CN117690040A - A target scene determination method, device and equipment - Google Patents

Abstract

The application discloses a target scene determination method, a target scene determination device, computer equipment and a storage medium. The method is applied to the technical field of remote sensing. The method comprises the steps of determining a satellite point track equation in each visible time window of each remote sensor and a corresponding area target, dividing the area target according to the satellite point track equation corresponding to each remote sensor and remote sensor parameters to obtain candidate observation scenes, and determining a target scene from the candidate observation scenes according to continuous observation time required for observing the candidate observation scenes and the corresponding visible time windows. By means of the scheme, the utilization rate of the visible time window can be improved.

Description

A target scene determination method, device and equipment

Technical field

This application relates to the field of remote sensing technology, and specifically to a target scene determination method, device and equipment.

Background technique

In view of the requirement that the strip-shaped area monitoring coverage is large, the image width of the remote sensor is limited, each observation activity can only cover part of the regional target, and the remote sensor needs to perform multiple observation activities to fully cover the regional target, research on strip-oriented The decomposition method of strip area monitoring tasks comprehensively considers factors such as satellite orbit, remote sensor observation range, remote sensor imaging mode, visible time window, and regional target geographical location to reasonably and effectively segment strip area targets, providing information for satellite collaborative planning. enter.

However, in the current scene determination process in satellite collaborative planning, factors such as satellite trajectory characteristics, remote sensor observation range, and regional target geographical location often lead to extreme situations in which target segmentation is unreasonable and the visible time window is wasted.

Contents of the invention

Based on this, it is necessary to provide a target scene determination method, device and equipment that can improve the utilization of the visible time window in view of the above technical problems.

In the first aspect, this application provides a method for determining target scenarios, which includes:

Determine the sub-satellite point trajectory equation within each visible time window between each remote sensor and the corresponding regional target; each remote sensor has its own remote sensor parameters;

Segment the regional targets according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios;

Based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window, the target scene is determined from the candidate observation scene.

In one embodiment, determining the sub-satellite point trajectory equation within each visible time window between each remote sensor and the corresponding regional target includes:

Select remote sensors based on targets in each region, and determine the visible time window between each remote sensor and the target in the corresponding region;

Use specific software to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the target in the corresponding area.

In one embodiment, the regional targets are segmented according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios, including:

Select the unprocessed visible time window;

Determine the observation range of the remote sensor based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to the remote sensor corresponding to the unprocessed visible time window;

According to the preselected regional target segmentation mode, the regional targets are segmented within the observation range to obtain candidate observation scenes.

In one embodiment, the regional targets are segmented within the observation range according to the preselected regional target segmentation mode to obtain a candidate observation scene, including:

When the preselected regional target segmentation mode is the strip segmentation mode, segment the regional target within the observation range according to the strip segmentation mode to obtain a candidate observation scene.

In one embodiment, when the preselected regional target segmentation mode is the strip segmentation mode, the regional target is segmented within the observation range according to the strip segmentation mode to obtain a candidate observation scene, including:

When the preselected regional target division mode is the strip division mode, divide the regional target into a set of mutually parallel strips;

When the remote sensor adopts single scene mode for imaging, the strip set within the observation range is divided into single scenes to obtain candidate observation scenes.

In one embodiment, the target scene is determined from the candidate observation scenes based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window, including:

Select an unvisited candidate observation scene as the current observation scene;

According to the flight speed and observation range of the remote sensor, calculate the continuous observation time of the remote sensor observation range;

Based on the continuous observation time and the corresponding visible time window, determine whether the current observation scene is the target scene.

In one embodiment, determining whether the current observation scene is a target scene based on the continuous observation time and the corresponding visible time window includes:

Determine whether the continuous observation time matches the corresponding visible time window;

If so, the current observation scene is determined to be the target scene.

In a second aspect, this application also provides a target scene determination device, which includes:

The equation determination module is used to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target; each remote sensor has its own remote sensor parameters;

The segmentation module is used to segment regional targets based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios;

The scene determination module is used to determine the target scene from the candidate observation scenes based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window.

In a third aspect, this application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the above target scene determination method are implemented.

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the above target scene determination method are implemented.

