Space target data processing system and processing method
By standardizing the format of spatial target data, data analysis and fusion, as well as encryption and security control, the problems of unstable data quality, difficulty in guaranteeing security and inconsistent standards are solved, and data processing with higher quality, security and availability are achieved.
Patent Information
- Application Number
- CN202411866511.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-18
- Publication Date
- 2025-03-14
AI Technical Summary
There are problems in the processing of spatial target data such as unstable data quality, difficulty in ensuring data security, and inconsistent data standards.
By setting the data processing methods of steps S1 to S3: S1 performs standardized processing and preprocessing operations for spatial target data format, S2 performs spatial target data analysis and fusion, and S3 performs encryption and security control of data.
It improves data quality and accuracy, ensures data security, and achieves the unification of data standards, reduces data redundancy and improves data sharing and utilization.
Smart Images
Figure CN119621868A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of data processing technology, and in particular to a data processing system and method for a space target. Background Art
[0002] With the increasing number of space activities and frequent space collision and disintegration events, the number of space targets has increased sharply. Under the influence of gravity and various perturbation factors, the orbital parameters of space targets are constantly changing. In order to accurately grasp the orbital parameter information and improve the space situation awareness capability, it is necessary to continuously observe them and obtain effective position information of space targets to complete the management of space target cataloging.
[0003] Although the processing of space target data has made some progress in technology, there are still some shortcomings, including: (1) Unstable data quality: Space target data is usually affected by many factors, such as weather, atmospheric conditions, terrain, etc., which may lead to unstable data quality and difficult to process accurately; (2) Data security is difficult to ensure: Space target data usually contains sensitive information, such as geographic location, privacy data, etc., which may lead to data leakage and security risks; (3) Inconsistent data standards: Spatial target data from different sources may adopt different standards and formats, making data integration and analysis difficult.
[0004] Therefore, we propose a data processing system and method for space targets. Summary of the invention
[0005] The main purpose of the present invention is to provide a space target data processing system and method, which solves the problems of (1) unstable data quality: space target data are usually affected by various factors, such as weather, atmospheric conditions, terrain, etc., which may lead to unstable data quality and difficulty in accurate processing; (2) data security is difficult to ensure: space target data usually contains sensitive information, such as geographic location, privacy data, etc., which may cause data leakage and security risks; (3) inconsistent data standards: space target data from different sources may adopt different standards and formats, resulting in difficulties in data integration and analysis.
[0006] To achieve the above object, the present invention provides the following technical solutions: A method for processing space target data comprises the following steps: S1. Standardization of space target data format. After obtaining the original data, preprocess the original data, standardize the format of the preprocessed data, and perform calculations on the standardized data before outputting it to a designated data storage device. S2. Space target data analysis: retrieve the space target data in the data storage device, compare and verify the space target data from different sources, and use data fusion technology to integrate and process the data from different sources, eliminate the inconsistency between the data, and generate a target data set; S3. Space target data security processing: encrypt and securely control the target data set, use encryption algorithms to protect data security, establish access control and authority management, and conduct regular security audits and monitoring of target data sets.
[0007] Preferably, the raw data in step S1 includes position information, attitude information, remote sensing data, motion trajectory, state parameters, environmental data and other information of the space target.
[0008] Preferably, the preprocessing operation on the raw data in step S1 includes: preprocessing operations of denoising, data cleaning and data correction on the raw data.
[0009] Preferably, the data format standardization in step S1 comprises the following steps: S11. Spatial data model, which defines the basic units of spatial data storage, such as points, lines, and surfaces, as well as the topological relationships and attribute information between spatial data; S12, Space Identifier, assigns a unique identifier to each space target data so that the space target can be accurately located and identified during space data operation and analysis; S13, spatial data type, defines the type and format of spatial data, such as the coordinates of points, the node sequence of lines, and the boundaries of surfaces, to ensure the consistency of spatial data during storage and processing; S14, spatial index, establish appropriate spatial index structure, such as R-tree, Quadtree, to improve the retrieval and query efficiency of spatial data; S15, spatial operation interface, provides a unified spatial data operation interface, including spatial query, spatial analysis, and spatial relationship judgment operations.
