A remote sensing satellite real shooting and real transmission feasible region analysis method

Abstract

A kind of remote sensing satellite real shooting real transmission feasible area analysis method.Belongs to satellite task planning and data transmission capacity analysis technical field.Can quickly calculate the area range of the ground station surrounding that can be executed real shooting real transmission under the condition of given imaging time and satellite state, suitable for task rapid adjustment and emergency response scene.Through directly constructing area boundary and outputting in polygon form, avoid analyzing a large number of discrete ground points one by one, significantly reduce the calculation complexity.Analysis process is based on clear geometric and time constraint calculation, has good program implementation conditions, is convenient for embedding into existing satellite task planning and management system.Get rid of the dependence on third-party commercial simulation software, improve the system autonomous controllable ability, reduce deployment and operation cost.Analysis result is output in polygon area form, is convenient for visual display, spatial analysis and data interaction with other task planning modules.

Description

Technical Field

[0001] This invention belongs to the field of satellite mission planning and data transmission capability analysis technology, specifically involving a method for analyzing feasible areas of remote sensing satellite real-time image and transmission. Background Technology

[0002] With the increasing demands for timeliness in data acquisition from low-Earth orbit remote sensing satellite applications, live imagery and transmission have become crucial technologies in high-time-sensitivity business scenarios. In practical engineering applications, in addition to conducting feasibility analyses for live imagery and transmission of individual ground point targets, mission planners typically need to determine the overall spatial range around a ground station that can be live imagery and transmission under specific time or imaging conditions to support regional mission planning, emergency response, and resource coordination decisions.

[0003] In these application scenarios, the feasible area for live imaging and transmission typically manifests as an irregular region surrounding the ground station. Its boundaries are influenced by a variety of factors, including satellite orbital position, imaging attitude, phased array antenna limitations, imaging data volume, and data transmission time window. This region is not a simple circle or a fixed radius, but rather a complex spatial form that dynamically changes with satellite status and mission conditions.

[0004] Therefore, how to quickly and accurately obtain the area range of a ground station that can perform live shooting and transmission under given conditions without relying on manual simulation and experience judgment, and output it in a calculable and displayable form such as polygons, has become a key problem that urgently needs to be solved in satellite mission planning and business systems.

[0005] In existing technologies, the analysis of areas for live-action shooting and transmission usually still relies on satellite orbit and mission simulation software, and the area determination is completed manually. The typical process includes: establishing satellite orbit, ground station and attitude models in simulation software; setting phased array antenna parameters and imaging attitude; manually deploying a large number of discrete ground points around the ground station; conducting live-action shooting and transmission feasibility simulation analysis for each discrete point; and manually delineating or stitching the boundaries of feasible areas based on the analysis results.

[0006] The above solution has obvious bottlenecks in practical applications: 1. The computational process is severely discretized, resulting in low efficiency. Approximating a continuous region using a large number of discrete points results in high computational complexity, low analysis efficiency, and difficulty in meeting real-time or near-real-time business requirements.

[0007] 2. High dependence on external simulation tools, making system integration difficult. The analysis process relies on third-party commercial software, making it difficult to automate calls and scale up deployments within business systems.

[0008] 3. High degree of human intervention leads to insufficient stability of results. The selection density of data points and the method of boundary splicing rely on human experience, resulting in poor consistency and reproducibility of analysis results.

[0009] 4. Difficult to support rapid recalculation under dynamic conditions When imaging time, attitude, or data transmission parameters change, it is often necessary to re-perform the entire simulation analysis, resulting in a long response cycle.

[0010] Therefore, traditional solutions struggle to meet the requirements of real-time performance, automation, and engineering feasibility for live-shot and live-transmitted area analysis while ensuring analytical accuracy. Summary of the Invention

[0011] To address the aforementioned technical problems, this invention provides a method for analyzing feasible areas for real-time imaging and transmission by remote sensing satellites, used to determine the spatial coverage area around a ground station that can meet the requirements for real-time imaging and transmission under given imaging conditions and data transmission constraints.

