Responsive synthetic aperture radar constellation imaging method and system for typhoon observation

Abstract

The invention provides a response type synthetic aperture radar constellation imaging method and system for typhoon observation, and the method comprises the steps: building a target observation region, setting a time window, carrying out the grid division of the target region, and forming a to-be-observed target set; determining satellite resources which can be used for executing observation tasks, configuring sensor view field parameters and geometric constraint conditions, and completing initialization; extrapolating the satellite orbit, and obtaining the coverage condition of the constellation in each observation window to the target area; taking maneuvering pulses of all satellites in the constellation as decision variables, and constructing a coverage rate and fuel consumption multi-objective optimization model; performing optimization search on the maneuvering scheme by adopting a multi-target genetic algorithm to obtain a Pareto optimal solution set; screening and comparing the candidate solutions to form an optimal or suboptimal maneuvering sequence scheme; and outputting a corresponding satellite imaging coverage rate and a maneuvering sequence.

Description

Technical Field

[0001] This invention relates to the field of satellite observation technology, and more specifically, to a responsive synthetic aperture radar constellation imaging method and system for typhoon observation. Background Technology

[0002] Synthetic Aperture Radar (SAR) satellites are capable of observing ground targets in all weather and all-time conditions, making them an important space-based remote sensing tool. In complex natural disaster monitoring missions, typhoons, due to their large-scale, rapid movement and uncertain spatiotemporal evolution, place higher demands on the observation capabilities of remote sensing systems. How to achieve rapid response coverage of typhoon areas under constraints such as limited time and fuel resources has become a key issue in SAR satellite constellation mission planning.

[0003] Patent document CN106156417A (application number: CN201610514705.4) discloses a method for optimizing the configuration of a satellite constellation with equal time intervals for rapid revisiting. This method uses the number of satellites, orbital altitude, and revisit time interval as optimization constraints, and leverages a multi-island genetic algorithm to achieve rapid revisiting of a specified target with fewer satellites at equal time intervals. However, this method is only suitable for optimizing fixed targets and is not applicable to the observation of moving targets such as typhoons.

[0004] Patent document CN115755047B (application number: CN202211354871.4) discloses a SAR satellite high-resolution imaging mission planning method. This method considers satellite resource constraints and the requirements of high-resolution imaging missions, and performs mission planning in terms of both attitude maneuvering and timing to improve the observation speed of satellite resources. However, this method only considers satellite attitude maneuvering and does not consider the impact of satellite orbital maneuvering and multi-satellite networking on the imaging mission.

[0005] Patent document CN119784093B (application number: CN202510264964.5) discloses a method for planning giant remote sensing constellations oriented towards regional targets. This method first generates the correspondence between observation grids and imaging satellites within the observation demand period based on the observation priority of the regional target's reference grid, thus obtaining a constellation mission pre-allocation scheme. This method is only applicable to global regional observation mission planning and is not suitable for responsive imaging.

[0006] Patent document CN119440753B (application number: CN202411450179.0) discloses a multi-satellite collaborative task scheduling and planning method based on an adaptive genetic algorithm for fused observations. This method transforms tasks into a weighted meta-task set and calculates selectable satellites and time windows by combining satellite resources, tasks, and attitude constraints. However, this method does not consider dynamic target observation windows and position changes, thus failing to achieve responsive imaging.

[0007] Patent document CN112330091B (application number: CN202011053084.7) discloses an autonomous mission planning method for spaceborne SAR imaging, which solves the problem of autonomous on-orbit imaging mission planning for high-precision, small-swath, multi-target imaging tasks. Based on the characteristics of ground target distribution, this method can determine a reasonable observation sequence for target areas, autonomously arrange imaging tasks, and calculate the final imaging time and angle for each target point. However, this method does not consider the constraint of the target observation window and cannot perform responsive imaging of moving targets such as typhoons.

[0008] In view of the above shortcomings, this invention proposes a responsive synthetic aperture radar (SAR) satellite coverage optimization method for typhoon observation. Based on establishing a target observation set that evolves over time, this method comprehensively considers various engineering constraints in the imaging mission, including fuel consumption constraints and maximum single-use payload uptime, to construct a multi-objective optimization model for coverage and fuel consumption. Through multi-objective optimization, it obtains the optimal or suboptimal maneuver control sequence that meets mission requirements. Compared with existing technologies, this invention can rapidly generate efficient imaging planning schemes under limited fuel and time conditions, achieving rapid response coverage of moving targets such as typhoons. Therefore, at the engineering implementation level, it effectively solves the shortcomings of existing methods in terms of real-time performance, resource constraints, and mission adaptability. Summary of the Invention

[0009] To address the shortcomings of existing technologies, the purpose of this invention is to provide a responsive synthetic aperture radar constellation imaging method and system for typhoon observation.

