CN118171825B - Element analysis method for influencing space remote sensing effect - Google Patents
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Abstract
An element analysis method for influencing a space remote sensing effect, comprising the following steps: the remote sensing task workflow abstracts S110, the influencing element analysis flow design S120, the influencing element comprehensive collection construction S130 and the influencing element analysis and association construction S140. The invention can acquire related data along with each remote sensing flow observation, analyzes the elements influencing the remote sensing effect, is more objective and real, analyzes the elements influencing the final effect by a new visual angle, and provides a new thought for the evaluation of the remote sensing effect.
Description
Technical Field
The invention relates to the technical field of space remote sensing, in particular to an element analysis method for influencing the space remote sensing effect.
Background
The space remote sensing is an effective means for rapidly acquiring the surface information, has the advantages of long term, repeatability, wide range, no national boundary limitation and the like, and has wide application in the aspects of search rescue, disaster monitoring and the like. However, with the rapid development of the space remote sensing technology, the number of satellites in orbit is increased, the working mechanism is diversified, the sensor load capacity is diversified, the data transmission link is multilevel, the remote sensing product generation process is intelligent, and the like, so that great opportunities are brought to the improvement of the remote sensing effect, and meanwhile, great challenges are brought to the evaluation of the remote sensing effect.
In the prior art, effect analysis in a space remote sensing system is mainly started from the view angles of the performance and the capability of the satellite system, analysis forms comprise factory testing errors, system errors, random errors, positioning accuracy, time delay and the like, analysis objects are independently developed aiming at related system platforms and remote sensing objects, analysis and chain-type association analysis aiming at remote sensing whole flow development are lacking, and influences caused by multi-source elements caused by environments, platforms, loads, communication, objects and the like cannot be comprehensively and accurately analyzed.
Therefore, how to overcome the defects, the problems that the existing space remote sensing related analysis works are single-level and uncorrelated, only can perform local analysis and give a single analysis conclusion are solved, and the method is a technical problem to be solved in the prior art.
The design method of the space remote sensing effect influence element analysis flow is provided for providing an effective means for finally influencing the space remote sensing product effect analysis and the exploration of the action mechanism of the relevant element.
Disclosure of Invention
The invention aims to provide an element analysis method for influencing the remote sensing effect of spaceflight, which establishes the influence element analysis of independence, links and multiple links on the scale of the remote sensing process, realizes the multi-source element analysis for influencing the remote sensing effect by utilizing methods such as abstract modeling, mathematical analysis and the like of the remote sensing process, provides an effective means for the effect analysis of a final spaceflight remote sensing product and the exploration of the action mechanism of the influence element, and solves the problems of single-level, uncorrelated and only partial analysis and single analysis conclusion in the existing related analysis work of the spaceflight remote sensing.
To achieve the purpose, the invention adopts the following technical scheme:
An element analysis method for influencing the aerospace remote sensing effect comprises the following steps:
remote sensing task workflow abstraction step S110:
Analyzing the implementation process for a specific task facing to space remote sensing, and abstracting to obtain a remote sensing task workflow meeting analysis requirements;
Impact element analysis flow design step S120:
Determining an analysis object and an analysis view angle of demand analysis facing to a specific effect, performing relation mapping from a remote sensing process to an analysis process, and considering influence elements of all links in the remote sensing process;
influence element comprehensive set construction step S130:
according to the remote sensing basic knowledge and subject expert knowledge, constructing an influence element comprehensive set by combining a specific scene, formulating a mapping format, supplementing mapping data and constructing an influence element-remote sensing effect mapping set;
impact element analysis and association construction step S140:
And carrying out data preprocessing on the influence elements, carrying out relevance analysis on the influence elements, adjusting and optimizing the influence elements to obtain a preliminary influence element-remote sensing effect mapping set and a preliminary mapping relevance graph of the influence elements-remote sensing effect, and carrying out iterative analysis to obtain a final mapping relevance graph of the optimized influence elements-remote sensing effect.
Optionally, the remote sensing task workflow in the remote sensing task workflow abstraction step S110 includes: demand analysis, resource analysis, scheme design, instruction uploading, remote sensing imaging, data downloading, data automation, manual processing and result issuing.
Optionally, the remote sensing task workflow further comprises resource window allocation and task coordination planning.
