Satellite observation task scheduling method, device and equipment based on visibility clustering

Abstract

The invention relates to the technical field of satellite observation, and discloses a satellite observation task scheduling method, device and equipment based on visibility clustering, and the method comprises the steps: determining an available satellite set, the satellite parameter information of each available satellite, a to-be-observed dense point target set, and the target parameter information of each to-be-observed dense point target; for any available satellite, determining a visibility window of each dense point target to be observed based on the satellite parameter information and the target parameter information of each dense point target to be observed, and obtaining a visibility window set; clustering the visibility window set to obtain a clustering result set; constructing a satellite observation task scheduling model based on the satellite parameter information, the target parameter information and the clustering result set; and solving the satellite observation task scheduling model to obtain a target observation task. According to the method, the to-be-observed dense point targets are observed as many as possible in single observation by clustering the visibility windows, so that the observation efficiency, the resource utilization rate and the satellite planning efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite observation technology, and in particular to a method, device and equipment for scheduling satellite observation tasks based on visibility clustering. Background Art

[0002] With the increase of imaging satellite resources, the number of observation tasks is also increasing. Due to the different performance parameters and constraints of different satellites, and the different observation time windows and geographical locations of observation tasks, the complexity of satellite task scheduling is increased. Satellite observation targets can be mainly divided into point targets and regional targets. When there are a large number of point targets, the traditional satellite observation task scheduling method requires multiple power on and off and attitude maneuvers to meet the observation conditions. In addition, there may be mutual exclusion between observation tasks, that is, the observation time of two tasks conflicts, or the time interval between tasks is too short, resulting in the satellite being unable to perform attitude conversion, making some targets unable to be observed, resulting in low observation efficiency and waste of satellite resources. Therefore, how to schedule satellite observation tasks to efficiently complete observations and save satellite resources is a problem that needs to be solved. Summary of the invention

[0003] In view of this, the present invention provides a satellite observation task scheduling method, device and equipment based on visibility clustering to solve the problem that the traditional satellite observation task scheduling method requires multiple power on and off and attitude maneuvers, resulting in low observation efficiency and waste of satellite resources.

[0004] In a first aspect, the present invention provides a satellite observation task scheduling method based on visibility clustering, the method comprising:

[0005] Determine an available satellite set, satellite parameter information of each available satellite in the available satellite set, a dense point target set to be observed, and target parameter information of each dense point target to be observed in the dense point target set to be observed;

[0006] For any available satellite in the available satellite set, based on the satellite parameter information of the available satellite and the target parameter information of each dense point target to be observed in the dense point target set to be observed, the visibility window corresponding to each dense point target to be observed is determined to obtain the visibility window set of the dense point target set to be observed;

[0007] Clustering the visibility window set of the observation dense point target set to obtain at least one clustering result set;

[0008] Building a satellite observation task scheduling model based on satellite parameter information of available satellites, target parameter information of each dense point target to be observed in the dense point target set to be observed, and at least one clustering result set;

[0009] Solve the satellite observation task scheduling model and obtain the target observation tasks of available satellites.

[0010] The satellite observation task scheduling method based on visibility clustering provided by an embodiment of the present invention determines the visibility window of each dense point target to be observed, thereby clustering the visibility windows of all dense point targets to be observed, so that available satellites can observe as many dense point targets to be observed as possible in a single observation, and build a model based on the clustering result set and then solve it. Since the number of clustering result sets is less than the number of visibility windows, the target observation tasks of available satellites can be obtained at a faster solution speed. Compared with the existing satellite observation scheduling method, the number of satellite conversions is reduced, the satellite observation efficiency and resource utilization are improved, and the satellite planning efficiency is improved.

[0011] In an optional implementation, the satellite parameter information includes three-dimensional space coordinates, and the target parameter information includes longitude and latitude coordinates;

[0012] For any available satellite in the available satellite set, based on the satellite parameter information of the available satellite and the target parameter information of each dense point target to be observed in the dense point target set to be observed, the visibility window corresponding to each dense point target to be observed is determined, and the visibility window set of the dense point target set to be observed is obtained, including:

[0013] For any dense point target to be observed, based on the three-dimensional spatial coordinates of the available satellites at any time and the longitude and latitude coordinates of the dense point target to be observed at the time, according to spatial analytic geometry, the visibility window of the available satellites for imaging observation of the dense point target to be observed at the time is determined;

[0014] The visibility windows corresponding to all the dense point targets to be observed in the dense point target set to be observed are used as the visibility window set of the dense point target set to be observed.

[0015] The satellite observation task scheduling method based on visibility clustering provided in an embodiment of the present invention, since the visibility window includes the time point and the swing range when the available satellite can observe the dense point target to be observed, the visibility window of the coordinates of the dense point to be observed is determined based on the coordinates of the available satellites and the dense point target to be observed, thereby obtaining a visibility window set, which provides support for subsequent clustering based on the visibility window set.

[0016] In an optional implementation, any visibility window corresponding to any dense point target to be observed includes an observation time point and a lateral swing range when the dense point target to be observed can be observed by an available satellite, and the satellite parameter information includes a maximum single power-on time;

[0017] Clustering the visibility window set of the observation dense point target set to obtain at least one clustering result set, including:

[0018] For any visibility window in the visibility window set, the neighbor window time range of the visibility window is determined based on the observation time point corresponding to the visibility window and the maximum single power-on time of the available satellite;

[0019] From the set of visibility windows, determine a neighbor window that satisfies the neighbor window time range of the visibility window;

[0020] Clustering is performed based on neighbor windows of all visibility windows in the visibility window set to obtain at least one clustering result set.

