CN114840139A - Hierarchical storage evaluation method for early warning detection images with high dynamic range - Google Patents
Hierarchical storage evaluation method for early warning detection images with high dynamic range Download PDFInfo
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Abstract
The invention relates to a hierarchical storage evaluation method, a system, equipment and a medium for early warning and detection images with high dynamic range, wherein the method comprises the following steps: acquiring high dynamic range early warning detection image data stored in a preset database; establishing a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes; determining a data storage standard aiming at each data storage type according to a preset division standard; and obtaining evaluation function values under different data storage standards based on the storage evaluation function. The method is visual and efficient, can adapt to fine-grained evaluation of data storage capacity of the whole life cycle of any early warning detection satellite, can effectively solve the problems of low efficiency and high cost due to extensive early warning detection image data storage management, and provides a new capacity evaluation approach for the efficient data storage management of the whole life cycle of early warning detection satellite equipment.
Description
Technical Field
The invention relates to the technical field of aerospace data storage, in particular to a hierarchical storage evaluation method, a hierarchical storage evaluation system, hierarchical storage evaluation equipment and a hierarchical storage evaluation medium for early warning and detection images with high dynamic ranges.
Background
The satellite equipment taking the space target and the missile target as sensing objects is continuously improved in load detection capacity and detection view field, high-value data generated in the processes of image acquisition, processing and object identification are continuously increased, the existing data volume in the current early warning detection field is about to reach the hundred PB level, and the satellite equipment is high in storage, management and use difficulty and cost. The current new generation satellite has the high dynamic characteristics of multiple loads, multiple modes and multiple numbers of bits, and the high-efficiency storage, use and management of the acquired high dynamic range early warning detection image can provide powerful guarantee for realizing the high-quality information generation of a target object.
The traditional early warning detection image storage mostly adopts a rough storage mode, single storage capacity maximization evaluation is generally carried out only on the basis of use scenes, firstly, data generation capacity and data transmission capacity are not considered comprehensively, secondly, the influence of a data transmission mode on the storage capacity is not considered, and thirdly, the influence of diversified data scenes such as original data, data products at all levels and intermediate data on the storage capacity is not considered. In the face of the current space target and missile target detection image processing scene, the storage, use and management efficiency of data is urgently improved by combining hierarchical storage and fine-grained evaluation.
The grading storage evaluation method for the early warning detection image with the high dynamic range is found by combining with the practical engineering application requirements, and is very necessary for providing powerful guarantee for the generation of the ground segment capacity of the satellite equipment in the early warning detection field.
Disclosure of Invention
Technical problem to be solved
In view of the above disadvantages and shortcomings of the prior art, the present invention provides a hierarchical storage evaluation method, system, device and medium for high dynamic range early warning detection images, which solves the technical problems of high difficulty and high cost in storing, managing and using business data in the early warning detection field.
(II) technical scheme
In order to achieve the purpose, the invention adopts the main technical scheme that:
in a first aspect, an embodiment of the present invention provides a hierarchical storage and evaluation method for a high dynamic range early warning detection image, including:
acquiring high dynamic range early warning detection image data stored in a preset database;
establishing a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes;
determining a data storage standard aiming at each data storage type according to a preset division standard;
obtaining evaluation function values under different data storage standards based on the storage evaluation function;
the data generation parameters comprise data generation frequency, data rate and unit data quantity, and the data transmission parameters comprise a plurality of transmission modes and transmission adjustment coefficients.
Optionally, the constructing a storage evaluation function according to the data generation parameters and the data transmission parameters of the high dynamic range early warning detection image data and in combination with the data storage types corresponding to different early warning detection service scenes comprises:
and constructing an evaluation function basic equation according to the data generation frequency, the data rate and the unit data quantity of the high dynamic range early warning detection image:
f(f,v,P,R,γ,t)＝min(v,f*R)*t (1)
determining a data transmission mode and a transmission adjustment coefficient according to the current high dynamic range early warning detection load working mode and the image generation mode, and constructing an evaluation function equation after considering the transmission mode:
determining a data storage type and a data storage type adjustment coefficient according to different early warning detection service scenes, and constructing an evaluation function equation after the data storage type is considered;
in the formula (1), f is data generation frequency, f is greater than 0 and less than or equal to 10, v is data transmission rate under the condition that data transmission indicates the front, R is unit data volume, namely R is data volume generated in 1/f of data generation unit time, and t is time. In formula (2), P is a data transmission mode; in the formula (3), gamma j The coefficients are adjusted for the data storage type.