Optionally, in the influencing element analysis flow design step S120,
Mapping modeling is carried out on the remote sensing process and the analysis process, specific task work links are synthesized, and multi-source elements influencing the remote sensing effect are identified.
Optionally, in step S120, the influencing elements of part of the working links can be ignored for the task workflow of the specific task remote sensing task.
Alternatively, in step S130,
The construction of the comprehensive set of influencing elements specifically comprises the following steps:
1) Through analyzing the space remote sensing flow under the general task, traversing the influence elements in the whole process, and constructing a basic complete set of the influence elements;
2) From the perspective of remote sensing effect, an influence element professional basic set oriented to a specific means platform is constructed through the conclusion of expert knowledge in the subject field;
3) Integrating, carding and cutting the influence element basic complete set and the influence element professional basic set to obtain a single-platform single-means influence element set;
4) Logic analysis is carried out according to the simulation data and the actual measurement data, or hidden influence elements are found through comparison of the simulation data and the actual data, so that a single-platform single-means influence element set is enriched and perfected;
5) If the remote sensing task is cooperatively executed by multiple satellites, determining platform means including satellite types and quantity by combining specific scenes and application requirements, and constructing a specific scene-oriented comprehensive set of influence elements including single-platform multi-means, multi-platform single-means and multi-platform multi-means.
Alternatively, in step S130,
The construction of the influence element-remote sensing effect mapping set specifically comprises the following steps:
1) Preparing a mapping format, wherein the mapping format is stored and presented in the form of a graph, a table and a matrix;
2) And (3) complementing the mapping data, complementing the missing data corresponding to the influence factors by a simulation means, wherein the data generation means comprises simulation and artificial inversion, and intelligent algorithm inversion based on the remote sensing effect.
Optionally, step S140 specifically includes:
The method comprises the following two substeps:
1) Impact element action analysis: firstly, carrying out influence element normalization processing, in particular to hierarchical discrete quantization processing; then, the influence element correlation analysis is carried out, and the utilization type Solving to obtain influence coefficients among the influence elements; then carrying out influence element integration optimization, calculating to obtain the quantitative weight of each element, removing the elements below the weight threshold after analyzing the requirement granularity evaluation, merging the strongly related influence elements, merging or deleting the intermediate influence elements through priori knowledge to obtain a final key influence element set,
Wherein x1 and x2 are influencing elements;
2) Influence element association diagram construction: obtaining a mapping set of the influence element and the remote sensing effect and a mapping association diagram of the influence element and the remote sensing effect preliminarily according to the analysis, and further checking through logic analysis and relation analysis; and combining more influence element data, performing iterative optimization with robustness as a target on the associated graph, enabling the element relationships and the influence coefficients to tend to be consistent and converged, obtaining a final mapping associated graph of the influence element-remote sensing effect, and completing the whole analysis flow if the effect analysis requirement is met.
The invention further discloses a storage medium for storing computer executable instructions which, when executed by a processor, perform the above-described element analysis method for influencing the remote sensing effect of space.
The invention has the following advantages:
(1) By adopting a concomitant and formative analysis method, a remote sensing flow model with different links and stages is constructed through abstraction, each link is accompanied by observation and collection of relevant data, and analysis is carried out aiming at elements influencing remote sensing effect, so that the method is more objective and real, and a systematic, scientific, interpretable and quantifiable influence element analysis means is provided for the space remote sensing process of complex objects influencing the elements.
(2) The expert knowledge and the mathematical method are combined, the influence elements and the association relation thereof are analyzed, and the method has strong realizability and scene applicability.
(3) The method has the advantages that the category of measuring the effect of the remote sensing product by completely predicting the load performance and the capacity of the platform in the traditional method is jumped out, and a way for analyzing and measuring the remote sensing effect through simulating an objective flow is provided, namely, the method for analyzing the remote sensing effect by analyzing and calculating the influence factors in the flow is provided.