[0021] The satellite observation task scheduling method based on visibility clustering provided in an embodiment of the present invention can effectively integrate adjacent or overlapping visibility windows by clustering multiple visibility windows in a visibility window set, thereby enabling observation of multiple visibility windows in one observation, that is, observation of multiple dense point targets to be observed, reducing the number of satellite power on and off and the number of movements, improving observation efficiency and saving satellite resources.

[0022] In an optional implementation, before clustering the visibility window set of the set of dense point targets to be observed to obtain at least one clustering result set, the method further includes:

[0023] Determine the intersection of the swing ranges corresponding to all visibility windows in the visibility window set;

[0024] Determine the earliest observation time point and the latest observation time point from the observation time points corresponding to all visibility windows in the visibility window set;

[0025] Determine the time difference between the earliest observation time point and the latest observation time point;

[0026] When the intersection is not empty and the time difference is less than the maximum single power-on time of the available satellite, it is determined that the visibility window set can be clustered.

[0027] The satellite observation task scheduling method based on visibility clustering provided in an embodiment of the present invention clusters visibility windows that meet observation time conditions and observation angle conditions. Compared with selecting to perform imaging for each visibility window of a dense point target to be observed separately, it is possible to complete the observation of multiple dense point targets to be observed in one observation, reduce the number of satellite observations, and achieve the purpose of saving resources and improving observation efficiency.

[0028] In an optional implementation, clustering is performed based on neighbor windows of all visibility windows in the visibility window set to obtain at least one clustering result set, including:

[0029] Initialize all clustering result sets to be empty;

[0030] Determine a visibility window with the most neighbor windows from the visibility window set, take the visibility window as the center point of any clustering result set, and add the visibility window to the clustering result set;

[0031] Traverse all neighbor windows of the center point in traversal order to determine whether there is a neighbor window that satisfies the observation angle constraint and the observation time constraint with the center point;

[0032] If there is a neighbor window and the center point that meet the observation angle constraint and observation time constraint, the observation time point and side swing range of the neighbor window are used as the observation time point and side swing range of the center point, and the neighbor window is added to the clustering result set;

[0033] Repeat the above traversal process until all neighbor windows of the center point are traversed once, and obtain a clustering result set;

[0034] The clustering result set is removed from the visibility window set, and the above process of obtaining the clustering result set is repeated until the visibility window set is empty, and at least one clustering result set is obtained.

[0035] The satellite observation task scheduling method based on visibility clustering provided in an embodiment of the present invention clusters a set of visibility windows so that the visibility windows in the same clustering result set have similar observation times and observation angles, thereby enabling observation of dense point targets to be observed corresponding to all visibility windows in the clustering result set in one observation, thereby reducing the number of satellite power ons and offs and the number of movements, improving observation efficiency and saving satellite resources.

[0036] In an optional implementation, a satellite observation task scheduling model is constructed based on satellite parameter information of available satellites, target parameter information of each dense point target to be observed in the dense point target set to be observed, and at least one clustering result set, including:

[0037] Taking at least one clustering result set as a decision variable;

[0038] Based on the satellite parameter information of the available satellites, the target parameter information and decision variables of each dense point target to be observed in the set of dense point targets to be observed, the objective function and constraint conditions are constructed;

[0039] Based on decision variables, objective function and constraints, a satellite observation task scheduling model for available satellites is constructed.

[0040] The satellite observation task scheduling method based on visibility clustering provided in an embodiment of the present invention, by converting the scheduling of satellite observation tasks into building a mathematical model, can scientifically and accurately obtain the observation task scheduling plan of available satellites from the solution of the mathematical model, thereby improving the scientific nature of satellite observation task scheduling and optimizing the scheduling efficiency.

[0041] In an optional implementation, solving the satellite observation task scheduling model to obtain the target observation tasks of the available satellites includes:

[0042] When the decision variables of the satellite observation task scheduling model are subject to constraints, the decision variables are adjusted, and the decision variables corresponding to when the objective function of the satellite observation task scheduling model reaches the maximum value are used as the target observation tasks of the available satellites.

[0043] The satellite observation task scheduling method based on visibility clustering provided in an embodiment of the present invention obtains the target observation task by solving the satellite observation task scheduling model, so that the available satellites do not need to be turned on and off and perform attitude conversion when performing imaging observations on the target observation tasks, thereby improving the observation efficiency and satellite resource utilization.

[0044] In a second aspect, the present invention provides a satellite observation task scheduling device based on visibility clustering, the device comprising:

[0045] A first determination module is used to determine an available satellite set, satellite parameter information of each available satellite in the available satellite set, a dense point target set to be observed, and target parameter information of each dense point target to be observed in the dense point target set to be observed;

[0046] The second determination module is used to determine, for any available satellite in the available satellite set, a visibility window corresponding to each dense point target to be observed based on satellite parameter information of the available satellite and target parameter information of each dense point target to be observed in the dense point target set to be observed, so as to obtain a visibility window set of the dense point target set to be observed;

[0047] A clustering module, used for clustering a set of visibility windows of a set of densely observed point targets to obtain at least one set of clustering results;

[0048] A construction module, for constructing a satellite observation task scheduling model based on satellite parameter information of available satellites, target parameter information of each dense point target to be observed in the dense point target set to be observed, and at least one clustering result set;

[0049] The solution module is used to solve the satellite observation task scheduling model and obtain the target observation tasks of the available satellites.

[0050] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the satellite observation task scheduling method based on visibility clustering of the above-mentioned first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0051] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the satellite observation task scheduling method based on visibility clustering of the above-mentioned first aspect or any corresponding embodiment thereof.