[0012] The method is specifically as follows: S1. Obtain the maneuver time required for satellite uploading (attitudeTime); S2. Set a maximum beam scanning angle limitAngle for data transmission; S3. Treat the ground station as an imaging point, calculate the list of visible times of the satellite to the ground station. The list of visible times contains several visible times (visibleTime). Select a visible time (visibleTime) from the list of visible times and proceed to step S4. S4. Based on visibleTime, calculate the data transmission start time (receivingStartTime) and data transmission end time (receivingStopTime) when the ground station can receive satellite data under the staring attitude. S5. Calculate the satellitePositionList, a collection of relevant satellite information between receivingStartTime and receivingStopTime; S6. Obtain the corresponding index visibleTimeindex of satellite information within the visibleTime period in satellitePositionList; S7. Calculate the data transmission time required from the ground station corresponding to the imaging time; S8. Obtain the latest possible imaging time maxImagingTime based on receivingDuration. The satellite position corresponding to this time is downPosition. S9. Obtain the earliest imageable time, minImagingTime, where the satellite position corresponding to this time is upPosition; S10. Loop from roll = -45 degrees → 45 degrees, call Algorithm 1 to obtain the minimum imageable nadir position positionOutput1 and the maximum imageable nadir position positionOutput2 under this lateral swing condition. If the values ​​of positionOutput1 and positionOutput2 are not obtained, proceed to the next loop. S11. Based on the positions of the two satellite sub-points, positionOutput1 and positionOutput2, and the current roll value, call Algorithm 2 to obtain the imaging point positions, point1 and point2, of the satellite under the current roll position; calculate the imaging point positions, leftUpPoint and leftDownPoint, corresponding to upPosition and downPosition under the roll attitude, and end the current loop. S12. Loop from roll = 45 degrees → -45 degrees, call Algorithm 1 to obtain the minimum imageable nadir position positionOutput3 and the maximum imageable nadir position positionOutput4 under this lateral swing condition. If the values ​​of positionOutput3 and positionOutput4 are not obtained, proceed to the next loop. S13. Based on the positions of the two satellite sub-points, positionOutput3 and positionOutput4, and the current roll value, call Algorithm 2 to obtain the imaging point positions, point3 and point4, of the satellite under the current roll position; calculate the imaging point positions, rightUpPoint and rightDownPoint, corresponding to upPosition and downPosition under the roll attitude, and end the current loop. S14. Check if the generated point1, point2, point3, point4, leftUpPoint, leftDownPoint, rightUpPoint, and rightDownPoint are valid. If all are valid, proceed to step S15. If one is invalid, return to step S3 and continue to select any remaining visible time (visibleTime) in the visible time list to proceed to step S4. S15. Generate the actual covering polygon Polygon(point1, point3, point4, point2); S16. Generate the data transfer constraint polygon clipPolygon(leftUp, rightUp, rightDown, leftDown); S17. Perform an intersection operation on the actual coverage polygon and the data transmission constraint polygon to obtain a final polygon. This polygon represents the feasible area of ​​remote sensing satellite real-time image and real-time transmission under the selected visibleTime. Return to step S3 and continue to select the remaining visibleTime in the visibleTime list to enter step S4, until the feasible area of ​​remote sensing satellite real-time image and real-time transmission corresponding to all visibleTime in the visibleTime list is calculated.

[0013] Furthermore, the information in the satellitePositionList collection includes the satellite's current time and its position coordinates in the WGS84 coordinate system at that time. and velocity components .

[0014] Furthermore, maxImagingTime = receivingStopTime - receivingDuration.

[0015] Furthermore, minImagingTime = receivingStartTime + attitudeTime.

[0016] Furthermore, Algorithm 1 is as follows: Obtain the minimum and maximum imageable positions under a certain roll angle condition, starting from the imaging time tm, and loop backward according to a preset time step Δt (1 second): Calculate the corresponding beam scanning angle θ_now at each moment. When θ_now>limitAngle appears for the first time, record the current moment as the latest countable transmission moment t_max and end the search. Starting from the imaging time tm, the time loop proceeds forward according to a preset time step Δt (1 second): Calculate the corresponding beam scanning angle θ_now at each moment. When θ_now>limitAngle appears for the first time, record the current moment as the earliest countable transmission moment t_min and end the search. Returning the satellite positions corresponding to t_min and t_max represents the minimum and maximum imageable nadir positions under a certain roll angle condition.

