Simulation test design method for remote sensing satellite system argumentation

Abstract

The invention relates to a remote sensing satellite system argumentation-oriented simulation test design method, which comprises the following steps of: extracting common influence factors of a specified remote sensing satellite in different typical deduction scenes to form a built-in test factor list; influence factors are extracted according to different task types, a test factor list for specific tasks is constructed, and a scene task template is formed; matching a scene task template according to a task type of simulation scenario, and loading and dynamically adjusting the test factor list to form a simulation test scheme; and selecting a test design method based on the simulation test scheme, generating test result data and mapping the test result data to a simulation scenario to form a test sample set. According to the method, automatic extraction of factors can be realized, and a user is assisted to quickly generate a system simulation test scheme.

Description

Technical Field

[0001] The present invention relates to the technical field of simulation and modeling, and in particular to a simulation test design method for remote sensing satellite system demonstration. Background Art

[0002] Simulation testing of remote sensing satellite systems in typical simulation scenarios requires the use of experimental design to rapidly generate a large number of test samples. These samples are then used to conduct large-scale simulation experiments, providing data for subsequent evaluation and analysis. Currently, a wide range of statistical analysis software offers powerful experimental design capabilities. However, these software programs are difficult to apply in remote sensing satellite simulation due to their detachment from practical operational contexts, complex application processes, and difficulty in correlating results with simulation test plans.

[0003] In addition, although many experimental design systems for specific remote sensing satellites have been widely used, such systems often cannot quickly adapt to changes in satellite types, simulation scenarios, and assigned tasks, and there are significant inconveniences in actual use. Summary of the Invention

[0004] In view of the above technical problems, the present invention proposes a simulation test design method for remote sensing satellite system demonstration, which can realize the automatic extraction of factors and assist users to quickly generate system simulation test plans.

[0005] The technical solution to the technical problem of the present invention is: a simulation test design method for remote sensing satellite system demonstration, comprising the following steps:

[0006] Step S1, common test factor extraction: extracting common influencing factors of a specified remote sensing satellite in different typical deduction scenarios to form a built-in test factor list;

[0007] Step S2, scenario task template construction: extract influencing factors according to different task types, construct a list of experimental factors for specific tasks, and form a scenario task template;

[0008] Step S3, simulation test plan generation: matching the scenario task template according to the task type assumed in the simulation, loading and dynamically adjusting the test factor list, and forming a simulation test plan;

[0009] Step S4, simulation test sample generation: select an experimental design method based on the simulation test plan, generate test result data and map it to the simulation scenario to form an experimental sample set.

[0010] According to a technical solution of the present invention, in step S1, the extraction of common experimental factors specifically includes:

[0011] Step S101: Analyze the workflow of a designated remote sensing satellite in different typical mission scenarios, extract common influencing factors, and form a built-in test factor list;

[0012] Step S102: for each experimental factor, set its value range, design method and design parameters, and generate a discrete factor level value list;

[0013] Step S103: The built-in test factor list is described in a format such as XML or JSON and stored in a database.

[0014] According to a technical solution of the present invention, the design parameters of the experimental factors include binomial distribution, exponential distribution, uniform distribution or manual design method.

[0015] According to a technical solution of the present invention, step S2 specifically includes:

[0016] Step S201: Analyze the workflow of the satellite under the specified mission, extract the influencing factors, add them to the test factor list of the corresponding mission type, and complete the setting of the test factors using the same operation as step S102;

[0017] Step S202: The built-in test factor list is described in a format such as XML or JSON to form a scenario task template, and is stored in a database.

[0018] According to a technical solution of the present invention, step S3 specifically includes:

[0019] Step S301: After the user selects a simulation scenario for which an experimental design is to be carried out, an applicable scenario task template is searched and matched from the database according to the type of task corresponding to the selected simulation scenario, and the experimental factor list information contained therein is loaded;

[0020] Step S302: Load the built-in test factor list generated in step S1 and merge it with the test factor list generated in step S301;

[0021] Step S303: Based on the test factor list generated by merging in step S302, test factors are added or deleted according to the characteristics of the simulation scenario selected by the user, and the construction of the test factor list for this simulation scenario is completed to form a simulation test plan.

[0022] According to a technical solution of the present invention, the algorithm of the matching process is a keyword matching algorithm.

[0023] According to a technical solution of the present invention, step S4 specifically includes:

[0024] Step S401: Load the simulation test plan generated in step S3, read the test factor list therein, and obtain the factor level value list of each test factor;

[0025] Step S402: Based on the preset experimental design method and the experimental factor information read in step S401, generate experimental design result data;

[0026] Step S403: Based on the mapping relationship between the experimental factors and the influencing factors in the simulation scenario, the level value of each experimental factor in each sample is substituted into the simulation scenario to form a simulation scenario corresponding to each sample, which is called an experimental sample.

