Remote sensing satellite raw data processing and management method, device and equipment and medium
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- AEROSPACE INFORMATION RES INST CAS
- Filing Date
- 2023-10-25
- Publication Date
- 2026-06-19
Smart Images
Figure CN117332134B_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of satellite data management technology, and in particular to a method, apparatus, electronic device, and medium for processing and managing raw remote sensing satellite data. Background Technology
[0002] With the development of information technology, the types of satellite equipment are constantly increasing, and the types of telemetry parameters representing the satellite status are also diverse. The existing satellite ground receiving station processing system uses a single-track, single-channel, single-data-file processing method for the received satellite raw data, that is, storing the raw data of satellites in the same orbit or the same channel in one data file, forming a super large data file.
[0003] However, with the increase in satellite code rates and the growing number of long-duration missions of geostationary satellites, an increasing number of ultra-large data files are being generated. The excessive size of individual data files poses significant inconvenience for data transmission and use. This is especially true when a portion of data within a single file—for example, a small segment or a few frames of data from a particular orbit—is of poor quality and needs to be retransmitted. This necessitates retransmitting the entire ultra-large data file, resulting in significant time consumption and bandwidth waste. Furthermore, due to the limited bandwidth of receiving stations, this wasted bandwidth also reduces the timeliness of data transmission from other satellites. Summary of the Invention
[0004] In view of the above problems, this disclosure provides a method, apparatus, electronic device and medium for processing and managing raw remote sensing satellite data, so as to solve the problems of inconvenient transmission, long time consumption, wasted bandwidth and reduced timeliness of transmission of other satellite data caused by the processing method of single track, single channel and single data file in the prior art.
[0005] The first aspect of this disclosure provides a method for processing and managing raw remote sensing satellite data, including:
[0006] While the satellite is passing overhead, the bitstream of raw remote sensing satellite data is collected in real time;
[0007] Define the segmentation mode of remote sensing satellite raw data. The segmentation method of remote sensing satellite raw data includes whether the remote sensing satellite raw data is segmented, the segmentation method of remote sensing satellite raw data, and the specific segmentation parameter values of each segmentation method.
[0008] For segmented remote sensing satellite raw data, the remote sensing satellite raw data is segmented according to the segmentation method of the data and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data.
[0009] Metadata information is generated for each segment of the raw remote sensing satellite data. This metadata information is used to manage and query the segmented raw remote sensing satellite data.
[0010] According to embodiments of this disclosure, the segmentation pattern of the defined data includes:
[0011] Define whether the raw remote sensing satellite data is segmented and the segmentation type. The segmentation type includes at least one of segmentation by data volume, segmentation by time, segmentation by frame number, and segmentation by satellite virtual channel identifier.
[0012] When the raw remote sensing satellite data needs to be segmented, the specific segmentation parameter values for each segmentation method are defined according to the segmentation type.
[0013] According to embodiments of this disclosure, defining specific segmentation parameter values for each segmentation method based on the segmentation type includes:
[0014] When the segmentation method is based on data volume, the unit of the specific segmentation parameter value is Mbps;
[0015] When the segmentation method is time-based segmentation, the unit of the specific segmentation parameter value is seconds;
[0016] When the segmentation method is segmentation by frame number, the unit of the specific segmentation parameter value is the frame number;
[0017] When the segmentation method is based on the satellite virtual channel identifier, the specific segmentation parameter value is the satellite virtual channel identifier.
[0018] According to embodiments of this disclosure, the step of segmenting the remote sensing satellite raw data according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data includes:
[0019] When the segmentation method is segmentation based on data volume, each time the data volume specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format;
[0020] When the segmentation method is time-based segmentation, the time code identifier of each frame of data is parsed according to the original satellite data format to calculate the time amount. Each time the time amount is reached, a segmented remote sensing satellite original data is reorganized and generated according to the original satellite data format.
[0021] When the segmentation method is segmented by frame number, each time the number of frames specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format;
[0022] When the segmentation method is based on satellite virtual channel identifiers, the virtual channel identifier of each frame of data is parsed according to the original satellite data format. Data with the same satellite virtual channel identifier are reorganized according to the original satellite data format to generate a segmented remote sensing satellite original data.