[0017] Furthermore, the specific method for calculating the beam scanning angle is as follows: S61. Calculation of imaging points under side-swing conditions: Calculate the latitude and longitude of the corresponding ground imaging point based on the satellite's position, velocity, and roll angle. ; S62. Transformation of latitude and longitude to geocentric and Earth-fixed coordinates: Image point With the target point Convert from latitude and longitude to WGS-84 geocentric coordinates: , ; S63. Calculation of spatial distance between three points: Calculate the Euclidean distance between three points. , , ; S64. Final Angle Calculation: Based on the cosine theorem, calculate the angle with the satellite as the vertex and the imaging point and the target point as the two sides. That is, the beam scanning angle: , .

[0018] Furthermore, Algorithm 2 specifically involves calculating the ground intersection point under satellite side-swing conditions to obtain the satellite's position coordinates in the WGS-84 geocentric-ground-fixed coordinate system. and velocity components : and side swing angle and front and rear swing angles ; S71. Establishing the orbital coordinate system: Constructing the transformation matrix from the orbital coordinate system to the Earth-centered, Earth-fixed coordinate system. ; S72. Attitude Rotation Matrix Construction: Construct the attitude rotation matrix from the side sway angle and the forward and backward sway angles. ; in: ; ; It is the identity matrix; S73. Calculation of line of sight direction: The sensor's line of sight is defined in its own coordinate system as ; The direction vector of the line of sight in the Earth-centered Earth-fixed coordinate system is defined as follows: ; Earth ellipsoid model construction: The Earth ellipsoid is defined as... ,in The radius is the equatorial radius. The polar radius; S74. Solving for the intersection of the line of sight and the ellipsoid: Construct the equation of the line of sight as follows: ,in, This indicates the distance the satellite has moved along the observation direction. This indicates the spatial location point corresponding to that distance; By substituting the ray equation representing the direction of satellite observation into the Earth ellipsoid equation, the spatial geometric intersection problem is transformed into a problem of solving a quadratic equation about the path parameters, thereby obtaining the intersection point between the line of sight and the Earth's surface.

[0019] We obtain the quadratic equation:

[0020] in: ; ; ; in, These represent the directional components of the sensor's line of sight in the WGS-84 geocentric coordinate system. Let these represent the satellite's position coordinates in the WGS-84 geocentric-earth-fixed coordinate system; take the condition that... The smallest real root: Intersection coordinates: .

[0021] The beneficial effects of the method described in this invention are as follows: 1. Highly real-time performance, suitable for dynamic task scenarios. It can quickly calculate the area around the ground station where live shooting and transmission can be performed, given the imaging time and satellite status, and is suitable for scenarios of rapid mission adjustment and emergency response.

[0022] 2. High analysis efficiency, avoiding large-scale simulation of discrete points. By directly constructing the region boundary and outputting it in polygon form, the computational complexity is significantly reduced by avoiding the need to analyze a large number of discrete ground points one by one.

[0023] 3. It is engineerable and suitable for integration into business systems. The analysis process is based on well-defined geometric and time-constrained calculations, has good program implementation conditions, and is easy to embed into existing satellite mission planning and management systems.

[0024] 4. Reduces system complexity by eliminating reliance on external simulation tools. This reduces reliance on third-party commercial simulation software, enhances the system's autonomy and controllability, and lowers deployment and maintenance costs.

[0025] 5. Standardized output format facilitates display and subsequent processing. The analysis results are output in the form of polygonal regions, which facilitates visualization, spatial analysis, and data interaction with other task planning modules. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the transmittable area obtained in an embodiment of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0028] Example 1 This embodiment provides a method for analyzing feasible areas captured and transmitted by remote sensing satellites. The specific process of the method is as follows: Step 1: Obtain the maneuver time required for satellite beating. This value depends on the specific satellite. If beating is not required in the current orbit, then attitudeTime = 0.

[0029] Step 2: Set a maximum beam scanning angle limitAngle for data transmission.