[0010] Preferably, the step S1 of calculating and processing the data after the format standardization comprises the following steps: S16, data analysis, statistical analysis, spatial analysis, and time series analysis of spatial target data to discover patterns and trends among the data; S17. Model establishment: Based on the data analysis results, establish the corresponding mathematical model for prediction, optimization or decision support.
[0011] Preferably, the spatial target data comparison and verification and data fusion technology obtained from multiple data sources in step S2 include the following steps: S21, setting a data similarity threshold, and matching multiple spatial data source entities based on similarity calculation of set data to complete entity matching of multiple data sources; S22, linking and merging the multiple groups of successfully matched data source entities respectively to generate a target data source entity, and using a collection data structure to store multi-valued attributes from the multiple target data source entities to generate a multi-valued attribute set; S23. Add a new data source entity, link and merge the newly added data source entity with the multiple groups of data source entities that failed to match, complete the dynamic data integration of the newly added data source entity, and merge the dynamic data integration set of the newly added data source entity and the multi-value attribute set into the database and store them as the target data set.
[0012] Preferably, the step S3 of using an encryption algorithm to protect the security of data includes the following steps: S31, dividing the spatial data in the target data set into primary data and secondary data according to the memory size, and encrypting the secondary data and primary data respectively; S32, data transmission encryption, the information transmission link is encrypted at the information sending end, and the data information is converted into garbled code that cannot be identified and read during the information transmission in the link; S33, supervision of the encryption and decryption process, collection of various characteristic information of personal identity, and verification and checking of the number of matches of the collected characteristic information and DES information protection processing; S34, information matching warning, during the identity information matching verification process, the data with a detection number greater than the preset value is sent to the server for timely warning; S35, DES information protection processing, in the early stage of personal identity information matching, the identity information is collected and backed up and transmitted to the DES information protection module, and the DES information protection module uses a one-time pad method to encrypt and protect the transmitted information; S36. Authentication of data integrity. The authentication objects are keys, information, passwords and identities. During the decryption process, effective verification processing is performed based on the characteristic values of the object input. If the characteristic value requirements are met, the verification will be passed, otherwise it will be directly rejected.
[0013] Preferably, the establishment of the access control and authority management mechanism for the space target data in step S3 includes the following steps: S301, divide data permissions, divide permissions for spatial target data according to the roles and needs of different users, and implement fine-grained access control; S302, establish an audit log, establish an audit log system, record the access and operation of spatial target data, and facilitate monitoring and tracking of data usage; S303. Implement multi-level authority management and establish a multi-level authority management mechanism to ensure that the access and processing of space target data comply with regulations and security requirements.
[0014] A space target data processing system, comprising: The acquisition module collects space target data through a variety of sensors to obtain raw data; The preprocessing module performs denoising, data cleaning, and data correction operations on the raw data through preset processing units; A retrieval module receives a retrieval command and converts the command into retrieval information, and retrieves the spatial target data in the data storage device through a preset transmission channel; The personal identity information matching terminal includes an identity information collection module, a DES information protection module and an information matching times detection module, which are used to collect various characteristic information of personal identity, and verify and check the matching times of the collected characteristic information and perform DES information protection processing; The server performs information matching warning and remote monitoring simultaneously during the process of personal identity information verification; The data integration module performs similarity calculation on multiple spatial source data through a preset calculation unit, and performs information matching on multiple spatial source data through a preset matching unit.
[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, various sensors are used to collect data from space targets and obtain raw data through format standardization and space target data analysis. Data preprocessing is performed on the raw data to perform preprocessing operations such as denoising, data cleaning, and data correction to improve data quality and accuracy; and the preprocessed data is format-standardized, including unified data structure, unified data unit, unified data accuracy, etc., to ensure that the data formats between different data sources are consistent, and the data after format standardization is calculated and processed, including data fusion, data analysis, model building and other operations, to obtain more useful information; finally, the calculated and processed data is output to a designated data storage device or system for further analysis and use by users; Improve data quality: improve data accuracy and completeness through preprocessing and format standardization; Reduce data redundancy: format standardization can remove redundant information in the data and reduce data storage and transmission costs; Facilitate data sharing: standardized data is easy to share and exchange between different systems, thereby improving data utilization.