[0010] According to the present invention, a responsive synthetic aperture radar constellation imaging method for typhoon observation includes: Step S1: Set the observation time window and the set of targets to be observed corresponding to each time window. ;in, Represents the i-th time window The target to be observed is divided into grids to generate meta-observation targets. ;in, Indicates time window The k-th meta-observation target among the targets to be observed, This represents the total number of observed targets in the i-th time window; Step S2: Set up the set of satellites available for mission execution ,in n Indicates the number of satellites; for each satellite Establish initial orbital state Fuel that can be used to perform observation missions Synthetic Aperture Radar Single Power-On Duration And configured with synthetic aperture radar field of view. ;in, and These represent the near-end downward view and the far-end downward view, respectively, completing the initialization of available constellation resources; Step S3: Extrapolate the satellite orbit and obtain the constellation pairs for the target area within each observation window. Coverage status; Step S4: Using the maneuvering pulses of each satellite in the constellation A multi-objective optimization model is constructed for coverage and fuel consumption as decision variables, where Indicates the first j The total number of maneuvers a satellite can perform within the mission window; Step S5: Use a multi-objective genetic algorithm to optimize and search for the maneuver scheme, and obtain the Pareto optimal solution set: ;in, This indicates the coverage of the target area by the constellation within the time window. This indicates the total fuel consumption of the constellation's satellites; Step S6: Process the candidate solution set Compare and select the optimal or second-best maneuver sequence scheme by taking into account task priority, resource consumption balance and time sensitivity. Step S7: Output the corresponding coverage results With the maneuver control sequence This generates responsive imaging planning results under finite fuel constraints.

[0011] Preferably, step S1 includes: when the target data region is not empty, dividing the observation region into grids according to a set resolution to obtain a target set. Otherwise, from the perspective of fuel consumption, the coverage rate can be set directly. maneuver control sequence This triggers step S7.

[0012] Preferably, step S3 includes: calculating each time window Set of targets to be observed by inner constellation satellites The coverage rate is calculated, and the time-series distribution curve of the coverage rate is output.

[0013] Preferably, step S4 includes: Step S4.1: Receive the maneuver pulse sequence for each satellite. As an optimization variable; Step S4.2: Establish the coverage objective function:

[0014] in, express Metatarget within the time window Covered by any satellite field of view, otherwise ; Indicates the total number of meta-targets; Step S4.3: Establish the fuel consumption objective function:

[0015] And set fuel consumption constraints:

[0016] in, This represents the total weight of fuel consumed by the j-th satellite during its observation mission. Indicates the specific impulse of the thruster. This is the acceleration due to gravity.

[0017] Preferably, step S5 includes: Step S5.1: Initialize the maneuver pulse sequence population using a multi-objective optimization algorithm. ; Step S5.2: Calculate the objective function value for each individual. ; Step S5.3: Generate a new generation of population through selection, crossover, and mutation operations until the optimization algorithm converges and the Pareto optimal solution set is obtained. .

[0018] Preferably, step S6 includes: Step S6.1: Process the candidate solution set Sort by task priority and coverage; Step S6.2: Under the condition of ensuring fuel consumption balance and mission timeliness, select the optimal or suboptimal maneuver pulse sequence. .

[0019] According to the present invention, a responsive synthetic aperture radar constellation imaging system for typhoon observation includes: Module M1: Set the observation time window and the set of targets to be observed corresponding to each time window. ;in, Represents the i-th time window The target to be observed is divided into grids to generate meta-observation targets. ;in, Indicates time window The k-th meta-observation target among the targets to be observed, This represents the total number of observed targets in the i-th time window; Module M2: Sets the set of satellites available for mission execution. ,in n Indicates the number of satellites; for each satellite Establish initial orbital state Fuel that can be used to perform observation missions Synthetic Aperture Radar Single Power-On Duration And configured with synthetic aperture radar field of view. ;in, and These represent the near-end downward view and the far-end downward view, respectively, completing the initialization of available constellation resources; Module M3: Extrapolates satellite orbits and obtains constellation pairs for the target region within each observation window. Coverage status; Module M4: Based on the maneuver pulses of each satellite in the constellation A multi-objective optimization model is constructed for coverage and fuel consumption as decision variables, where Indicates the first j The total number of maneuvers a satellite can perform within the mission window; Module M5 uses a multi-objective genetic algorithm to optimize and search for maneuver schemes, obtaining a Pareto optimal solution set: ;in, This indicates the coverage of the target area by the constellation within the time window. This indicates the total fuel consumption of the constellation's satellites; Module M6: For candidate solution sets Compare and select the optimal or second-best maneuver sequence scheme by taking into account task priority, resource consumption balance and time sensitivity. Module M7: Outputs the corresponding coverage results With the maneuver control sequence This generates responsive imaging planning results under finite fuel constraints.