[0030] Step 3: Treat the ground station as an imaging point, calculate the list of visible times for the satellite to the ground station. The list of visible times contains several visible times (visibleTime). Select one visible time (visibleTime) from the list of visible times and proceed to Step 4.

[0031] Step 4: Calculate the data transmission start time (receivingStartTime) and data transmission end time (receivingStopTime) of the ground station when it can receive satellite data under the staring attitude, based on visibleTime.

[0032] Step 5: Calculate a set of satellite-related information, satellitePositionList, between receivingStartTime and receivingStopTime. The information in the set includes the satellite's current time and its position coordinates in the WGS84 coordinate system at that time. and velocity components .

[0033] Step 6: Obtain the corresponding index visibleTimeindex of the satellite information within the visibleTime period in satellitePositionList.

[0034] Step 7: Calculate the data transmission time required from the ground station corresponding to the imaging time. The imaging time is the time of this satellite image capture.

[0035] Step 8: Obtain the latest possible imaging time based on receivingDuration: maxImagingTime = receivingStopTime - receivingDuration. Imaging points that exceed this time will not meet the requirement because the data transmission time is insufficient. The satellite position corresponding to this time is downPosition.

[0036] Step 9: Obtain the earliest time when imaging can be performed as minImagingTime = receivingStartTime + attitudeTime, and the satellite position corresponding to this time is upPosition.

[0037] Step 10: Loop from roll = -45 degrees → 45 degrees, call Algorithm 1 to obtain the minimum imageable nadir position positionOutput1 and the maximum imageable nadir position positionOutput2 under this lateral swing condition. If the values ​​of positionOutput1 and positionOutput2 are not obtained, proceed to the next loop.

[0038] Step 11: Based on the positions of the two sub-satellite points, positionOutput1 and positionOutput2, and the current roll value, call Algorithm 2 to obtain the imaging point positions point1 and point2 of the satellite under the current roll (i.e., the intersection of a ray emitted by the satellite in the roll attitude with the Earth's surface). Calculate the imaging point positions leftUpPoint and leftDownPoint corresponding to upPosition and downPosition under the roll attitude, and end the current loop.

[0039] Step 12: Loop from roll = 45 degrees to -45 degrees, call Algorithm 1 to obtain the minimum imageable nadir position positionOutput3 and the maximum imageable nadir position positionOutput4 under this lateral swing condition. If the values ​​of positionOutput3 and positionOutput4 are not obtained, proceed to the next loop.

[0040] Step 13: Based on the positions of the two sub-satellite points, positionOutput3 and positionOutput4, and the current roll value, call Algorithm 2 to obtain the imaging point positions, point3 and point4, of the satellite under the current roll (i.e., the intersection of a ray emitted by the satellite in the roll attitude with the Earth's surface). Calculate the imaging point positions, rightUpPoint and rightDownPoint, corresponding to upPosition and downPosition under the roll attitude, and end the current loop.

[0041] Step 14: Check if the generated point1, point2, point3, point4, leftUpPoint, leftDownPoint, rightUpPoint, and rightDownPoint are valid. The valid indicator is that all 8 data points are calculated and there is no null value as represented in computer language. If all are valid, proceed to step 15. If one is invalid, return to step 3 and continue to select any remaining visible time (visibleTime) in the visible time list to proceed to step 4.

[0042] Step 15: Generate the actual covering polygon Polygon(point1, point3, point4, point2).

[0043] Step 16: Generate the data transfer constraint polygon clipPolygon(leftUp, rightUp, rightDown, leftDown).

[0044] Step 17: Perform an intersection operation on the actual coverage polygon and the data transmission constraint polygon to obtain a final polygon. This polygon represents the feasible area for real-time remote sensing satellite imagery and transmission under the selected visibleTime. Return to Step 3 and continue selecting the remaining visibleTimes in the visibleTime list to proceed to Step 4, until the feasible areas for real-time remote sensing satellite imagery and transmission corresponding to all visibleTimes in the visibleTime list are calculated.

[0045] like Figure 1 The diagram shows a real-time transmittable area around Changchun Station obtained using the method in this embodiment.