[0027] According to a technical solution of the present invention, the preset experimental design method is a full factorial design method, a uniform design method, an orthogonal design method or a Latin hypercube design method.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] According to the concept of the present invention, a simulation test design method for remote sensing satellite system demonstration is proposed. In response to the demand for rapid generation of large samples of simulation tests, based on the research and analysis of remote sensing satellites, common factors that may affect satellite performance in typical deduction scenarios are extracted to form built-in factors. Other influencing factors are extracted according to the characteristics of specific mission types, and a list of test factors for specific tasks is constructed to form scenario task templates. This realizes the automatic extraction of factors and assists users in quickly generating simulation test plans.

[0030] The present invention extracts common influencing factors based on the characteristics of a specified remote sensing satellite in different typical mission scenarios to form a built-in factor list, thereby avoiding repeated operations and improving the efficiency of experimental design.

[0031] The present invention establishes a scenario mission template for each specific mission type, stores a list of test factors for a specified remote sensing satellite under such mission, and automatically matches the combat mission template based on the mission type assumed in the simulation, thereby improving the efficiency of experimental design.

[0032] The present invention supports adding or deleting test factors according to the characteristics of simulation scenarios on the basis of scenario task templates, thereby ensuring the flexibility of simulation test design.

[0033] The present invention uses experimental design to quickly generate a large number of test samples in simulation experiments in typical deduction scenarios, and conducts large-sample simulation experiments based on the test samples, thereby providing data for subsequent evaluation and analysis. It has good application prospects for experimental design of remote sensing satellites. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1The flowchart of the simulation test design method for remote sensing satellite system demonstration according to one embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0035] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments. Obviously, the drawings described below only illustrate some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0036] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The embodiments cannot be described one by one here, but the embodiments of the present invention are not limited to the following embodiments.

[0037] like Figure 1 As shown, a simulation test design method for remote sensing satellite system demonstration of the present invention includes the following steps:

[0038] Step S1: Extracting common test factors: Extract the common influencing factors of a specified remote sensing satellite in different typical scenarios to form a list of common test factors for the weapon satellite, which will be used as a built-in factor list for each simulation test plan.

[0039] First, we analyze the factors that may affect the combat effectiveness of the remote sensing satellite under study in different typical mission scenarios, and extract the common influencing factors as the built-in test factors for all simulation test plans of the satellite.

[0040] The specific steps of step S1 include:

[0041] Step S101: Analyze the workflow of a designated remote sensing satellite in different typical mission scenarios, extract common influencing factors, and form a built-in test factor list.

[0042] Step S102: For each experimental factor in the built-in factor list generated in step S101, set its value range, design method, and design parameters, and generate a discrete factor level value list. The design method can use a statistical distribution-based method such as binomial distribution, exponential distribution, uniform distribution, or a manual design method.

[0043] Step S103: The built-in test factor list is described in a format such as XML or JSON and stored in a database.

[0044] Step S2: Scenario mission template construction: Based on the characteristics of different mission types, other factors that may affect satellite performance are extracted as test factors, and a list of test factors for specific missions is constructed to form a scenario mission template.

[0045] According to the characteristics of different mission types, other factors that may affect the effectiveness of the specified satellite mission are extracted to form experimental factors, and a list of experimental factors for specific missions is generated, namely the scenario mission template.

[0046] The specific steps of step S2 include:

[0047] Step S201: Analyze the workflow of the satellite under the specified mission, extract the influencing factors, add them to the test factor list of this mission type, and complete the setting of the test factors using the same operation as step 102.

[0048] Step S202: The built-in test factor list is described in a format such as XML or JSON to form a scenario task template, and is stored in a database.

[0049] Step S3: Generate a simulation test plan. Based on the task type corresponding to the simulation scenario, automatically match an applicable scenario task template, load the test factor list, and add or delete test factors based on the characteristics of the simulation scenario to complete the construction of the test factor list for this scenario and form a simulation test plan.

[0050] According to the task type corresponding to the simulation scenario selected by the user for the experimental design, the applicable scenario task template is searched from the database, the experimental factor list information contained therein is loaded, and on this basis, the experimental factors are added or deleted according to the characteristics of the scenario, and the construction of the experimental factor list for the simulation scenario is completed to form a simulation test plan.

[0051] Step S3 specifically includes:

[0052] Step S301: After the user selects a simulation scenario for which to conduct an experimental design, a suitable scenario task template is searched and matched from the database based on the task type corresponding to the selected simulation scenario, and the list of experimental factors contained therein is loaded. The matching process can be implemented using a keyword matching algorithm.

[0053] Step S302: Load the built-in experimental factor list generated in step S1 and merge it with the experimental factor list generated in step S301.

[0054] Step S303: Based on the test factor list generated by merging in step S302, test factors are added or deleted according to the characteristics of the simulation scenario selected by the user, and the construction of the test factor list for this simulation scenario is completed to form a simulation test plan.

[0055] Step S4: Simulation test sample generation: Based on the simulation test plan, select an applicable test design method, generate test design result data, and map the test design result data to the corresponding factors in the simulation scenario to generate simulation test samples, providing input for large-sample simulation tests.

