Parameter acquisition method for satellite space plasma environment analysis
By using AE9AP9 software and a fitting and interpolation optimization method for dual Maxwell distribution parameters, the difficulty in obtaining parameters for satellite space plasma environment analysis was solved, the analysis accuracy was improved, and the accuracy of the charged analysis of the spacecraft surface was ensured.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-10
AI Technical Summary
In existing technologies, it is difficult to obtain parameters for satellite space plasma environment analysis, and these parameters are difficult to accurately reflect the real situation, affecting the accuracy of the analysis of the charged surface of spacecraft.
The orbital parameters were simulated using AE9AP9 software. Energy spectrum fitting and batch interpolation were performed using double Maxwell distribution parameters to calculate the relative error of the energy spectrum. When the error exceeded the threshold, the parameters were optimized to obtain the optimal parameters.
It improves the parameter accuracy of satellite space plasma environment analysis, ensures the accuracy and precision of output data, avoids computational redundancy, and enhances the accuracy of spacecraft surface charge analysis.
Smart Images
Figure CN121835331A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of satellite space technology, and more specifically, to a method for obtaining parameters for satellite space plasma environment analysis. Background Technology
[0002] The charging of spacecraft surfaces is an important issue related to the space environment. The analysis of the charging of spacecraft surfaces has always been an important part of aerospace research, and some software for the analysis of the charging of spacecraft surfaces has been initially developed.
[0003] The accuracy of current simulation software for analyzing the charge on spacecraft surfaces is highly dependent on the precise input of the space plasma environment (such as density and temperature). These environmental parameters often need to be obtained through inversion from space environment models or measured data. Due to limitations in computational algorithms, parameter acquisition is difficult, and it is hard to accurately reflect the real situation. Summary of the Invention
[0004] The problem addressed by this invention is how to improve the accuracy of parameters in satellite space plasma environment analysis.
[0005] In a first aspect, the present invention provides a method for obtaining parameters for satellite space plasma environment analysis, comprising: Based on the AE9AP9 software, the energy spectrum data of the target orbit is obtained through the orbital parameters of different orbits; Energy spectrum fitting was performed on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitted energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values; By performing batch interpolation on the fitted energy spectrum data of each target, interpolated fitted energy spectrum data is obtained. The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially to obtain the relative error of the energy spectrum; When the relative error of the energy spectrum is greater than a preset error threshold, the parameters are optimized based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters.
[0006] Optionally, the step of performing energy spectrum fitting on multiple sets of double Maxwell distribution parameters to obtain corresponding target fitted energy spectrum data includes: The dual Maxwell distribution parameters are sequentially decomposed into cold plasma parameters and hot plasma parameters; Based on the Maxwell velocity distribution function, the cold plasma energy spectrum and the hot plasma energy spectrum are obtained using the cold plasma parameters and the hot plasma parameters, respectively. The dual Maxwell energy spectrum is obtained based on the cold plasma energy spectrum and the hot plasma energy spectrum; The target fitted energy spectrum data is obtained by performing energy spectrum fitting based on the dual Maxwell energy spectrum.
[0007] Optionally, obtaining the dual Maxwell energy spectrum based on the cold plasma energy spectrum and the hot plasma energy spectrum includes: The cold plasma energy spectrum and the hot plasma energy spectrum are input into the dual Maxwell distribution function to obtain the dual Maxwell energy spectrum; The dual Maxwell distribution function includes: , in, The double Maxwell energy spectrum, The energy spectrum of the cold plasma, The thermal plasma energy spectrum is described above.
[0008] Optionally, it also includes: The optimal parameters are input into the dual Maxwell distribution function and the Maxwell velocity distribution function to obtain the orbital particle velocity distribution. The Maxwell energy spectrum distribution across the entire energy range of the orbit is obtained by utilizing the velocity-energy conversion relationship through the velocity distribution of the orbital particles.
[0009] Optionally, the step of obtaining interpolated fitted energy spectrum data by performing batch interpolation on each of the target fitted energy spectrum data includes: A batch interpolation algorithm based on Python was developed to establish energy spectrum curves by fitting energy spectrum data to the target parameters. Interpolate between any two adjacent parameter nodes according to the parameter difference ratio, and then fit the energy spectrum data after traversing all parameter nodes to obtain the interpolated values.
