CN117743773A - Remote sensing satellite continuous observation method based on historical big data - Google Patents
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Abstract
The invention discloses a remote sensing satellite continuous observation method based on historical big data, which relates to the technical field of earth observation and comprises the following steps: according to the parameters of the low-orbit satellite, planning an observation plan of the low-orbit satellite on an observation site to obtain an observation task sequence; judging whether the continuous observation vacant time of the low orbit satellite to the observation site is larger than the maximum vacant time or not according to the observation task sequence; if the continuous observation vacant time of the low-orbit satellite to the observation site is larger than the maximum vacant time, the high-orbit satellite is started to observe the observation site at the target observation vacant time; searching a redundant observation plan in the observation task sequence; removing redundant observation plans from the observation task sequence according to the historical earth observation big data set; and executing the rest observation plans in the observation task sequence. The method can optimize the satellite resource utilization rate and ensure the continuous earth observation time.
Description
Technical Field
The invention relates to the technical field of earth observation, in particular to a remote sensing satellite continuous observation method based on historical big data.
Background
Satellite earth observation acquires information by various sensors mounted on a spacecraft such as a satellite. The main modes of satellite earth observation comprise various means such as visible light, electrons, radar and the like, and the earth observation satellite orbit covers a low orbit and a high orbit. The low rail refers to a rail with a rail height of 200 km to 2000 km, and the high rail refers to a rail with a rail height of 20000 km or more. The high-orbit satellite has larger earth observation range, but relatively poor precision, and limited resource quantity, so the high-orbit satellite is mainly used for large-scale earth monitoring. The number of low-orbit satellites is large, and the earth observation accuracy is high because the distance to the ground is short, so that the earth observation of satellites mainly comprises low-orbit satellites. In order to successfully acquire information, a reasonable observation plan is required to be formulated, and various contents such as earth observation areas, task purposes, satellite resource scheduling, earth observation time limit and the like are comprehensively planned. When continuous attention needs to be paid to a key target and a key region, because the overhead time of a single satellite (the time that the satellite passes through a certain space above the ground) is limited, in order to ensure the continuity and timeliness of earth observation results, a multi-satellite cooperative method is generally adopted to carry out task planning.
In the existing continuous observation planning and planning for key targets and areas, the overhead time near the key targets is generally calculated through satellite operation parameters, so that a multi-satellite continuous observation task sequence is formed, and the task planning is completed. However, the optimality of the multi-satellite continuous observation plan is difficult to control, and how to optimize the satellite resource utilization rate and fully guarantee the continuous earth observation time is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The invention aims to provide a remote sensing satellite continuous observation method based on historical big data, which can optimize the satellite resource utilization rate and fully ensure the continuous earth observation time.
In order to solve the technical problems, the invention provides a remote sensing satellite continuous observation method based on historical big data, which comprises the following steps:
according to the parameters of the low-orbit satellite, planning an observation plan of the low-orbit satellite on an observation site to obtain an observation task sequence;
judging whether the continuous observation vacant time of the low orbit satellite to the observation site is larger than the maximum vacant time or not according to the observation task sequence;
if the continuous observation vacant time of the low-orbit satellite to the observation site is larger than the maximum vacant time, starting the high-orbit satellite to observe the observation site at the target observation vacant time;
retrieving redundant observation plans in the observation task sequence;
removing redundant observation plans from the observation task sequence according to the historical earth observation big data set;
and executing the rest observation plans in the observation task sequence.
Optionally, the removing the redundant observation plan from the observation task sequence according to the historical earth observation big data set includes:
retrieving the historical earth observation big data set, and judging whether a historical observation plan for the observation site exists in the historical earth observation big data set;
if so, eliminating a redundant observation plan from the observation task sequence according to the historical observation plan;
if the historical observation plan is not available, the range of the observation site is expanded, the historical earth observation big data set is searched after the range of the observation site is expanded, and the redundant observation plan is removed from the observation task sequence according to the historical observation plan of the observation site with the expanded range in the historical earth observation big data set.
Optionally, the method further comprises:
judging whether a redundant observation plan still exists in the observation task sequence or not after eliminating the redundant observation plan from the observation task sequence according to the historical observation plan;
and if the redundant observation plans still exist, extending the range of the observation site, searching the historical earth observation big data set after extending the range of the observation site, and removing the redundant observation plans from the observation task sequence according to the historical observation plans of the observation site with the extended range in the historical earth observation big data set.
