CN112711736B - Method and device for calibrating atmospheric density detection data, storage medium and processor - Google Patents
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Abstract
The invention discloses a calibration method and device for atmospheric density detection data, a storage medium and a processor. Wherein the method comprises the following steps: acquiring in-situ atmospheric density detection data of an atmospheric density detector, and establishing a first linear calibration model of the in-situ atmospheric density detection data; acquiring satellite orbit data, and determining a target value corresponding to a linear calibration coefficient of a first linear calibration model based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient; and converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating in-situ atmospheric density detection data based on the second linear calibration model. The invention solves the technical problem of poor timeliness of calibrating the atmospheric density detection data.
Description
Technical Field
The invention relates to the field of data processing, in particular to a calibration method, a device, a storage medium and a processor of atmospheric density detection data.
Background
Currently, uncertainty of the atmospheric density of a thermal layer is a key factor affecting orbit determination and prediction accuracy of a low-orbit spacecraft. Because the atmospheric density is affected by the solar radiation and the bottom atmospheric fluctuation, the change is very complex, and the physical mechanism of the change is not completely known so far. The development of the in-situ detection of the hot layer atmosphere has very important significance for knowing the change rule of the hot layer atmosphere and improving the precision of the existing empirical density model.
The current space-borne miniaturized atmospheric density detector mainly comprises a hot cathode vacuum gauge (pressure gauge) and a temperature and pressure sensing temperature sensor, has the advantages of small volume, low power consumption, low price and the like, and is atmospheric density detection equipment widely applied to low-orbit spacecrafts. However, as the ground cannot simulate the real atmosphere environment, long-term drift of instrument electronic components, other unknown uncertain factors and the like, the detection result of the pressure gauge has larger systematic deviation, in addition, the atmospheric density detector of the pressure gauge can only measure the temperature and the pressure in the sampling chamber, and further, atmospheric density data information is obtained, the atmospheric composition information needs to be given by depending on an empirical density mode or a physical atmospheric mode, so that mode errors can be caused, and although the output result of the empirical density mode or the physical atmospheric mode can be directly utilized for calibration, the method can lead to larger mode errors of the calibration result. Aiming at the systematic deviation of the in-situ atmospheric density detection data, domestic scholars usually use third party data for calibration: the atmospheric density is inverted by adopting a precise orbit ephemeris or two lines of root data (TLE), and then the in-situ detection data is calibrated by utilizing the inversion density data, but due to the difference of time scales of the two data, the in-situ detection data is required to be averaged within an inversion time interval, and then a set of calibration coefficients are matched within a long period of time by utilizing the averaged density data. Taking TLE data as an example, the density inversion interval is greater than 3 days, the fitted calibration coefficient interval is about 6 months, and TLE data from the north american air defense commander is often delayed by 2 weeks for external release. Thereby causing the problem of poor timeliness of calibrating the data
Aiming at the problem of poor timeliness of the atmospheric density detection data calibration, no effective solution is proposed at present.
Disclosure of Invention
The embodiment of the invention provides a method, a device, a storage medium and a processor for calibrating atmospheric density detection data, which are used for at least solving the technical problem of poor timeliness in calibrating the atmospheric density detection data.
According to an aspect of the embodiment of the present invention, there is provided a calibration method for atmospheric density detection data, including: acquiring in-situ atmospheric density detection data of an atmospheric density detector, and establishing a first linear calibration model of the in-situ atmospheric density detection data; acquiring satellite orbit data, and determining a target value corresponding to a linear calibration coefficient of a first linear calibration model based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient; and converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating in-situ atmospheric density detection data based on the second linear calibration model.
Optionally, calculating satellite orbit data based on the orbit estimation method, determining a target value corresponding to the linear calibration coefficient of the first linear calibration model includes: establishing an atmospheric resistance acceleration calculation model; obtaining a partial derivative by solving a partial derivative of the linear calibration coefficient through an atmospheric resistance acceleration calculation model; the target value is determined based on the trajectory estimation method and the partial derivative.
