A method, system and device for closed-loop analysis of requirements

Abstract

The present invention provides a demand closed-loop analysis method, system and device, which includes: obtaining satellite view data, obtaining demand data, and demand timing coverage analysis and calculation. Starting from the two entrances of demand and view data, a small amount of calculation is performed in real time to obtain a certain correlation relationship, and finally the coverage rate, number of observations and observation duration are summarized and calculated, and the large amount of calculation at the same time in the prior art is amortized into small amounts of calculation at different times, which reduces the database calculation burden, thereby ensuring the calculation efficiency and alleviating the database pressure.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite observation, and in particular, to a requirement closed-loop analysis method, system and device. Background Art

[0002] Currently, the requirement closed-loop analysis in the technical field of satellite observation refers to analyzing the completion situation of the observation requirements proposed by users within a specified time through the obtained satellite image scene data. Generally speaking, the observation targets come from the vulnerability areas and specific areas to be observed, and there may also be multiple discrete areas, which need to be jointly completed by multiple satellites, multiple transits, and multiple observations. And this process usually cannot be completed in a very short time. We need to always master the requirement completion situation, so it is necessary to track the coverage shooting situation of the requirements in real time, which can also provide a basis for formulating subsequent shooting plans and adjusting the priority of tasks.

[0003] The existing method for statistically analyzing the completion situation of shooting requirements is to first propose requirements to form an area to be calculated, and then perform timed coverage analysis based on the satellite scene data. Since the calculation area needs to continuously receive new scene data information to dynamically update its coverage, and calculating unilaterally from the requirement side will cause the coordinate graphic calculation tool to work continuously, consuming its computing power for a long time, bringing huge pressure to the database and reducing the calculation efficiency. The specific description is as follows:

[0004] When scanning the disk array scene data, for each parsed scene data, find out its associated target requirements, and input the relationship between the requirement id, target id and scene id into the database;

[0005] When creating or submitting requirements, query the associated scene data according to information such as requirement time, satellite conditions, and geographical coordinates, and input the relationship between the requirement id, target id and scene id into the database;

[0006] Through the timed analysis task, query the database of the unprocessed associated relationship table, gradually delete the relevant positions of the scene data and the target, obtain the remaining targets, perform coverage analysis, and iterate continuously until the remaining targets are cleared to complete full coverage.

[0007] The defects of the above-mentioned existing technologies are as follows:

[0008] Whenever a new requirement or new scene data is imported, it is necessary to recalculate the relevant data;

[0009] When importing targets with a large number of vulnerability areas, each target needs to obtain results through multi-dimensional matching such as time and space from a large amount of scene data. At this time, the database calculation pressure is huge, affecting the execution efficiency of the database, and the waiting time for saving and submitting requirements is long and the user experience is poor;

[0010] Each piece of scene data needs to be processed geographically separately, resulting in a large amount of data, slow execution, and huge pressure on the database. Summary of the Invention

[0011] The purpose of the present invention is to provide a requirements closed-loop analysis method, system, and device to solve the above technical problems existing in the prior art.

[0012] To solve the above technical problems, a requirements closed-loop analysis method provided by the present invention includes the following steps:

[0013] Step 1: Obtain scene data. By reading the parsed scene data file in the receiving disk array, obtain the details of the scene data. This scene data file can be, for example, in XML format, etc. It includes shooting time, resource information, payload information, cloud cover information, geographical location information, etc. Its coordinates are converted into a professional geographical data format to facilitate subsequent coordinate operations using professional algorithms. Further preferably, the format of the converted geographical data can be expressed as:

[0014] P 区域 ={"type":"Polygon","coordinates":[[[lon,lat]...]]};

[0015] Where: type represents the category; Polygon represents the area; coordinates represents the coordinates; lon represents the longitude; lat represents the latitude.

[0016] Step 2: Obtain requirements data. Import the user-specified requirements target file or vulnerability area file, and convert the coordinates of the requirements target into a professional geographical data format and store them in the corresponding system.

[0017] Preferably, the professional geographical coordinate format uses the GeoJson coordinate format.

[0018] Preferably, use the Postgis algorithm for coordinate operations to facilitate general and rapid calculation and analysis.

[0019] In addition to the above formats and algorithms, other commonly used formats and algorithms well-known in the art can also be used to achieve the same technical effects.