The above target scene determination method determines the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target, and then segments the regional target according to the sub-satellite point trajectory equation corresponding to each remote sensor and the remote sensor parameters, and obtains Candidate observation scenes are used to determine the target scene from the candidate observation scenes based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window. Compared with the extreme situations in the existing technology methods that often lead to unreasonable target segmentation and waste of visible time windows, the target scene determination method of this application can determine regional targets based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor. Segmentation is performed, and since the sub-satellite point trajectory equation and remote sensor parameters are obtained based on the corresponding remote sensors, the credibility is high, allowing the regional targets to be segmented based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor. The segmentation is more reasonable and improves the utilization of the visible time window.

Description of the drawings

Figure 1 is a schematic flowchart of a target scene determination method in an embodiment;

Figure 2 is a schematic flowchart of determining the sub-satellite point trajectory equation in one embodiment;

Figure 3 is a schematic flowchart of determining candidate observation scenarios in one embodiment;

Figure 4 is a schematic flowchart of determining a target scenario in one embodiment;

Figure 5 is a structural block diagram of a target scene determination device in one embodiment;

Figure 6 is an internal structure diagram of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

In view of the requirement that the strip-shaped area monitoring coverage is large, the image width of the remote sensor is limited, each observation activity can only cover part of the regional target, and the remote sensor needs to perform multiple observation activities to fully cover the regional target, research on strip-oriented The decomposition method of strip area monitoring tasks comprehensively considers factors such as satellite orbit, remote sensor observation range, remote sensor imaging mode, visible time window, and regional target geographical location to reasonably and effectively segment strip area targets, providing information for satellite collaborative planning. enter. However, in the current scene determination process in satellite collaborative planning, factors such as satellite trajectory characteristics, remote sensor observation range, and regional target geographical location often lead to extreme situations in which target segmentation is unreasonable and the visible time window is wasted. Based on this, embodiments of the present application provide a target scene determination method to improve the above technical problems.

In one embodiment, Figure 1 is a target scene determination method provided according to an embodiment of the present application, and the method is applied to a server for illustration. The method includes the following steps:

S101. Determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target.

Optionally, each remote sensor has its own remote sensor parameters. It can be seen that the time window can be the time window between the remote sensor and the target in the entire area; the sub-satellite point trajectory equation can be the curve formed by all sub-satellite points during the movement of the satellite around the earth in the time window.

Specifically, the satellite orbit model built into professional software or the existing domestic satellite orbit model is used to determine the sub-satellite point trajectory equation within each visible time window.

It should be noted that according to user requirements in terms of image type, ground resolution, remote sensing resource preferences, etc., appropriate satellites and remote sensors are allocated, and the set of visible time windows for remote sensors and regional targets to be observed is calculated.

S102: Segment the regional targets according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios.

Optionally, when the strip area monitoring coverage is large, the image width of the remote sensor is limited, and each observation activity can only cover part of the regional target. The remote sensor needs to perform multiple observation activities to fully cover the area. At this time, the strip-shaped area targets need to be segmented to completely cover the needs of the area targets.

S103: Determine the target scene from the candidate observation scenes according to the continuous observation time required to observe the candidate observation scene and the corresponding visible time window.

Optionally, determine the continuous observation time required to observe the candidate observation scene and the corresponding visible time window, and compare the similarity between the continuous observation time and the corresponding visible time window. When the similarity exceeds the predetermined time window, When setting the similarity threshold and determining the matching of the continuous observation time and the corresponding visible time window, the current candidate observation scene can be determined as the target scene. Otherwise, delete the current candidate observation scenario from the candidate observation scenarios.

The above target scene determination method determines the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target, and then segments the regional target according to the sub-satellite point trajectory equation corresponding to each remote sensor and the remote sensor parameters, and obtains Candidate observation scenes are used to determine the target scene from the candidate observation scenes based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window. Compared with the extreme situations in the existing technology methods that often lead to unreasonable target segmentation and waste of visible time windows, the target scene determination method of this application can determine regional targets based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor. Segmentation is carried out, and since the sub-satellite point trajectory equation and remote sensor parameters are obtained based on the corresponding remote sensors, the credibility is high, so that the regional targets can be classified according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor. The segmentation is more reasonable and improves the utilization of the visible time window.

On the basis of the above embodiment, the steps of determining the sub-satellite point trajectory equation are decomposed and refined through Figure 2. As shown in Figure 2, it includes the following implementation process:

S201. Select remote sensors based on targets in each region, and determine the visible time window between each remote sensor and the target in the corresponding region.