[0052] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the satellite observation task scheduling method based on visibility clustering of the above-mentioned first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 is a flow chart of a satellite observation task scheduling method based on visibility clustering according to an embodiment of the present invention;

[0055] Figure 2 is a structural block diagram of a satellite observation task scheduling device based on visibility clustering according to an embodiment of the present invention;

[0056] Figure 3 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0058] When there are a large number of point targets among the satellite observation targets, the traditional satellite observation task scheduling method requires multiple power on / off and attitude maneuvers to meet the observation conditions. In addition, there may be mutual exclusion between the observation tasks, that is, the observation time of the two tasks conflicts, or the time interval between the tasks is too short, resulting in the satellite being unable to perform attitude conversion, so that some targets cannot be observed, resulting in low observation efficiency and waste of satellite resources. Therefore, the satellite observation task scheduling method based on visibility clustering provided by the embodiment of the present invention determines the visibility window of each dense point target to be observed, thereby clustering the visibility windows of all dense point targets to be observed, so that the available satellite can observe as many dense point targets to be observed as possible in a single observation, reducing the number of satellite conversions, improving the satellite's observation efficiency and resource utilization, and at the same time improving the satellite planning efficiency.

[0059] According to an embodiment of the present invention, an embodiment of a satellite observation task scheduling method based on visibility clustering is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0060] In this embodiment, a satellite observation task scheduling method based on visibility clustering is provided, which can be used for electronic devices. Figure 1 is a flow chart of a satellite observation task scheduling method based on visibility clustering according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0061] Step S101, determine the available satellite set, the satellite parameter information of each available satellite in the available satellite set, the dense point target set to be observed, and the target parameter information of each dense point target to be observed in the dense point target set to be observed. Specifically, the satellite performs imaging observation tasks on the observation target to achieve activities such as observation and data collection of the observation target. The available satellite set includes a plurality of available satellites that can perform imaging observation tasks, and the satellite parameter information of each available satellite includes attribute data information and trajectory data information. Among them, the attribute data information specifically includes satellite name, satellite type (optical or synthetic aperture), width, maximum left swing, maximum right swing, minimum solar altitude angle required for imaging, maximum resolution, minimum duration of single imaging, maximum duration of single track imaging, time required for conversion side swing 0-10°, time required for conversion side swing 10°-20°, and time required for conversion side swing above 20°. The trajectory data information specifically includes satellite name, time, longitude and latitude of the subsatellite point corresponding to the time, altitude corresponding to the time, earth radius of the subsatellite point, and solar altitude angle of the subsatellite point. The embodiment of the present invention is applied to the situation where there are a large number of observation point targets. Therefore, the set of dense point targets to be observed includes multiple point targets to be observed, but in actual situations, imaging observations can also be performed on regional targets. The target parameter information of each dense point target to be observed specifically includes the task name, longitude and latitude coordinates, observation benefit, observation requirement frequency, and the minimum time interval between two adjacent observations. Optionally, the above-mentioned satellite parameter information and target parameter information are only taken as examples, and different data can be obtained as needed, which is not limited by the embodiment of the present invention. By determining the available satellites, the point targets to be observed, and the corresponding parameter information, support is provided for subsequent satellite observation task scheduling.

[0062] Step S102, for any available satellite in the available satellite set, based on the satellite parameter information of the available satellite and the target parameter information of each dense point target to be observed in the dense point target set to be observed, determine the visibility window corresponding to each dense point target to be observed, and obtain the visibility window set of the dense point target set to be observed. Specifically, the visibility window includes the time point and the side swing range when the available satellite can observe the dense point target to be observed. If imaging observation is performed separately for each dense point target to be observed, that is, each visibility window, the observation efficiency is low and satellite resources are wasted. Therefore, the embodiment of the present invention can perform clustering based on the visibility window by determining the visibility window, thereby reducing frequent adjustments in the satellite imaging process.

[0063] Step S103, clustering the visibility window set of the set of dense point targets to be observed to obtain at least one set of clustering results. Specifically, since the set of dense point targets to be observed includes multiple dense point targets to be observed, a large number of visibility windows can be obtained, and the visibility windows of all the dense point targets to be observed form a visibility window set. The traditional satellite observation scheduling method enables the available satellite to observe each visibility window in the visibility window set respectively, so frequent power on and off and attitude conversion are required, which leads to low observation efficiency and waste of satellite resources. The embodiment of the present invention clusters multiple visibility windows in the visibility window set, and realizes the observation of multiple visibility windows in one observation, that is, the observation of multiple dense point targets to be observed, thereby reducing the number of power on and off and the number of movements of the satellite, improving the observation efficiency and saving satellite resources.

[0064] Step S104, based on the satellite parameter information of the available satellites, the target parameter information of each dense point target to be observed in the set of dense point targets to be observed, and at least one clustering result set, a satellite observation task scheduling model is constructed. Specifically, based on the satellite parameter information, target parameter information, and clustering result set in the above steps S101 to S103, a mathematical model, i.e., a satellite observation task scheduling model, is constructed. By converting the scheduling of satellite observation tasks into the construction of a mathematical model, the observation task scheduling plan of the available satellites can be obtained scientifically and accurately from the solution of the mathematical model, thereby improving the scientific nature of satellite observation task scheduling and optimizing scheduling efficiency.

[0065] Step S105, solve the satellite observation task scheduling model to obtain the target observation tasks of the available satellites. Specifically, by solving the satellite observation task scheduling model, the target observation tasks of the available satellites can be obtained, that is, when imaging and observing any dense point target to be observed, other dense point targets to be observed can be observed without turning on and off and transferring the power, thereby improving the observation efficiency and saving satellite resources.