[0046] Example 2 This embodiment further defines and explains Embodiment 1.

[0047] Algorithm 1 Description: Obtain the minimum and maximum imageable positions under a certain roll angle condition.

[0048] Starting from the imaging time tm, the time loop proceeds sequentially according to a preset time step Δt (1 second): Calculate the corresponding beam scanning angle θ_now at each moment. When θ_now>limitAngle appears for the first time, record the current moment as the latest countable transmission moment t_max and end the search.

[0049] Starting from the imaging time tm, the time loop proceeds forward according to a preset time step Δt (1 second): Calculate the corresponding beam scanning angle θ_now at each moment. When θ_now>limitAngle appears for the first time, record the current moment as the earliest countable transmission moment t_min and end the search.

[0050] Returning the satellite positions corresponding to t_min and t_max represents the minimum and maximum imageable nadir positions under a certain roll angle condition.

[0051] Algorithm 2 Description: Calculation of ground intersection points under satellite side-swing conditions.

[0052] Obtain the satellite's position coordinates in the WGS-84 geocentric-ground-fixed coordinate system. and velocity components : and side swing angle and front and rear swing angles .

[0053] (1) Establishment of the satellite orbit coordinate system Radial unit vector from the satellite to the Earth's center:

[0054] Considering the Earth's rotational angular velocity The velocity component caused by Earth's rotation:

[0055] Lateral unit vector of the track:

[0056] Forward unit vector of the orbit:

[0057] Construct the transformation matrix from the orbital coordinate system to the Earth-centered Earth-fixed coordinate system:

[0058] The transformation matrix consists of three orthogonal unit basis vectors of the satellite's instantaneous orbital coordinate system. Its column vectors represent the direction cosines of the orbital coordinate axes in the geocentric-geocentric coordinate system. This matrix enables a linear coordinate transformation from the orbital coordinate system to the geocentric-geocentric coordinate system.

[0059] This transformation matrix is ​​essentially equivalent to expressing the satellite's front, side, and bottom directions using the XYZ components of Earth's fixed coordinates.

[0060] (2) Attitude rotation matrix The attitude rotation matrix is ​​constructed from the side sway angle and the front and rear sway angles:

[0061] in:

[0062]

[0063] This is the identity matrix, which uses a three-axis Euler angle representation in attitude transformation, with the rotation order being ZYX. Since this embodiment does not involve yaw attitude control, the yaw angle is set to zero, and its corresponding rotation matrix is ​​the identity matrix. This item is used to maintain the complete three-axis representation of the attitude model so that it can be extended to cases that include yaw control in the future.

[0064] (3) Calculation of line of sight direction The sensor's line of sight is defined in its own coordinate system as:

[0065] The direction vector of the line of sight in the Earth-centered, Earth-fixed coordinate system:

[0066] (4) Earth ellipsoid model The Earth's ellipsoid is defined as:

[0067] in The radius is the equatorial radius. is the polar radius.

[0068] (5) Solving for the intersection of the line of sight and the ellipsoid Line of sight equation:

[0069] in, This indicates the distance the satellite has moved along the observation direction. This indicates the spatial location point corresponding to that distance.

[0070] By substituting the ray equation representing the direction of satellite observation into the Earth ellipsoid equation, the spatial geometric intersection problem can be transformed into a problem of solving a quadratic equation about the path parameters, thereby obtaining the intersection point between the line of sight and the Earth's surface.

[0071] We obtain the quadratic equation:

[0072] in:

[0073]

[0074]

[0075] in, These represent the directional components of the sensor's line of sight in the WGS-84 geocentric coordinate system. These represent the satellite's position coordinates in the WGS-84 geocentric-ground-fixed coordinate system.

[0076] Take the satisfaction The smallest real root: Intersection coordinates: .

[0077] Because Algorithm 1 will eventually provide two satellite positions, and Algorithm 2 will be called based on these two satellite positions, thus obtaining two intersection points.

[0078] (6) Calculation of the latitude and longitude of the intersection point Eccentricity:

[0079] longitude:

[0080] latitude: ,in, .