[0020] Step 3: Perform timed coverage analysis calculation for requirements. Record the association relationships between the requirements side and the scene data side respectively, and then perform timed coverage analysis data calculation on the association relationships uniformly to timely, completely, and dynamically count the new requirements and scene data into the coverage analysis results.

[0021] Further, when starting from the demand side, the user enters a new demand. From aspects such as the effective time of the demand, selected resources, cloud amount requirements, and target geographical location, a professional algorithm is used to calculate the intersection of the demand target and the geographical location coordinates in the data table library. In this way, the intersecting scene data is calculated, which is the associated scene data of the demand data, and is input into the database for subsequent coverage analysis calculations.

[0022] Further, when starting from the scene data side, after parsing the scene data file and obtaining detailed data, a professional spatial calculation algorithm is used to inversely search for demands that meet the requirements in terms of time, resources, cloud amount, space, etc., to form management data and input it into the database.

[0023] Further, after obtaining the associated scene data, geographical location calculations are performed between the demand target and each associated scene data. Through the remaining area after the intersection part, the remaining target after each associated scene data covers the demand target is calculated.

[0024] Further, the remaining area is calculated from the remaining target.

[0025] Further, the coverage rate, number of observations, and observation duration are calculated from the remaining area.

[0026] Preferably, a professional algorithm, such as the GeoTools algorithm, is used to calculate geographical information such as the intersection, remaining target, remaining area, and coverage rate, so as to quickly obtain accurate results.

[0027] In addition to the above algorithms, other commonly used algorithms well-known in the art can also be used for calculation to achieve the same technical effect.

[0028] Further, when dynamically recording at the demand side in step three, a separate new scene data matching logic asynchronous thread is used for processing to improve the intuitive efficiency when saving or submitting the demand.

[0029] Further, a field for determining whether statistical processing has been done is added to the demand list. Unprocessed demands are scanned through a timed analysis task, and this task only processes demands that have not been statistically processed, thus avoiding repeated operations. Each demand will only be processed once in this task, improving efficiency.

[0030] Further, when receiving scene data and performing matching, step-by-step processing is carried out. First, demands are filtered according to parameters such as satellites and time, and then the filtered demands are geographically matched to obtain the final statistical result, so as to save the most time-consuming geographical matching time in the operation.

[0031] Further, since demands are all based on future time, data matching when creating and submitting demands can be discarded. Directly relying on the associated scene data table generated when inserting scene data, the coverage analysis of demands is completed regularly to improve efficiency.

[0032] In addition, the present invention also provides a demand closed-loop analysis system, which mainly includes: a data receiving module, a data processing module, and a data generating module:

[0033] The data receiving module is used to process the scene data and demand data of the satellite, convert them into a professional format, and transmit them to the data processing module;

[0034] The data processing module includes a matching unit and a calculation unit. The matching unit is used to record and match the associated scene data of the demand and the scene data. The calculation unit is used to perform a timing coverage analysis, and transmit calculation results such as the coverage rate, the number of observations, and the observation duration to the data generating module;

[0035] The data generating module is used to output the coverage analysis result.

[0036] On the other hand, the present invention also provides a demand closed-loop analysis device, which mainly includes a processor, a memory, and a bus. The memory stores instructions that can be read by the processor; the processor is used to call the instructions in the memory to execute the demand closed-loop analysis method described above; the bus is used to transmit information between the various functional components of the computer.

[0037] Adopting the above technical solution, the present invention has the following beneficial effects:

[0038] The demand closed-loop analysis method, system, and device provided by the present invention start from two entrances of demand and scene data, perform a small amount of operations in real time to obtain a certain association relationship, and finally summarize and calculate the coverage rate, the number of observations, and the observation duration, so as to allocate the large amount of calculations at the same moment in the prior art to different moments, reduce the calculation burden on the database, thereby ensuring the calculation efficiency and reducing the pressure on the database. Description of the Drawings

[0039] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0040] Figure 1 It is a schematic diagram for explaining Step 3 of the embodiment of the present invention;

[0041] Figure 2 It is a structural diagram of the demand closed-loop analysis system of the embodiment of the present invention. Specific Embodiments

[0042] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. In addition, the terms "first", "second", "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0044] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0045] The following further explains the present invention in combination with specific implementation manners.

