine grid atmosphere, σ s (E) represents the absorption cross section of the s component, E represents the energy of the X-ray photon; h k Indicates the altitude of each layer of the fine grid;

[0020] Step S4) calculating the logarithmic Poisson likelihood function based on the model calculated value and the screened satellite measured data points to obtain the C statistic;

[0021] Step S5) Adjust γ k Repeat steps S2) to S4) until the C statistic is maximized, and the optimal fitting parameters in the sub-region are obtained, and the fine grid correction factor γ is adjusted. k to update.

[0022] As an improvement of the above method, in step S4), the C statistic calculation formula is:

[0023]

[0024] Among them, d j =t j (H j ) is the transmittance fitting value of the jth satellite measured data point, m j =t0(H j ) is the transmittance model calculated value of the jth satellite measured data point.

[0025] As an improvement of the above method, the transmittance fitting value of the j-th satellite measured data point is calculated as follows:

[0026]

[0027] Among them, I j I0 represents the intensity of solar radiation recorded by the satellite after atmospheric attenuation, and I1 represents the intensity of solar radiation recorded by the satellite without attenuation.

[0028] The present invention also provides a piecewise fitting inversion system for detecting the density of the middle and upper atmosphere, which is implemented based on the above method, and the system comprises:

[0029] The fine grid division module is used to evenly divide the atmosphere into layers, generate fine grids, calculate the atmospheric density of each layer in the fine grid using the atmospheric model, and set the initial value of the atmospheric density correction factor to 1;

[0030] The sub-region division module is used to evenly segment the atmosphere into several sub-regions, with the altitudes of adjacent sub-regions overlapping;

[0031] A module for fitting the atmospheric density of a sub-region is used to traverse each sub-region, screen out the satellite measured data points whose tangent point height is within the sub-region, divide the sub-region into coarse grids, use the atmospheric density correction factors at the vertices of the coarse grids as the atmospheric density fitting inversion parameters of the sub-region, generate and replace the atmospheric density correction factors of the fine grids by interpolation, and fit and solve the atmospheric density of the sub-region; and

[0032] The density profile calculation module is used to solve the atmospheric density of each sub-area separately and obtain the density profile of the entire atmosphere.

[0033] Compared with the prior art, the advantages of the present invention are:

[0034] The present invention designs a piecewise fitting inversion calculation method, which can improve the calculation speed, realize the dynamic adjustment of the resolution, and ensure the continuity of the inversion result. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of the method of the present invention;

[0036] Figure 2 This is a schematic diagram of dividing the atmosphere into coarse grids and fine grids;

[0037] Figure 3 is the satellite measured solar occultation transmittance and the solar occultation transmittance of the inversion result;

[0038] Figure 4 It is a comparison between the atmospheric density inversion results and the nrlmsise atmospheric model. DETAILED DESCRIPTION

[0039] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0040] Example 1

[0041] The present invention provides a segmented fitting inversion method for detecting the middle and upper atmospheric density. On the basis of the middle and upper atmospheric density detection method of X-ray occultation, the target area for atmospheric density inversion is divided into sub-areas, and the atmospheric density in each sub-area is solved respectively.

[0042] like Figure 1 As shown, the actual implementation process includes the following steps:

[0043] Step 1) Use Beer's law to construct the solar occultation rate function t0(H) with the tangent point height H as the independent variable:

[0044] t0(H)=e -τ(H)

[0045] where τ is the integral of the product of the atomic number density and the absorption cross section along the X-ray path:

[0046]

[0047] Where s is the atomic composition of the atmosphere, n s and σ s They represent the number density and absorption cross section of different atoms in the atmosphere respectively, and E represents the energy of X-ray photons.

[0048] In the actual calculation process, the atmosphere needs to be discretized into layers, then:

[0049]

[0050] Among them, l k represents the distance that the light travels in the kth layer of the atmosphere, n s0 (h k ) represents the number density of component s in the kth layer of the atmosphere, γ k It represents the correction factor of atmospheric density and participates in the atmospheric density inversion calculation as a parameter.