Optionally, determining the target value based on the trajectory estimation method and the partial derivative comprises: establishing an orbit variation equation based on the partial derivative, and integrating the orbit variation equation comprising the partial derivative by adopting a numerical integration method to obtain a state transition matrix, wherein the orbit variation equation is at least determined by the orbit position of the spacecraft, the speed of the spacecraft, the acceleration of the spacecraft, parameters to be estimated and the partial derivative, and the parameters to be estimated comprise linear calibration coefficients; estimating an improvement value of the target value based on the state transition matrix and the least square method, and updating the target value based on the improvement value; and carrying out iterative improvement on the target value.
Optionally, building an atmospheric resistance acceleration calculation model, including: acquiring the atmospheric density and the resistance coefficient, and acquiring a first product between the atmospheric density and the resistance coefficient; acquiring a spacecraft reference section and a spacecraft mass, and acquiring a first quotient between the spacecraft reference section and the spacecraft mass; acquiring the movement speed of the spacecraft relative to the atmosphere, and acquiring a first product, a first quotient and a second product among the movement speed; obtaining a mould of the movement speed, and obtaining a third product between the second product and the mould; the third product is determined as the atmospheric resistance acceleration.
Optionally, acquiring the movement speed of the spacecraft relative to the atmosphere includes: acquiring the movement speed of the spacecraft and the atmospheric wind speed, wherein the atmospheric wind speed is calculated by an atmospheric wind field model; acquiring a difference value between the movement speed of the spacecraft and the atmospheric wind speed; the difference is determined as the velocity of the spacecraft relative to the atmosphere.
Optionally, obtaining the drag coefficient includes: dividing the surface of the spacecraft into a plurality of single-sided flat plate combinations; obtaining a fourth product between the resistance coefficient of each single-sided flat plate and the reference section of the single-sided flat plate, and summing the fourth product to obtain a first sum; a second quotient between the first sum and the spacecraft reference section is obtained and the second quotient is determined as a drag coefficient.
Optionally, the in situ barometric density probe data is used to calculate the barometric density.
According to another aspect of the embodiment of the present invention, there is also provided a calibration device for atmospheric density detection data, including: the first acquisition unit is used for acquiring in-situ atmospheric density detection data of the atmospheric density detector and establishing a first linear calibration model of the in-situ atmospheric density detection data; the second acquisition unit is used for acquiring satellite orbit data and determining a target value corresponding to the linear calibration coefficient of the first linear calibration model based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient; and the calibration unit is used for converting the first linear calibration model into a second linear calibration model based on the target value and calibrating in-situ atmospheric density detection data based on the second linear calibration model.
According to another aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium. The computer readable storage medium comprises a stored program, wherein the device in which the computer readable storage medium is located is controlled to execute the method for calibrating the atmospheric density detection data according to the embodiment of the invention when the program runs.
According to another aspect of an embodiment of the present invention, there is also provided a processor. The processor is used for running a program, wherein the calibration method of the atmospheric density detection data is executed when the program runs.
In the embodiment of the application, in-situ atmospheric density detection data of an atmospheric density detector are acquired, and a first linear calibration model of the in-situ atmospheric density detection data is established; acquiring satellite orbit data, and determining a target value corresponding to a linear calibration coefficient of a first linear calibration model based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient; and converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating in-situ atmospheric density detection data based on the second linear calibration model. That is, the application determines the calibration coefficient of the linear calibration model through satellite orbit data, thereby determining the linear calibration model of the atmospheric density detection data, realizing the purpose of accurately and efficiently calibrating the atmospheric density detection data, correcting the systematic error and the mode error brought by adopting a pressure gauge to detect the atmospheric density in the prior art, avoiding the problems of long calibration period and low time resolution of the atmospheric density detection data by utilizing third party data, further solving the technical problem of poor timeliness of calibrating the atmospheric density detection data, and achieving the technical effect of enhancing the timeliness of calibrating the in-situ atmospheric density detection data.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method of calibrating barometric density probe data according to an embodiment of the invention;
FIG. 2 is a flow chart of another method of calibrating barometric density probe data according to an embodiment of the invention;
fig. 3 is a schematic diagram of an apparatus for calibrating atmospheric density detection data according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided an embodiment of a method for calibrating barometric pressure probe data, it being noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and that although a logical sequence is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in a different order than what is illustrated herein.