[0023] According to embodiments of this disclosure, the metadata information includes basic attribute information and proprietary attribute information of the segmented remote sensing satellite raw data;
[0024] The basic attribute information includes satellite, orbit number, channel number, and mission number;
[0025] The proprietary attribute information includes the file name of the segmented remote sensing satellite raw data, the file size of the segmented remote sensing satellite raw data, the segment number of the segmented remote sensing satellite raw data, the start time of the segmented remote sensing satellite raw data, the end time of the segmented remote sensing satellite raw data, the frame number of the first frame of the segmented remote sensing satellite raw data in the original satellite data, the frame number of the last frame of the segmented remote sensing satellite raw data in the original satellite data, and the virtual channel identifier number of the segmented remote sensing satellite raw data.
[0026] According to embodiments of this disclosure, the method further includes:
[0027] Each segment of the raw remote sensing satellite data obtained from a single data file is stored in a separate folder.
[0028] According to embodiments of this disclosure, the method further includes:
[0029] Parse the metadata information of the segmented remote sensing satellite raw data;
[0030] The segmented remote sensing satellite raw data and its metadata information are injected into the database, and a query and retrieval interface is provided. The query and retrieval interface supports searching by at least one of the following: segmented remote sensing satellite raw data file name, file size, file sequence number, data start time, data frame count, and virtual channel number.
[0031] A second aspect of this disclosure provides a data management apparatus, comprising:
[0032] The acquisition module is used to acquire the bitstream of raw remote sensing satellite data in real time while the satellite is passing overhead;
[0033] The data segmentation mode definition module is used to define the segmentation mode of remote sensing satellite raw data. The segmentation method of the remote sensing satellite raw data includes whether the remote sensing satellite raw data is segmented, the segmentation method of the remote sensing satellite raw data, and the specific segmentation parameter values of each segmentation method.
[0034] The data segmentation and recording processing module is used to segment the remote sensing satellite raw data according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method, and generate segmented remote sensing satellite raw data.
[0035] The segmented remote sensing satellite raw data metadata file generation module is used to generate metadata information for each segment of remote sensing satellite raw data. The metadata information is used for managing and querying the remote sensing satellite raw data.
[0036] A third aspect of this disclosure provides an electronic device comprising:
[0037] One or more processors;
[0038] Storage device for storing one or more programs.
[0039] Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method described in the first aspect above.
[0040] A fourth aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method described in the first aspect above.
[0041] This disclosure divides a large file of raw remote sensing satellite data into multiple smaller data files and utilizes various segmentation methods to meet users' business needs, facilitates accurate data selection, transmission and use, and effectively saves time, resources and network bandwidth. Attached Figure Description
[0042] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:
[0043] Figure 1 The illustration schematically depicts an application scenario of a remote sensing satellite raw data processing and management method, system, electronic device, and medium according to embodiments of the present disclosure.
[0044] Figure 2 The illustration shows a flowchart of a method for processing and managing raw remote sensing satellite data according to an embodiment of the present disclosure.
[0045] Figure 3 The illustration schematically shows a flowchart of another method for processing and managing raw remote sensing satellite data according to an embodiment of the present disclosure;
[0046] Figure 4This schematically illustrates a structural block diagram of a remote sensing satellite raw data processing and management apparatus according to an embodiment of the present disclosure; and
[0047] Figure 5 A block diagram schematically illustrates an electronic device suitable for implementing a method for processing and managing raw data from remote sensing satellites, according to embodiments of the present disclosure. Detailed Implementation
[0048] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.
[0049] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.
[0050] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.
[0051] Figure 1 The illustration schematically depicts an application scenario of a remote sensing satellite raw data processing and management method, system, electronic device, and medium according to embodiments of the present disclosure.
[0052] like Figure 1 As shown, network 102 is a medium used to provide a communication link between remote sensing satellite 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.
[0053] Server 103 can be a server that provides various services. For example, a ground base station uses network 102 to obtain data from remote sensing satellite 101. Server 103 analyzes and processes the received data and feeds back the processing results to the ground base station through network 102.