Drawings
FIG. 1 is a flow chart of a method of element analysis for affecting a remote sensing effect of space in accordance with a specific embodiment of the present invention;
FIG. 2 is an abstract and impact element analysis flow of a satellite remote sensing flow under specific tasks according to an embodiment of the invention;
FIG. 3 is a flow chart of remotely sensing an implementation procedure according to another embodiment of the present invention;
FIG. 4 is a map correlation of impact elements versus remote sensing effect preliminary in accordance with an embodiment of the present invention;
Fig. 5 is a final map correlation of optimized impact elements to remote sensing effects according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
The invention mainly comprises the following steps: and performing abstract construction of a remote sensing process model of a sub-link stage by stage, comprehensively obtaining an influence element set from different angles including elements such as a platform, expert knowledge, a task platform and means according to the process analysis under a specific task and an analysis view, constructing an influence element-remote sensing effect mapping set, analyzing the influence element, and performing iterative optimization to finally obtain an influence element-remote sensing effect mapping relation diagram. The invention can acquire related data along with each remote sensing flow observation, analyzes the elements influencing the remote sensing effect, is more objective and real, analyzes the elements influencing the final effect by a new visual angle, and provides a new thought for the evaluation of the remote sensing effect.
Specifically, referring to fig. 1, a flowchart of an element analysis method for influencing the remote sensing effect of space according to the present invention is shown, including the following steps:
remote sensing task workflow abstraction step S110:
The implementation process is analyzed for the specific task of the space remote sensing, and the remote sensing task workflow meeting the analysis requirement is abstracted.
The invention is a multisource influence element analysis method for space remote sensing effect analysis, so that priori knowledge is firstly utilized to abstract the space remote sensing flow, and a foundation is laid for the next influence element analysis, analysis points, analysis objects, analysis view angles and influence elements.
In a specific embodiment, the remote sensing task workflow includes: the method comprises eight links of demand analysis, resource analysis, scheme design, instruction uploading, remote sensing imaging, data downloading, data automation and manual processing, result issuing and the like.
Specifically, in some remote sensing tasks with more tasks, the workflow also comprises resource window allocation and task coordination planning, and the next level of decomposition with finer granularity can be performed according to the specific tasks.
Impact element analysis flow design step S120:
The method mainly comprises the following steps: modeling is performed on the process of analyzing the influencing elements corresponding to the above working flow abstract step S110 of the remote sensing task, so as to clarify what process the influencing elements with different effects should follow under different remote sensing tasks.
Comprising the following steps: and determining an analysis object and an analysis view angle of demand analysis facing to a specific effect, performing relation mapping from a remote sensing process to an analysis process, and considering influence elements of all links in the remote sensing process.
For an analysis object and an analysis view angle which need to be analyzed, under different tasks and different research objects, analysis is needed from different view angles, for example, in a remote sensing task of checking the number of rare trees in a forest zone, the remote sensing identification effect of the tree species is the analysis object, the identification accuracy is the analysis view angle, and the factors influencing the identification accuracy are further researched; in the remote sensing task of determining the position of a certain building, the analysis object is the position of the building, the visual angle is positioning accuracy, and the influence element analysis is further performed by combining a positioning mechanism.
For the relation mapping from the remote sensing process to the analysis process, the biggest difference of the conventional analysis process is that the influence element analysis is carried out on the space remote sensing effect in the concomitance and formative view, and the summary analysis is not carried out on the result only, or the predictive analysis is carried out only from the view of formulas or principles.
In an alternative embodiment, mapping modeling can be performed on the remote sensing process and the analysis process, specific task work links are synthesized, and multi-source elements influencing the remote sensing effect are identified, wherein the remote sensing effect comprises identification precision, positioning accuracy and the like.
Referring to fig. 2, taking a remote sensing identification task of a certain visible light imaging satellite on a certain forest potential fire vegetation as an example, an analysis object is a vegetation identification effect of the certain area, an analysis view angle is identification accuracy, and multi-source elements influencing the identification remote sensing effect in links such as remote sensing, data transmission, processing analysis and the like are analyzed based on a corresponding satellite remote sensing process. The influence element analysis flow for the space remote sensing effect is the influence element analysis of analysis flow frame design, resource influence element analysis, scheme design influence element analysis and data generation and processing links.
Wherein the analysis flow framework design comprises: determining the subsequent analysis specific steps according to specific tasks, such as designing a positioning task aiming at a satellite positioning mechanism, distinguishing on-board preprocessing, complete ground processing and the like aiming at the task emergency degree and platform loading capacity of the recognition task.
The resource impact element analysis includes: in-orbit satellite response satellite meets the actual task requirement, whether the health condition is in a higher robustness range and the like.