Optionally, the data transmission mode satisfies the following formula:
wherein the data transmission mode comprises: a transmission holding mode, a scanning mode, an even transmission mode and a fixed transmission mode;
at p i When the data transmission mode is 1, the data transmission mode is a transmission sustaining mode;
at p i ＝1-τ 1 The data transmission mode is a scanning transmission mode, Z is a satellite orbit period, and tau 1 Is a scan-off period within the satellite orbit period Z;
at p i ＝ωτ 2 The data transmission mode is a coupling mode, omega is the transmission times in the satellite orbit period Z, and tau 2 A single transmission active time;
at p i ＝τ 3 /Z，The data transmission mode is a fixed transmission mode, tau 3 Is the effective transmission time within the satellite orbit period Z.
Optionally, the data storage types are divided into: control data class gamma 1 Space segment processing data class gamma 2 Ground segment raw data class gamma 3 Ground section product data class gamma of all levels 4 Surface section intermediate process data class gamma 5 And management data class gamma 6 And the status data class gamma 7 ；
The control class data γ 1 The value range is [00.1,0.06 ]]；
The spatial segment processes data class γ 2 The value range is 0.05;
said ground segment raw data class γ 3 The value range is 1;
the ground section product data of each level is gamma 4 The value range is 3;
said ground segment intermediate process data class γ 5 The value range is [1,3 ]]；
The management data class γ 6 The value range is [0.005,0.01 ]]；
Said status data class γ 7 The value range is [0.005,0.01 ]]。
Optionally, determining the data storage standard for each data storage type according to the preset division standard includes:
dividing the high dynamic range early warning detection image data into:
the control data class is high-value structured data, the space segment processing data class is high-value unstructured data, the ground segment original data class is high-value unstructured data, the ground segment product data classes are other unstructured data, the ground segment middle process data class is low-value unstructured data, the management data class is low-value structured data, and the state data class is low-value structured data.
Optionally, obtaining evaluation function values under different data storage standards based on the storage evaluation function includes:
subdividing the storage evaluation function into the following equations according to the data storage criteria:
high-value structured data evaluation function equation:
f 1 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 1 (5)
high-value unstructured data evaluation function equation:
f 2 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 2 +∑(min(v,f*R)*t*P i )*γ 3 (6)
low-value structured data evaluation function equation:
f 3 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 6 +∑(min(v,f*R)*t*P i )*γ 7 (7)
low-value unstructured data evaluation function equation:
f 4 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 5 (8)
other unstructured data evaluate function equations:
f 5 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 4 (9)
and respectively solving the formulas (5) to (9) to obtain evaluation function values under different data storage standards.
Optionally, after obtaining evaluation function values under different data storage standards based on the storage evaluation function, the method further includes:
and carrying out hierarchical optimization storage on the high dynamic range early warning detection image data stored in a preset database according to the evaluation function value.
In a second aspect, an embodiment of the present invention provides a hierarchical storage and evaluation system for a high dynamic range early warning detection image, including:
the data acquisition module is used for acquiring and storing high dynamic range early warning detection image data in a preset database;
the evaluation function building module is used for building a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes;
the classification standard determining module is used for determining a data storage standard aiming at each data storage type according to a preset division standard;
the evaluation value solving module is used for obtaining evaluation function values under different data storage standards based on the storage evaluation function;
wherein the data generation parameters comprise data generation frequency, data transmission rate and unit data amount; the data transmission parameters include a plurality of transmission modes and transmission adjustment coefficients.
In a third aspect, an embodiment of the present invention provides a hierarchical storage and evaluation device for a high dynamic range early warning detection image, including: at least one database; and a memory communicatively coupled to the at least one database; wherein the memory stores instructions executable by the at least one database to enable the at least one database to perform a high dynamic range early warning detection image oriented hierarchical storage assessment method as described above.
In a fourth aspect, embodiments of the present invention provide a computer-readable medium, on which computer-executable instructions are stored, and when executed by a processor, the computer-readable medium implements a hierarchical storage evaluation method for high dynamic range early warning detection images as described above.
(III) advantageous effects
The invention has the beneficial effects that: the method is visual and efficient, can be suitable for fine-grained evaluation of the data storage capacity of any early warning detection satellite in the whole life cycle, can effectively solve the problems of low efficiency and high cost caused by extensive data storage management of the early warning detection image, and provides a new capacity evaluation way for efficient data storage management of the whole life cycle of early warning detection satellite equipment.