[0081] Algorithm 3: Calculation method for beam scanning angle The input data is: the satellite's position in the WGS-84 coordinate system. With speed

[0082] Side swing angle

[0083] Latitude and longitude of the ground station

[0084] Output: Angle formed by satellite, imaging point, and ground station That is, the beam scanning angle.

[0085] (1) Calculation of imaging points under lateral swing conditions Calculate the latitude and longitude of the corresponding ground imaging point based on the satellite's position, velocity, and roll angle:

[0086] in This describes the process of calculating the imaging point based on the intersection of the line of sight and the Earth's ellipsoid, which is the calculation process of Algorithm 2. and These represent the satellite's position and velocity in the WGS-84 geocentric coordinate system at a given moment.

[0087] (2) Conversion from latitude and longitude to geocentric coordinates Image point With the target point Convert from latitude and longitude to WGS-84 geocentric coordinates:

[0088]

[0089] (3) Calculation of spatial distance between three points Calculate the Euclidean distance between three points:

[0090]

[0091]

[0092] (4) Calculation of the final included angle Based on the law of cosines, calculate the angle between the satellite (vertices) and the image point and the target point (two sides):

[0093]

[0094] And convert the angle from radians to degrees.

Claims

1. A method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission, characterized in that, The method is specifically as follows: S1. Obtain the maneuver time required for satellite uploading (attitudeTime); S2. Set a maximum beam scanning angle limitAngle for data transmission; S3. Treat the ground station as an imaging point, calculate the list of visible times of the satellite to the ground station. The list of visible times contains several visible times (visibleTime). Select a visible time (visibleTime) from the list of visible times and proceed to step S4. S4. Based on visibleTime, calculate the data transmission start time (receivingStartTime) and data transmission end time (receivingStopTime) when the ground station can receive satellite data under the staring attitude. S5. Calculate the satellitePositionList, a collection of relevant satellite information between receivingStartTime and receivingStopTime; S6. Obtain the corresponding index visibleTimeindex of satellite information within the visibleTime period in satellitePositionList; S7. Calculate the data transmission time required from the ground station corresponding to the imaging time; S8. Obtain the latest possible imaging time maxImagingTime based on receivingDuration. The satellite position corresponding to this time is downPosition. S9. Obtain the earliest imageable time, minImagingTime, where the satellite position corresponding to this time is upPosition; S10. Loop from roll = -45 degrees → 45 degrees, call Algorithm 1 to obtain the minimum imageable nadir position positionOutput1 and the maximum imageable nadir position positionOutput2 under this lateral swing condition. If the values ​​of positionOutput1 and positionOutput2 are not obtained, proceed to the next loop. S11. Based on the positions of the two satellite sub-points, positionOutput1 and positionOutput2, and the current roll value, call Algorithm 2 to obtain the imaging point positions, point1 and point2, of the satellite under the current roll position; calculate the imaging point positions, leftUpPoint and leftDownPoint, corresponding to upPosition and downPosition under the roll attitude, and end the current loop. S12. Loop from roll = 45 degrees → -45 degrees, call Algorithm 1 to obtain the minimum imageable nadir position positionOutput3 and the maximum imageable nadir position positionOutput4 under this lateral swing condition. If the values ​​of positionOutput3 and positionOutput4 are not obtained, proceed to the next loop. S13. Based on the positions of the two satellite sub-points, positionOutput3 and positionOutput4, and the current roll value, call Algorithm 2 to obtain the imaging point positions, point3 and point4, of the satellite under the current roll position; calculate the imaging point positions, rightUpPoint and rightDownPoint, corresponding to upPosition and downPosition under the roll attitude, and end the current loop. S14. Check if the generated point1, point2, point3, point4, leftUpPoint, leftDownPoint, rightUpPoint, and rightDownPoint are valid. If all are valid, proceed to step S15. If one is invalid, return to step S3 and continue to select any remaining visible time (visibleTime) in the visible time list to proceed to step S4. S15. Generate the actual covering polygon Polygon(point1, point3, point4, point2); S16. Generate the data transfer constraint polygon clipPolygon(leftUp, rightUp, rightDown, leftDown); S17. Perform an intersection operation on the actual coverage polygon and the data transmission constraint polygon to obtain a final polygon. This polygon represents the feasible area of ​​remote sensing satellite real-time image and real-time transmission under the selected visibleTime. Return to step S3 and continue to select the remaining visibleTime in the visibleTime list to enter step S4, until the feasible area of ​​remote sensing satellite real-time image and real-time transmission corresponding to all visibleTime in the visibleTime list is calculated.