[0054] It should be noted that the remote sensing satellite raw data processing and management method provided in this disclosure embodiment can generally be executed by server 103. Correspondingly, the data management device provided in this disclosure embodiment can generally be located in server 103. The remote sensing satellite raw data processing and management method provided in this disclosure embodiment can also be executed by a server or server cluster that is different from server 103 but capable of communicating with remote sensing satellite 101 and / or server 103. Correspondingly, the data management device provided in this disclosure embodiment can also be located in a server or server cluster that is different from server 103 but capable of communicating with remote sensing satellite 101 and / or server 103.
[0055] It should be understood that Figure 1 The number of remote sensing satellites, networks, and servers shown is merely illustrative. Any number of remote sensing satellites, networks, and servers can be included depending on implementation needs.
[0056] The following will be based on Figure 1 The described scene, through Figure 2 The remote sensing satellite raw data processing and management method according to embodiments of this disclosure will be described in detail.
[0057] Figure 2 The illustration shows a flowchart of a method for processing and managing raw remote sensing satellite data according to an embodiment of the present disclosure. The method includes steps S1-S4.
[0058] In step S1, the bitstream of raw remote sensing satellite data is collected in real time while the satellite is passing overhead;
[0059] In step S2, the segmentation mode of the remote sensing satellite raw data is defined. The segmentation mode of the remote sensing satellite raw data includes whether the remote sensing satellite raw data is segmented, the segmentation mode of the remote sensing satellite raw data, and the specific segmentation parameter values for each segmentation mode.
[0060] In step S3, for the segmented remote sensing satellite raw data, the satellite data is segmented according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data.
[0061] In step S4, metadata information for each segment of remote sensing satellite raw data is generated. This metadata information is used to manage and query the raw data of that segment of remote sensing satellite.
[0062] In this disclosure, while receiving raw satellite data, the ground base station uses a demodulator to collect the raw satellite data bitstream and generates multiple smaller segmented remote sensing satellite raw data files according to a preset segmentation method, which facilitates the replacement of raw satellite data and saves data query time.
[0063] In some embodiments of this disclosure, the segmentation mode of the remote sensing satellite raw data includes: defining whether the remote sensing satellite raw data is segmented and the segmentation type, wherein the segmentation type includes at least one of segmentation by data volume, segmentation by time, segmentation by frame number, and segmentation by satellite virtual channel identifier; and when the remote sensing satellite raw data needs to be segmented, defining specific segmentation parameter values for each segmentation method according to the segmentation type.
[0064] The specific segmentation parameter values defined for each segmentation method according to the segmentation type include: when the segmentation method is segmented by data volume, the unit of the specific segmentation parameter value is Mbps; when the segmentation method is segmented by time, the unit of the specific segmentation parameter value is seconds (s); when the segmentation method is segmented by frame number, the unit of the specific segmentation parameter value is the frame number; and when the segmentation method is segmented by satellite virtual channel identifier, the specific segmentation parameter value is the satellite virtual channel identifier.
[0065] Specifically, SplitType defines whether a large data file is segmented and the type of segmentation. NULL: indicates no segmentation; DATASIZE: segment by data volume; TIME: segment by time; FRAME: segment by frame number; VCID: segment by satellite virtual channel identifier (VCID).
[0066] SplitContent: When segmentation is required, the specific parameter value for segmentation is defined in conjunction with the SplitType segmentation method mentioned above. When SplitType=DATASIZE, it indicates the amount of data to be segmented in Mbps; when SplitType=TIME, it indicates the amount of time to be segmented in seconds; when SplitType=FRAME, it indicates the number of frames to be segmented.