[0016] 2. In the present invention, by performing security processing on space target data, the supervision of space data decryption and encryption is improved, personal identity information is strictly reviewed, personal characteristic information is strictly identified and analyzed, the risk of data leakage is reduced, and data transmission is encrypted and converted into ciphertext, which cannot be identified and read. Hackers cannot steal important data, thus avoiding major losses. The integrity of the data can be identified and checked to see if there are any changes during data transmission, thereby ensuring data security. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 This is a flow chart of the space target processing method of the present invention; Figure 2 The data format standardization and calculation process flow chart of the present invention; Figure 3 A flow chart of the spatial target data comparison and verification and data fusion technology obtained from multiple data sources of the present invention; Figure 4 This is a security flow chart of the present invention using encryption algorithm to protect data; Figure 5 A flow chart is established for the access control and authority management mechanism of the space target data of the present invention. DETAILED DESCRIPTION
[0018] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.
[0019] Example: Figure 1-5 As shown, a method for processing space target data includes the following steps: S1. Standardization of space target data format. After obtaining the original data, preprocess the original data, standardize the format of the preprocessed data, and perform calculations on the standardized data before outputting it to a designated data storage device. S2. Space target data analysis: retrieve the space target data in the data storage device, compare and verify the space target data from different sources, and use data fusion technology to integrate and process the data from different sources, eliminate the inconsistency between the data, and generate a target data set; S3. Space target data security processing: encrypt and securely control the target data set, use encryption algorithms to protect data security, establish access control and authority management, and conduct regular security audits and monitoring of target data sets.
[0020] The raw data in step S1 includes the position information, attitude information, remote sensing data, motion trajectory, state parameters, environmental data and other information of the space target; Position information includes the longitude, latitude, altitude and other position coordinate information of the space target. This information can be used to determine the specific location of the space target on the earth's surface.
[0021] Attitude information includes the attitude angle, direction, attitude change speed, etc. of the space target. This information can describe the direction and motion state of the space target.
[0022] Remote sensing data includes image data, spectral data, radar data, etc. obtained through remote sensing technology. These data can reflect the environmental conditions around space targets, such as terrain, vegetation, water bodies, etc.
[0023] The motion trajectory includes the motion trajectory data of the space target, including the change of position over time, which can be used to analyze the motion trajectory and orbital parameters of the space target.
[0024] State parameters include state parameter data of space targets, such as velocity, acceleration, angular velocity, etc. These parameters can describe the motion state and dynamic characteristics of space targets.
[0025] Environmental data includes data about the environment in which the space target is located, such as atmospheric pressure, temperature, humidity, etc. These data can affect the operation and performance of the space target.
[0026] Other information includes space target data may also include other information based on specific needs, such as target feature description, target identification information, target control instructions, etc.
[0027] Among them, the preprocessing operation of the original data in step S1 includes: preprocessing operations of denoising, data cleaning, and data correction on the original data. Preferably, the preprocessing operations such as denoising, data cleaning, and data correction are all existing technologies and will not be elaborated here.
[0028] The data format standardization in step S1 includes the following steps: S11. Spatial data model, which defines the basic units of spatial data storage, such as points, lines, and surfaces, as well as the topological relationships and attribute information between spatial data; S12, Space Identifier, assigns a unique identifier to each space target data so that the space target can be accurately located and identified during space data operation and analysis; S13, spatial data type, defines the type and format of spatial data, such as the coordinates of points, the node sequence of lines, and the boundaries of surfaces, to ensure the consistency of spatial data during storage and processing; S14, spatial index, establish appropriate spatial index structure, such as R-tree, Quadtree, to improve the retrieval and query efficiency of spatial data; S15, spatial operation interface, provides a unified spatial data operation interface, including spatial query, spatial analysis, and spatial relationship judgment operations.
[0029] The step S1 of calculating and processing the data after the format standardization includes the following steps: S16, data analysis, statistical analysis, spatial analysis, and time series analysis of spatial target data to discover patterns and trends among the data; S17. Model establishment: Based on the data analysis results, establish the corresponding mathematical model for prediction, optimization or decision support.