Optionally, removing redundant observation plans from the observation task sequence according to the historical observation plans includes:
and selecting a satellite corresponding to an optimal observation plan of a pre-preset proportion in the historical earth observation big data set and a satellite corresponding to a worst observation plan of a post-preset proportion, comparing the selected satellite with the satellite in the time period of the redundant observation plan, reserving the observation plan of the satellite corresponding to the optimal observation plan on the observation site in the time period, and eliminating the observation plan of the satellite corresponding to the worst observation plan on the observation site in the time period.
Optionally, the method further comprises:
if the number of times of expanding the range of the observation site reaches the preset number of times, the historical observation plan of the observation site still does not exist in the historical earth observation big data set, or if the number of times of eliminating the redundant observation plan from the observation task sequence according to the historical observation plan reaches the preset number of times, the redundant observation plan still exists in the observation task sequence, then the observation plan of the observation site by the optimal satellite with the preset proportion in the front in the observation task sequence in the time period is reserved, and the observation plan of the observation site by the worst satellite with the preset proportion in the time period after elimination is reserved.
Optionally, the method further comprises:
and if redundant observation plans still exist in the observation task sequence after the observation plans of the worst satellites with the preset proportion are subjected to the elimination in the time period, randomly eliminating the observation plans, and enabling the number of the observation plans in the observation task sequence to be equal to the number of the simultaneous observation plans.
Optionally, the generating process of the historical earth observation big data set includes:
acquiring a historical observation plan and a ground observation result of the historical observation plan;
traversing the historical observation plan, and obtaining observation sites covered by the historical observation plan to form a ground observation site hot spot intensity map;
traversing the historical observation plan, and obtaining the observation time and duration of the historical observation plan to form a earth observation time hot spot intensity map;
traversing the historical observation plans according to the sequence from high to low of the location and the time hot spot, classifying the observation locations, and sorting and classifying the earth observation results of different satellites to generate the historical earth observation big data set.
The remote sensing satellite continuous observation method based on historical big data provided by the invention comprises the following steps: according to the parameters of the low-orbit satellite, planning an observation plan of the low-orbit satellite on an observation site to obtain an observation task sequence; judging whether the continuous observation vacant time of the low orbit satellite to the observation site is larger than the maximum vacant time or not according to the observation task sequence; if the continuous observation vacant time of the low-orbit satellite to the observation site is larger than the maximum vacant time, starting the high-orbit satellite to observe the observation site at the target observation vacant time; retrieving redundant observation plans in the observation task sequence; removing redundant observation plans from the observation task sequence according to the historical earth observation big data set; and executing the rest observation plans in the observation task sequence.
Therefore, according to the remote sensing satellite continuous observation method based on the historical big data, after the observation task sequence of the low-orbit satellite is planned and formed, the observation vacant time of the low-orbit satellite to the observation site is supplemented through the high-orbit satellite, so that the continuous earth observation time is fully ensured. In addition, the historical earth observation big data set is used as a basis, redundant observation plans in the observation task sequence are removed, and the utilization rate of satellite resources can be optimized. Meanwhile, the observation is continuously carried out, the data in the historical earth observation big data set is continuously accumulated, and the optimality of the observation task sequence can be continuously improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required in the prior art and the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a remote sensing satellite continuous observation method based on historical big data provided by the embodiment of the invention;
fig. 2 is a schematic view of optimization of an observation plan according to an embodiment of the present invention.
Detailed Description
The core of the invention is to provide a remote sensing satellite continuous observation method based on historical big data, which can optimize the satellite resource utilization rate and fully ensure the continuous earth observation time.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flow chart of a remote sensing satellite continuous observation method based on historical big data according to an embodiment of the present invention, and referring to fig. 1, the method includes:
s101: according to the parameters of the low-orbit satellite, planning an observation plan of the low-orbit satellite on an observation site to obtain an observation task sequence;
the parameters of the low-orbit satellite include the orbit parameters and the load performance parameters of the low-orbit satellite. Orbit parameters include orbit semi-major axis, orbit eccentricity, orbit tilt angle, longitude of intersection point, amplitude angle of near place, and angle of near point. The load performance parameters comprise load center distance, maximum lifting height, free lifting height, rated lifting weight, portal inclination angle, maximum lifting speed, maximum running speed, maximum climbing gradient, minimum transition radius and the like. The observation site is a point location or area.