[0067] In some embodiments of this disclosure, the remote sensing satellite raw data is segmented according to the segmentation method and the specific segmentation parameter values for each segmentation method to generate segmented remote sensing satellite raw data. This includes: when the segmentation method is based on data volume, a new segmented remote sensing satellite raw data is generated by reorganizing the data according to the satellite raw data format each time the data volume specified by the specific segmentation parameter value is reached; when the segmentation method is based on time, the time code identifier bit of each frame of data is parsed according to the satellite raw data format to calculate the time amount, and a new segmented remote sensing satellite raw data is generated according to the satellite raw data format each time the time amount is reached; when the segmentation method is based on the number of frames, a new segmented remote sensing satellite raw data is generated according to the satellite raw data format each time the number of frames specified by the specific segmentation parameter value is reached; when the segmentation method is based on the satellite virtual channel identifier number, the virtual channel identifier number of each frame of data is parsed according to the satellite raw data format, and data with the same satellite virtual channel identifier number is reorganized according to the satellite raw data format to generate a new segmented remote sensing satellite raw data.
[0068] Specifically, the data is segmented according to the amount of data: when SplitType is DATASIZE, the data is segmented according to the amount of data specified by SplitContent. Once the specified amount of data is reached, a segment of remote sensing satellite raw data is generated.
[0069] Segmented by time: When SplitType is TIME, the data is segmented according to the time specified by SplitContent. Once the specified time length is reached, a segment of remote sensing satellite raw data is generated.
[0070] Segmentation by frame number: When SplitType is FRAME, the data is segmented according to the number of frames specified by SplitContent. Once the specified number of frames is reached, a segment of remote sensing satellite raw data is generated.
[0071] Segmentation by Virtual Channel Identifier: When SplitType is VCID, the data is segmented according to the virtual channel identifier, and data with the same virtual channel identifier are generated into a segment of remote sensing satellite raw data.
[0072] In some embodiments of this disclosure, the metadata information includes basic attribute information and proprietary attribute information of the segmented remote sensing satellite raw data.
[0073] This basic attribute information includes satellite, orbit number, channel number, and mission number.
[0074] This proprietary attribute information includes:
[0075] data_filename: Filename of the original data segment from the remote sensing satellite;
[0076] file_size: Size of the original data file for the segmented remote sensing satellites;
[0077] split_start_time: Start time of the raw data segmentation from remote sensing satellites;
[0078] split_end_time: The end time of the original data segmentation from the remote sensing satellite;
[0079] frame_start_num: The frame number of the first frame of the segmented remote sensing satellite raw data in the original file;
[0080] frame_end_num: The frame number of the last frame of the segmented remote sensing satellite raw data in the original file;
[0081] vcid: The virtual channel identifier for the raw remote sensing satellite data segment.
[0082] It is understandable that, in addition to the above illustrative examples, the basic and proprietary attribute information of the segmented remote sensing satellite raw data may include other necessary information, and this disclosure does not impose any restrictions on this.
[0083] In some embodiments of this disclosure, Figure 1 The method also includes storing the raw data of each segment of remote sensing satellite obtained from a data file into a folder, that is, storing the raw data of the segmented remote sensing satellite generated from the original large data file into a folder.
[0084] Figure 3 The illustration shows a flowchart of a method for processing and managing raw remote sensing satellite data according to an embodiment of the present disclosure. In addition to steps S1-S4, the method also includes steps S5-S6.
[0085] In step S1, the raw data stream of the remote sensing satellite is collected in real time while the satellite is passing overhead.
[0086] In step S2, a segmentation mode for the raw remote sensing satellite data is defined. The segmentation mode for the raw remote sensing satellite data includes whether the raw remote sensing satellite data is segmented, the segmentation method of the raw remote sensing satellite data, and the specific segmentation parameter values for each segmentation method.
[0087] In step S3, for the segmented remote sensing satellite raw data, the remote sensing satellite raw data is segmented according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data.
[0088] In step S4, metadata information for each segment of the remote sensing satellite raw data is generated. This metadata information is used to manage and query the remote sensing satellite raw data.
[0089] In step S5, the metadata information of the segmented remote sensing satellite raw data is parsed.
[0090] In step S6, the raw data of the segmented remote sensing satellite and its metadata are injected into the database, and a query and retrieval interface is provided. This query and retrieval interface supports searching by at least one of the following: file name, file size, file sequence number, data start time, data frame count, and virtual channel number.