[0020] Preferably, module M1 includes: when the target data region is not empty, dividing the observation region into grids according to a set resolution to obtain a target set. Otherwise, from the perspective of fuel consumption, the coverage rate can be set directly. maneuver control sequence And trigger module M7; The module M3 includes: calculating each time window. Set of targets to be observed by inner constellation satellites The coverage rate is calculated, and the time-series distribution curve of the coverage rate is output.

[0021] Preferably, the module M4 includes: Module M4.1: Transmits the maneuver pulse sequence of each satellite. As an optimization variable; Module M4.2: Establish the coverage objective function:

[0022] in, express Metatarget within the time window Covered by any satellite field of view, otherwise ; Indicates the total number of meta-targets; Module M4.3: Establish the fuel consumption objective function:

[0023] And set fuel consumption constraints:

[0024] in, This represents the total weight of fuel consumed by the j-th satellite during its observation mission. Indicates the specific impulse of the thruster. This is the acceleration due to gravity.

[0025] Preferably, the module M5 includes: Module M5.1: Initializes the maneuver pulse sequence population using a multi-objective optimization algorithm. ; Module M5.2: Calculate the objective function value for each individual. ; Module M5.3: Generates a new generation of population through selection, crossover, and mutation operations until the optimization algorithm converges, yielding the Pareto optimal solution set. ; The module M6 includes: Module M6.1: For candidate solution sets Sort by task priority and coverage; Module M6.2: Select the optimal or suboptimal maneuver pulse sequence while ensuring fuel consumption balance and mission timeliness. .

[0026] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention addresses the dynamic coverage requirements for typhoon observation. Combining the unique field of view and all-weather imaging characteristics of SAR satellites, it establishes a responsive imaging optimization model that considers multiple factors such as maximum payload operating time and fuel availability constraints. By optimizing the selection of maneuver pulse sequences for each satellite in the constellation, rapid coverage of targets can be achieved under limited time and resource conditions. 2. This invention can rapidly generate efficient responsive imaging schemes under limited fuel conditions, improving the satellite's coverage efficiency for sudden mission targets and the utilization rate of mission resources; 3. The responsive coverage optimization framework proposed in this invention is not only applicable to typhoon observation, but can also be extended to scenarios such as disaster monitoring, marine vessel tracking, and large-scale event emergency response, and has good adaptability and application prospects. Attached Figure Description

[0027] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart of a responsive synthetic aperture radar constellation imaging method for typhoon observation. Detailed Implementation

[0028] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0029] Example 1 According to the present invention, a responsive synthetic aperture radar constellation imaging method for typhoon observation is provided, such as... Figure 1 As shown, it includes: Step S10: Set the observation time window and the set of targets to be observed corresponding to each time window. ,in, Indicates the first i Time window The target area is divided into grids to generate meta-observation targets. .in, Indicates time window The first target to be observed k Individual observation targets, Indicates the first i The total number of observed targets within a time window.

[0030] Specifically, step S10 involves: when the target data region is not empty, dividing the observation region into grids according to a set resolution to obtain an initial target set. Otherwise, from a fuel consumption perspective, the coverage rate can be set directly. maneuver control sequence And trigger step S70.

[0031] Step S20: Set up the set of satellites that can be used to perform the mission. ,in n Indicates the number of satellites. For each satellite... Establish initial orbital state Fuel that can be used to perform observation missions Synthetic Aperture Radar Single Power-On Duration And configured with synthetic aperture radar field of view. ,in and These represent the near-end downward view and the far-end downward view, respectively, completing the initialization of available constellation resources.

[0032] Step S30: Extrapolate the satellite orbit and obtain the constellation pairs for the target region within each observation window. Coverage status.