And according to the orbit operation parameters and the load performance parameters of the low-orbit satellite, an observation plan of the low-orbit satellite on an observation site is planned to form an observation task sequence. The sequence of observation tasks includes the observation plans of the different low-orbit satellites. The observation plan includes the observation locations, and the starting observation times and durations of the observation locations for the different low-orbit satellites.
S102: judging whether the continuous observation vacant time of the low orbit satellite to the observation site is larger than the maximum vacant time or not according to the observation task sequence;
s103: if the continuous observation vacant time of the low-orbit satellite to the observation site is larger than the maximum vacant time, starting the high-orbit satellite to observe the observation site at the target observation vacant time;
the continuous observation free time refers to the accumulated time during which no observation is made on the observation site within the observation time requirement. After the observation task sequence is formed, the continuous observation vacancy time of the observation site can be determined according to the observation task sequence. Steps S102 and S103 aim to supplement the time of the lack of earth observation to ensure continuous observation of the observation site. And if the continuous observation vacancy time of the observation site is greater than the set maximum vacancy time, enabling the high orbit satellite to observe the observation site at the target observation time. If the duration of the observation period for the observation site is not greater than the set maximum period, then the high orbit satellite is not enabled.
The target observation time may be equal to the continuous observation period. Illustratively, the duration of observation of the absence time includes time 1 to time 5, and time 9 to time 12. The corresponding target observation time may include time 1 to time 5, time 9 to time 12, i.e. at time 1 to time 5, time 9 to time 12 each enable the high orbit satellite to observe the observation site.
The target observation time may also be unequal to the continuous observation time, so that the continuous observation time of the observation site after the high-orbit satellite is started is ensured to be not greater than the maximum time.
S104: retrieving redundant observation plans in the observation task sequence;
s105: removing redundant observation plans from the observation task sequence according to the historical earth observation big data set;
s106: and executing the rest observation plans in the observation task sequence.
Redundant observation plans refer to multiple low-orbit satellites simultaneously observing the same observation site. Multiple low-orbit satellites simultaneously observe the same observation site, which causes waste of satellite resources. And S104 and S105 aim at eliminating redundant observation plans, so as to optimize the observation task sequence and optimize the satellite resource utilization rate.
In some embodiments, the removing redundant observation plans from the observation task sequence based on the historical earth observation big dataset comprises:
retrieving the historical earth observation big data set, and judging whether a historical observation plan for the observation site exists in the historical earth observation big data set;
if so, eliminating a redundant observation plan from the observation task sequence according to the historical observation plan;
if the historical observation plan is not available, the range of the observation site is expanded, the historical earth observation big data set is searched after the range of the observation site is expanded, and the redundant observation plan is removed from the observation task sequence according to the historical observation plan of the observation site with the expanded range in the historical earth observation big data set.
Wherein in some embodiments, removing redundant observation plans from the observation task sequence according to the historical observation plans comprises:
and selecting a satellite corresponding to an optimal observation plan of a pre-preset proportion in the historical earth observation big data set and a satellite corresponding to a worst observation plan of a post-preset proportion, comparing the selected satellite with the satellite in the time period of the redundant observation plan, reserving the observation plan of the satellite corresponding to the optimal observation plan on the observation site in the time period, and eliminating the observation plan of the satellite corresponding to the worst observation plan on the observation site in the time period.
Referring to fig. 2, a history earth observation big data set is searched, and it is determined whether or not a history observation plan for an observation point exists in the history earth observation big data set. And if the observation site is a point location, judging whether a history observation plan for a preset range taking the point location as a center exists in the history earth observation big data set. For example, it is determined whether or not there is a history observation plan for a 10km range centered on the point in the history earth observation large data set.