[0046] The demand closed-loop refers to the dynamic analysis of the completion situation of the demand within a specified time for the observation demand proposed by the user through the acquired satellite image scene data. Generally speaking, the observation targets come from the vulnerability area and specific observation areas, and there may also be multiple discrete areas. Therefore, it is necessary to complete the task jointly by multiple satellites, multiple overpasses, and multiple observations. And this process usually may not be completed in a very short time. If we need to always know the demand completion situation, it is very necessary to track the coverage shooting situation of each demand in real time, which can also provide a basis for formulating the subsequent shooting plan and adjusting the priority of the subsequent tasks. To complete this work, this patent proposes a calculation method for real-time following and calculating the demand coverage analysis situation.

[0047] The main steps of the present invention are as follows: when obtaining all satellite scene data, the conditions such as time, space, resources, and payload in these data are matched with the demand targets to be analyzed. When the scene data covers the demand, professional geographic coordinate algorithms, such as the GeoJson coordinate algorithm, are used to delete the spatial positions, and the remaining targets are obtained for coverage analysis calculation. And so on, until the target is completely covered by the scene data of the specified resources, that is, the observation of the entire demand is completed, and at the same time, the closed-loop analysis task is completed. The specific implementation steps are as follows:

[0048] 1) Obtain scene data. The details of the scene data are obtained by reading and parsing XML files in the receiving disk array, including shooting time, resource information, payload information, cloud amount information, geographical location information, etc. Its coordinates are converted into a professional data form, such as the GeoJson form, to facilitate subsequent use of professional algorithms, such as the Postgis algorithm, for coordinate operations. Its format is mainly expressed as:

[0049] P 区域 = {"type": "Polygon", "coordinates": [[[lon, lat]...]]};

[0050] Where: type represents the category; Polygon represents the area; coordinates represents the coordinates; lon represents the longitude; lat represents the latitude.

[0051] 2) Obtain demand data. Through user specification or import of vulnerability files, the coordinates of the demand targets are converted into a professional data form, such as the GeoJson form, and stored in the corresponding system;

[0052] 3) Perform demand timing coverage analysis calculation, as Figure 1 shown:

[0053] Considering that users may put forward new demands at any time, and at the same time, new data will be pushed into the scene data files at any time, we record the association relationships between demands and scene data in two directions simultaneously, and then uniformly perform timed data coverage analysis calculation on their association relationships. In this way, whether it is a newly proposed demand or newly parsed scene data, the coverage analysis results can be completely and timely counted.

[0054] Starting from the demand side, when a user enters a new demand, professional algorithms are used to calculate, such as tools like GeoTools, from aspects such as the effective time of the demand, the selected resources, cloud amount requirements, and target geographical location, to determine whether there is an intersection between the two geographical location coordinates. The specific calculation method is as follows:

[0055] Lj = La - Lb;

[0056] Among them, La represents the required target geographical location information, and Lb represents the geographical location information to be queried in the table library. In this way, the scenic data with intersections and the associated scenic data Lj that can form an association with the required data are calculated and entered into the database for subsequent coverage analysis and calculation.

[0057] In a specific embodiment, the above algorithm can be implemented through logical language:

[0058] Select st_astext(st_intersection(st_geomfromgeojson(#{locationA}),st_geomfromgeojson(locationB)))!='GEOMETRYCOLLECTION EMPTY';

[0059] Among them, locationA represents the required target geographical location information, and locationB represents the geographical location information to be queried in the table library.

[0060] Starting from the scenic data side, after obtaining detailed data by parsing the scenic data XML file, through professional algorithms such as the GeoTools algorithm, the provided spatial calculation methods are used to reverse-search for requirements that meet in terms of time, resources, cloud amount, space, etc., and form associated relationship data, which is entered into the database.

[0061] After the above steps, the associated scenic data table of all requirements and all the scenic data that can be captured by them can be obtained. Then, through this associated scenic data relationship, the coverage situation is calculated:

[0062] a) Perform geographical location calculations on the required target and each associated scenic data. By calculating the remaining area after finding the intersection part, calculate the remaining target after each scenic data covers the required target. The main calculation formula is:

[0063] Gs = Ga - Gb;

[0064] Among them, Ga is the geographical location coordinate of the target, and Gb is the geographical location coordinate of the scenic data. After calculation, the Gs coordinate of the remaining target is obtained;

[0065] In a specific embodiment, the above algorithm can be implemented through logical language:

[0066] SELECT st_asgeojson(ST_AsText(ST_Difference(st_geomfromgeojson(#{geoJsonA}),st_geomfromgeojson(#{geoJsonB}))));

[0067] Among them, geoJsonA is the target geographical location coordinate, and geoJsonB is the geographical location coordinate of the scene data. After calculation, the geoJson coordinates of the remaining targets are obtained;

[0068] b) The formula for calculating the target area is:

[0069] A = area(Gs);

[0070] It can be used to calculate the original area of the target and the area of the remaining targets (that is, 1 - remaining area / original area) to obtain the coverage rate;

[0071] In a specific embodiment, the above algorithm can be implemented through logical language: select st_area(geography(st_geomfromgeojson(#{geoJson})))

[0072] For all scene data related to this requirement, they are collected uniformly. After statistical analysis, the total number of observations and the total observation duration covered by the requirement are obtained.