[0066] The satellite observation task scheduling method based on visibility clustering provided by an embodiment of the present invention determines the visibility window of each dense point target to be observed, thereby clustering the visibility windows of all dense point targets to be observed, so that available satellites can observe as many dense point targets to be observed as possible in a single observation, and build a model based on the clustering result set and then solve it. Since the number of clustering result sets is less than the number of visibility windows, the target observation tasks of available satellites can be obtained at a faster solution speed. Compared with the existing satellite observation scheduling method, the number of satellite conversions is reduced, the satellite observation efficiency and resource utilization are improved, and the satellite planning efficiency is improved.

[0067] In this embodiment, a satellite observation task scheduling method based on visibility clustering is provided, which can be used for electronic devices. The method specifically includes the following steps:

[0068] Step S201, determine the available satellite set, satellite parameter information of each available satellite in the available satellite set, the dense point target set to be observed, and target parameter information of each dense point target to be observed in the dense point target set to be observed. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0069] Step S202, for any available satellite in the available satellite set, based on the satellite parameter information of the available satellite and the target parameter information of each dense point target to be observed in the dense point target set to be observed, determine the visibility window corresponding to each dense point target to be observed, and obtain the visibility window set of the dense point target set to be observed, the satellite parameter information includes three-dimensional space coordinates, and the target parameter information includes longitude and latitude coordinates.

[0070] Specifically, the above step S202 includes:

[0071] Step S2021, for any dense point target to be observed, based on the three-dimensional spatial coordinates of the available satellites at any time and the longitude and latitude coordinates of the dense point target to be observed at the time, according to spatial analytic geometry, determine the visibility window of the available satellites for imaging observation of the dense point target to be observed at the time. Specifically, based on any available satellite S j The three-dimensional space coordinates of the J2000 geocentric inertial coordinate system at time t and any dense point target P to be observed i The longitude and latitude coordinates in the WGS84 coordinate system at time t According to the space analytic geometry calculation, the available satellite S is obtained. j Able to observe the dense point target P to be observed i Visibility window when The visibility window includes the available satellites S j Able to observe the dense point target P to be observed i Observation time point and side swing range Among them, S j represents the jth available satellite in the available satellite set; P i Represents the coordinates of the i-th dense point to be observed in the dense point target set to be observed; Represents the coordinate value of the three-dimensional space coordinate of the jth available satellite on the x-axis; Represents the coordinate value of the three-dimensional space coordinate of the jth available satellite on the y-axis; Represents the coordinate value of the three-dimensional space coordinate of the jth available satellite on the z-axis; The longitude coordinates representing the longitude and latitude coordinates of the i-th dense point to be observed; The latitude coordinates representing the longitude and latitude coordinates of the i-th dense point to be observed; It represents the minimum observable side swing of the kth visibility window obtained by the jth available satellite imaging the coordinates of the ith dense point to be observed; It represents the maximum observable side swing of the kth visibility window obtained by the jth available satellite imaging the coordinates of the ith dense point to be observed. Optionally, the visibility window is calculated according to the spatial analytical geometry, which is a prior art and will not be described here. By determining the visibility window of the available satellite for the dense point target to be observed, clustering can be performed based on the visibility window, thereby reducing the frequent adjustment in the satellite imaging process.

[0072] Step S2022, the visibility windows corresponding to all the dense point targets to be observed in the dense point target set to be observed are used as the visibility window set of the dense point target set to be observed. Specifically, the visibility window of any dense point target to be observed by the available satellite can be obtained through the above step S2021, thereby obtaining the visibility windows corresponding to all the dense point targets to be observed in the dense point target set to be observed, and forming a visibility window set. By forming a visibility window set, support is provided for subsequent clustering based on multiple visibility windows in the visibility window set.

[0073] Step S203, determine the intersection of the side swing ranges corresponding to all visibility windows in the visibility window set. Specifically, the satellite single track energy and the number of observations are limited. In the case of a large number of dense point targets to be observed, if it is chosen to perform imaging separately for each visibility window of the dense point target to be observed, the cost is too high. It can be determined through steps S203 to S206 whether the visibility windows can be clustered, so that the visibility windows that meet certain conditions can be clustered, and the observation of multiple dense point targets to be observed can be completed in one observation, reducing the number of satellite observations, and achieving the purpose of saving resources and improving observation efficiency. Optionally, it can be determined whether clustering can be performed based on the observation time and the observation angle. When clustering judgment is performed from the observation angle, the intersection of the side swing ranges of all visibility windows in the visibility window set is determined.

[0074] Step S204, determining the earliest observation time point and the latest observation time point from the observation time points corresponding to all visibility windows in the visibility window set. Specifically, each visibility window corresponds to an observation time point, and the earliest observation time point and the latest observation time point are determined from the observation time points corresponding to all visibility windows. The earliest observation time point and the latest observation time point can be expressed by the following formulas (1) and (2).

[0075] Cstw=min(tw1,tw2,…,tw n )(1)

[0076] Cetw=max(tw1,tw2,…,tw n )(2)

[0077] Among them, Cstw represents the earliest observation time point; Cetw represents the latest observation time point; n represents the number of visibility windows, that is, the number of dense point targets to be observed; tw n Represents the observation time point corresponding to the nth visibility window.

[0078] Step S205, determining the time difference between the earliest observation time point and the latest observation time point. Specifically, when clustering the observation time, the time difference between the earliest observation time point and the latest observation time point is determined to obtain the total time from the earliest observation to the latest observation end.

[0079] Step S206, when the intersection is not empty and the time difference is less than the maximum single power-on time of the available satellite, it is determined that the visibility window set can be clustered. Specifically, the above-calculated time difference is compared with the maximum single power-on time maxopent of the available satellite. If Cetw-Cstw<maxopent, it is possible to observe from the earliest visibility window to the end of the latest visibility window without shutting down the satellite equipment in the middle, that is, the dense point targets to be observed can be observed uninterruptedly within a single operation cycle of the satellite. When the visibility window set meets the clustering requirements of both observation time and observation angle, the visibility window set can be clustered to reduce the number of switches and attitude changes of the available satellites during observation, which helps to optimize satellite resource utilization.