Drawings
Fig. 1 is a schematic flowchart of a hierarchical storage evaluation method for a high dynamic range early warning detection image according to an embodiment of the present invention;
fig. 2 is a schematic composition diagram of a hierarchical storage evaluation system for high dynamic range early warning detection images according to an embodiment of the present invention.
[ instruction of reference ]
100: a hierarchical storage evaluation system;
110: a data acquisition module;
120: an evaluation function construction module;
130: a classification standard determination module;
140: and an evaluation value solving module.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
As shown in fig. 1, a hierarchical storage and evaluation method for a high dynamic range early warning detection image according to an embodiment of the present invention includes: firstly, acquiring high dynamic range early warning detection image data stored in a preset database; secondly, establishing a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes; then, determining a data storage standard aiming at each data storage type according to a preset division standard; and finally, obtaining evaluation function values under different data storage standards based on the storage evaluation function.
The method is visual and efficient, can be suitable for fine-grained evaluation of the data storage capacity of any early warning detection satellite in the whole life cycle, can effectively solve the problems of low efficiency and high cost of data storage management of the early warning detection image, and provides a new capacity evaluation way for efficient data storage management of the whole life cycle of early warning detection satellite equipment.
In order to better understand the above technical solution, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Specifically, the invention provides a high dynamic range early warning detection image oriented hierarchical storage evaluation method, which comprises the following steps:
and S1, acquiring the high dynamic range early warning detection image data stored in a preset database.
And S2, establishing a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes.
The data generation parameters comprise data generation frequency f, data rate v and unit data quantity R; the data transmission parameters include a plurality of transmission modes and transmission adjustment coefficients.
Further, step S2 includes:
according to the data generation frequency, the data rate and the unit data quantity of the early warning detection image with the high dynamic range, an evaluation function basic equation is constructed:
f(f,v,P,R,γ,t)＝min(v,f*R)*t (1)
the high dynamic range early warning detection load working modes comprise a scanning mode, a regional staring mode, a scanning stopping mode and the like, a pass holding and fixed pass mode is often adopted as a data transmission mode in the scanning working mode, a coupling mode is often adopted as the data transmission mode in the regional staring mode, and a scanning mode is often adopted as the data transmission mode in the scanning stopping mode.
Determining a data transmission mode p and a transmission adjustment coefficient p according to the current high dynamic range early warning detection load working mode and the image generation mode i And constructing an evaluation function equation after considering the transmission mode:
determining a data storage type and a data storage type adjustment coefficient according to different early warning detection service scenes, and constructing an evaluation function equation after the data storage type is considered;
in the formula (1), f is data generation frequency, f is more than 0 and less than or equal to 10, f can be any positive real number, and is an integer between 1 and 10 in most scenes, and is also a decimal number such as 0.2, 0.5 and the like; v is the rate of data transmission under the premise of data transmission indication, R is unit data volume, namely R is the data volume generated in the unit time 1/f of data generation; in formula (2), P is a data transmission mode; in the formula (3), gamma j To adjust the coefficients.
Further, the data transmission mode satisfies the following formula:
wherein, the data transmission mode includes: a sustained transmission mode, a sweep transmission mode, an even transmission mode and a fixed transmission mode. Preferably, each of the above transmission modes is determined to be partially or fully used according to a specific satellite load detection mode after one storage task is repeated.
At p i When the data transmission mode is 1, the data transmission mode is a transmission sustaining mode;
at p i ＝1-τ 1 The data transmission mode is a scanning transmission mode, and Z is satellitePeriod of the satellite orbit, tau 1 Is a scan-off period within the satellite orbit period Z;
at p i ＝ωτ 2 The data transmission mode is a coupling mode, omega is the transmission times in the satellite orbit period Z, and tau 2 A single transmission active time;
at p i ＝τ 3 Z, the data transmission mode is a fixed transmission mode, tau 3 Is the effective transmission time within the satellite orbit period Z.
The implementation process in the fixed transmission mode is as follows:
1) determining values of f, v and R, wherein f is 10, v is 100MB/s, and R is 200 MB;
2) assuming that the data transmission mode is a single constant transmission mode, the track period is 90 minutes, the constant transmission time is 5 minutes, and the calculation is performed according to the formula (4), and the value of P is 1/18.