Fig. 1 is a flowchart of a method of calibrating barometric density probe data according to an embodiment of the invention. As shown in fig. 1, the method may include the steps of:
Step S102, acquiring in-situ atmospheric density detection data of an atmospheric density detector, and establishing a first linear calibration model of the in-situ atmospheric density detection data.
In the technical scheme provided in the step S102, after the in-situ atmospheric density detection data is obtained, the correlation between the obtained in-situ atmospheric density detection data and the inversion atmospheric density data can be analyzed, so as to obtain a stronger correlation, such as a linear correlation, between the two. Assuming that this linear correlation also exists between the in-situ barometric pressure probe data and the true barometric pressure data, a first linear calibration model of the in-situ barometric pressure probe data may be established, which may be formulated as follows:
ρtrue＝aρobs+b
Where ρ true can be used to represent true atmospheric density, ρ obs can be used to represent in situ probe atmospheric density, and a and b can be used to represent linear calibration coefficients.
Step S104, satellite orbit data are acquired, and a target value corresponding to the linear calibration coefficient of the first linear calibration model is determined based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient.
In the technical scheme provided in the step S104, a refined atmospheric resistance acceleration calculation model can be established, then a track variation equation is established by utilizing a track dynamics principle based on the established atmospheric resistance acceleration calculation model, and a target value corresponding to a linear calibration coefficient of the first linear calibration model can be determined based on a least square method and an iterative improvement method.
And S106, converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating in-situ atmospheric density detection data based on the second linear calibration model.
In the technical scheme provided in the step S106 of the present invention, after the target value of the linear calibration coefficient of the first linear calibration model is obtained, the target value of the linear calibration coefficient may be substituted into the first linear calibration model, and the first linear calibration model is converted into the second linear calibration model, so as to achieve the purpose of calibrating the in-situ atmospheric density detection data by using the linear calibration model.
Through the steps S102 to S106, in-situ atmospheric density detection data of the atmospheric density detector are obtained, and a first linear calibration model of the in-situ atmospheric density detection data is established; acquiring satellite orbit data, and determining a target value corresponding to a linear calibration coefficient of a first linear calibration model based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient; and converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating in-situ atmospheric density detection data based on the second linear calibration model. That is, the embodiment determines the calibration coefficient of the linear calibration model through satellite orbit data, thereby determining the linear calibration model of the atmospheric density detection data, realizing the purpose of accurately and efficiently calibrating the atmospheric density detection data, correcting the systematic error and the mode error brought by adopting a pressure gauge to detect the atmospheric density in the prior art, avoiding the problems of long calibration period and low time resolution of the atmospheric density detection data by utilizing third party data, further solving the technical problem of poor timeliness of calibrating the atmospheric density detection data, and achieving the technical effect of enhancing the timeliness of the in-situ atmospheric density detection data.
The above-described method of this embodiment is further described below.
As an alternative embodiment, calculating satellite orbit data based on an orbit estimation method, determining a target value corresponding to a linear calibration coefficient of a first linear calibration model, includes: establishing an atmospheric resistance acceleration calculation model; obtaining a partial derivative by solving a partial derivative of the linear calibration coefficient through an atmospheric resistance acceleration calculation model; the target value is determined based on the trajectory estimation method and the partial derivative.
In this embodiment, the linear calibration coefficient may be biased by the established atmospheric resistance acceleration calculation model to obtain a partial derivative, so that the target value corresponding to the linear calibration coefficient may be determined based on the track estimation method.
Optionally, the process of determining the target value corresponding to the linear calibration coefficient in this embodiment is track determination or track estimation.
In the above embodiment, the calculation model of the atmospheric resistance acceleration may be expressed as follows:
Wherein, Can be used to represent atmospheric drag acceleration, ρ can be used to represent atmospheric density, C D can be used to represent drag coefficient, A can be used to represent spacecraft reference section, m can be used to represent spacecraft mass, V r can be used to represent the mode of the spacecraft velocity relative to the atmosphere,/>Can be used to represent the speed of movement of the spacecraft relative to the atmosphere.