And if the historical earth observation big data set has a historical observation plan for the observation site, selecting a satellite corresponding to the optimal observation plan with the front preset proportion and a satellite corresponding to the worst observation plan with the rear preset proportion. Calculating the time period of the redundant observation plan, comparing the selected satellite with the satellite in the time period of the redundant observation plan, reserving the observation plan of the satellite corresponding to the optimal observation plan for the observation place in the time period, and eliminating the observation plan of the satellite corresponding to the worst observation plan for the observation place in the time period.
Illustratively, if there is a historical observation plan for the observation site in the historical earth observation big dataset, then a satellite is selected in which the satellite corresponding to the top 10% of the optimal observation plan corresponds to the bottom 10% of the worst observation plan. Calculating the time period of the redundant observation plan, comparing the selected satellite with the satellite in the time period of the redundant observation plan, reserving the observation plan of the satellite corresponding to the optimal observation plan for the observation place in the time period, and eliminating the observation plan of the satellite corresponding to the worst observation plan for the observation place in the time period.
If there is no historical observation plan for the observation site in the historical earth observation big dataset, the scope of the observation site is extended. For example, the observation point is a point location, and a 10km range centered on the point location is extended to a 20km range centered on the point location. The observation site is an area, and the area is expanded by 1 time.
After the scope of the observation site is expanded, the historical earth observation big data set is searched again, and whether a historical observation plan for the observation site with the expanded scope exists in the historical earth observation big data set is judged. If a historical observation plan of the observation site with the extended range exists, a satellite corresponding to the optimal observation plan with the front preset proportion and a satellite corresponding to the worst observation plan with the rear preset proportion are selected, the selected satellite is compared with the satellite in the time period of the redundant observation plan, the observation plan of the satellite corresponding to the optimal observation plan to the observation site in the time period is reserved, and the observation plan of the satellite corresponding to the worst observation plan to the observation site in the time period is removed. If there is no history observation plan for the observation site after the range expansion, the range of the observation site can be expanded again to make the range of the observation site larger, and after the range of the observation site is expanded, the history earth observation large dataset can be retrieved again.
By expanding the range of the observation site, redundant observation plans can be eliminated more effectively, and a plurality of satellites are prevented from observing the same observation target.
In some embodiments, further comprising:
judging whether a redundant observation plan still exists in the observation task sequence or not after eliminating the redundant observation plan from the observation task sequence according to the historical observation plan;
if the redundant observation plan still exists, the range of the observation site is expanded, the historical earth observation big data set is searched after the range of the observation site is expanded, and the redundant observation plan is removed from the observation task sequence according to the historical observation plan of the observation site with the expanded range in the historical earth observation big data set.
Referring to fig. 2, if a redundant observation plan exists after eliminating an observation plan for an observation site by a satellite corresponding to the worst observation plan in a time period of the redundant observation plan, the range of the observation site is extended, and after the range of the observation site is extended, it is determined whether or not a history observation plan for the observation site whose range is extended exists in the history earth observation big data set. If a historical observation plan of the observation site with the extended range exists, a satellite corresponding to the optimal observation plan with the front preset proportion and a satellite corresponding to the worst observation plan with the rear preset proportion are selected, the selected satellite is compared with the satellite in the time period of the redundant observation plan, the observation plan of the satellite corresponding to the optimal observation plan to the observation site in the time period is reserved, and the observation plan of the satellite corresponding to the worst observation plan to the observation site in the time period is removed. If there is no history observation plan for the observation site after the range expansion, the range of the observation site can be expanded again to make the range of the observation site larger, and after the range of the observation site is expanded, the history earth observation large dataset can be retrieved again.
Referring to fig. 2, in some embodiments, further comprising:
if the number of times of expanding the range of the observation site reaches the preset number of times, the historical observation plan of the observation site still does not exist in the historical earth observation big data set, or if the number of times of eliminating the redundant observation plan from the observation task sequence according to the historical observation plan reaches the preset number of times, the redundant observation plan still exists in the observation task sequence, then the observation plan of the observation site by the optimal satellite with the preset proportion in the front in the observation task sequence in the time period is reserved, and the observation plan of the observation site by the worst satellite with the preset proportion in the time period after elimination is reserved.
For example, if the number of times of extending the range of the observation site reaches three, there is no history observation plan for the observation site in the history earth observation big data set, or if the number of times of eliminating the redundant observation plan from the observation task sequence according to the history observation plan reaches three, there is still a redundant observation plan in the observation task sequence, then the observation plan of the first 10% of the optimal satellites for the observation site in the time period is retained, and the observation plan of the worst 10% of the satellites for the observation site in the time period is eliminated.