3) t is calculated by taking 3 years and combining the formula (5) to the formula (9) to obtain f 1 ＝63.07TB，f 2 ＝1103.76TB，f 3 ＝21.02TB，f 4 ＝1576.8TB，f 5 ＝3153.6TB。
Further, as shown in table 1, the data storage types may be divided into: control data class, space section processing data class, ground section original data class, ground section product data class, ground section middle process data class, management data class and state data class;
TABLE 1 upsilon j Value-taking meter
The control data is obtained mainly according to the type and quantity of the satellite load, when the load quantity is less than or equal to 3, the gamma is 1 The value is 0.01; when the load number is more than 3 and less than or equal to 6, gamma 1 The value is 0.02; when the load number is more than 6 and less than or equal to 12, gamma 1 The value is 0.05; when 12 < the number of loads, gamma 1 The value is 0.06.
The space section processing data mainly comprises data which are processed on the satellite and then transmitted to the ground, and the data are processed on the satelliteThe data volume of the later target point is smaller, and the current gamma is 2 The value was 0.05. The ground segment original data class data is mainly the original detection data received on the ground, gamma 3 The value is 1. The ground section product data at all levels are mainly data, gamma, generated by processing according to the requirements of three-level data products 4 The value is 3.
The middle process data of the ground section is mainly process data generated in the software running process, the influence of software development capacity is large, but the data product quantity cannot be exceeded, the data product quantity is larger than the original data quantity, and the value is between the data product quantity and the original data quantity. Gamma when task is newer 5 Value 3, which is gradually reduced along with the improvement of the maturity of the same type of tasks, and the prior early warning and detection image processing field gamma 5 The value is 1.5.
The management data and the state data are auxiliary data and closely related to software engineering degree, software management requirements, software operation and maintenance requirements and the like, the higher the requirement is, the higher the value is, and the gamma in the field of early warning detection image processing at present 6 、γ 7 All values are 0.01.
And S3, determining data storage standards for the data storage types according to preset division standards.
Then, according to the principles of temporary storage of low-value data, permanent storage of high-value data and storage of other data as required, a hierarchical data storage standard is constructed in combination with data storage types, the specific data storage standard can be flexibly adjusted according to actual project requirements, and various types of data hierarchical standards of the high-dynamic-range early-warning detection image are formulated as shown in table 2. The evaluation function equation can be further refined according to the classification criteria.
TABLE 2 hierarchical storage criteria for early warning detection image data
And S4, obtaining evaluation function values under different data storage standards based on the storage evaluation function.
Step S4 includes:
based on a multi-level data storage standard, the storage evaluation function is subdivided into the following equations:
high-value structured data evaluation function equation:
f 1 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 1 (5)
high-value unstructured data evaluation function equation:
f 2 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 2 +∑(min(v,f*R)*t*P i )*γ 3 (6)
low-value structured data evaluation function equation:
f 3 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 6 +∑(min(v,f*R)*t*P i )*γ 7 (7)
low-value unstructured data evaluation function equation:
f 4 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 5 (8)
other unstructured data evaluate function equations:
f 5 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 4 (9)
and (5) solving the formulas (5) to (9) respectively to obtain evaluation function values under different data storage standards. By applying the method, the capability of producing various data in the whole life cycle of the satellite system can be evaluated according to the constraints from the formula (5) to the formula (9), and the storage equipment construction in ground segment related engineering can be developed according to the capability.
Further, after step S4, the method further includes: and carrying out hierarchical optimization storage on the high dynamic range early warning detection image data stored in a preset database according to the evaluation function value. Namely, the existing storage, use and management modes are optimized according to the evaluation function values.
As shown in fig. 2, an embodiment of the present invention further provides a hierarchical storage and evaluation system 100 for a high dynamic range early warning detection image, including:
the data obtaining module 110 is configured to obtain and obtain high dynamic range early warning detection image data stored in a preset database.
The evaluation function constructing module 120 is configured to construct a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes. The data generation parameters comprise data generation frequency, data transmission rate and unit data quantity; the data transmission parameters include a plurality of transmission modes and transmission adjustment coefficients.
A grading standard determining module 130, configured to determine, according to a preset division standard, a data storage standard for each data storage type.
And the evaluation value solving module 140 is configured to obtain evaluation function values under different data storage standards based on the storage evaluation function.
Since the system/apparatus described in the above embodiments of the present invention is a system/apparatus used for implementing the method of the above embodiments of the present invention, a person skilled in the art can understand the specific structure and modification of the system/apparatus based on the method described in the above embodiments of the present invention, and thus the detailed description is omitted here. All systems/devices adopted by the methods of the above embodiments of the present invention are within the intended scope of the present invention.