The solution design influence element analysis comprises the following steps: for example, the remote sensing of targets in a large original forest requires the high-orbit satellite to guide first and then the low-orbit satellite to generate a clearer image due to the large-scale searching.
The influence element analysis of the data generation and processing link comprises the following steps: because influence element coupling can occur according to flow division, the influence element analysis logic of different objects of a platform, a load, data processing, a target state and an environment is adopted, and the targets appear in the links of data automation and manual processing.
The instruction uploading process is related to the satellite and related equipment states, and once uploading cannot be completed, the instruction uploading process can be obviously found, so that the elements are not considered; the effect is also negligible since the results are generally reported to whom.
Therefore, in step S120, the influence elements of a part of the work links can be ignored for the task-specific remote sensing task workflow.
The method is different from the effect analysis method in the processes of equipment development, test experiment, numerical simulation and the like in the past, is not a summary analysis of existing data and information, is not a possibility prediction of future performance trend, and is a concomitant and formative analysis method.
Influence element comprehensive set construction step S130:
according to the remote sensing basic knowledge and subject expert knowledge, an influence element comprehensive set is built by combining specific scenes, a mapping format is formulated, mapping data are supplemented, and an influence element-remote sensing effect mapping set is built.
The method comprises the steps of synthesizing different angles, comprehensively obtaining an influence element set by elements such as a platform, expert knowledge, a task platform and means, constructing an influence element-remote sensing effect mapping set, and facilitating the analysis of the influence elements in the next step.
Specifically, the construction of the comprehensive set of influencing elements specifically includes:
1) Through analyzing the space remote sensing flow under the general task, traversing the influence elements in the whole process under the general condition, and constructing a basic corpus of the influence elements;
2) From the perspective of remote sensing effect, an influence element professional basic set oriented to a specific means platform is constructed through the conclusion of expert knowledge in the subject field;
3) Aiming at specific tasks, integrating, carding and cutting to integrate the influence element basic total set and the influence element professional basic set to obtain a single-platform single-means influence element set, wherein the substep is equivalent to the set obtained by integrating the two substeps.
4) Logic analysis is carried out according to the simulation data and the actual measurement data, or hidden influence elements are found through comparison of the simulation data and the actual data, so that a single-platform single-means influence element set is enriched and perfected; this sub-step corresponds to supplementing the single-platform single-means impact element set.
5) If the remote sensing task is cooperatively executed by multiple satellites, determining platform means including satellite types and quantity by combining specific scenes and application requirements, and constructing a specific scene-oriented comprehensive set of influence elements including single-platform multi-means, multi-platform single-means, multi-platform multi-means and the like.
The construction of the influence element-remote sensing effect mapping set specifically comprises the following steps:
1) Preparing a mapping format, wherein the mapping format is stored and presented in the form of a graph, a table and a matrix;
2) And complementing the mapping data, complementing the missing data corresponding to the influence factors by simulation means, wherein the simulation means comprise data generation means, simulation and manual interpretation inversion, and intelligent algorithm inversion based on remote sensing effect, wherein the simulation is to consider how to model and build the environment from the simulation data generation angle to finally generate data.
Impact element analysis and association construction step S140:
And carrying out data preprocessing on the influence elements, carrying out relevance analysis on the influence elements, adjusting and optimizing the influence elements to obtain a preliminary influence element-remote sensing effect mapping set and a preliminary mapping relevance graph of the influence elements-remote sensing effect, and carrying out iterative analysis to obtain a final mapping relevance graph of the optimized influence elements-remote sensing effect.
Specifically, the method comprises the following two sub-steps:
1) Impact element action analysis: firstly, carrying out influence element normalization processing, wherein the influence element data is continuous or discrete data due to various patterns and formats, the influence element data is vector or matrix, unified processing is carried out on the influence element data, and hierarchical discrete quantization processing can be carried out based on the current calculation level and the requirement; then, the influence element correlation analysis is carried out, and the utilization type Solving to obtain influence coefficients among the influence elements; and then carrying out influence element integration optimization, calculating to obtain the quantitative weight of each element, removing the elements below a weight threshold after analysis requirement granularity evaluation, merging strongly related influence elements, merging or deleting intermediate influence elements through priori knowledge, and obtaining a final key influence element set.
Wherein x1 and x2 are influence elements, and the formula is used for calculating the association relation between every two influence elements and providing a quantitative basis for association analysis.