In the above embodiment, the partial derivatives of the atmospheric resistance acceleration with respect to the linear calibration coefficients a and b, respectively, may be expressed as follows:
Wherein, Can be used to represent the partial conductance of the atmospheric resistance acceleration with respect to the linear calibration coefficient a respectively,Can be used to represent the partial conductance of the atmospheric resistance acceleration with respect to the linear calibration coefficient b, respectively.
As an alternative embodiment, determining the target value based on the trajectory estimation method and the partial derivative includes: and establishing an orbit variation equation based on the partial derivative, and integrating the orbit variation equation comprising the partial derivative by adopting a numerical integration method to obtain a state transition matrix, wherein the orbit variation equation is at least determined by the orbit position of the spacecraft, the speed of the spacecraft, the acceleration of the spacecraft, parameters to be estimated and the partial derivative, and the parameters to be estimated comprise linear calibration coefficients.
In this embodiment, after obtaining the partial derivative of the linear calibration coefficient, a track variation equation may be established according to the obtained partial derivative, and then the established track variation equation may be integrated by a numerical integration method, thereby obtaining a state transition matrix, and an improved value of the target value of the linear calibration coefficient may be estimated by a least square method (least square method) using the state transition matrix, and then the target value may be iteratively updated using the improved value, thereby obtaining an optimal value of the target value.
In the above embodiment, the orbit variability equation may be determined by the orbit position of the spacecraft, the velocity of the spacecraft, and the acceleration of the spacecraft, and the orbit variability equation may be expressed as follows:
Wherein, Can be used to represent the second derivative of Y (t) with respect to time, A (t) can be used to represent the partial derivative of the acceleration at time t with respect to the orbital position of the spacecraft, B (t) can be used to represent the partial derivative of the acceleration at time t with respect to the speed of the spacecraft, C (t) can be used to represent the partial derivative of the acceleration at time t with respect to the parameter to be estimated, Y can be used to represent the partial derivative of the orbital position of the spacecraft at time t with respect to the parameter to be estimated,/>May be used to represent the first derivative of Y (t) with respect to time.
The linear calibration coefficients a and b are made to be equal to the initial position of the trackSpeed/>Together as parameters to be estimated, and substituting the partial derivatives of the atmospheric resistance acceleration with respect to the linear calibration coefficients a and b, respectively, into the orbit variation equation, the result may be as follows:
Wherein Y (t) can be used to represent the partial derivative of the orbit position of the spacecraft at time t with respect to the parameter to be estimated, Can be used to represent the track position at time t,/>Can be used to represent the speed at time t,/>Can be used to represent acceleration at time t,/>May be used to represent the parameters to be estimated.
Optionally, in the foregoing embodiment, in a track determining process, the linear calibration coefficient may be solved by dividing the linear calibration coefficient into a plurality of intervals according to time, to obtain a set of sequences of the linear calibration coefficients, and then comparing calibration effects of the sequences of the calibration coefficients with different piecewise time lengths to determine an optimal piecewise time length, so as to determine the target value corresponding to the linear calibration coefficient of the first linear calibration model based on the track estimating method.
For example, the embodiment may select 1 day of track data to perform a track calibration operation, solve a plurality of linear calibration coefficients in a segmented manner, respectively solve 1 group of calibration coefficients every 24, 12, 6, and 4 hours, compare correction effects of calibration coefficients of different time scales, find that it is reasonable to solve 1 group of calibration coefficients every 24 hours every day, and at this time, substitute the result into the first linear calibration model to determine a final linear calibration model.
As an alternative embodiment, the building of the atmospheric resistance acceleration calculation model includes: acquiring the atmospheric density and the resistance coefficient, and acquiring a first product between the atmospheric density and the resistance coefficient; acquiring a spacecraft reference section and a spacecraft mass, and acquiring a first quotient between the spacecraft reference section and the spacecraft mass; acquiring the movement speed of the spacecraft relative to the atmosphere, and acquiring a first product, a first quotient and a second product among the movement speed; obtaining a mould of the movement speed, and obtaining a third product between the second product and the mould; and determining the third product as the atmospheric resistance acceleration, wherein the atmospheric resistance acceleration is calculated by an atmospheric resistance acceleration model.