[0051] Step 2) Divide the solar radiation intensity I recorded by the satellite after atmospheric attenuation by the solar radiation intensity I0 without attenuation to obtain the transmittance of the jth satellite measured data point. At the same time, the height H of the heliocentric tangent point is calculated based on the positional relationship between the sun, the earth, and the satellite. j , and obtain a series of fitting data t j (H j );

[0052] Step 3) Evenly layer the atmosphere and generate a fine grid (such as Figure 2 As shown), the altitude of each layer is h k , use the atmospheric model to calculate the atmospheric density n of each layer in the fine grid s0 (h k ), set the correction factor γ k The initial value of is 1;

[0053] The fine grid division interval should be determined by the expected vertical resolution, which should be one order of magnitude smaller than the expected vertical resolution. The expected vertical resolution is determined by the satellite sampling tangent point height interval, and the two should be of the same order of magnitude.

[0054] Step 4) Divide the atmosphere into sub-regions and use h upi and h downi represents the upper and lower limits of the ith sub-region, and arranges them from high to low altitude. The heights of two adjacent sub-regions overlap slightly, which satisfies h upi >h upi+1 ,h downi <h upi+1 ;

[0055] The division of sub-regions should be such that the number of fitting parameters in each sub-region in step 6) can reach between 5 and 15, so as to achieve a good balance between the goodness of fit of the inversion and the time required for calculation;

[0056] Step 5), for the i-th sub-region, select the tangent point height in step 2) that satisfies h downi ≤H j≤h upi Satellite measured data points;

[0057] Step 6), divide the i-th sub-region into a coarse grid (such as Figure 2 The spacing is the expected vertical resolution, which is determined by the sampling tangent point height interval of the data points in the sub-area, and the atmospheric density correction factor at the grid vertex is used as the parameter for the atmospheric density fitting inversion in the sub-area;

[0058] Step 7) Linearly interpolate the coarse grid in step 6) and generate and replace the atmospheric density correction factor γ of the corresponding sub-region in the fine grid k , substitute into the occultation rate function t0(H) in step 1) to calculate the model value;

[0059] Step 8) Calculate the logarithmic Poisson likelihood function (C statistic) based on the model value of step 7) and the satellite measured data selected in step 5):

[0060]

[0061] where d j is the transmittance fitting value of the jth satellite measured data point, m j is the transmittance model calculated value of the jth satellite measured data point;

[0062] d j =t j (H j )

[0063] m j =t0(H j )

[0064] Step 9), adjust the fitting parameters of step 6), repeat steps 7) and 8) to maximize the C statistics, obtain the optimal fitting parameters in the sub-region, and adjust the fine grid correction factor γ k to update.

[0065] Step 10), traverse each sub-region in step 4), repeat steps 5) to 9), and solve the atmospheric density of each pair of sub-regions in turn, so as to obtain the density profile of the entire atmosphere.

[0066] The method described in the present invention was used to invert the atmospheric density using the solar occultation data observed by the DAXSS payload on the INSPIRESat-1 satellite at around 10UT on April 24, 2022. The results are as follows: Figure 3 and Figure 4 shown.

[0067] Example 2

[0068] The present invention also provides a piecewise fitting inversion system for detecting the density of the middle and upper atmosphere, which is implemented based on the above method, and the system comprises:

[0069] The fine grid division module is used to evenly divide the atmosphere into layers, generate fine grids, calculate the atmospheric density of each layer in the fine grid using the atmospheric model, and set the initial value of the atmospheric density correction factor to 1;

[0070] The sub-region division module is used to evenly segment the atmosphere into several sub-regions, with the altitudes of adjacent sub-regions overlapping;

[0071] The module for fitting the atmospheric density of sub-regions is used to traverse each sub-region, filter out the satellite measured data points whose tangent point height is within the sub-region, divide the sub-region into coarse grids, and use the atmospheric density correction factors at the vertices of the coarse grids as the atmospheric density fitting inversion parameters of the sub-region. The atmospheric density correction factors of the fine grids are generated and replaced by interpolation to fit and solve the atmospheric density of the sub-region.

[0072] The density profile calculation module is used to solve the atmospheric density of each sub-area separately and obtain the density profile of the entire atmosphere.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention is described in detail with reference to the embodiments, it should be understood by those skilled in the art that any modification or equivalent replacement of the technical solutions of the present invention does not depart from the spirit and scope of the technical solutions of the present invention and should be included in the scope of the claims of the present invention.