In addition, the invention also provides a hierarchical storage evaluation device for the early warning detection image with high dynamic range, which comprises: at least one database; and a memory communicatively coupled to the at least one database; the memory stores instructions executable by the at least one database, so that the at least one database can execute the high dynamic range early warning detection image oriented hierarchical storage evaluation method.
Also, an embodiment of the present invention provides a computer-readable medium, on which computer-executable instructions are stored, where the computer-executable instructions, when executed by a processor, implement the above hierarchical storage evaluation method for high dynamic range early warning detection images.
In summary, the present invention discloses a hierarchical storage evaluation method, system, device and medium for high dynamic range early warning detection images, which mainly comprises the following steps: analyzing a data transmission mode according to a load working mode, and solving a data transmission adjustment coefficient according to a formula (2) by combining a satellite orbit period; analyzing and defining a data grading standard, and determining a data storage type adjustment coefficient; and solving the evaluation function value of the importation data standard according to the formulas (5) to (9).
The method comprehensively considers the influence of the data generation capacity and the data transmission capacity of the satellite load on data storage, and analyzes and constructs a storage evaluation function basic equation based on known basic parameters. And the data transmission mode is defined by combining the depth with the load working mode, the data transmission adjustment coefficients under different transmission modes are given, the influence of different data transmission adjustment coefficients on data storage is fully considered, and the influence of the data storage capacity evaluation process on the load working mode, the data transmission mode and the like which are not fully considered can be effectively compensated. Moreover, the data generation scene in the whole process of image acquisition, processing, object recognition and knowledge base construction is considered, the data storage type related to the early warning detection image with the high dynamic range is basically solidified, the adjustment coefficient of the data storage type of the satellite system in the whole life cycle is analyzed and determined, and the influence of the data storage capacity evaluation process on the data generation scene and the data storage type is effectively compensated. Furthermore, by formulating a data grading standard, grading storage models of different value data are further refined, and management and use are more efficient.
Therefore, the scheme of the invention is very important for developing the grading storage evaluation for the early warning and detection image with the high dynamic range, and can provide support for improving the data management efficiency of the whole life cycle of the satellite system, provide evaluation basis for reducing the storage cost of the low-value data part, and provide support for making the use and storage strategy of the high-value data and improving the storage efficiency.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third and the like are for convenience only and do not denote any order. These words are to be understood as part of the name of the component.
Furthermore, it should be noted that in the description of the present specification, the description of the term "one embodiment", "some embodiments", "examples", "specific examples" or "some examples", etc., means that a specific feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, the claims should be construed to include preferred embodiments and all changes and modifications that fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include such modifications and variations.
Claims (10)
1. A hierarchical storage evaluation method for early warning detection images with high dynamic range is characterized by comprising the following steps:
acquiring high dynamic range early warning detection image data stored in a preset database;
establishing a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes;
determining a data storage standard aiming at each data storage type according to a preset division standard;
obtaining evaluation function values under different data storage standards based on the storage evaluation function;
the data generation parameters comprise data generation frequency, data rate and unit data quantity, and the data transmission parameters comprise a plurality of transmission modes and transmission adjustment coefficients.
2. The high-dynamic-range early warning and detection image-oriented hierarchical storage evaluation method as claimed in claim 1, wherein the step of constructing a storage evaluation function according to data generation parameters and data transmission parameters of the high-dynamic-range early warning and detection image data and in combination with data storage types corresponding to different early warning and detection service scenes comprises:
and constructing an evaluation function basic equation according to the data generation frequency, the data rate and the unit data quantity of the high dynamic range early warning detection image:
f(f,v,P,R,γ,t)＝min(v,f*R)*t (1)
determining a data transmission mode and a transmission adjustment coefficient according to the current high dynamic range early warning detection load working mode and the image generation mode, and constructing an evaluation function equation after considering the transmission mode:
determining a data storage type and a data storage type adjustment coefficient according to different early warning detection service scenes, and constructing an evaluation function equation after the data storage type is considered;
in the formula (1), f is data generation frequency, f is more than 0 and less than or equal to 10, v is the rate of data transmission under the condition that data transmission indicates the front, R is unit data volume, namely R is the data volume generated in the unit time 1/f of data generation, and t is time; in formula (2), P is a data transmission mode; in the formula (3), gamma j The coefficients are adjusted for the data storage type.