In this embodiment, before determining the third product as the atmospheric resistance acceleration, the third product may be multiplied by-1/2, and then the final result is determined as the atmospheric resistance acceleration, and a calculation model of the atmospheric resistance acceleration may be expressed as follows:
Wherein, Can be used to represent atmospheric drag acceleration, ρ can be used to represent atmospheric density, C D can be used to represent drag coefficient, A can be used to represent spacecraft reference section, m can be used to represent spacecraft mass, V r can be used to represent the mode of the spacecraft velocity relative to the atmosphere,/>Can be used to represent the speed of movement of the spacecraft relative to the atmosphere.
As an alternative embodiment, acquiring the movement velocity of the spacecraft with respect to the atmosphere includes: acquiring the movement speed of the spacecraft and the atmospheric wind speed, wherein the atmospheric wind speed is calculated by an atmospheric wind field model; acquiring a difference value between the movement speed of the spacecraft and the atmospheric wind speed; the difference is determined as the velocity of the spacecraft relative to the atmosphere.
In this embodiment, the velocity of the spacecraft relative to the atmosphere may be expressed as follows:
Wherein, Can be used for representing the movement speed of a spacecraft,/>Can be used to represent the atmospheric wind speed, optionally,/>Can be obtained from the ephemeris of a spacecraft,/>May be calculated using HWM14 empirical atmospheric wind field models.
As an alternative embodiment, obtaining the drag coefficient includes: dividing the surface of the spacecraft into a plurality of single-sided flat plate combinations; obtaining a fourth product between the resistance coefficient of each single-sided flat plate and the reference cross section of the spacecraft, and summing the fourth product to obtain a first sum; a second quotient between the first sum and the spacecraft reference section is obtained and the second quotient is determined as a drag coefficient.
In this embodiment, the surface of the spacecraft may be divided into a combination of a plurality of single-sided plates, then the product of the drag coefficient of each single-sided plate and the reference cross section of the spacecraft may be calculated, and all the products may be added, and finally the quotient between the sum calculated and the reference cross section of the spacecraft may be determined as the drag coefficient.
In the above embodiment, the drag coefficient C D may be calculated using a free molecular flow aerodynamic parameter model.
For example, taking a cubic satellite as an example, the calculation method of the drag coefficient C D may be as follows:
According to the free molecular flow aerodynamic parameter model, the calculation formula of the resistance coefficient C D of the single-sided plate of the cube satellite can be as follows:
where γ may be used to represent the angle cosine of the incoming flow direction to the in-plane normal, S may be used to represent the ratio of the macroscopic velocity of the gas to the maximum likelihood velocity of thermal motion, erf (x) may be used to represent the error function, T i may be used to represent the incident gas molecular temperature, T γ may be used to represent the reflected gas molecular temperature, S may be used to represent the plate area, and A ref may be used to represent the cross-sectional area of the plate. Alternatively, the cube satellite in this embodiment is generally simplified to be composed of 6 single-sided plates, and then the resistance coefficient of each single-sided plate can be calculated by the calculation formula of the resistance coefficient C D described above.
The actual movement speed of the gas molecules is equal to the macroscopic movement speed plus the random thermal movement speed due to the random thermal movement of the gas molecules. When the gas molecules are glancing, the macroscopic motion speed direction (i.e. the incoming flow direction) is parallel to the surface of the flat plate, and is influenced by the random thermal motion speed, the aerodynamic force born by the surface of the flat plate is not zero, the cross section area A ref of the flat plate is zero at the moment, and singular points can be caused by singly calculating the aerodynamic parameters of the flat plate. In order to avoid the occurrence of such a situation, the present application does not solve the aerodynamic parameters of each plate surface separately, but calculates the product of the drag coefficient and the cross-sectional area of each plate surface as an independent variable, and the calculation formula may be as follows:
Where (C DAref)|i) can be used to represent the product of the drag coefficient and cross-sectional area of each plate surface.
The calculation of the resistance coefficient of the cube satellite can be realized by summing the products of the resistance coefficients and the cross sectional areas of the surfaces of the 6 flat plates of the cube satellite and dividing the products by the reference cross section of the whole satellite, and the calculation formula can be as follows:
Wherein a may be used to represent a reference cross section of the satellite as a whole.