[0080] Step S207, clustering the visibility window set of the set of dense point targets to be observed to obtain at least one clustering result set, wherein any visibility window corresponding to any dense point target to be observed includes the observation time point and the lateral swing range when the dense point target to be observed can be observed by the available satellite, and the satellite parameter information includes the maximum single power-on time.

[0081] Specifically, the above step S207 includes:

[0082] Step S2071, for any visibility window in the visibility window set, based on the observation time point corresponding to the visibility window and the maximum single power-on time of the available satellite, determine the neighbor window time range of the visibility window. Specifically, by determining the neighbor window time range of the visibility window, a neighbor window close to the observation time point of the visibility window is determined according to the neighbor window time range. Optionally, the neighbor window time range can be expressed by the following formula (3).

[0083]

[0084] Among them, tw i Indicates the observation time point corresponding to the visibility window of the ith dense point target to be observed; maxopent j Indicates the maximum single power-on time of the jth available satellite.

[0085] Step S2072, from the visibility window set, determine a neighbor window that satisfies the neighbor window time range of the visibility window. Specifically, in the visibility window set, if there is any other visibility window other than the visibility window whose observation time point falls within the range of the above formula (3), then the other visibility window is the neighbor window of the visibility window.

[0086] Step S2073: clustering neighbor windows of all visibility windows in the visibility window set to obtain at least one clustering result set.

[0087] In some optional implementations, the above step S2073 includes:

[0088] Step a1, initializing all clustering result sets to be empty. Specifically, all clustering result sets are initialized so that all clustering result sets are empty, which is convenient for subsequent clustering.

[0089] Step a2, determining the visibility window with the most neighbor windows from the visibility window set, taking the visibility window as the center point of any clustering result set, and adding the visibility window to the clustering result set. Specifically, according to the above steps S2071 and S2072, the neighbor windows of each visibility window are determined, and the visibility window with the most neighbor windows is taken as the center point of any clustering result set, so as to perform clustering with the visibility window as the center point.

[0090] Step a3, traverse all neighbor windows of the center point based on the traversal order, and determine whether there is a neighbor window that satisfies the observation angle constraint and the observation time constraint with the center point. Specifically, the traversal order can be in order from small to large according to the absolute value of the difference between the observation time point of the neighbor window and the observation time point of the center point, and other traversal orders can also be used, which is not limited by the embodiment of the present invention. The observation angle constraint and the observation time constraint refer to the above steps S203 to S206, that is, the intersection of the side swing range corresponding to the neighbor window and the side swing range corresponding to the center point is not empty, and the time difference between the observation time point corresponding to the neighbor window and the observation time point corresponding to the center point is less than the maximum single power-on time of the available satellite.

[0091] Step a4: If there is a neighbor window that satisfies the observation angle constraint and the observation time constraint with the center point, the observation time point and the side swing range of the neighbor window are used as the observation time point and the side swing range of the center point, and the neighbor window is added to the clustering result set. Specifically, it is determined whether the neighbor window satisfies the above two constraints at the same time. If so, the center point is updated based on the observation time point and the side swing range of the neighbor window, and the neighbor window is added to the clustering result set where the center point is located.

[0092] Step a5, repeat the above traversal process until all neighbor windows of the center point are traversed once, and a clustering result set is obtained. Specifically, all neighbor windows of the center point are judged in the traversal order, and it is judged whether the neighbor window at the first position in the traversal order satisfies the above two constraints at the same time. If so, the neighbor window is added to the clustering result set where the center point is located, and the observation time point and the side swing range of the center point are updated. If not, the neighbor window at the second position in the traversal order is continued to be judged until all neighbor windows of the center point are traversed once, and a clustering result set where the center point is located is obtained.

[0093] Step a6, remove the clustering result set from the visibility window set, repeat the above process of obtaining the clustering result set until the visibility window set is empty, and obtain at least one clustering result set. Specifically, remove the clustering result set obtained based on the current center point from the visibility window set. Determine the visibility window with the most neighbor windows again from the removed visibility window set, use the visibility window as the center point of the new clustering result set, determine the new clustering result set according to the above steps a3 to a5, and remove the new clustering result set from the visibility window set again until the visibility window set is empty, the clustering ends, and obtains at least one clustering result set. By clustering the visibility window set, the visibility windows in the same clustering result set have close observation time and observation angle, so that the observation of the dense point targets to be observed corresponding to all visibility windows in the clustering result set can be achieved in one observation, thereby reducing the number of satellite power on and off and the number of movements, improving observation efficiency and saving satellite resources.

[0094] It should be noted that, according to the type of available satellite, the clustering result set corresponding to the available satellite can be post-processed. Assuming that the available satellite is a SAR satellite (Synthetic Aperture Radar), the maximum side swing value in the side swing range corresponding to all visibility windows in the clustering result set is used as the observation angle corresponding to the clustering result set. Assuming that the available satellite is an optical satellite, the minimum side swing value in the side swing range corresponding to all visibility windows in the clustering result set is used as the observation angle corresponding to the clustering result set, and the earliest time and the latest time in the observation time points corresponding to all visibility windows are used as the observation start and end time corresponding to the clustering result set. Optionally, the above-mentioned types of available satellites and the corresponding post-processing operations are only examples, and personalized adjustments can be made in actual situations, which are not limited in the embodiments of the present invention.

[0095] Step S208, constructing a satellite observation task scheduling model based on satellite parameter information of available satellites, target parameter information of each dense point target to be observed in the dense point target set to be observed, and at least one clustering result set.