[0010] Optionally, the step of optimizing the parameters based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters includes: The objective function is established by minimizing the sum of squared errors of the relative energy spectrum error. The interpolated fitted energy spectrum data is iteratively optimized according to the objective function until the convergence condition is met to obtain the optimal parameters.
[0011] Optionally, the step of sequentially comparing the interpolated fitted energy spectrum data and the target orbit energy spectrum data to obtain the relative energy spectrum error includes: The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially using a traversal matching method to obtain the relative error of the energy spectrum.
[0012] Secondly, the present invention provides a parameter acquisition device for satellite space plasma environment analysis, comprising: a target orbit energy spectrum data acquisition module, used to obtain target orbit energy spectrum data through orbital parameters of different orbits based on AE9AP9 software; The target fitting energy spectrum data acquisition module is used to perform energy spectrum fitting on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitting energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values; The batch interpolation module is used to perform batch interpolation on the fitted energy spectrum data of each target to obtain interpolated fitted energy spectrum data. The energy spectrum relative error acquisition module is used to compare the interpolated fitted energy spectrum data and the target orbit energy spectrum data in sequence to obtain the energy spectrum relative error. The optimal parameter acquisition module is used to optimize the parameters based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum when the relative error of the energy spectrum is greater than a preset error threshold, so as to obtain the optimal parameters.
[0013] Thirdly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is configured to, when executing the computer program, implement the parameter acquisition method for satellite space plasma environment analysis as described in the first aspect.
[0014] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the parameter acquisition method for satellite space plasma environment analysis as described in the first aspect.
[0015] The beneficial effects of the parameter acquisition method for satellite space plasma environment analysis of the present invention are as follows: Real target orbit energy spectrum data are obtained using AE9AP9 software to simulate near-Earth space radiation. Energy spectrum fitting is performed on the double Maxwell distribution parameters, and the target fitted energy spectrum data is obtained based on the double Maxwell distribution, thus improving fitting accuracy. Batch interpolation of each target fitted energy spectrum data generates continuous intermediate energy spectrum data based on the limited target fitted energy spectrum data, effectively filling parameter space gaps. The relative error of the energy spectrum is calculated by comparing the interpolated fitted energy spectrum data and the target orbit energy spectrum data point by point, and a preset error threshold is set as a trigger condition. When the relative error of the energy spectrum is greater than the preset error threshold, parameter optimization is performed based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters, avoiding unnecessary computational redundancy and ensuring the accuracy requirements of the final output. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating a method for obtaining parameters for satellite space plasma environment analysis according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a parameter acquisition device for satellite space plasma environment analysis according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation
[0017] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.
[0018] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.
[0019] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.
[0020] It should be noted that the terms "one" and "more" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0021] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.
[0022] like Figure 1As shown in the figure, an embodiment of the present invention provides a method for obtaining parameters for satellite space plasma environment analysis, comprising: Step 110: Based on the AE9AP9 software, obtain the target orbit energy spectrum data through the orbital parameters of different orbits.
[0023] Specifically, AE9AP9 software, developed by the U.S. Air Force Research Laboratory, is used to simulate near-Earth space radiation. It includes various simulation models such as high-energy electrons, high-energy protons, and plasma. Based on publicly available data, the six orbital roots for different orbits are extracted as orbital parameters. The corresponding orbital and time parameters are input into the AE9AP9 application, energy levels and particle types are selected, the plasma model is invoked, and the energy spectrum data of the target orbit is obtained. The target orbit energy spectrum data is then filtered for effective energy ranges (noise data and electron data below the critical energy level are removed), and the energy spectrum data is standardized into a two-dimensional "energy-particle flux" array format.
[0024] Step 120: Perform energy spectrum fitting on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitted energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values.