[0030] The spatial target data comparison and verification and data fusion technology obtained from multiple data sources in step S2 include the following steps: S21, setting a data similarity threshold, and matching multiple spatial data source entities based on similarity calculation of set data to complete entity matching of multiple data sources; S22, linking and merging the multiple groups of successfully matched data source entities respectively to generate a target data source entity, and using a collection data structure to store multi-valued attributes from the multiple target data source entities to generate a multi-valued attribute set; S23. Add a new data source entity, link and merge the newly added data source entity with the multiple groups of data source entities that failed to match, complete the dynamic data integration of the newly added data source entity, and merge the dynamic data integration set of the newly added data source entity and the multi-value attribute set into the database and store them as the target data set.
[0031] Preferably, the similarity calculation of set data adopts the formula: for set A and set B, for each element (a, b) in set A and set B respectively, take the maximum similarity with the element of the other set, add the sum and divide it by the sum of the lengths of set A and set B; Multiple data source entities are combined into a multi-valued attribute set. For one attribute of the multi-valued attribute set, different values of the same attribute of all multiple data sources are saved in a set form.
[0032] Wherein, using encryption algorithm to protect data security in step S3 includes the following steps: S31, dividing the spatial data in the target data set into primary data and secondary data according to the memory size, and encrypting the secondary data and primary data respectively; Preferably, both primary data and secondary data are encrypted using a high-strength encryption method; S32, data transmission encryption, the information transmission link is encrypted at the information sending end, and the data information is converted into garbled code that cannot be identified and read during the information transmission in the link; S33, supervision of the encryption and decryption process, collection of various characteristic information of personal identity, and verification and checking of the number of matches of the collected characteristic information and DES information protection processing; S34, information matching warning, during the identity information matching verification process, the data with a detection number greater than the preset value is sent to the server for timely warning; S35, DES information protection processing, in the early stage of personal identity information matching, the identity information is collected and backed up and transmitted to the DES information protection module, and the DES information protection module uses a one-time pad method to encrypt and protect the transmitted information; S36. Authentication of data integrity. The authentication objects are keys, information, passwords and identities. During the decryption process, effective verification processing is performed based on the characteristic values of the object input. If the characteristic value requirements are met, the verification will be passed, otherwise it will be directly rejected.
[0033] The establishment of the access control and authority management mechanism for the spatial target data in step S3 includes the following steps: S301, divide data permissions, divide permissions for spatial target data according to the roles and needs of different users, and implement fine-grained access control; S302, establish an audit log, establish an audit log system, record the access and operation of spatial target data, and facilitate monitoring and tracking of data usage; S303. Implement multi-level authority management and establish a multi-level authority management mechanism to ensure that the access and processing of space target data comply with regulations and security requirements.
[0034] A space target data processing system, comprising: The acquisition module collects space target data through a variety of sensors to obtain raw data; The preprocessing module performs denoising, data cleaning, and data correction operations on the raw data through preset processing units; A retrieval module receives a retrieval command and converts the command into retrieval information, and retrieves the spatial target data in the data storage device through a preset transmission channel; The personal identity information matching terminal includes an identity information collection module, a DES information protection module and an information matching times detection module, which are used to collect various characteristic information of personal identity, and verify and check the matching times of the collected characteristic information and perform DES information protection processing; The server performs information matching warning and remote monitoring simultaneously during the process of personal identity information verification; The data integration module performs similarity calculation on multiple spatial source data through a preset calculation unit, and performs information matching on multiple spatial source data through a preset matching unit.
Claims
1. A method for processing space target data, characterized in that: The following steps are involved: S1. Standardization of space target data format. After obtaining the original data, preprocess the original data, standardize the format of the preprocessed data, and perform calculations on the standardized data before outputting it to a designated data storage device. S2. Space target data analysis: retrieve the space target data in the data storage device, compare and verify the space target data from different sources, and use data fusion technology to integrate and process the data from different sources, eliminate the inconsistency between the data, and generate a target data set; S3. Space target data security processing: encrypt and securely control the target data set, use encryption algorithms to protect data security, establish access control and authority management, and conduct regular security audits and monitoring of target data sets.
2. The method for processing space target data according to claim 1, characterized in that: The raw data in step S1 includes the position information, attitude information, remote sensing data, motion trajectory, state parameters, environmental data and other information of the space target.
3. The method for processing space target data according to claim 2, characterized in that: The preprocessing operation of the raw data in step S1 includes: preprocessing operations of denoising, data cleaning, and data correction on the raw data.