[0096] Specifically, the above step S208 includes:

[0097] Step S2081: Use at least one clustering result set as a decision variable. Specifically, use the clustering result set as a decision variable, and the value of the decision variable determines the final scheduling solution, that is, the scheduling of the satellite observation task is adjusted by changing the clustering result set.

[0098] Step S2082, based on the satellite parameter information of the available satellites, the target parameter information of each dense point target to be observed in the set of dense point targets to be observed, and the decision variables, construct an objective function and constraint conditions. Specifically, the constraint conditions are satellite sway conversion time constraint conditions, satellite single power-on maximum duration constraint conditions, and mission time interval constraint conditions, as examples, and are respectively expressed by the following equations (4) to (6). Optionally, the objective function is expressed by the following equation (7).

[0099] M*(2-x t -x s )+ot s -ct t >trantime j (4)

[0100] Among them, M represents the maximum value, which is equivalent to infinity; x t represents the t-th decision variable, that is, the t-th clustering result set; x s represents the sth decision variable, that is, the sth clustering result set, and x t The execution order is before x s ots Indicates the observation time point corresponding to the s-th decision variable, that is, the earliest observation time point; ct t Indicates the observation time point corresponding to the end of observation of the t-th decision variable, that is, the latest observation time point; j It represents the roll angle conversion time of the jth available satellite.

[0101]

[0102] Among them, s represents the decision variable, that is, the clustering result set; X s represents the number of decision variables, that is, the number of clustering result sets; x s represents the sth decision variable, that is, the sth clustering result set; ot s Indicates the observation time point corresponding to the s-th decision variable, that is, the earliest observation time point; ct s Indicates the observation time point corresponding to the end of observation of the s-th decision variable, that is, the latest observation time point; maxopent j Indicates the maximum single power-on time of the jth available satellite.

[0103] M*(2-x t -x s )+ot s -ct t > interval i (6)

[0104] Among them, M represents the maximum value, which is equivalent to infinity; x t represents the t-th decision variable, that is, the t-th clustering result set; x s represents the sth decision variable, that is, the sth clustering result set, and x t The execution order is before x s ot s Indicates the observation time point corresponding to the s-th decision variable, that is, the earliest observation time point; ct t Indicates the observation time point corresponding to the end of observation of the t-th decision variable, that is, the latest observation time point; interval i It represents the minimum time interval between two consecutive observations of the i-th observation task, that is, the minimum time interval between two consecutive observations of the i-th dense point target to be observed.

[0105]

[0106] Among them, n represents the number of observation tasks, that is, the number of dense point targets to be observed; weight irepresents the observation benefit of the ith observation task, that is, the observation benefit of the ith dense point target to be observed; X t represents the number of decision variables, that is, the number of clustering result sets; x t represents the t-th decision variable, that is, the t-th clustering result set; freq i It represents the observation requirement frequency of the i-th observation task, that is, the observation requirement frequency of the i-th dense point target to be observed.

[0107] Step S2083, based on the decision variables, objective function and constraints, a satellite observation task scheduling model for available satellites is constructed. Specifically, based on the above decision variables, objective function and constraints, a mathematical model is performed on the scheduling problem of the satellite observation tasks for the available satellites to obtain a satellite observation task scheduling model, so that the target observation tasks of the available satellites can be obtained scientifically and accurately in a mathematical solution, which helps to improve planning efficiency.

[0108] Step S209, solving the satellite observation task scheduling model to obtain the target observation tasks of the available satellites.

[0109] Specifically, the above step S209 includes:

[0110] Step S2091, when the decision variables of the satellite observation task scheduling model are constrained by the constraints, the decision variables are adjusted, and the decision variables corresponding to the objective function of the satellite observation task scheduling model reaching the maximum value are used as the target observation tasks of the available satellites. Specifically, the CP-SAT solver can be used to solve the satellite observation task scheduling model to obtain the target observation tasks of the available satellites. The target observation tasks meet the constraints and can make the objective function reach the maximum value. Since the target observation task is represented in the form of a clustering result set, the target observation task is imaged, that is, the dense point targets to be observed in one or more clustering result sets corresponding to the target observation task are imaged. The available satellite does not need to be turned on and off and the attitude conversion during the imaging observation of the target observation task, which improves the observation efficiency and satellite resource utilization.

[0111] In some optional implementations, it is assumed that there are 1000 dense point targets to be observed in any area to be observed, the observation benefit is 14861, and it is assumed that there are 32 available satellites in the available satellite set, specifically including 20 SAR satellites and 12 optical satellites, and the observation start and end time is 2023 / 11 / 20 00:00:00-2023 / 11 / 21 00:00:00. The following Table 1 shows the observation results obtained by applying the satellite observation task scheduling method based on visibility clustering provided by an embodiment of the present invention and the satellite observation scheduling method without clustering in the prior art. It can be seen from Table 1 that compared with the prior art, the scheduling time of the embodiment of the present invention is greatly reduced and the observation benefit is greatly improved.

[0112] Table 1 Observation results

[0113] method Clustering time Modeling solution time Scheduling time Observational benefits Prior art - 304.1 seconds 304.1 seconds 4764.67 Embodiments of the present invention 77.06 seconds 0.34 seconds 77.4 seconds 14861.00

[0114] The satellite observation task scheduling method based on visibility clustering provided by an embodiment of the present invention determines the visibility window of each dense point target to be observed, thereby clustering the visibility windows of all dense point targets to be observed, so that available satellites can observe as many dense point targets to be observed as possible in a single observation, and build a model based on the clustering result set and then solve it. Since the number of clustering result sets is less than the number of visibility windows, the target observation tasks of available satellites can be obtained at a faster solution speed. Compared with the existing satellite observation scheduling method, the number of satellite conversions is reduced, the satellite observation efficiency and resource utilization are improved, and the satellite planning efficiency is improved.