Referring to fig. 2, in some embodiments, further comprising:
and if redundant observation plans still exist in the observation task sequence after the observation plans of the worst satellites with the preset proportion are subjected to the elimination in the time period, randomly eliminating the observation plans, and enabling the number of the observation plans in the observation task sequence to be equal to the number of the simultaneous observation plans.
The number of simultaneous observation plans is the number of observation plans in which the observation points overlap at the same time. If redundant observation plans still exist in the observation task sequence after the observation plans of the worst satellites with the preset proportion to the observation sites in the time period are eliminated, the observation plans are eliminated randomly, and the number of the observation plans to the observation sites is equal to the number of the simultaneous observation plans.
The determining process of the simultaneous observation plan number comprises the following steps:
retrieving the historical optimal simultaneous observation plan number of the historical earth observation big data set observation sites;
if the historical optimal simultaneous observation plan number of the observation site is retrieved, determining the historical optimal simultaneous observation plan number as the simultaneous observation plan number;
if the historical optimal simultaneous observation plan number of the observation site is not retrieved, determining that the simultaneous observation plan number is the default simultaneous observation plan number. For example, if the default simultaneous observation plan number is 2, when the history of the observation point is not retrieved, the optimal simultaneous observation plan number is determined to be 2.
In some embodiments, the process of generating the historical earth observation large dataset includes:
acquiring a historical observation plan and a ground observation result of the historical observation plan;
traversing the historical observation plan, and obtaining observation sites covered by the historical observation plan to form a ground observation site hot spot intensity map;
traversing the historical observation plan, and obtaining the observation time and duration of the historical observation plan to form a earth observation time hot spot intensity map;
traversing the historical observation plans according to the sequence from high to low of the location and the time hot spot, classifying the observation locations, and sorting and classifying the earth observation results of different satellites to generate the historical earth observation big data set.
The earth observation site hotspot intensity map reflects how many times the observation site is observed. The more times an observation site is observed, the higher the hotspot intensity of the observation site, and the more important it is to characterize the observation site. The earth observation time hotspot intensity map reflects the coincidence of time periods of different observation plans. The more times a time period coincides, the higher the intensity of the hot spot for that time period, indicating that the observation plans for multiple satellites are within that time period. The shorter the duration, the shorter the time that the observation site needs to observe. The longer the duration, the longer the time that the observation site needs to observe. The time required for the observation site to be observed is allocated according to the duration in the historical observation big dataset.
And traversing the historical observation plan according to the point and time hot spot from high to low according to the point and time hot spot intensity map of the earth observation point and the earth observation time hot spot intensity map, and classifying the observation points. For example, the observation site is classified as a site where the number of observations exceeds a set number of times (for example, 10 times) as an observation plan full-time coverage, the observation site is classified as 2 to 4 points per day for an observation time, the number of times required for observation is a preset number of times, and the like.
And sorting and grading the earth observation results of different satellites. For example, a certain observation plan ranking is classified as a good observation plan, and a certain observation plan ranking is classified as a bad observation plan. For example, if a satellite is observed for 2 hours at 2 to 4 points and 1 hour at 0 to 1 point, the satellite can be observed for 1 hour at 0 to 1 point to a poor observation plan.
In summary, according to the remote sensing satellite continuous observation method based on the historical big data provided by the invention, after an observation task sequence of a low-orbit satellite is planned and formed, the observation vacant time of the low-orbit satellite to an observation site is supplemented through the high-orbit satellite, so that the continuous earth observation time is fully ensured. In addition, the historical earth observation big data set is used as a basis, redundant observation plans in the observation task sequence are removed, and the utilization rate of satellite resources can be optimized. Meanwhile, the observation is continuously carried out, the data in the historical earth observation big data set is continuously accumulated, and the optimality of the observation task sequence can be continuously improved.
In the description, each embodiment is described in a progressive manner, and each embodiment is mainly described by the differences from other embodiments, so that the same similar parts among the embodiments are mutually referred.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The remote sensing satellite continuous observation method based on the historical big data provided by the invention is described in detail. The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to facilitate an understanding of the method of the present invention and its core ideas. It should be noted that it will be apparent to those skilled in the art that the present invention may be modified and practiced without departing from the spirit of the invention.