[0091] According to the remote sensing satellite raw data processing and management method provided in this disclosure, large data files can be segmented into multiple small data files in different ways according to user business needs, which facilitates accurate data selection, transmission and use, and saves time, resources and network bandwidth.
[0092] Based on the aforementioned methods for processing and managing raw remote sensing satellite data, this disclosure also provides a device for processing and managing raw remote sensing satellite data. The following will be combined with... Figure 4 The device for processing and managing the raw data of the remote sensing satellite is described in detail.
[0093] Figure 4 The diagram illustrates a structural block diagram of a remote sensing satellite raw data processing and management apparatus according to an embodiment of the present disclosure.
[0094] like Figure 4 As shown, the remote sensing satellite raw data processing and management device 400 in this embodiment includes an acquisition module 401, a data segmentation mode definition module 402, a data segmentation record processing module 403, and a segmented remote sensing satellite raw data metadata file generation module 404.
[0095] The acquisition module 401 is used to acquire the bit stream of raw remote sensing satellite data in real time while the satellite is passing overhead;
[0096] The data segmentation mode definition module 402 is used to define the segmentation mode of the remote sensing satellite raw data. The segmentation method of the remote sensing satellite raw data includes whether the remote sensing satellite raw data is segmented, the segmentation method of the remote sensing satellite raw data, and the specific segmentation parameter values of each segmentation method.
[0097] The data segmentation and recording processing module 403 is used to segment the remote sensing satellite raw data according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method, and generate segmented remote sensing satellite raw data.
[0098] The segmented remote sensing satellite raw data metadata file generation module 404 is used to generate metadata information for each segment of remote sensing satellite raw data. This metadata information is used for managing and querying the raw data of the segmented remote sensing satellite.
[0099] In some embodiments of this disclosure, the segmentation mode for defining raw remote sensing satellite data includes:
[0100] Define whether the raw remote sensing satellite data is segmented and the segmentation type. The segmentation type includes at least one of segmentation by data volume, segmentation by time, segmentation by frame number, and segmentation by satellite virtual channel identifier.
[0101] When the raw remote sensing satellite data needs to be segmented, the specific segmentation parameter values for each segmentation method are defined according to the segmentation type.
[0102] In some embodiments of this disclosure, the specific segmentation parameter values for each segmentation method defined according to the segmentation type include:
[0103] When the segmentation method is based on data volume, the unit of the specific segmentation parameter value is Mbps;
[0104] When the segmentation method is based on time segmentation, the unit of the specific segmentation parameter value is seconds (s).
[0105] When the segmentation method is based on frame count, the unit of the specific segmentation parameter value is the number of frames.
[0106] When the segmentation method is based on the satellite virtual channel identifier, the specific segmentation parameter value is the satellite virtual channel identifier.
[0107] In some embodiments of this disclosure, the process of segmenting the remote sensing satellite raw data according to the segmentation method and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data includes:
[0108] When the segmentation method is segmentation based on data volume, each time the data volume specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format;
[0109] When the segmentation method is time-based segmentation, the time code identifier of each frame of data is parsed according to the original satellite data format to calculate the time amount. Each time the time amount is reached, a segmented remote sensing satellite original data is reorganized and generated according to the original satellite data format.
[0110] When the segmentation method is segmented by frame number, each time the number of frames specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format;
[0111] When the segmentation method is based on satellite virtual channel identifiers, the virtual channel identifier of each frame of data is parsed according to the original satellite data format. Data with the same satellite virtual channel identifier are reorganized according to the original satellite data format to generate a segmented remote sensing satellite original data.
[0112] In some embodiments of this disclosure, the metadata information includes basic attribute information and proprietary attribute information of the segmented remote sensing satellite raw data;
[0113] This basic attribute information includes at least one of the following: satellite, orbit number, channel number, and mission number;
[0114] The proprietary attribute information includes the file name of the segmented remote sensing satellite raw data, the file size of the segmented remote sensing satellite raw data, the segment number of the segmented remote sensing satellite raw data, the start time of the segmented remote sensing satellite raw data, the end time of the segmented remote sensing satellite raw data, the number of frames of the first frame of the segmented remote sensing satellite raw data in the original satellite data, the number of frames of the last frame of the segmented remote sensing satellite raw data in the original satellite data, and the virtual channel identifier number of the segmented remote sensing satellite raw data.