2. The method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission as described in claim 1, characterized in that, The information in the satellitePositionList collection includes the satellite's current time and its position coordinates in the WGS84 coordinate system at that time. and velocity components .

3. The method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission according to claim 2, characterized in that, maxImagingTime= receivingStopTime - receivingDuration.

4. The method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission according to claim 3, characterized in that, minImagingTime = receivingStartTime + attitudeTime.

5. The method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission according to claim 4, characterized in that, Algorithm 1 is as follows: Obtain the minimum and maximum imageable positions under a certain roll angle condition, and loop backward according to the preset time step Δt, starting from the imaging time tm: Calculate the corresponding beam scanning angle θ_now at each moment. When θ_now>limitAngle appears for the first time, record the current moment as the latest countable transmission moment t_max and end the search. Starting from the imaging time tm, the process iterates forward according to a preset time step Δt: Calculate the corresponding beam scanning angle θ_now at each moment. When θ_now>limitAngle appears for the first time, record the current moment as the earliest countable transmission moment t_min and end the search. Returning the satellite positions corresponding to t_min and t_max represents the minimum and maximum imageable nadir positions under a certain roll angle condition.

6. The method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission according to claim 5, characterized in that, The specific method for calculating the beam scanning angle is as follows: S61. Calculation of imaging points under side-swing conditions: Calculate the latitude and longitude of the corresponding ground imaging point based on the satellite's position, velocity, and roll angle. ; S62. Transformation of latitude and longitude to geocentric and Earth-fixed coordinates: Image point With the target point Convert from latitude and longitude to WGS-84 geocentric coordinates: , ; S63. Calculation of spatial distance between three points: Calculate the Euclidean distance between three points. , , ; S64. Final Angle Calculation: Based on the cosine theorem, calculate the angle with the satellite as the vertex and the imaging point and the target point as the two sides. That is, the beam scanning angle: , .

7. The method for analyzing feasible regions using real-time remote sensing satellite imagery and transmission according to claim 6, characterized in that, Algorithm 2 specifically involves calculating the ground intersection point under satellite side-swing conditions to obtain the satellite's position coordinates in the WGS-84 geocentric-ground-fixed coordinate system. and velocity components : and side swing angle and front and rear swing angles ; S71. Establishing the orbital coordinate system: Constructing the transformation matrix from the orbital coordinate system to the Earth-centered, Earth-fixed coordinate system. ; S72. Attitude Rotation Matrix Construction: Construct the attitude rotation matrix from the side sway angle and the forward and backward sway angles. ; in: ； ； It is the identity matrix; S73. Calculation of line of sight direction: The sensor's line of sight is defined in its own coordinate system as ; The direction vector of the line of sight in the Earth-centered Earth-fixed coordinate system is defined as follows: ; Earth ellipsoid model construction: The Earth ellipsoid is defined as... ,in The radius is the equatorial radius. The polar radius; S74. Solving for the intersection of the line of sight and the ellipsoid: Construct the equation of the line of sight as follows: ,in, This indicates the distance the satellite has moved along the observation direction. This indicates the spatial location point corresponding to that distance; By substituting the ray equation representing the direction of satellite observation into the Earth ellipsoid equation, the spatial geometric intersection problem is transformed into a problem of solving a quadratic equation about the path parameters, thereby obtaining the intersection point between the line of sight and the Earth's surface. We obtain the quadratic equation: ; in: ； ； ； in, These represent the directional components of the sensor's line of sight in the WGS-84 geocentric coordinate system. Let these represent the satellite's position coordinates in the WGS-84 geocentric-earth-fixed coordinate system; take the condition that... The smallest real root: Intersection coordinates: .

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium for storing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-7.

Images