Optionally, after each regional target is determined, based on the principle of the shortest distance between each regional target and the remote sensor, select the remote sensor for each regional target, and determine the visible time window for each remote sensor and its corresponding regional target.

S202, use specific software to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target.

Optionally, use software such as STK (Satellite Tool Kit) to determine the subsatellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target.

It can be understood that this embodiment provides a possible implementation method for determining the sub-satellite point trajectory equation, which lays a foundation for subsequent determination of the target scenario.

On the basis of the above embodiments, the steps for determining candidate observation scenes are decomposed and refined through Figure 3 . As shown in Figure 3, it includes the following implementation process:

S301: Select an unprocessed visible time window.

Optional, assuming required within a given time frame Arrange imaging reconnaissance satellite remote sensors (usually within 24 hours)/> , for multiple regional targets/> Make observations and know the range definitions of all regional targets in their respective plane coordinate systems/> , image type requirements, remote sensor parameters, lighting condition requirements and other information, set any remote sensor/> For regional targets/> The set of time windows is , of which/> For remote sensors/> with regional goals/> The total number of visible time windows, for any time window/> , the local trajectory equation of the satellite platform where the remote sensor is located is ,/> , of which/> and/> are respectively the abscissa coordinate of the starting point and the end point of the trajectory line.

Optionally, select an unprocessed time window ,/> ,/> ,/> , .

S302: Determine the observation range of the remote sensor based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to the remote sensor corresponding to the unprocessed visible time window.

Based on its corresponding sub-satellite point trajectory equation and remote sensor Calculate the observation range of the remote sensor in the plane Cartesian coordinate system/> , where the observation range of the remote sensor refers to the area that can be observed by adjusting the side angle and front and rear elevation angles while meeting the spatial resolution requirements.

S303: Segment the regional targets within the observation range according to the preselected regional target segmentation mode to obtain candidate observation scenes.

Optionally, determine the regional target segmentation mode preselected by the user, and determine candidate observation scenarios according to the situation after determining the regional target segmentation mode preselected by the user.

Specifically, when the preselected regional target segmentation mode is the strip segmentation mode, the regional target is segmented into a set of mutually parallel strips, and when the remote sensor adopts single scene mode imaging, the objects within the observation range are The strip set is divided into single scenes to obtain candidate observation scenes; when the preselected regional target segmentation mode is manual intervention mode, candidate observation scenes are screened from the user-predefined scene reference library according to the observation range of the remote sensor. .

It can be understood that this embodiment provides a possible implementation method for determining candidate observation scenarios, which lays a foundation for subsequent determination of target scenarios.

On the basis of the above embodiments, the steps of determining the target scene are decomposed and refined through Figure 4 . As shown in Figure 4, it includes the following implementation process:

S401: Select an unvisited candidate observation scene as the current observation scene.

S402: Calculate the continuous observation time of the remote sensor's observation range based on the flight speed and observation range of the remote sensor.

Optionally, select an unvisited candidate observation scene from the candidate observation scenes as the current observation scene, and calculate the continuous observation time required for remote sensing resources to complete the observation based on the flight speed of the satellite platform and the coverage of the observation scene.

S403: Determine whether the current observation scene is the target scene according to the continuous observation time and the corresponding visible time window.

Optionally, calculate the visible time window of the current observation scene and the corresponding remote sensor within the specified orbit circle. The method of calculating the time window of the current observation scene is: use the coordinate projection inverse formula to convert the coordinates of the boundary vertices of the observation scene from the plane coordinates The system is converted to the geodetic coordinate system, and then these longitude and latitude coordinates are used to generate the corresponding regional target definition in the STK software, and the STK software is used to calculate the visible time window between the remote sensor and the current observation scene. At this stage, the remote sensor used to calculate the continuous observation time requirement must be the same as the remote sensor used to segment the scene.

After the continuous observation time and the corresponding visible time window, in order to obtain the target scene, it is necessary to determine whether the continuous observation time and the corresponding visible time window match; when the continuous observation time and the corresponding visible time window match, determine the current observation scene is the target scene; if the continuous observation time does not match the corresponding visible time window, the current observation scene will be deleted.

It can be understood that this embodiment provides a possible implementation method for determining the target scenario, which lays a foundation for subsequent determination of the target scenario.