2) Influence element association diagram construction: preliminary influence element-remote sensing effect mapping sets and preliminary influence element-remote sensing effect mapping association diagrams are obtained according to the analysis, and further verification is carried out through means of logic analysis, relation analysis and the like; and combining more influence element data, performing iterative optimization with robustness as a target on the association graph, enabling the element relationships and the influence coefficients to tend to be consistent and converged, obtaining a final mapping association graph of the influence elements and the remote sensing effect, and if the effect analysis requirement is met, completing the whole process of the influence element analysis for the space remote sensing effect analysis.
The more influencing element data can be that the preliminary analysis is possibly in the initial stage of evaluation, the data is not comprehensive, more data can be analyzed along with the progress of the process, and more influencing element data can be obtained because the longer the time is, the more data are accumulated, the more the participating elements are, and the more the influencing element data are; or in the construction of the influence element association diagram, only partial data in the total data is initially used for constructing the preliminary mapping association diagram, and other data in the total data are subsequently used for target iterative optimization.
In particular, referring to FIG. 3, exemplary specific steps described above are shown. It can be seen from the above that in the data analysis, multiple iterative analyses can be performed on the influence element and the effect of the influence element-product according to whether the effect analysis requirement is met, so as to finally obtain the final mapping association diagram of the influence element-remote sensing effect.
Examples: the remote sensing identification task analysis of a certain forest potential fire vegetation is described by taking a certain visible light imaging satellite as an example.
(1) Remote sensing task workflow abstraction
The method is characterized in that a visible light satellite is utilized to roughly position a geographic image of potential fire points in a certain forest, vegetation in the range is further identified, and the identification accuracy of certain flammable vegetation is analyzed. In the imaging process of the visible light satellite, the imaging effect can generate distortion due to the influence of factors such as a platform, load, weather, data processing and the like, and the imaging effect has influence on vegetation detail matching and feature recognition, so that element analysis on recognition accuracy is required.
In order to construct a complete influence element set as much as possible, the imaging process needs to be abstracted, and the influence elements are analyzed in links. The process is satellite demand acceptance (comprehensively planning demands and carrying out task sequencing according to the emergency degree of the demands), resource analysis (satellite orbit number and health degree), scheme design (conflict resolution, whether multi-satellite cooperation is needed or not), instruction uploading, satellite remote sensing (starting up and shooting when reaching a planned orbit position), data downloading, data processing and result publishing; the corresponding analysis flow is that according to the requirement, the vegetation identification effect is an analysis object, the accuracy of the vegetation identification effect and the vegetation identification effect is an analysis view angle, and the analysis flow is formed by accompanying the satellite imaging flow, and as the satellite orbit space, the atmosphere layer and other mediums exist between the satellite and the imaging object, the environment can influence the accuracy except for the factors such as a platform, a load, an object and an algorithm, and finally the multi-source factors influencing the identification accuracy are analyzed according to the flow.
(2) Element analysis flow design for influencing vegetation remote sensing recognition effect of potential fire point of certain forest
For further clarity, in this case, a single star, visible light, and direct transmission to a ground base station are selected.
Referring to fig. 2, a specific remote sensing process abstraction and element analysis process of the present embodiment is shown.
(3) Single-star visible light remote sensing recognition effect influence element analysis
3.1 Influence element set construction
First, a basic corpus of influencing elements is constructed.
On-orbit resource impact element analysis: the task time window has high requirements on satellite resources and timeliness, and the satellite can not respond in time, so that the imaging effect can be negatively influenced.
Platform (satellite) impact element analysis: satellite orbit, satellite velocity, satellite attitude (imaging view), flutter, positioning model errors
Load influencing element analysis: exposure time, focal length, and sensitivity
Target state: target color, target type, shape characteristics, and target optical emission characteristics
And (3) data processing: contrast processing, saturation processing, radiometric scaling processing, image super-resolution algorithm, multi-source image fusion algorithm, and target detection and recognition algorithm
Environmental impact factor analysis: illumination environment (sun incidence direction, illumination intensity), satellite orbit space environment (electromagnetic radiation, sun storm, etc.)