[0073] In addition, as Figure 2 shown, the embodiment of the present invention also provides a demand closed-loop analysis system, which mainly includes: a data receiving module, a data processing module, and a data generating module:

[0074] The data receiving module is used to process the scene data and demand data of the satellite, convert them into a professional format, and transmit them to the data processing module;

[0075] The data processing module includes a matching unit and a calculation unit. The matching unit is used to record and match the associated scene data of the demand and the satellite scene data. The calculation unit is used to perform timed coverage analysis and transmit calculation results such as the coverage rate, the number of observations, and the observation duration to the data generating module;

[0076] The matching unit starts from the following two aspects to perform data matching:

[0077] 1. Starting from the demand side, when a user enters a new demand, from aspects such as the effective time of the demand, the selected resources, the cloud cover requirement, and the target geographical location, it can be one or more of these information and any combination form thereof. Using professional algorithms for calculation, such as tools like GeoTools, to calculate whether the two geographical location coordinates have an intersection. The specific calculation method is as follows:

[0078] Lj = La - Lb;

[0079] Among them, La represents the required target geographical location information, and Lb represents the geographical location information to be queried in the database. By this method, the scene data with intersections and the associated scene data Lj that can form an association with the required data are calculated and entered into the database for subsequent coverage analysis and calculation.

[0080] 2. Starting from the scene data side, after obtaining detailed data by parsing the scene data XML file, through professional algorithms such as the spatial calculation methods provided by the GeoTools algorithm, reverse search for requirements that match in terms of time, resources, cloud cover, space, etc., which can be one or more of these information and any combination thereof, and form associated relationship data, which is entered into the database.

[0081] After the above steps, an associated scene data table of all requirements and all scene data that can capture them can be obtained and transmitted to the calculation unit.

[0082] The calculation unit performs regular coverage analysis, and the specific steps are as follows:

[0083] a) Calculate the geographical location of the required target and each associated scene data. By finding the remaining area after the intersection, calculate the remaining target after each scene data covers the required target. The main calculation formula is:

[0084] Gs = Ga - Gb;

[0085] Where Ga is the geographical location coordinate of the target, and Gb is the geographical location coordinate of the scene data. After calculation, the Gs coordinate of the remaining target is obtained;

[0086] b) The formula statement for calculating the target area is:

[0087] A = area(Gs);

[0088] It can be used to calculate the original area of the target and the remaining target area (i.e., 1 - remaining area / original area) to obtain the coverage rate.

[0089] For all scene data related to this requirement, collect them uniformly. After regular statistical analysis, obtain the total number of observed times and the total observation duration of the requirement coverage.

[0090] The data generation module is used to output the coverage analysis result.

[0091] On the other hand, an embodiment of the present invention also provides a demand closed-loop analysis device, which mainly includes a processor, a memory, and a bus. The memory stores instructions that can be read by the processor; the processor is used to call the instructions in the memory to execute the above-mentioned demand closed-loop analysis method; the bus transmits information between the various functional components of the computer.

[0092] In another implementation manner of this solution, it can be implemented by means of a device, and the device may include corresponding modules for executing each or several steps in the above various implementation manners. Therefore, each step or several steps in the above various implementation manners can be executed by the corresponding modules, and the electronic device may include one or more of these modules. The module may be one or more hardware modules specifically configured to execute the corresponding steps, or implemented by a processor configured to execute the corresponding steps, or stored in a computer-readable medium for implementation by the processor, or implemented through a certain combination.

[0093] The device can be implemented by using a bus architecture. The bus architecture may include any number of interconnecting buses and bridges, depending on the specific application of the hardware and the overall design constraints. The bus connects various circuits including one or more processors, memories, and / or hardware modules together. The bus may also connect various other circuits such as peripheral devices, voltage regulators, power management circuits, external antennas, etc.