[0025] Specifically, the corresponding energy spectrum is calculated using the Maxwell distribution. Starting from a forward-thinking approach, the classic Maxwell formula is used to obtain known density and temperature parameter values of common plasma double Maxwell distributions from publicly available data, resulting in multiple sets of double Maxwell distribution parameters. The corresponding energy spectrum is then fitted to obtain the corresponding target fitted energy spectrum data.
[0026] Step 130: By performing batch interpolation on the fitted energy spectrum data of each target, interpolated fitted energy spectrum data is obtained.
[0027] Specifically, a batch interpolation script was written in Python. Based on the idea of enumeration algorithm, batch interpolation was performed on the fitted energy spectrum data of each target. For various conditions of density and temperature, the script was used to perform batch interpolation to generate the energy spectrum corresponding to the intermediate parameter combination.
[0028] Step 140: The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially to obtain the relative error of the energy spectrum.
[0029] Specifically, the interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared over one period to find the minimum error, and the relative error is averaged over one orbit.
[0030] Step 150: When the relative error of the energy spectrum is greater than a preset error threshold, the parameters are optimized based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters.
[0031] Specifically, when the relative error of the energy spectrum is greater than 10 For the interpolated fitted energy spectrum data, the gradient descent method is used to iteratively solve for the optimal parameters with the objective function of minimizing the sum of squared relative errors in the energy spectrum. When the relative error in the energy spectrum is less than or equal to 10... If the time is not found, return to step 120 and re-perform the energy spectrum fitting to obtain the corresponding target fitted energy spectrum data.
[0032] In this embodiment, the AE9AP9 software, which simulates near-Earth space radiation, is used to obtain the actual target orbit energy spectrum data. The double Maxwell distribution parameters are fitted to the energy spectrum, and the target fitted energy spectrum data is obtained using the double Maxwell distribution as the fitting basis, improving the fitting accuracy. By performing batch interpolation on each target fitted energy spectrum data, continuous intermediate energy spectrum data is generated based on the limited target fitted energy spectrum data, effectively filling the parameter space gaps. The relative energy spectrum error is calculated by comparing the interpolated fitted energy spectrum data and the target orbit energy spectrum data point by point, and a preset error threshold is set as a trigger condition. When the relative energy spectrum error exceeds the preset error threshold, the parameters are optimized based on the interpolated fitted energy spectrum data and the relative energy spectrum error to obtain the optimal parameters, avoiding unnecessary computational redundancy and ensuring the final output accuracy requirements.
[0033] Optionally, the step of performing energy spectrum fitting on multiple sets of double Maxwell distribution parameters to obtain corresponding target fitted energy spectrum data includes: The dual Maxwell distribution parameters are sequentially decomposed into cold plasma parameters and hot plasma parameters; Based on the Maxwell velocity distribution function, the cold plasma energy spectrum and the hot plasma energy spectrum are obtained using the cold plasma parameters and the hot plasma parameters, respectively. The dual Maxwell energy spectrum is obtained based on the cold plasma energy spectrum and the hot plasma energy spectrum; The target fitted energy spectrum data is obtained by performing energy spectrum fitting based on the dual Maxwell energy spectrum.
[0034] Specifically, the dual Maxwell distribution parameters are divided into two groups: cold plasma parameters and hot plasma parameters. The parameter value ranges for this type of plasma are extracted from publicly available data (e.g., cold plasma Tc is typically 1-10 eV, and hot plasma Th is typically 100-1000 eV). Discretized value points for each group of parameters are then determined (the interval is set according to accuracy requirements; one point is taken every 10 eV for temperature and every 1 e6 for density). (Taking a single point). Energy spectra were calculated for both cold and hot plasma parameters to obtain the cold plasma energy spectrum and the hot plasma energy spectrum. Based on the double Maxwell distribution function and the particle number flux formula, the energy spectrum data of the single components of cold and hot plasma were calculated respectively.
[0035] The dual Maxwell distribution function includes: , Where m is the electron mass (unit: kg), K is the Boltzmann constant (unit: J / K), and N is the electron density (unit: ...). T is the electron temperature (unit: eV, converted to temperature unit K). 11605), where v is the particle velocity. Given the double Maxwell distribution function, for cold plasma, substituting Tc into the equation yields the particle number flux for the corresponding energy range, and vice versa for hot plasma, substituting Th into the equation yields the particle number flux for the corresponding energy range, and vice versa.