[0115] In some embodiments of this disclosure, the apparatus 400 further includes:
[0116] The storage module is used to store the raw remote sensing satellite data of each segment obtained from a data file in a folder.
[0117] In some embodiments of this disclosure, the apparatus 400 further includes:
[0118] The parsing module parses the metadata information of the raw remote sensing satellite data segment.
[0119] The retrieval module is used to inject the raw data of the segmented remote sensing satellite and its metadata into the database, and to provide a query retrieval interface. This query retrieval interface supports searching by at least one of the following: file name, file size, file sequence number, data start time, data frame count, and virtual channel number of the raw data segmented remote sensing satellite.
[0120] According to embodiments of this disclosure, any and multiple modules among the acquisition module 401, data segmentation mode definition module 402, data segmentation record processing module 403, and segmented remote sensing satellite raw data metadata file generation module 404 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module.
[0121] According to embodiments of this disclosure, at least one of the acquisition module 401, the data segmentation mode definition module 402, the data segmentation recording and processing module 403, and the segmented remote sensing satellite raw data metadata file generation module 404 can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the acquisition module 401, the data segmentation mode definition module 402, the data segmentation recording and processing module 403, and the segmented remote sensing satellite raw data metadata file generation module 404 can be at least partially implemented as computer program modules, which can perform corresponding functions when the computer program module is run.
[0122] Figure 5 A block diagram schematically illustrates an electronic device suitable for implementing a method for processing and managing raw data from remote sensing satellites, according to embodiments of the present disclosure.
[0123] like Figure 5 As shown, an electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.
[0124] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 502 and / or RAM 503. It should be noted that the program may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in such one or more memories.
[0125] According to embodiments of this disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.
[0126] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.
[0127] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.
[0128] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0129] The acquisition and storage of remote sensing satellite data involved in the above-disclosed technical solutions all comply with the provisions of relevant laws and regulations, have taken necessary confidentiality measures, and do not violate public order and good morals.
[0130] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.
[0131] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.
Claims
1. A remote sensing satellite raw data processing and management method, characterized in that, include: While the satellite is passing overhead, the bitstream of raw remote sensing satellite data is collected in real time; Define the segmentation mode of remote sensing satellite raw data. The segmentation method of remote sensing satellite raw data includes whether the remote sensing satellite raw data is segmented, the segmentation method of remote sensing satellite raw data, and the specific segmentation parameter values of each segmentation method. For segmented remote sensing satellite raw data, the remote sensing satellite raw data is segmented according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data. Metadata information is generated for each segment of remote sensing satellite raw data. The metadata information is used to manage and query the segment of remote sensing satellite raw data. The metadata information includes: the file name of the segment of remote sensing satellite raw data, the file size, the segment start time, the segment end time, the number of frames of the first frame of the segment data in the original file, the number of frames of the last frame of the segment data in the original file, and the virtual channel identifier. The step of segmenting the remote sensing satellite raw data according to the segmentation method and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data includes: When the segmentation method is segmentation based on data volume, each time the data volume specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format; When the segmentation method is time-based segmentation, the time code identifier of each frame of data is parsed according to the original satellite data format to calculate the time amount. Each time the time amount is reached, a segmented remote sensing satellite original data is reorganized and generated according to the original satellite data format. When the segmentation method is segmented by frame number, each time the number of frames specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format; When the segmentation method is based on satellite virtual channel identifiers, the virtual channel identifier of each frame of data is parsed according to the original satellite data format. Data with the same satellite virtual channel identifier are reorganized according to the original satellite data format to generate a segmented remote sensing satellite original data.