As an alternative embodiment, the in situ atmospheric density probe data is used to calculate the atmospheric density.
In this embodiment, the in-situ atmospheric density probe data may be used to calculate the atmospheric density ρ at any time by linear interpolation.
In the related art, because the ground cannot simulate the real atmosphere environment, the long-term drift of instrument electronic components, other unknown uncertain factors and the like, the detection result of the pressure gauge has larger systematic deviation, in addition, the pressure gauge atmosphere density detector can only measure the temperature and the pressure in the sampling chamber, and further, the atmosphere density data information is obtained, and the atmosphere composition information needs to be given depending on an empirical density mode or a physical atmosphere mode, so that the mode error can be caused.
In another related technology, a domestic scholars usually use third party data to calibrate the atmospheric density detection data, use precise orbit ephemeris or two-line root data (TLE) to invert the atmospheric density, and then use inversion atmospheric density data to calibrate the in-situ atmospheric density detection data.
According to the calibration method for the atmospheric density detection data, the calibration coefficient of the linear calibration model is determined through the satellite orbit data, so that the linear calibration model of the atmospheric density detection data is determined, the aim of accurately and efficiently calibrating the atmospheric density detection data is fulfilled, the systematic errors and the mode errors caused by the adoption of the pressure gauge for atmospheric density detection in the prior art are corrected, the problems that the calibration period of the atmospheric density detection data is long and the time resolution of the calibration coefficient is low by the aid of the third party data are avoided, the technical problem that the calibration timeliness of the atmospheric density detection data is poor is solved, and the technical effect of enhancing the timeliness of the in-situ atmospheric density detection data is achieved.
Example 2
The technical scheme of the embodiment of the invention is further described below.
FIG. 2 is a flow chart of another method for calibrating barometric pressure probe data according to an embodiment of the invention. As shown in fig. 2, the method may include the steps of:
Step S202, orbit data and attitude data of the spacecraft and atmospheric wind field data are acquired.
In the technical scheme provided in the step S202, engineering factors and atmospheric environmental factors of the spacecraft can be comprehensively considered to obtain orbit data and attitude data of the spacecraft and obtain wind field data of the atmosphere.
Step S204, an atmospheric resistance model is established.
In the technical solution provided in the above step S204 of the present invention, after the orbit data and the attitude data of the spacecraft and the atmospheric wind field data are acquired, an atmospheric resistance model may be established, and optionally, the atmospheric resistance model may be represented by a formula.
In the above embodiment, the atmospheric resistance acceleration may be calculated based on the orbit data, the attitude data, the wind farm data, and the like, so that the atmospheric resistance is calculated from the atmospheric resistance acceleration, and the calculation formula of the atmospheric resistance acceleration in this embodiment is as that in embodiment 1.
In step S206, atmospheric density data is acquired.
In the solution provided in the above step S206 of the present invention, the barometric data may include in-situ barometric data.
Step S208, a linear calibration model is established.
In the technical scheme provided in the step S208, after the atmospheric density data is obtained, the correlation between the atmospheric density data can be analyzed to obtain a stronger correlation, such as a linear correlation, between the data, and then a linear calibration model can be established.
Step S210, determining calibration coefficients by using a track estimation method.
In the technical solution provided in the above step S210 of the present invention, after the linear calibration model is established, the calibration coefficient of the linear calibration model may be determined by using the track estimation method.
In this embodiment, the linear calibration coefficient may be biased by the established atmospheric resistance acceleration calculation model to obtain a partial derivative, so that the calibration coefficient of the linear calibration model may be determined based on the orbit estimation method.
Step S212, evaluating whether the calibration coefficients are reasonable.
In the technical scheme provided in the above step S212 of the present invention, the calibration coefficients may be solved in sections according to the accuracy and distribution of the track data, and the solved calibration coefficients may be evaluated, if the calibration coefficients are unreasonable, the step S214 is skipped, the calibration coefficients may be solved in sections again, if the calibration coefficients are reasonable, the calibration coefficients are used as final calibration coefficients, for example, 1 day of track data is selected as a calibration operation, after a plurality of linear calibration coefficients are grouped, 1, 2, 4, 6 groups of calibration coefficients are respectively solved each day are selected, and then the result of solving the calibration coefficients of different time scales is compared, so that it is found that it is reasonable to solve 1 group of calibration coefficients each day.