[0036] A plasma environment in which particle motion follows a Maxwell-Boltzmann distribution is called a Maxwell plasma environment. Based on the properties of the particles in the environment, it can be divided into single-Maxwell plasma and double-Maxwell plasma. A single-Maxwell plasma environment macroscopically exhibits only one temperature and number density, while a double-Maxwell plasma environment contains two single-Maxwell plasma clusters, one cold and one hot, thus having two temperatures and number densities. Generally, the LEO orbit charging and discharging environment is a dense, low-temperature plasma, which can be considered a single-Maxwell plasma environment; the GEO orbit charging and discharging environment is mainly a geomagnetic substorm plasma, usually considered a double-Maxwell plasma environment. The integral considers the particle number flux across all energy ranges during spacecraft operation. Since a large amount of charge accumulates on the spacecraft surface after it reaches electrical equilibrium, it repels electrons approaching the surface, preventing lower-energy electrons from reaching the surface. This indicates that electrons contributing to the spacecraft's electrical potential have a critical velocity or critical energy. Therefore, this invention only considers electrons with velocities above a certain threshold. For a single Maxwell plasma environment, calculate the differential fractional flux F, with the default electron mass m = 9.10956e-31; Boltzmann constant k = 1.38e-23; and temperature T = 11605.0. t1, where t1 is energy; the rate determined by t = sqrt(2) E0 JpeV / (m)); the most probable speed Vp=sqrt(2 k T / (m)). In this optional embodiment, by explicitly separating the dual Maxwell distribution parameters into cold plasma parameters and hot plasma parameters, and independently calculating the cold and hot energy spectra based on the Maxwell velocity distribution function, and then superimposing them to form the total energy spectrum, the physical rationality of the fitted energy spectrum and its ability to characterize the real environment are significantly improved.
[0037] Optionally, obtaining the dual Maxwell energy spectrum based on the cold plasma energy spectrum and the hot plasma energy spectrum includes: The cold plasma energy spectrum and the hot plasma energy spectrum are input into the dual Maxwell distribution function to obtain the dual Maxwell energy spectrum; The dual Maxwell distribution function includes: , in, The double Maxwell energy spectrum, The energy spectrum of the cold plasma, The thermal plasma energy spectrum is described above.
[0038] Specifically, the energy spectra of cold and hot plasmas are input into a dual Maxwell distribution function to obtain the dual Maxwell energy spectrum. The individual component energy spectra of the cold and hot plasmas are then weighted and superimposed according to their respective density proportions to obtain the dual Maxwell energy spectrum corresponding to this set of parameters. The corresponding energy spectrum is fitted to obtain fitted energy spectrum data. Using the discretized parameter combination (nc, Tc, nh, Th) as input and the corresponding synthesized energy spectrum as output, a multi-parameter-energy spectrum mapping model is constructed. The least squares method is used to optimize the parameter weights, ensuring that the deviation between the fitted energy spectrum and the theoretical distribution is less than a set threshold (relative error less than or equal to 5). ).
[0039] Optionally, the optimal parameters are input into the dual Maxwell distribution function and the Maxwell velocity distribution function to obtain the orbital particle velocity distribution; The Maxwell energy spectrum distribution across the entire energy range of the orbit is obtained by utilizing the velocity-energy conversion relationship through the velocity distribution of the orbital particles.
[0040] Specifically, the optimal parameters are input into the dual Maxwell distribution function and the Maxwell velocity distribution function to calculate the particle velocity distribution at each position on the orbit. Then, the velocity-energy conversion relationship is used... Let E represent the energy E possessed by an object of mass m moving at velocity v, and then we obtain the Maxwell energy spectrum distribution across the entire energy range of the orbit.
[0041] Optionally, the step of obtaining interpolated fitted energy spectrum data by performing batch interpolation on each of the target fitted energy spectrum data includes: A batch interpolation algorithm based on Python was developed to establish energy spectrum curves by fitting energy spectrum data to the target parameters. Interpolate between any two adjacent parameter nodes according to the parameter difference ratio, and then fit the energy spectrum data after traversing all parameter nodes to obtain the interpolated values.