It should be understood that although the steps in the flowcharts involved in the above-mentioned embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above embodiments may include multiple steps or stages. These steps or stages are not necessarily executed at the same time, but may be completed at different times. The execution order of these steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

Based on the same inventive concept, embodiments of the present application also provide a target scene determination device for implementing the above-mentioned target scene determination method. The solution to the problem provided by this device is similar to the solution recorded in the above method. Therefore, for the specific limitations in the embodiments of one or more target scene determination devices provided below, please refer to the above description of the target scene determination method. Limitations will not be repeated here.

In one embodiment, FIG. 5 shows a structural block diagram of a target scene determination device in an embodiment. As shown in Figure 5, a target scene determination device 5 is provided. The device 5 includes: an equation determination module 50, a segmentation module 51 and a scene determination module 52, wherein:

The equation determination module 50 is used to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target.

Among them, each remote sensor has its own remote sensor parameters.

The segmentation module 51 is used to segment regional targets according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenes.

The scene determination module 52 is used to determine the target scene from the candidate observation scenes based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window.

The above-mentioned target scene determination device determines the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target, and then segments the regional target according to the sub-satellite point trajectory equation corresponding to each remote sensor and the remote sensor parameters, and obtains Candidate observation scenes are used to determine the target scene from the candidate observation scenes based on the continuous observation time required to observe the candidate observation scene and the corresponding visible time window. Compared with the extreme situations in the prior art devices that often lead to unreasonable target segmentation and waste of visible time windows, the target scene determination device of the present application can determine regional targets based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor. Segmentation is performed, and since the sub-satellite point trajectory equation and remote sensor parameters are obtained based on the corresponding remote sensors, the credibility is high, allowing the regional targets to be segmented based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor. The segmentation is more reasonable and improves the utilization of the visible time window.

In one embodiment, the target scene determination system also includes an image sensor. The image sensor is interconnected with an analog-to-digital converter and a central control processor. The above equation determination module 50 is specifically used to:

Select a remote sensor based on each regional target, and determine the visible time window of each remote sensor and the corresponding regional target; use specific software to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target.

In one embodiment, the above-mentioned segmentation module 51 includes:

The first selection unit is used to select an unprocessed visible time window;

The first determination unit is used to determine the observation range of the remote sensor based on the sub-satellite point trajectory equation corresponding to the remote sensor corresponding to the unprocessed visible time window and the remote sensor parameters;

The segmentation unit is used to segment regional targets within the observation range according to the preselected regional target segmentation mode to obtain candidate observation scenes.

In one embodiment, the above-mentioned dividing unit includes:

The segmentation subunit is used to segment regional targets within the observation range according to the strip segmentation mode to obtain candidate observation scenes when the preselected regional target segmentation mode is the strip segmentation mode.

In one embodiment, the above-mentioned segmentation subunit is specifically used for:

When the preselected regional target segmentation mode is the strip segmentation mode, the regional target is segmented into a set of parallel strips; when the remote sensor adopts single scene mode imaging, the strip set within the observation range is segmented. into a single scene to obtain a candidate observation scene.

In one embodiment, the above-mentioned scene determination module 52 includes:

The second selection unit is used to select an unvisited candidate observation scene as the current observation scene;

A calculation unit used to calculate the continuous observation time of the remote sensor's observation range based on the flight speed and observation range of the remote sensor;

The second determination unit is used to determine whether the current observation scene is the target scene according to the continuous observation time and the corresponding visible time window.

In one embodiment, the above-mentioned second determining unit is specifically used to:

Determine whether the continuous observation time matches the corresponding visible time window; if so, determine the current observation scene as the target scene.

Each module in the above target scene determination device can be implemented in whole or in part by software, hardware, and combinations thereof. Each of the above modules may be embedded in or independent of the processor of the computer device in the form of hardware, or may be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be shown in Figure 6 . The computer device includes a processor, memory, network interface, and transceiver connected by a system bus. Wherein, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The transceiver of the computer device is used to perform operations of receiving data or transmitting data under the control of the processor. The non-volatile storage medium stores operating systems, computer programs and databases. This internal memory provides an environment for the execution of operating systems and computer programs in non-volatile storage media. The computer device's database is used to store data such as sample data. The network interface of the computer device is used to communicate with external terminals through a network connection. The computer program implements a target scenario determination method when executed by a processor.