3.2 Construction of professional Foundation set
Since the task is a target in the forest, in addition to the above elements, the cloud thickness in the environmental element, the resolution of the load influencing element, the satellite shake in the platform, the pitch angle, the yaw angle are added in consideration of possible conditions such as shielding and remote sensing distortion
Integrating, carding, cutting and fusing the influence element basic set and the professional basic set to obtain a single-platform single-means influence element set
On-orbit resource influencing element: satellite health status, task urgency, and satellite response
Platform (satellite) influencing elements: satellite attitude, positioning model error, satellite shake, pitch angle, yaw angle
Load influencing element analysis: exposure time, focal length, sensitivity, resolution
Target state: target color, target type, shape characteristics, and target optical emission characteristics
And (3) data processing: contrast processing, image super-resolution algorithm, multi-source image fusion algorithm and target detection and identification algorithm
Environmental impact factor analysis: atmospheric cloud thickness and illumination intensity
3.3 Logic analysis is carried out according to simulation data and actual measurement data, or the motion characteristics (moving speed, direction and the like) of the target of the hidden influencing element are found through comparison of the simulation data and the actual data, and the set is added, so that the single-platform single-means influencing element set is enriched and perfected
3.4 Influence element-remote sensing effect mapping set construction
① And (5) mapping format establishment. The present case is presented in a tree diagram.
② Mapping data complement, in this case a schematic example of a flow, does not involve actual data. Such as complement data:
| Resolution ratio | Side swing angle | Satellite dithering | …… | Object type | Target color | Cloud layer |
| 0.5m | 5° | A | …… | Dried Chinese pine and deposit | [(69,75,27), (95,158,160)] | Sparse |
(3) Impact element action analysis and correlation construction step
After the analysis method, calculating to obtain the quantitative weights of all the elements, and after analysis requirement granularity evaluation, removing the elements below a weight threshold value to finally obtain the key elements as follows: satellite shake, satellite side sway angle, satellite pitching angle, resolution, photosensitivity, target type, target color, illumination intensity, cloud layer and target detection and identification algorithm.
And constructing an influence element association diagram.
Referring to fig. 4, an influence element-remote sensing effect mapping association diagram is shown, after iterative optimization, the target type and the target color are found to belong to the same influence element, and the sensitivity and the illumination intensity belong to the same element, and after merging, the final influence element-remote sensing effect mapping association diagram is shown in fig. 5.
The invention further discloses a storage medium for storing computer executable instructions which, when executed by a processor, perform the above-described element analysis method for influencing the remote sensing effect of space.
The invention has the following advantages:
(1) By adopting a concomitant and formative analysis method, a remote sensing flow model with different links and stages is constructed through abstraction, each link is accompanied by observation and collection of relevant data, and analysis is carried out aiming at elements influencing remote sensing effect, so that the method is more objective and real, and a systematic, scientific, interpretable and quantifiable influence element analysis means is provided for the space remote sensing process of complex objects influencing the elements.
(2) And the method combines expert knowledge and a mathematical method to analyze the elements influencing the satellite remote sensing effect and the association relation thereof, and has stronger realizability and scene applicability.
(3) The method has the advantages that the category of measuring the effect of the remote sensing product by completely predicting the load performance and the capacity of the platform in the traditional method is jumped out, and a way for analyzing and measuring the remote sensing effect through simulating an objective flow is provided, namely, the method for analyzing the remote sensing effect by analyzing and calculating the influence factors in the flow is provided.
It will be apparent to those skilled in the art that the elements or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or they may alternatively be implemented in program code executable by a computer device, such that they may be stored in a storage device for execution by the computing device, or they may be separately fabricated into individual integrated circuit modules, or a plurality of modules or steps in them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
While the invention has been described in detail in connection with specific preferred embodiments thereof, it is not to be construed as limited thereto, but rather as a result of a simple deduction or substitution by a person having ordinary skill in the art without departing from the spirit of the invention, which is to be construed as falling within the scope of the invention defined by the appended claims.