[0042] Specifically, a batch interpolation script was written in Python to read the target fitted energy spectrum data, i.e., the fitted energy spectrum data corresponding to all parameter combinations. A library of energy spectrum curves corresponding to each parameter node was established, with energy as the x-axis and particle flux as the y-axis. For any two adjacent parameter nodes, the flux at each energy point of the energy spectrum curve was interpolated according to the parameter difference ratio, generating the energy spectrum corresponding to the intermediate parameter combination. The script's loop logic was set to traverse all adjacent combinations of parameter grid nodes, automatically completing the interpolation calculation across the entire parameter space, and outputting a data file containing all interpolated parameter combinations and their corresponding energy spectra, ensuring no omissions in the parameter space and continuous interpolation results.
[0043] In this optional embodiment, by interpolating between discrete initial parameter nodes, a large number of energy spectrum curves corresponding to intermediate parameters are automatically generated, effectively expanding the originally sparse parameter grid into continuous data. This significantly improves the model's ability to characterize plasma energy spectrum changes under complex orbital environments and avoids fitting blind spots caused by insufficient parameter sampling.
[0044] Optionally, the step of optimizing the parameters based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters includes: The objective function is established by minimizing the sum of squared errors of the relative energy spectrum error. The interpolated fitted energy spectrum data is iteratively optimized according to the objective function until the convergence condition is met to obtain the optimal parameters.
[0045] Specifically, for the candidate parameter combinations, the gradient descent method is used to further optimize the density and temperature parameters of cold and hot plasmas. The optimal parameter values are iteratively solved with the objective function of minimizing the sum of squared errors between the energy spectra of each orbit and the model energy spectrum.
[0046] Optionally, the step of sequentially comparing the interpolated fitted energy spectrum data and the target orbit energy spectrum data to obtain the relative energy spectrum error includes: The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially using a traversal matching method to obtain the relative error of the energy spectrum.
[0047] Specifically, the interpolated fitted energy spectrum data and the target orbital energy spectrum data are compared. A traversal matching method is used to calculate the relative error of the energy spectrum for each combination, and samples with a mean relative error less than 10 are selected. Candidate parameter combinations.
[0048] like Figure 2 As shown in the figure, an embodiment of the present invention provides a parameter acquisition device for satellite space plasma environment analysis, comprising: The target orbit energy spectrum data acquisition module 10 is used to obtain target orbit energy spectrum data based on the orbital parameters of different orbits using AE9AP9 software; The target fitting energy spectrum data acquisition module 20 is used to perform energy spectrum fitting on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitting energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values. The batch interpolation module 30 is used to perform batch interpolation on the fitted energy spectrum data of each target to obtain interpolated fitted energy spectrum data. The energy spectrum relative error acquisition module 40 is used to compare the interpolated fitted energy spectrum data and the target orbit energy spectrum data in sequence to obtain the energy spectrum relative error. The optimal parameter acquisition module 50 is used to optimize the parameters based on the interpolated fitted energy spectrum data and the energy spectrum relative error when the relative error of the energy spectrum is greater than a preset error threshold, so as to obtain the optimal parameters.
[0049] The parameter acquisition device for satellite space plasma environment analysis in this embodiment is used to implement the parameter acquisition method for satellite space plasma environment analysis as described above. Its advantages over the prior art are the same as the advantages of the parameter acquisition method for satellite space plasma environment analysis over the prior art, and will not be repeated here.
[0050] Optionally, the target fitting energy spectrum data acquisition module 20 is specifically used to: sequentially split the dual Maxwell distribution parameters into cold plasma parameters and hot plasma parameters; Based on the Maxwell velocity distribution function, the cold plasma energy spectrum and the hot plasma energy spectrum are obtained using the cold plasma parameters and the hot plasma parameters, respectively. The dual Maxwell energy spectrum is obtained based on the cold plasma energy spectrum and the hot plasma energy spectrum; The target fitted energy spectrum data is obtained by performing energy spectrum fitting based on the dual Maxwell energy spectrum.