[0033] Specifically, step S30 includes: Step S301: Calculate each time window Inside, the constellation satellites target the set The coverage rate is the union of the coverage areas of each satellite in the constellation over the target set; Step S302: Output the coverage time-series distribution curve to provide a basis for subsequent comparison and selection.

[0034] Step S40, using the maneuvering pulses of each satellite in the constellation A multi-objective optimization model is constructed for coverage and fuel consumption as decision variables, where Indicates the first j The total number of maneuvers a satellite can perform within the mission window; Specifically, step S40 includes: Step S401: Receive the maneuver pulse sequence for each satellite. As an optimization variable; Step S402: Establish the coverage objective function:

[0035] in, express Metatarget within the time window Covered by any satellite field of view, otherwise ; This indicates the total number of meta-targets.

[0036] Step S403: Establish the fuel consumption objective function:

[0037] And set fuel consumption constraints:

[0038] in, Indicates the first j The total weight of fuel consumed by the satellites during their observation missions. Indicates the specific impulse of the thruster. This is the acceleration due to gravity.

[0039] Step S50: A multi-objective genetic algorithm is used to optimize and search for the maneuver scheme, obtaining the Pareto optimal solution set.

[0040] in, This indicates the coverage of the target area by the constellation within the time window. This indicates the total fuel consumption of the constellation's satellites.

[0041] Specifically, step S50 includes: Step S501: Initialize the maneuver pulse sequence population using a multi-objective optimization algorithm. ; .

[0042] Step S502: Calculate the objective function value for each individual. ; Step S503: Generate a new generation of population through selection, crossover, and mutation operations until the optimization algorithm converges and the Pareto optimal solution set is obtained. .

[0043] Step S60: For the candidate solution set Compare and select the optimal or second-best maneuver sequence scheme by taking into account task priority, resource consumption balance and time sensitivity. Specifically, step S60 includes: Step S601: For the candidate solution set Sort by task priority and coverage; Step S602: Under the condition of ensuring fuel consumption balance and mission timeliness, select the optimal or suboptimal maneuver pulse sequence. .

[0044] Step S70: Output the corresponding coverage result With the maneuver control sequence This generates responsive imaging planning results under finite fuel constraints.

[0045] Specifically, step S70 involves outputting the corresponding coverage result. and maneuver control sequence And thus, a final imaging planning scheme is formed.

[0046] According to the present invention, a responsive synthetic aperture radar constellation coverage optimization system for typhoon observation includes: Module M10: Set the observation time window and the set of targets to be observed corresponding to each time window. ,in, Represents the i-th time window The target area is divided into grids to generate meta-observation targets. .in, Indicates time window The k-th meta-observation target among the targets to be observed, Indicates the first i The total number of observed targets within a time window.

[0047] Specifically, module M10 employs the following method: when the target data region is not empty, it divides the observation region into grids according to a set resolution to obtain an initial target set. Otherwise, from a fuel consumption perspective, the coverage rate can be set directly. maneuver control sequence And trigger module M70.

[0048] Module M20 sets the set of satellites available for mission execution. ,in n Indicates the number of satellites. For each satellite... Establish initial orbital state Fuel that can be used to perform observation missions Synthetic Aperture Radar Single Power-On Duration And configured with synthetic aperture radar field of view. ,in and These represent the near-end downward view and the far-end downward view, respectively, completing the initialization of available constellation resources.

[0049] Module M30 extrapolates the satellite orbits and obtains the constellation pairs for the target area within each observation window. Coverage status.

[0050] Specifically, the module M30 includes: Module M301: Calculates each time window Inside, the constellation satellites target the set The coverage rate is the union of the coverage areas of each satellite in the constellation over the target set; Module M302: Outputs the time-series distribution curve of coverage, providing a basis for subsequent comparison and selection.

[0051] Module M40 uses the maneuver pulses of each satellite in the constellation. A multi-objective optimization model is constructed for coverage and fuel consumption as decision variables, where Indicates the first j The total number of maneuvers a satellite can perform within the mission window; Specifically, the module M40 includes: Module M401: Transmits the maneuver pulse sequence of each satellite As an optimization variable; Module M402: Establish the coverage objective function:

[0052] in, express Metatarget within the time window Covered by any satellite field of view, otherwise ; This indicates the total number of meta-targets.

[0053] Module M403: Establish the fuel consumption objective function:

[0054] And set fuel consumption constraints:

[0055] in, This represents the total weight of fuel consumed by the j-th satellite during its observation mission. Indicates the specific impulse of the thruster. This is the acceleration due to gravity.