[0115] In this embodiment, a satellite observation task scheduling device based on visibility clustering is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0116] This embodiment provides a satellite observation task scheduling device based on visibility clustering, such as Figure 2 As shown, including:

[0117] The first determination module 201 is used to determine an available satellite set, satellite parameter information of each available satellite in the available satellite set, a dense point target set to be observed, and target parameter information of each dense point target to be observed in the dense point target set to be observed.

[0118] The second determination module 202 is used to determine the visibility window corresponding to each dense point target to be observed for any available satellite in the available satellite set based on the satellite parameter information of the available satellite and the target parameter information of each dense point target to be observed in the dense point target set to be observed, so as to obtain the visibility window set of the dense point target set to be observed.

[0119] The clustering module 203 is used to cluster the visibility window set of the observation dense point target set to obtain at least one clustering result set.

[0120] The construction module 204 is used to construct a satellite observation task scheduling model based on satellite parameter information of available satellites, target parameter information of each dense point target to be observed in the dense point target set to be observed, and at least one clustering result set.

[0121] The solving module 205 is used to solve the satellite observation task scheduling model to obtain the target observation tasks of the available satellites.

[0122] In some optional implementations, the satellite parameter information includes three-dimensional space coordinates, and the target parameter information includes longitude and latitude coordinates;

[0123] The second determining module 202 includes:

[0124] The first determination unit is used to determine, for any dense point target to be observed, a visibility window for the available satellite to perform imaging observation on the dense point target to be observed at a moment in time, based on the three-dimensional spatial coordinates of the available satellites at any moment and the longitude and latitude coordinates of the dense point target to be observed at a moment in time, according to spatial analytic geometry.

[0125] The second determining unit is used to use the visibility windows corresponding to all the dense point targets to be observed in the dense point target set to be observed as the visibility window set of the dense point target set to be observed.

[0126] In some optional implementations, any visibility window corresponding to any dense point target to be observed includes an observation time point and a lateral swing range when the dense point target to be observed can be observed by an available satellite, and the satellite parameter information includes a maximum single power-on time;

[0127] The clustering module 203 includes:

[0128] The third determination unit is used to determine, for any visibility window in the visibility window set, a neighbor window time range of the visibility window based on an observation time point corresponding to the visibility window and a maximum single power-on time of an available satellite.

[0129] The fourth determining unit is used to determine, from the visibility window set, a neighbor window that satisfies the neighbor window time range of the visibility window.

[0130] The clustering unit is used to cluster neighbor windows of all visibility windows in the visibility window set to obtain at least one clustering result set.

[0131] In some optional implementations, before the clustering module 203, the apparatus further includes:

[0132] The third determination module is used to determine the intersection of the side swing ranges corresponding to all visibility windows in the visibility window set.

[0133] The fourth determination module is used to determine the earliest observation time point and the latest observation time point from the observation time points corresponding to all visibility windows in the visibility window set.

[0134] The fifth determination module is used to determine the time difference between the earliest observation time point and the latest observation time point.

[0135] The judgment module is used to judge whether the visibility window set can be clustered when the intersection is not empty and the time difference is less than the maximum single power-on time of the available satellite.

[0136] In some optional implementations, the clustering module 203 includes:

[0137] Initialization unit, used to initialize all clustering result sets to be empty.

[0138] The fifth determining unit is used to determine the visibility window with the most neighbor windows from the visibility window set, take the visibility window as the center point of any clustering result set, and add the visibility window to the clustering result set.

[0139] The judgment unit is used to traverse all neighbor windows of the center point based on the traversal order, and judge whether there is a neighbor window that satisfies the observation angle constraint condition and the observation time constraint condition with the center point.

[0140] The adding unit is used to take the observation time point and side swing range of the neighbor window as the observation time point and side swing range of the center point if there is a neighbor window and the center point satisfying the observation angle constraint and the observation time constraint, and add the neighbor window to the clustering result set.

[0141] The traversal unit is used to repeat the above traversal process until all neighbor windows of the center point are traversed once to obtain a clustering result set.

[0142] The sixth determining unit is used to remove the clustering result set from the visibility window set, and repeat the above process of obtaining the clustering result set until the visibility window set is empty, and at least one clustering result set is obtained.

[0143] In some optional implementations, the construction module 204 includes:

[0144] The seventh determining unit is used to use at least one clustering result set as a decision variable.

[0145] The first construction unit is used to construct an objective function and constraint conditions based on satellite parameter information of available satellites, target parameter information of each dense point target to be observed in the dense point target set to be observed, and decision variables.

[0146] The second construction unit is used to construct a satellite observation task scheduling model for available satellites based on decision variables, objective functions and constraints.

[0147] In some optional implementations, the solution module 205 includes:

[0148] The solving unit is used to adjust the decision variables when the decision variables of the satellite observation task scheduling model are subject to constraints, and use the decision variables corresponding to when the objective function of the satellite observation task scheduling model reaches a maximum value as the target observation task of the available satellite.

[0149] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0150] The satellite observation task scheduling device based on visibility clustering in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0151] The embodiment of the present invention also provides a computer device having the above Figure 2 A satellite observation task scheduling device based on visibility clustering is shown.

[0152] See also Figure 3 , Figure 3 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 3As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 10 is taken as an example.

[0153] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0154] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0155] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0156] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0157] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0158] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0159] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0160] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the present invention.