[0051] Optionally, the target fitting energy spectrum data acquisition module 20 is specifically used to: input the cold plasma energy spectrum and the hot plasma energy spectrum into a dual Maxwell distribution function to obtain the dual Maxwell energy spectrum; The dual Maxwell distribution function includes: , in, The double Maxwell energy spectrum, The energy spectrum of the cold plasma, The thermal plasma energy spectrum is described above.
[0052] Optionally, the parameter acquisition device for satellite space plasma environment analysis further includes a Maxwell energy spectrum distribution acquisition module, which is used to: input the optimal parameters into the double Maxwell distribution function and the Maxwell velocity distribution function to obtain the orbital particle velocity distribution; The Maxwell energy spectrum distribution across the entire energy range of the orbit is obtained by utilizing the velocity-energy conversion relationship through the velocity distribution of the orbital particles.
[0053] Optionally, the batch interpolation module 30 is specifically used to: write a batch interpolation algorithm based on Python, and establish an energy spectrum curve by using the parameter nodes of the fitted energy spectrum data of each target; Interpolate between any two adjacent parameter nodes according to the parameter difference ratio, and then fit the energy spectrum data after traversing all parameter nodes to obtain the interpolated values.
[0054] Optionally, the optimal parameter acquisition module 50 is specifically used to: establish an objective function with minimizing the sum of squared errors of the relative energy spectrum error as the objective; The interpolated fitted energy spectrum data is iteratively optimized according to the objective function until the convergence condition is met to obtain the optimal parameters.
[0055] Optionally, the energy spectrum relative error acquisition module 40 is specifically used to: sequentially compare the interpolated fitted energy spectrum data and the target orbit energy spectrum data using a traversal matching method to obtain the energy spectrum relative error.
[0056] like Figure 3 As shown, an electronic device 300 provided in this embodiment of the invention includes a memory 310 and a processor 320; the memory 310 is used to store a computer program; the processor 320 is used to implement the parameter acquisition method for satellite space plasma environment analysis as described above when the computer program is executed.
[0057] Alternatively, an electronic device 300 includes a memory 310 and a processor 320 coupled to the memory 310; the memory 310 is configured to store a computer program; and the processor 320 is configured to perform the following operations when the computer program is executed: Based on the AE9AP9 software, the energy spectrum data of the target orbit is obtained through the orbital parameters of different orbits; Energy spectrum fitting was performed on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitted energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values; By performing batch interpolation on the fitted energy spectrum data of each target, interpolated fitted energy spectrum data is obtained. The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially to obtain the relative error of the energy spectrum; When the relative error of the energy spectrum is greater than a preset error threshold, the parameters are optimized based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters.
[0058] This invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the parameter acquisition method for satellite space plasma environment analysis as described above.
[0059] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations: Based on the AE9AP9 software, the energy spectrum data of the target orbit is obtained through the orbital parameters of different orbits; Energy spectrum fitting was performed on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitted energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values; By performing batch interpolation on the fitted energy spectrum data of each target, interpolated fitted energy spectrum data is obtained. The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially to obtain the relative error of the energy spectrum; When the relative error of the energy spectrum is greater than a preset error threshold, the parameters are optimized based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters.
[0060] The present invention will now be described an electronic device 300 that can serve as a server or client of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. Electronic device 300 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 300 can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.
[0061] Electronic device 300 includes a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or a computer program loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.
[0062] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.
[0063] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.
Claims
1. A method for obtaining parameters for satellite space plasma environment analysis, characterized in that, include: Based on the AE9AP9 software, the energy spectrum data of the target orbit is obtained through the orbital parameters of different orbits; Energy spectrum fitting was performed on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitted energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values; By performing batch interpolation on the fitted energy spectrum data of each target, interpolated fitted energy spectrum data is obtained. The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially to obtain the relative error of the energy spectrum; When the relative error of the energy spectrum is greater than a preset error threshold, the parameters are optimized based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain the optimal parameters.