[0094] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Component (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, only one connecting line is used in this figure, but it does not mean that there is only one bus or one type of bus.

[0095] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. And the scope of the preferred implementation manner of this solution includes additional implementations, where the functions can be executed in a manner that is not in the order shown or discussed, including in a substantially simultaneous manner or in the reverse order according to the involved functions, which should be understood by those skilled in the art to which the implementation manner of this solution belongs. The processor executes the various methods and processes described above. For example, the method implementation manner in this solution can be implemented as a software program that is tangibly included in a machine-readable medium, such as a memory. In some implementation manners, part or all of the software program can be loaded and / or installed via the memory and / or the communication interface. When the software program is loaded into the memory and executed by the processor, one or more steps in the method described above can be executed. Alternatively, in other implementation manners, the processor can be configured to execute one of the above methods in any other appropriate way (for example, by means of firmware).

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for closed-loop analysis of requirements, characterized in that, It includes the following steps: Step 1: Obtain satellite scene data, convert its coordinates into XML format and store them; Step 2: Obtain requirement data, convert its coordinates into GeoJson format and store them; Step 3: Dynamically record and match from the requirement side and the scene data side respectively to form associated scene data, and then uniformly perform timed coverage analysis; specifically, it includes simultaneously recording the association relationship between requirements and scene data from two directions, and then uniformly performing timed data coverage analysis and calculation on their association relationship: Starting from the requirement side, when a user enters a new requirement, use the GeoTools tool to find whether there is an intersection between the coordinates of two geographical locations in terms of the effective time of the requirement, the selected resources, the cloud cover requirement, and the target geographical location. The specific calculation method is as follows: Lj = La - Lb; Where, La represents the demand target geographical location information; Lb represents the geographical location information required to be queried in the database; Lj represents the associated scene data; Starting from the scene data side, when detailed data is obtained by parsing the scene data XML file, use the spatial calculation method provided by the GeoTools algorithm to inversely find the requirements that meet the conditions in terms of effective time, selected resources, cloud cover requirement, and target geographical location, and form associated scene data and enter it into the database; After obtaining the associated scene data table of all requirements and all scene data that can be photographed, then calculate the coverage situation through this associated scene data relationship: a) Perform geographical location calculation on the demand target and each associated scene data, and calculate the remaining target after the demand target is covered by each scene data through the remaining area after finding the intersection part. The calculation formula is: Gs = Ga - Gb; Where, Ga is the target geographical location coordinate, Gb is the geographical location coordinate of the scene data, and Gs is the remaining target coordinate; b) The formula for calculating the target area A is: A = area(Gs).

2. The demand closed-loop analysis method according to claim 1, wherein The coverage analysis described in Step 3 includes calculating the coverage rate, the number of observations, and the observation duration.

3. The demand closed-loop analysis method according to claim 1, characterized in that When dynamically recording on the requirement side in Step 3, it also includes asynchronously processing the matching logic of newly opened scene data through a separate thread.

4. The demand closed-loop analysis method according to claim 1, characterized in that When obtaining requirement data in Step 2, it also includes adding a processing status flag to the requirement data, and the timed coverage analysis only scans the requirement data that has not been processed to avoid repeated operations.

5. The requirement closed-loop analysis method according to claim 1, wherein When performing matching in Step 3, it also includes performing step-by-step processing. First, filter the requirements according to the satellite and time parameters, and then perform geographical location matching.

6. The demand closed-loop analysis method according to claim 1, characterized in that When generating associated scene data in Step 3, it also includes discarding the matching and directly generating associated scene data by inserting scene data to complete the timed coverage analysis.

7. A demand closed-loop analysis system using the method described in any one of claims 1-6, characterized in that, It includes a data receiving module, a data processing module, and a data generating module: The data receiving module is used to process the scene data and requirement data of the satellite, convert the format, and transmit it to the data processing module; The data processing module includes a matching unit and a calculation unit. The matching unit is used to record and match the associated scene data of requirements and scene data, and the calculation unit is used to perform timed coverage analysis and transmit the calculation results of the coverage rate, the number of observations, and the observation duration to the data generating module; The data generating module is used to output the coverage analysis result.

8. A demand closed-loop analysis device, characterized in that The device includes a processor, a memory, and a bus. The memory stores instructions that can be read by the processor. The processor is configured to invoke the instructions in the memory to execute the demand closed-loop analysis method according to any one of claims 1 to 6. The bus connects the various functional components of the computer to transfer information.

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