[0056] Based on the simulation test plan generated in step S3, an applicable test design method is selected to generate test design results. The test design result data is mapped with the corresponding influencing factors in the simulation scenario, and then a test sample is generated as the input of the large-sample simulation test.

[0057] The specific steps of step S4 include:

[0058] Step S401: Load the simulation test plan generated in step S3, read the test factor list therein, and obtain the factor level value list of each test factor.

[0059] Step S402: Select an appropriate experimental design method, such as full factorial design, uniform design, orthogonal design, or Latin hypercube design, and generate experimental design result data based on the experimental factor information read in step S401. The experimental design result is expressed as the factor level value of each experimental factor in each sample.

[0060] Step S403: Based on the mapping relationship between the experimental factors and the influencing factors in the simulation scenario, the level value of each experimental factor in each sample is substituted into the simulation scenario to form a simulation scenario corresponding to each sample, which is called an experimental sample.

[0061] The test sample set generated in step S4 will serve as input data for subsequent large-sample simulation tests.

[0062] The present invention discloses a simulation test design method for remote sensing satellite system demonstration. It adopts a process-based design approach to form a remote sensing satellite system demonstration simulation test design process from common test factor extraction, scenario task template construction, simulation test plan generation to test sample generation. It quickly forms a list of test factors for a specified remote sensing satellite under different deduction scenarios and tasks, thereby efficiently generating a simulation test sample set that meets the requirements of large-sample simulation deduction.

[0063] The present invention, aimed at the demonstration needs of remote sensing satellite systems, extracts the common key elements of specified remote sensing satellites in different typical deduction scenarios, forms a list of common test factors as built-in factors for each simulation test plan, and on this basis, extracts other task-related test factors according to the characteristics of different task types, generates a list of test factors associated with the task type, and forms a scenario task template, so that users can quickly form simulation test plans based on simulation assumptions of different task types.

[0064] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements but also other elements not explicitly listed, or also includes elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the element.

[0065] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be noted that although the preferred embodiment of the present invention has been described, it is clear that those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles of the present invention. Such improvements and modifications should also be considered as within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A simulation test design method for remote sensing satellite system demonstration, characterized by: The following steps are involved: Step S1, common test factor extraction: extracting common influencing factors of a specified remote sensing satellite in different typical deduction scenarios to form a built-in test factor list; Step S2, scenario task template construction: extract influencing factors according to different task types, construct a list of experimental factors for specific tasks, and form a scenario task template; Step S3, simulation test plan generation: matching scenario task templates according to the task type assumed in the simulation, loading and dynamically adjusting the test factor list, and forming a simulation test plan; Step S4, simulation test sample generation: select an experimental design method based on the simulation test plan, generate test result data and map it to the simulation scenario to form an experimental sample set.

2. The method according to claim 1, characterized in that In step S1, the extraction of common experimental factors specifically includes: Step S101: Analyze the workflow of a designated remote sensing satellite in different typical mission scenarios, extract common influencing factors, and form a built-in test factor list; Step S102: for each experimental factor, set its value range, design method and design parameters, and generate a discrete factor level value list; Step S103: The built-in test factor list is described in a format such as XML or JSON and stored in a database.

3. The method according to claim 2, characterized in that The design parameters of the experimental factors include binomial distribution, exponential distribution, uniform distribution or manual design method.

4. The method according to claim 2, characterized in that The step S2 specifically includes: Step S201: Analyze the workflow of the satellite under the specified mission, extract the influencing factors, add them to the test factor list of the corresponding mission type, and complete the setting of the test factors using the same operation as step S102; Step S202: The built-in test factor list is described in a format such as XML or JSON to form a scenario task template, and is stored in a database.

5. The method according to claim 1, wherein Step S3 specifically includes: Step S301: After the user selects a simulation scenario for which an experimental design is to be carried out, an applicable scenario task template is searched and matched from the database according to the type of task corresponding to the selected simulation scenario, and the experimental factor list information contained therein is loaded; Step S302: Load the built-in test factor list generated in step S1 and merge it with the test factor list generated in step S301; Step S303: Based on the test factor list generated by merging in step S302, test factors are added or deleted according to the characteristics of the simulation scenario selected by the user, and the construction of the test factor list for this simulation scenario is completed to form a simulation test plan.

6. The method according to claim 5, characterized in that The algorithm of the matching process is the keyword matching algorithm.

7. The method according to claim 1, characterized in that Step S4 specifically includes: Step S401: Load the simulation test plan generated in step S3, read the test factor list therein, and obtain the factor level value list of each test factor; Step S402: Based on the preset experimental design method and the experimental factor information read in step S401, generate experimental design result data; Step S403: Based on the mapping relationship between the experimental factors and the influencing factors in the simulation scenario, the level value of each experimental factor in each sample is substituted into the simulation scenario to form a simulation scenario corresponding to each sample, which is called an experimental sample.

8. The method according to claim 7, characterized in that The preset experimental design method is a full factorial design method, a uniform design method, an orthogonal design method or a Latin hypercube design method.

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