3. The high-dynamic-range early-warning detection-image-oriented hierarchical storage evaluation method according to claim 2, wherein the data transmission mode satisfies the following formula:
wherein the data transmission mode comprises: a transmission holding mode, a scanning mode, an even transmission mode and a fixed transmission mode;
at p i When the data transmission mode is 1, the data transmission mode is a transmission sustaining mode;
at p i ＝1-τ 1 The data transmission mode is a scanning transmission mode, Z is a satellite orbit period, and tau 1 Is a scan-off period within the satellite orbit period Z;
at p i ＝ωτ 2 The data transmission mode is a coupling mode, omega is the transmission times in the satellite orbit period Z, and tau 2 A single transmission active time;
at p i ＝τ 3 Z, the data transmission mode is a fixed transmission mode, tau 3 Is the effective transmission time within the satellite orbit period Z.
4. The high-dynamic-range early warning detection image-oriented hierarchical storage evaluation method according to claim 2, wherein the data storage types are divided into: control data class gamma 1 Space segment processing data class gamma 2 Ground segment raw data class gamma 3 Ground section product data class gamma of all levels 4 Surface section intermediate process data class gamma 5 And management data class gamma 6 And the status data class γ 7 ；
The control class data γ 1 The value range is [00.1,0.06 ]]；
The spatial segment processes data class γ 2 The value range is 0.05;
said ground segment raw data class γ 3 The value range is 1;
the ground section product data of each level is gamma 4 The value range is 3;
said ground segment intermediate process data class γ 5 The value range is [1,3 ]]；
The management data class γ 6 The value range is [0.005,0.01 ]]；
The status data class γ 7 The value range is [0.005,0.01 ]]。
5. The high-dynamic-range early-warning detection-image-oriented hierarchical storage evaluation method according to claim 4, wherein determining the data storage standard for each data storage type according to a preset division standard comprises:
dividing the high dynamic range early warning detection image data into:
the control data class is high-value structured data, the space segment processing data class is high-value unstructured data, the ground segment original data class is high-value unstructured data, the ground segment product data classes are other unstructured data, the ground segment middle process data class is low-value unstructured data, the management data class is low-value structured data, and the state data class is low-value structured data.
6. The high-dynamic-range early-warning detection-image-oriented hierarchical storage evaluation method according to claim 5, wherein obtaining evaluation function values under different data storage standards based on the storage evaluation function comprises:
subdividing the storage evaluation function into the following equations according to the data storage criteria:
high-value structured data evaluation function equation:
f 1 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 1 (5)
high-value unstructured data evaluation function equation:
f 2 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 2 +∑(min(v,f*R)*t*P i )*γ 3 (6)
low-value structured data evaluation function equation:
f 3 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 6 +∑(min(v,f*R)*t*P i )*γ 7 (7)
low-value unstructured data evaluation function equation:
f 4 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 5 (8)
other unstructured data evaluate function equations:
f 5 (f,v,P,R,γ,t)＝∑(min(v,f*R)*t*P i )*γ 4 (9)
and (4) respectively solving the formulas (5) to (9) to obtain evaluation function values under different data storage standards.
7. The hierarchical storage evaluation system for the early warning and detection image with high dynamic range as claimed in claim 1, further comprising, after obtaining evaluation function values under different data storage standards based on the storage evaluation function:
and carrying out hierarchical optimization storage on the high dynamic range early warning detection image data stored in a preset database according to the evaluation function value.
8. A hierarchical storage evaluation system for high dynamic range early warning detection images, comprising:
the data acquisition module is used for acquiring and storing high dynamic range early warning detection image data in a preset database;
the evaluation function building module is used for building a storage evaluation function according to data generation parameters and data transmission parameters of the high dynamic range early warning detection image data and in combination with data storage types corresponding to different early warning detection service scenes;
the classification standard determining module is used for determining a data storage standard aiming at each data storage type according to a preset division standard;
the evaluation value solving module is used for obtaining evaluation function values under different data storage standards based on the storage evaluation function;
wherein the data generation parameters comprise data generation frequency, data transmission rate and unit data amount; the data transmission parameters include a plurality of transmission modes and transmission adjustment coefficients.
9. A hierarchical storage evaluation device for high dynamic range early warning detection images, comprising:
at least one database;
and a memory communicatively coupled to the at least one database;
wherein the memory stores instructions executable by the at least one database to enable the at least one database to perform a method of hierarchical storage evaluation of high dynamic range early warning detection images as claimed in any one of claims 1 to 7.
10. A computer readable medium having stored thereon computer executable instructions, which when executed by a processor, implement a method of hierarchical storage evaluation for high dynamic range early warning detection images as claimed in any one of claims 1 to 7.
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