Step S214, adjusting the segment solving duration.
In the technical scheme provided in the step S214, after the effect of multiple groups of calibration coefficients is evaluated, the time length for carrying out the sectional solution on the calibration coefficients can be adjusted, and then the calibration coefficients are determined again by using the track estimation method, so that the calibration coefficients are accurately calculated, and the aim of calibrating the atmospheric density detection data in real time by using the linear calibration model after substituting the calibration coefficients into the linear calibration model is fulfilled.
According to the method for calibrating the atmospheric density detection data, the atmospheric density detection data can be calibrated only by the original density detection data and spacecraft orbit data, the density data are not required to be acquired first by other methods (usually an orbit inversion method) and then calibrated, and the atmospheric density detection data can be calibrated in daily orbit calibration operation of the spacecraft, so that the convenience and timeliness of calibrating the atmospheric density detection data are realized. In addition, the calibration coefficients can be solved in a segmented mode according to the accuracy and the distribution condition of spacecraft orbit data, the calibration coefficients of different time scales are obtained, the limitation of the time resolution of third-party density data is avoided, the purpose of calibrating the calibration coefficients of different time scales through comparative analysis is achieved, and therefore the stability and the effectiveness of calibrating the atmospheric density detection data are achieved.
Example 3
The embodiment of the invention also provides a device for calibrating the atmospheric density detection data. It should be noted that the calibration device for the atmospheric density detection data in this embodiment may be used to execute the calibration method for the atmospheric density detection data in the embodiment of the present invention.
Fig. 3 is a schematic diagram of an apparatus for calibrating atmospheric density detection data according to an embodiment of the present invention. As shown in fig. 3, the calibration device 30 for the air density detection data may include: a first acquisition unit 31, a second acquisition unit 32, and a calibration unit 33.
The first acquiring unit 31 is configured to acquire in-situ atmospheric density detection data of the atmospheric density detector, and establish a first linear calibration model of the in-situ atmospheric density detection data.
A second acquiring unit 32, configured to acquire satellite orbit data, and determine a target value corresponding to a linear calibration coefficient of the first linear calibration model based on an orbit estimation method, where the orbit estimation method is used to determine the linear calibration coefficient.
And a calibration unit 33 for converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating the in-situ atmospheric density detection data based on the second linear calibration model.
According to the calibration device for the atmospheric density detection data, the calibration coefficient of the linear calibration model is determined through satellite orbit data, so that the linear calibration model of the atmospheric density detection data is determined, the aim of accurately and efficiently calibrating the atmospheric density detection data is fulfilled, the system error and the mode error caused by the adoption of a pressure gauge for atmospheric density detection in the prior art are corrected, the problems that the atmospheric density detection data calibration period is long and the time resolution is low by the adoption of third-party data are avoided, the technical problem that the timeliness of calibrating the atmospheric density detection data is poor is solved, and the technical effect of enhancing the timeliness of in-situ atmospheric density detection data calibration is achieved.
Example 4
According to an embodiment of the present invention, there is also provided a computer-readable storage medium including a stored program, wherein the program performs the method of calibrating the atmospheric density detection data described in embodiment 1.