Claims

1. A satellite observation task scheduling method based on visibility clustering, characterized in that: The method comprises: Determine an available satellite set, satellite parameter information of each available satellite in the available satellite set, a dense point target set to be observed, and target parameter information of each dense point target to be observed in the dense point target set to be observed; For any available satellite in the available satellite set, based on satellite parameter information of the available satellite and target parameter information of each dense point target to be observed in the dense point target set to be observed, determine a visibility window corresponding to each dense point target to be observed, and obtain a visibility window set of the dense point target set to be observed; Clustering the visibility window set of the set of dense point targets to be observed to obtain at least one clustering result set; Building a satellite observation task scheduling model based on the satellite parameter information of the available satellites, the target parameter information of each dense point target to be observed in the set of dense point targets to be observed, and the at least one clustering result set; Solve the satellite observation task scheduling model to obtain the target observation tasks of the available satellites.

2. The method according to claim 1, characterized in that The satellite parameter information includes three-dimensional space coordinates, and the target parameter information includes longitude and latitude coordinates; The step of determining, for any available satellite in the available satellite set, a visibility window corresponding to each dense point target to be observed based on satellite parameter information of the available satellite and target parameter information of each dense point target to be observed in the dense point target set to be observed, and obtaining a visibility window set of the dense point target set to be observed, comprises: For any dense point target to be observed, based on the three-dimensional spatial coordinates of the available satellite at any time and the latitude and longitude coordinates of the dense point target to be observed at the time, according to spatial analytic geometry, determine the visibility window for the available satellite to perform imaging observation on the dense point target to be observed at the time; The visibility windows corresponding to all the dense point targets to be observed in the dense point target set to be observed are used as the visibility window set of the dense point target set to be observed.

3. The method according to claim 1, characterized in that Any visibility window corresponding to any dense point target to be observed includes the observation time point and the side swing range when the available satellite observes the dense point target to be observed, and the satellite parameter information includes the maximum single power-on time; The clustering of the visibility window set of the set of dense point targets to be observed to obtain at least one clustering result set includes: For any visibility window in the visibility window set, determining a neighbor window time range of the visibility window based on an observation time point corresponding to the visibility window and a maximum single power-on time of the available satellite; Determining, from the visibility window set, a neighbor window that satisfies a neighbor window time range of the visibility window; Clustering is performed based on neighbor windows of all visibility windows in the visibility window set to obtain the at least one clustering result set.

4. The method according to claim 1, characterized in that: Before clustering the visibility window set of the set of dense point targets to be observed to obtain at least one clustering result set, the method further includes: Determine the intersection of the side swing ranges corresponding to all visibility windows in the visibility window set; Determining the earliest observation time point and the latest observation time point from the observation time points corresponding to all visibility windows in the visibility window set; Determine the time difference between the earliest observation time point and the latest observation time point; When the intersection is not empty and the time difference is less than the maximum single power-on time of the available satellite, it is determined that the visibility window set can be clustered.

5. The method according to claim 3, characterized in that: The clustering of neighbor windows of all visibility windows in the visibility window set to obtain the at least one clustering result set includes: Initialize all clustering result sets to be empty; Determining a visibility window with the most neighbor windows from the visibility window set, taking the visibility window as the center point of any clustering result set, and adding the visibility window to the clustering result set; Traverse all neighbor windows of the center point based on the traversal order, and determine whether there is a neighbor window that satisfies the observation angle constraint and the observation time constraint with the center point; If there is a neighbor window that satisfies the observation angle constraint and the observation time constraint with the center point, the observation time point and the side swing range of the neighbor window are used as the observation time point and the side swing range of the center point, and the neighbor window is added to the clustering result set; Repeat the above traversal process until all neighbor windows of the center point are traversed once, and obtain the clustering result set; The clustering result set is removed from the visibility window set, and the above process of obtaining the clustering result set is repeated until the visibility window set is empty, thereby obtaining the at least one clustering result set.

6. The method according to claim 1, characterized in that The constructing of a satellite observation task scheduling model based on the satellite parameter information of the available satellites, the target parameter information of each dense point target to be observed in the dense point target set to be observed, and the at least one clustering result set includes: Using the at least one clustering result set as a decision variable; Constructing an objective function and constraint conditions based on satellite parameter information of the available satellites, target parameter information of each dense point target to be observed in the set of dense point targets to be observed, and the decision variables; Based on the decision variables, the objective function and the constraint conditions, a satellite observation task scheduling model for the available satellites is constructed.

7. The method according to claim 6, characterized in that The step of solving the satellite observation task scheduling model to obtain the target observation tasks of the available satellites includes: When the decision variables of the satellite observation task scheduling model are subject to the constraint conditions, the decision variables are adjusted, and the decision variables corresponding to when the objective function of the satellite observation task scheduling model reaches a maximum value are used as the target observation tasks of the available satellites.

8. A satellite observation task scheduling device based on visibility clustering, characterized in that: The device comprises: A first determination module is used to determine an available satellite set, satellite parameter information of each available satellite in the available satellite set, a dense point target set to be observed, and target parameter information of each dense point target to be observed in the dense point target set to be observed; A second determination module is used to determine, for any available satellite in the available satellite set, a visibility window corresponding to each dense point target to be observed based on satellite parameter information of the available satellite and target parameter information of each dense point target to be observed in the dense point target set to be observed, so as to obtain a visibility window set of the dense point target set to be observed; A clustering module, used for clustering the visibility window set of the dense point target set to be observed to obtain at least one clustering result set; A construction module, configured to construct a satellite observation task scheduling model based on the satellite parameter information of the available satellites, the target parameter information of each dense point target to be observed in the set of dense point targets to be observed, and the at least one clustering result set; The solution module is used to solve the satellite observation task scheduling model to obtain the target observation tasks of the available satellites.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the satellite observation task scheduling method based on visibility clustering as described in any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the satellite observation task scheduling method based on visibility clustering according to any one of claims 1 to 7.

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