Claims (7)
1. An element analysis method for influencing the aerospace remote sensing effect is characterized by comprising the following steps:
remote sensing task workflow abstraction step S110:
Analyzing the implementation process for a specific task facing to space remote sensing, and abstracting to obtain a remote sensing task workflow meeting analysis requirements;
Impact element analysis flow design step S120:
Determining an analysis object and an analysis view angle of demand analysis facing to a specific effect, performing relation mapping from a remote sensing process to an analysis process, and considering influence elements of all links in the remote sensing process;
influence element comprehensive set construction step S130:
according to the remote sensing basic knowledge and subject expert knowledge, constructing an influence element comprehensive set by combining a specific scene, formulating a mapping format, supplementing mapping data and constructing an influence element-remote sensing effect mapping set;
impact element analysis and association construction step S140:
preprocessing the data of the influence elements, carrying out relevance analysis of the influence elements, adjusting and optimizing the influence elements to obtain a preliminary influence element-remote sensing effect mapping set and a preliminary mapping relevance graph of the influence elements-remote sensing effect, and carrying out iterative analysis to obtain a final mapping relevance graph of the optimized influence elements-remote sensing effect;
specifically, in step S130,
The construction of the comprehensive set of influencing elements specifically comprises the following steps:
1) Through analyzing the space remote sensing flow under the general task, traversing the influence elements in the whole process, and constructing a basic complete set of the influence elements;
2) From the perspective of remote sensing effect, an influence element professional basic set oriented to a specific means platform is constructed through the conclusion of expert knowledge in the subject field;
3) Integrating, carding and cutting the influence element basic complete set and the influence element professional basic set to obtain a single-platform single-means influence element set;
4) Logic analysis is carried out according to the simulation data and the actual measurement data, or hidden influence elements are found through comparison of the simulation data and the actual data, so that a single-platform single-means influence element set is enriched and perfected;
5) If the remote sensing task is cooperatively executed by multiple satellites, determining platform means including satellite types and quantity by combining specific scenes and application requirements, and constructing a specific scene-oriented comprehensive set of influence elements including single-platform multi-means, multi-platform single-means and multi-platform multi-means;
the step S140 specifically includes:
The method comprises the following two substeps:
1) Impact element action analysis: firstly, carrying out influence element normalization processing, in particular to hierarchical discrete quantization processing; then, the influence element correlation analysis is carried out, and the utilization type Solving to obtain influence coefficients among the influence elements; then carrying out influence element integration optimization, calculating to obtain the quantitative weight of each element, removing the elements below the weight threshold after analyzing the requirement granularity evaluation, merging the strongly related influence elements, merging or deleting the intermediate influence elements through priori knowledge to obtain a final key influence element set,
Wherein x1 and x2 are influencing elements;
2) Influence element association diagram construction: obtaining a mapping set of the influence element and the remote sensing effect and a mapping association diagram of the influence element and the remote sensing effect preliminarily according to the analysis, and further checking through logic analysis and relation analysis; and combining more influence element data, performing iterative optimization with robustness as a target on the associated graph, enabling the element relationships and the influence coefficients to tend to be consistent and converged, obtaining a final mapping associated graph of the influence element-remote sensing effect, and analyzing the whole flow if the effect analysis requirement is met.
2. The method for analyzing elements according to claim 1, wherein,
The remote sensing task workflow in the remote sensing task workflow abstraction step S110 includes: demand analysis, resource analysis, scheme design, instruction uploading, remote sensing imaging, data downloading, data automation, manual processing and result issuing.
3. The element analysis method according to claim 2, wherein,
The remote sensing task workflow also comprises resource window allocation and task coordination planning.
4. The method for analyzing elements according to claim 1, wherein,
In the influence element analysis flow design step S120,
Mapping modeling is carried out on the remote sensing process and the analysis process, specific task work links are synthesized, and multi-source elements influencing the remote sensing effect are identified.
5. The method for analyzing elements according to claim 4, wherein,
In step S120, the influencing elements of part of the working links can be ignored for the task workflow of the specific task remote sensing task.
6. The method for analyzing elements according to claim 1, wherein,
In the step S130 of the process of the present invention,
The construction of the influence element-remote sensing effect mapping set specifically comprises the following steps:
1) Preparing a mapping format, wherein the mapping format is stored and presented in the form of a graph, a table and a matrix;
2) And (3) complementing the mapping data, complementing the missing data corresponding to the influence factors by a simulation means, wherein the data generation means comprises simulation and artificial inversion, and intelligent algorithm inversion based on the remote sensing effect.
7. A storage medium storing computer-executable instructions, characterized by:
the computer executable instructions, when executed by a processor, perform the method of element analysis affecting a remote sensing effect of space as claimed in any one of claims 1 to 6.
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