Claims (7)
1. A remote sensing satellite continuous observation method based on historical big data is characterized by comprising the following steps:
according to the parameters of the low-orbit satellite, planning an observation plan of the low-orbit satellite on an observation site to obtain an observation task sequence;
judging whether the continuous observation vacant time of the low orbit satellite to the observation site is larger than the maximum vacant time or not according to the observation task sequence;
if the continuous observation vacant time of the low-orbit satellite to the observation site is larger than the maximum vacant time, starting the high-orbit satellite to observe the observation site at the target observation vacant time;
retrieving redundant observation plans in the observation task sequence;
removing redundant observation plans from the observation task sequence according to the historical earth observation big data set;
and executing the rest observation plans in the observation task sequence.
2. The method of claim 1, wherein removing redundant observation plans from the observation task sequence based on historical big data sets of earth observations comprises:
retrieving the historical earth observation big data set, and judging whether a historical observation plan for the observation site exists in the historical earth observation big data set;
if so, eliminating a redundant observation plan from the observation task sequence according to the historical observation plan;
if the historical observation plan is not available, the range of the observation site is expanded, the historical earth observation big data set is searched after the range of the observation site is expanded, and the redundant observation plan is removed from the observation task sequence according to the historical observation plan of the observation site with the expanded range in the historical earth observation big data set.
3. The method for continuously observing remote sensing satellites based on historical big data according to claim 2, further comprising:
judging whether a redundant observation plan still exists in the observation task sequence or not after eliminating the redundant observation plan from the observation task sequence according to the historical observation plan;
and if the redundant observation plan still exists, extending the range of the observation site, searching the historical earth observation big data set after extending the range of the observation site, and removing the redundant observation plan from the observation task sequence according to the historical observation plan of the observation site with the extended range in the historical earth observation big data set.
4. A method of continuous observation of remote sensing satellites based on historical big data according to claim 2 or 3 wherein removing redundant observation plans from a sequence of observation tasks according to the historical observation plans comprises:
and selecting a satellite corresponding to an optimal observation plan of a pre-preset proportion in the historical earth observation big data set and a satellite corresponding to a worst observation plan of a post-preset proportion, comparing the selected satellite with the satellite in the time period of the redundant observation plan, reserving the observation plan of the satellite corresponding to the optimal observation plan on the observation site in the time period, and eliminating the observation plan of the satellite corresponding to the worst observation plan on the observation site in the time period.
5. The method for continuously observing a remote sensing satellite based on historical big data according to claim 4, further comprising:
if the number of times of extending the range of the observation site reaches the preset number of times, the historical observation plan of the observation site still does not exist in the historical earth observation big data set, or the number of times of eliminating the redundant observation plan from the observation task sequence according to the historical observation plan reaches the preset number of times, and the redundant observation plan still exists in the observation task sequence, the observation plan of the observation site by the optimal satellite with the preset proportion in the front in the observation task sequence in the time period is reserved, and the observation plan of the observation site by the worst satellite with the preset proportion in the time period after the elimination is eliminated.
6. The method for continuously observing a remote sensing satellite based on historical big data according to claim 5, further comprising:
and if redundant observation plans still exist in the observation task sequence after the observation plans of the worst satellites with the preset proportion are subjected to the elimination in the time period, randomly eliminating the observation plans, and enabling the number of the observation plans in the observation task sequence to be equal to the number of the simultaneous observation plans.
7. The method for continuously observing remote sensing satellites based on historical big data according to claim 1, wherein the generating process of the historical earth observation big data set comprises:
acquiring a historical observation plan and a ground observation result of the historical observation plan;
traversing the historical observation plan, and obtaining observation sites covered by the historical observation plan to form a ground observation site hot spot intensity map;
traversing the historical observation plan, and obtaining the observation time and duration of the historical observation plan to form a earth observation time hot spot intensity map;
traversing the historical observation plans according to the sequence from high to low of the location and the time hot spot, classifying the observation locations, and sorting and classifying the earth observation results of different satellites to generate the historical earth observation big data set.
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