2. The remote sensing satellite raw data processing and management method according to claim 1, characterized in that, The segmentation mode for the raw remote sensing satellite data is defined as follows: Define whether the raw remote sensing satellite data is segmented and the segmentation type. The segmentation type includes at least one of segmentation by data volume, segmentation by time, segmentation by frame number, and segmentation by satellite virtual channel identifier. When the raw remote sensing satellite data needs to be segmented, the specific segmentation parameter values for each segmentation method are defined according to the segmentation type.
3. The remote sensing satellite raw data processing and management method according to claim 2, characterized in that, The specific segmentation parameter values for each segmentation method defined according to the segmentation type include: When the segmentation method is based on data volume, the unit of the specific segmentation parameter value is Mbps; When the segmentation method is time-based segmentation, the unit of the specific segmentation parameter value is seconds; When the segmentation method is segmentation by frame number, the unit of the specific segmentation parameter value is the frame number; When the segmentation method is based on the satellite virtual channel identifier, the specific segmentation parameter value is the satellite virtual channel identifier.
4. The remote sensing satellite raw data processing and management method of claim 1, wherein, The metadata information includes the basic attribute information and proprietary attribute information of the segmented remote sensing satellite raw data; The basic attribute information includes satellite, orbit number, channel number, and mission number; The proprietary attribute information includes the file name of the segmented remote sensing satellite raw data, the file size of the segmented remote sensing satellite raw data, the segment number of the segmented remote sensing satellite raw data, the start time of the segmented remote sensing satellite raw data, the end time of the segmented remote sensing satellite raw data, the frame number of the first frame of the segmented remote sensing satellite raw data in the original satellite data, the frame number of the last frame of the segmented remote sensing satellite raw data in the original satellite data, and the virtual channel identifier number of the segmented remote sensing satellite raw data.
5. The remote sensing satellite raw data processing and management method according to claim 1, characterized in that, The method further includes: Parse the metadata information of the segmented remote sensing satellite raw data; The segmented remote sensing satellite raw data and its metadata information are injected into the database, and a query and retrieval interface is provided. The query and retrieval interface supports searching by at least one of the following: segmented remote sensing satellite raw data file name, file size, file sequence number, data start time, data frame count, and virtual channel number.
6. A data management apparatus characterized by comprising: include: The acquisition module is used to acquire the bitstream of raw remote sensing satellite data in real time while the satellite is passing overhead; The data segmentation mode definition module is used to define the segmentation mode of remote sensing satellite raw data. The segmentation method of the remote sensing satellite raw data includes whether the remote sensing satellite raw data is segmented, the segmentation method of the remote sensing satellite raw data, and the specific segmentation parameter values of each segmentation method. The data segmentation and recording processing module is used to segment the remote sensing satellite raw data according to the segmentation method of the remote sensing satellite raw data and the specific segmentation parameter values of each segmentation method, and generate segmented remote sensing satellite raw data. The segmented remote sensing satellite raw data metadata file generation module is used to generate metadata information for each segment of remote sensing satellite raw data. The metadata information is used to manage and query the remote sensing satellite raw data. The metadata information includes: segmented remote sensing satellite raw data file name, file size, segment start time, segment end time, number of frames of the first frame of the segmented data in the original file, number of frames of the last frame of the segmented data in the original file, and virtual channel identifier. The step of segmenting the remote sensing satellite raw data according to the segmentation method and the specific segmentation parameter values of each segmentation method to generate segmented remote sensing satellite raw data includes: When the segmentation method is segmentation based on data volume, each time the data volume specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format; When the segmentation method is time-based segmentation, the time code identifier of each frame of data is parsed according to the original satellite data format to calculate the time amount. Each time the time amount is reached, a segmented remote sensing satellite original data is reorganized and generated according to the original satellite data format. When the segmentation method is segmented by frame number, each time the number of frames specified by the specific segmentation parameter value is reached, a segmented remote sensing satellite raw data is reorganized and generated according to the original satellite data format; When the segmentation method is based on satellite virtual channel identifiers, the virtual channel identifier of each frame of data is parsed according to the original satellite data format. Data with the same satellite virtual channel identifier are reorganized according to the original satellite data format to generate a segmented remote sensing satellite original data.
7. An electronic device, comprising: include: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 6.
8. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 6.