Example 5
According to an embodiment of the present invention, there is also provided a processor for running a program, wherein the program runs to execute the method for calibrating the air density detection data described in embodiment 1.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (8)
1. A method for calibrating atmospheric density probe data, comprising:
acquiring in-situ atmospheric density detection data of an atmospheric density detector, and establishing a first linear calibration model of the in-situ atmospheric density detection data;
acquiring satellite orbit data, and determining a target value corresponding to a linear calibration coefficient of the first linear calibration model based on an orbit estimation method, wherein the orbit estimation method is used for determining the linear calibration coefficient;
Converting the first linear calibration model into a second linear calibration model based on the target value, and calibrating the in-situ atmospheric density detection data based on the second linear calibration model;
The method for determining the target value corresponding to the linear calibration coefficient of the first linear calibration model based on the satellite orbit data calculated by an orbit estimation method comprises the following steps:
establishing an atmospheric resistance acceleration calculation model;
obtaining a partial derivative by solving a partial derivative of the linear calibration coefficient through the atmospheric resistance acceleration calculation model;
Establishing an orbit variation equation based on the partial derivative, and integrating the orbit variation equation comprising the partial derivative by adopting a numerical integration method to obtain a state transition matrix, wherein the orbit variation equation is at least determined by an orbit position of a spacecraft, a speed of the spacecraft, an acceleration of the spacecraft, parameters to be estimated and the partial derivative, and the parameters to be estimated comprise the linear calibration coefficient;
estimating an improvement value of the target value based on the state transition matrix and a least square method, and updating the target value based on the improvement value;
And carrying out iterative improvement on the target value.
2. The method of claim 1, wherein building an atmospheric resistance acceleration calculation model comprises:
Acquiring the atmospheric density and the resistance coefficient, and acquiring a first product between the atmospheric density and the resistance coefficient;
acquiring a spacecraft reference section and a spacecraft mass, and acquiring a first quotient between the spacecraft reference section and the spacecraft mass;
Acquiring the movement speed of the spacecraft relative to the atmosphere, and acquiring a second product among the first product, the first quotient and the movement speed;
Obtaining a model of the movement speed, and obtaining a third product between the second product and the model;
And determining the third product as the atmospheric resistance acceleration, wherein the atmospheric resistance acceleration is calculated by the atmospheric resistance acceleration calculation model.
3. The method of claim 2, wherein obtaining the velocity of movement of the spacecraft relative to the atmosphere comprises:
Acquiring the movement speed of a spacecraft and the atmospheric wind speed, wherein the atmospheric wind speed is calculated by an atmospheric wind field model;
Acquiring a difference value between the spacecraft motion speed and the atmospheric wind speed;
the difference is determined as the movement speed.
4. The method of claim 2, wherein obtaining a drag coefficient comprises:
Dividing the surface of the spacecraft into a plurality of single-sided flat plate combinations;
obtaining a fourth product between the resistance coefficient of each single-sided flat plate and a reference section of the single-sided flat plate, and summing the fourth product to obtain a first sum;
a second quotient between the first sum and the spacecraft reference section is obtained and the second quotient is determined as the drag coefficient.
5. The method of claim 2, wherein the atmospheric density is calculated using the in situ atmospheric density probe data.
6. An apparatus for calibrating atmospheric density detection data, comprising:
the first acquisition unit is used for acquiring in-situ atmospheric density detection data of the atmospheric density detector and establishing a first linear calibration model of the in-situ atmospheric density detection data;
A second acquisition unit, configured to acquire satellite orbit data, and determine a target value corresponding to a linear calibration coefficient of the first linear calibration model based on an orbit estimation method, where the orbit estimation method is used to determine the linear calibration coefficient;
the calibration unit is used for converting the first linear calibration model into a second linear calibration model based on the target value and calibrating the in-situ atmospheric density detection data based on the second linear calibration model;
The calibration unit is also used for establishing an atmospheric resistance acceleration calculation model; obtaining a partial derivative by solving a partial derivative of the linear calibration coefficient through the atmospheric resistance acceleration calculation model; determining the target value based on the trajectory estimation method and the partial derivative;
The calibration unit is further configured to establish an orbit variation equation based on the partial derivative, and integrate the orbit variation equation including the partial derivative by using a numerical integration method to obtain a state transition matrix, where the orbit variation equation is at least determined by an orbit position of a spacecraft, a speed of the spacecraft, an acceleration of the spacecraft, a parameter to be estimated, and the partial derivative, and the parameter to be estimated includes the linear calibration coefficient; estimating an improvement value of the target value based on the state transition matrix and a least square method, and updating the target value based on the improvement value; and carrying out iterative improvement on the target value.
7. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program, when run, controls a device in which the storage medium is located to perform the method of any one of claims 1 to 5.
8. A processor for running a program, wherein the program when run performs the method of any one of claims 1 to 5.
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