2. The method for obtaining parameters for satellite space plasma environment analysis according to claim 1, characterized in that, The process of fitting the energy spectrum of multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitted energy spectrum data includes: The dual Maxwell distribution parameters are sequentially decomposed into cold plasma parameters and hot plasma parameters; Based on the Maxwell velocity distribution function, the cold plasma energy spectrum and the hot plasma energy spectrum are obtained using the cold plasma parameters and the hot plasma parameters, respectively. The dual Maxwell energy spectrum is obtained based on the cold plasma energy spectrum and the hot plasma energy spectrum; The target fitted energy spectrum data is obtained by performing energy spectrum fitting based on the dual Maxwell energy spectrum.
3. The method for obtaining parameters for satellite space plasma environment analysis according to claim 2, characterized in that, The process of obtaining the dual Maxwell energy spectrum based on the cold plasma energy spectrum and the hot plasma energy spectrum includes: The cold plasma energy spectrum and the hot plasma energy spectrum are input into the dual Maxwell distribution function to obtain the dual Maxwell energy spectrum; The dual Maxwell distribution function includes: ， in, The double Maxwell energy spectrum, The energy spectrum of the cold plasma, The thermal plasma energy spectrum is described above.
4. The method for obtaining parameters for satellite space plasma environment analysis according to claim 3, characterized in that, Also includes: The optimal parameters are input into the dual Maxwell distribution function and the Maxwell velocity distribution function to obtain the orbital particle velocity distribution. The Maxwell energy spectrum distribution across the entire energy range of the orbit is obtained by utilizing the velocity-energy conversion relationship through the velocity distribution of the orbital particles.
5. The method for obtaining parameters for satellite space plasma environment analysis according to claim 1, characterized in that, The step of obtaining interpolated fitted energy spectrum data by batch interpolating each of the target fitted energy spectrum data includes: A batch interpolation algorithm based on Python was developed to establish energy spectrum curves by fitting energy spectrum data to the target parameters. Interpolate between any two adjacent parameter nodes according to the parameter difference ratio, and then fit the energy spectrum data after traversing all parameter nodes to obtain the interpolated values.
6. The method for obtaining parameters for satellite space plasma environment analysis according to claim 1, characterized in that, The step of optimizing parameters based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum to obtain optimal parameters includes: The objective function is established by minimizing the sum of squared errors of the relative energy spectrum error. The interpolated fitted energy spectrum data is iteratively optimized according to the objective function until the convergence condition is met to obtain the optimal parameters.
7. The method for obtaining parameters for satellite space plasma environment analysis according to claim 1, characterized in that, The step of sequentially comparing the interpolated fitted energy spectrum data and the target orbit energy spectrum data to obtain the relative energy spectrum error includes: The interpolated fitted energy spectrum data and the target orbit energy spectrum data are compared sequentially using a traversal matching method to obtain the relative error of the energy spectrum.
8. A parameter acquisition device for satellite space plasma environment analysis, characterized in that, include: The target orbit energy spectrum data acquisition module is used to obtain target orbit energy spectrum data based on the orbital parameters of different orbits using AE9AP9 software. The target fitting energy spectrum data acquisition module is used to perform energy spectrum fitting on multiple sets of double Maxwell distribution parameters to obtain the corresponding target fitting energy spectrum data, wherein the double Maxwell distribution parameters include density parameter values and temperature parameter values; The batch interpolation module is used to perform batch interpolation on the fitted energy spectrum data of each target to obtain interpolated fitted energy spectrum data. The energy spectrum relative error acquisition module is used to compare the interpolated fitted energy spectrum data and the target orbit energy spectrum data in sequence to obtain the energy spectrum relative error. The optimal parameter acquisition module is used to optimize the parameters based on the interpolated fitted energy spectrum data and the relative error of the energy spectrum when the relative error of the energy spectrum is greater than a preset error threshold, so as to obtain the optimal parameters.
9. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to, when executing the computer program, implement the parameter acquisition method for satellite space plasma environment analysis as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the parameter acquisition method for satellite space plasma environment analysis as described in any one of claims 1 to 7.