Claims

1. A piecewise fitting inversion method for detecting the density of the middle and upper atmosphere, comprising: Step 1) The atmosphere is evenly layered to generate a fine grid, the atmospheric density of each layer in the fine grid is calculated using the atmospheric model, and the initial value of the atmospheric density correction factor is set to 1; Step 2) Evenly segment the atmosphere to generate several sub-areas, with the altitudes of adjacent sub-areas overlapping; Step 3) Traverse each sub-region, select the satellite measured data points whose tangent point height is within the sub-region, divide the sub-region into coarse grids, use the atmospheric density correction factor at the vertex of the coarse grid as the atmospheric density fitting inversion parameter of the sub-region, generate and replace the atmospheric density correction factor of the fine grid by interpolation, and fit and solve the atmospheric density of the sub-region; Step 4) After the traversal is completed, the atmospheric density of each sub-region is solved respectively, so as to obtain the density profile of the entire atmosphere; In the step 3), the atmospheric density correction factor at the vertex of the coarse grid is used as the atmospheric density fitting inversion parameter of the sub-region, and the atmospheric density correction factor of the fine grid is generated and replaced by interpolation to fit and solve the atmospheric density of the sub-region; include: Step S1) using the atmospheric density correction factor at the vertex coarse grid as the atmospheric density fitting inversion parameter of the sub-region; Step S2) Linear interpolation is performed on the coarse grid to generate and replace the atmospheric density correction factor of the corresponding sub-region in the fine grid ; Step S3) Calculate the transmittance of the satellite measured data point, combined with the tangent point height H , the model value is calculated by the occultation rate function : in, Indicates that the light k The distance propagated in the atmosphere of a fine grid layer, Indicates k Layer fine grid atmosphere s The number density of the components, express s The absorption cross section of the component, E represents the energy of X-ray photons; Indicates the altitude of each layer of the fine grid; Step S4) calculating the logarithmic Poisson likelihood function based on the model calculated value and the screened satellite measured data points to obtain the C statistic; Step S5) Adjust Repeat steps S2) to S4) until the C statistic is maximized, and the optimal fitting parameters in the sub-region are obtained, and the fine grid correction factor to update.

2. The segmented fitting inversion method for detecting the middle and upper atmospheric density according to claim 1 is characterized in that: Step 2) i The upper and lower limits of the sub-regions are and , the adjacent i sub-regions and i +1 sub-areas have some overlap in height, which satisfies , .

3. The segmented fitting inversion method for detecting the middle and upper atmospheric density according to claim 2 is characterized in that: In step 3), the satellite measured data points whose tangent point height is within the sub-area are selected. The following conditions are met: .

4. The segmented fitting inversion method for detecting the middle and upper atmospheric density according to claim 3 is characterized in that: In step 3), the spacing of the coarse grid is the expected vertical resolution, which is determined by the height interval of the satellite measured data points in the sub-area.

5. The segmented fitting inversion method for detecting the density of the middle and upper atmosphere according to claim 4 is characterized in that: The division interval of the fine grid is determined by the expected vertical resolution and is one order of magnitude smaller than the expected vertical resolution.

6. The segmented fitting inversion method for detecting the density of the middle and upper atmosphere according to claim 1 is characterized in that: In step S4), the C statistic calculation formula is: in, For the j The transmittance fitting value of the satellite measured data point is For the j The transmittance model calculated value of the satellite measured data point.

7. The segmented fitting inversion method for detecting the density of the middle and upper atmosphere according to claim 6 is characterized in that: The said j The transmittance fitting value of the satellite measured data point is calculated as follows: = in, I j represents the intensity of solar radiation attenuated by the atmosphere as recorded by the satellite, I 0 Represents the unabridged solar radiation intensity recorded by the satellite.

8. A piecewise fitting inversion system for detecting the density of the middle and upper atmosphere, implemented based on the method described in any one of claims 1 to 7, characterized in that: The system comprises: The fine grid division module is used to evenly divide the atmosphere into layers, generate fine grids, calculate the atmospheric density of each layer in the fine grid using the atmospheric model, and set the initial value of the atmospheric density correction factor to 1; The sub-region division module is used to evenly segment the atmosphere into several sub-regions, with the altitudes of adjacent sub-regions overlapping; A module for fitting the atmospheric density of a sub-region is used to traverse each sub-region, screen out the satellite measured data points whose tangent point height is within the sub-region, divide the sub-region into coarse grids, use the atmospheric density correction factors at the vertices of the coarse grids as the atmospheric density fitting inversion parameters of the sub-region, generate and replace the atmospheric density correction factors of the fine grids by interpolation, and fit and solve the atmospheric density of the sub-region; and The density profile calculation module is used to solve the atmospheric density of each sub-area separately and obtain the density profile of the entire atmosphere.

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