4. The method for processing space target data according to claim 3, characterized in that: The data format standardization in step S1 includes the following steps: S11. Spatial data model, which defines the basic units of spatial data storage, such as points, lines, and surfaces, as well as the topological relationships and attribute information between spatial data; S12, Space Identifier, assigns a unique identifier to each space target data so that the space target can be accurately located and identified during space data operation and analysis; S13, spatial data type, defines the type and format of spatial data, such as the coordinates of points, the node sequence of lines, and the boundaries of surfaces, to ensure the consistency of spatial data during storage and processing; S14, spatial index, establish appropriate spatial index structure, such as R-tree, Quadtree, to improve the retrieval and query efficiency of spatial data; S15, spatial operation interface, provides a unified spatial data operation interface, including spatial query, spatial analysis, and spatial relationship judgment operations.
5. The method for processing space target data according to claim 4, characterized in that: The step S1 of calculating and processing the data after the format standardization comprises the following steps: S16, data analysis, statistical analysis, spatial analysis, and time series analysis of spatial target data to discover patterns and trends among the data; S17. Model establishment: Based on the data analysis results, establish the corresponding mathematical model for prediction, optimization or decision support.
6. The method for processing space target data according to claim 5, characterized in that: The spatial target data comparison and verification and data fusion technology implemented in step S2 obtained from multiple data sources include the following steps: S21, setting a data similarity threshold, and matching multiple spatial data source entities based on similarity calculation of set data to complete entity matching of multiple data sources; S22, linking and merging the multiple groups of successfully matched data source entities respectively to generate a target data source entity, and using a collection data structure to store multi-valued attributes from the multiple target data source entities to generate a multi-valued attribute set; S23. Add a new data source entity, link and merge the newly added data source entity with the multiple groups of data source entities that failed to match, complete the dynamic data integration of the newly added data source entity, and merge the dynamic data integration set of the newly added data source entity and the multi-value attribute set into the database and store them as the target data set.
7. The method for processing space target data according to claim 6, characterized in that: The step S3 in which the encryption algorithm is used to protect the security of data includes the following steps: S31, dividing the spatial data in the target data set into primary data and secondary data according to the memory size, and encrypting the secondary data and primary data respectively; S32, data transmission encryption, the information transmission link is encrypted at the information sending end, and the data information is converted into garbled code that cannot be identified and read during the information transmission in the link; S33, supervision of the encryption and decryption process, collection of various characteristic information of personal identity, and verification and checking of the number of matches of the collected characteristic information and DES information protection processing; S34, information matching warning, during the identity information matching verification process, the data with a detection number greater than the preset value is sent to the server for timely warning; S35, DES information protection processing, in the early stage of personal identity information matching, the identity information is collected and backed up and transmitted to the DES information protection module, and the DES information protection module uses a one-time pad method to encrypt and protect the transmitted information; S36. Authentication of data integrity. The authentication objects are keys, information, passwords and identities. During the decryption process, effective verification processing is performed based on the characteristic values of the object input. If the characteristic value requirements are met, the verification will be passed, otherwise it will be directly rejected.
8. The method for processing space target data according to claim 7, characterized in that: The establishment of the access control and authority management mechanism for the space target data in step S3 includes the following steps: S301, divide data permissions, divide permissions for spatial target data according to the roles and needs of different users, and implement fine-grained access control; S302, establish an audit log, establish an audit log system, record the access and operation of spatial target data, and facilitate monitoring and tracking of data usage; S303. Implement multi-level authority management and establish a multi-level authority management mechanism to ensure that the access and processing of space target data comply with regulations and security requirements.
9. A space target data processing system, characterized in that: include: The acquisition module collects space target data through a variety of sensors to obtain raw data; The preprocessing module performs denoising, data cleaning, and data correction operations on the raw data through preset processing units; A retrieval module receives a retrieval command and converts the command into retrieval information, and retrieves the spatial target data in the data storage device through a preset transmission channel; The personal identity information matching terminal includes an identity information collection module, a DES information protection module and an information matching times detection module, which are used to collect various characteristic information of personal identity, and verify and check the matching times of the collected characteristic information and perform DES information protection processing; The server performs information matching warning and remote monitoring simultaneously during the process of personal identity information verification; The data integration module performs similarity calculation on multiple spatial source data through a preset calculation unit, and performs information matching on multiple spatial source data through a preset matching unit.