Those skilled in the art can understand that the structure shown in Figure 6 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Specifically, the computer equipment More or fewer components may be included than shown in the figures, or certain components may be combined, or may have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. For the principles and specific processes implemented by the processor in each embodiment, please refer to the target scene determination method in the previous embodiments. The descriptions in the embodiments will not be repeated here.

In one of the embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the principles and specific processes in each embodiment can be realized by referring to the target scenario determination in the previous embodiments. The descriptions in the method embodiments will not be repeated here.

It should be noted that the information involved in this application (including but not limited to information related to the observation scene and remote sensor parameters in this application) is information or data fully authorized by all parties.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage. In the media, when executed, the computer program may include the processes of the above method embodiments. Any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetic variable memory (Magnetoresistive Random) Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene memory, etc. Volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration and not a limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM). The databases involved in the various embodiments provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include blockchain-based distributed databases, etc., but are not limited thereto. The processors involved in the various embodiments provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to this.

The technical features of the above embodiments can be combined in any way. To simplify the description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, all possible combinations should be used. It is considered to be within the scope of this manual.

The above-described embodiments only express several implementation modes of the present application, and their descriptions are relatively specific and detailed, but should not be construed as limiting the patent scope of the present application. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all fall within the protection scope of the present application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims (10)

1. A target scene determination method, characterized in that the method includes: Determine the sub-satellite point trajectory equation within each visible time window between each remote sensor and the corresponding regional target; each remote sensor has its own remote sensor parameters; Segment the regional targets according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios; The target scene is determined from the candidate observation scenes according to the continuous observation time required for observing the candidate observation scene and the corresponding visible time window. 2. The method according to claim 1, characterized in that determining the sub-satellite point trajectory equation within each visible time window of each remote sensor and corresponding regional target includes: Select remote sensors based on targets in each region, and determine the visible time window between each remote sensor and the target in the corresponding region; Use specific software to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the target in the corresponding area. 3. The method according to claim 1, characterized in that the regional targets are segmented according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios, including: Select the unprocessed visible time window; Determine the observation range of the remote sensor according to the sub-satellite point trajectory equation and remote sensor parameters corresponding to the remote sensor corresponding to the unprocessed visible time window; According to the preselected regional target segmentation mode, the regional target is segmented within the observation range to obtain a candidate observation scene. 4. The method according to claim 3, characterized in that, segmenting regional targets within the observation range according to a preselected regional target segmentation mode to obtain candidate observation scenes includes: When the preselected regional target segmentation mode is the strip segmentation mode, segment the regional target within the observation range according to the strip segmentation mode to obtain a candidate observation scene. 5. The method according to claim 4, characterized in that, when the preselected regional target segmentation mode is a strip segmentation mode, the regional target is detected within the observation range according to the strip segmentation mode. Carry out segmentation to obtain candidate observation scenes, including: When the preselected regional target division mode is the strip division mode, divide the regional target into a set of mutually parallel strips; When the remote sensor adopts single scene mode for imaging, the strip set within the observation range is divided into single scenes to obtain candidate observation scenes. 6. The method according to claim 5, wherein the target scene is determined from the candidate observation scene according to the continuous observation time required for observing the candidate observation scene and the corresponding visible time window, include: Select an unvisited candidate observation scene as the current observation scene; Calculate the continuous observation time for the remote sensor to observe the observation range according to the flight speed and observation range of the remote sensor; According to the continuous observation time and the corresponding visible time window, it is determined whether the current observation scene is a target scene. 7. The method of claim 6, wherein determining whether the current observation scene is a target scene according to the continuous observation time and the corresponding visible time window includes: Determine whether the continuous observation time and the corresponding visible time window match; If so, the current observation scene is determined to be the target scene. 8. A target scene determination device, characterized in that the device includes: The equation determination module is used to determine the sub-satellite point trajectory equation within each visible time window of each remote sensor and the corresponding regional target; each remote sensor has its own remote sensor parameters; The segmentation module is used to segment regional targets based on the sub-satellite point trajectory equation and remote sensor parameters corresponding to each remote sensor to obtain candidate observation scenarios; A scene determination module, configured to determine a target scene from the candidate observation scenes according to the continuous observation time required for observing the candidate observation scene and the corresponding visible time window. 9. A computer device, comprising a memory and a processor, the memory stores a computer program, characterized in that when the processor executes the computer program, the method of any one of claims 1 to 7 is implemented. step. 10. A computer-readable storage medium with a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.