[0056] Module M50 uses a multi-objective genetic algorithm to optimize and search for maneuver schemes, obtaining a Pareto optimal solution set:

[0057] in, This indicates the coverage of the target area by the constellation within the time window. This indicates the total fuel consumption of the constellation's satellites.

[0058] Specifically, the module M50 includes: Module M501: Initializes the maneuver pulse sequence population using a multi-objective optimization algorithm. ; Module M502: Calculates the objective function value for each individual. ; Module M503: Generates a new generation of population through selection, crossover, and mutation operations until the optimization algorithm converges, yielding the Pareto optimal solution set. .

[0059] Module M60: For candidate solution sets Compare and select the optimal or second-best maneuver sequence scheme by taking into account task priority, resource consumption balance and time sensitivity. Specifically, the module M60 includes: Module M601: For candidate solution sets Sort by task priority and coverage; Module M602: Selects the optimal or suboptimal maneuver pulse sequence while ensuring fuel consumption balance and mission timeliness. .

[0060] Module M70: Outputs the corresponding coverage results With the maneuver control sequence This generates responsive imaging planning results under limited fuel constraints. Specifically, module M70 outputs the corresponding coverage result. and maneuver control sequence And thus, a final imaging planning scheme is formed.

[0061] This invention can rationally allocate the maneuvering and imaging tasks of each satellite in the constellation during typhoon observations within a preset observation window, and can quickly generate optimal or suboptimal maneuvering sequence schemes that meet the constraints. The solutions selected from the candidate solution set recorded in step S60 are the locally optimal solutions chosen for this mission planning, including satellite maneuvering pulse sequences and coverage indicators. With the maneuver control sequence By conducting collaborative observations according to this scheme, SAR satellites can achieve efficient coverage and rapid response to the target set while simultaneously meeting requirements such as the maximum single-use power-on time constraint of the SAR payload, fuel reserve constraint, and observation geometry conditions.

[0062] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0063] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A responsive synthetic aperture radar constellation imaging method for typhoon observation, characterized in that, include: Step S1: Set the observation time window and the set of targets to be observed corresponding to each time window. ;in, Represents the i-th time window The target to be observed is divided into grids to generate meta-observation targets. ;in, Indicates time window The k-th meta-observation target among the targets to be observed, This represents the total number of observed targets in the i-th time window; Step S2: Set up the set of satellites available for mission execution ,in n Indicates the number of satellites; for each satellite Establish initial orbital state Fuel that can be used to perform observation missions Synthetic Aperture Radar Single Power-On Duration And configured with synthetic aperture radar field of view. ;in, and These represent the near-end downward view and the far-end downward view, respectively, completing the initialization of available constellation resources; Step S3: Extrapolate the satellite orbit and obtain the constellation pairs for the target area within each observation window. Coverage status; Step S4: Using the maneuvering pulses of each satellite in the constellation A multi-objective optimization model is constructed for coverage and fuel consumption as decision variables, where Indicates the first j The total number of maneuvers a satellite can perform within the mission window; Step S5: Use a multi-objective genetic algorithm to optimize and search for the maneuver scheme, and obtain the Pareto optimal solution set: ;in, This indicates the coverage of the target area by the constellation within the time window. This indicates the total fuel consumption of the constellation's satellites; Step S6: Process the candidate solution set Compare and select the optimal or second-best maneuver sequence scheme by taking into account task priority, resource consumption balance and time sensitivity. Step S7: Output the corresponding coverage results With the maneuver control sequence This generates responsive imaging planning results under limited fuel constraints.

2. The responsive synthetic aperture radar constellation imaging method for typhoon observation according to claim 1, characterized in that, Step S1 includes: when the target data region is not empty, dividing the observation region into grids according to a set resolution to obtain a target set. Otherwise, from the perspective of fuel consumption, the coverage rate can be set directly. maneuver control sequence This triggers step S7.

3. The responsive synthetic aperture radar constellation imaging method for typhoon observation according to claim 1, characterized in that, Step S3 includes: calculating each time window Set of targets to be observed by inner constellation satellites The coverage rate is calculated, and the time-series distribution curve of the coverage rate is output.

4. The responsive synthetic aperture radar constellation imaging method for typhoon observation according to claim 1, characterized in that, Step S4 includes: Step S4.1: Generate the maneuver pulse sequence for each satellite. As an optimization variable; Step S4.2: Establish the coverage objective function: in, express Metatarget within the time window Covered by any satellite field of view, otherwise ; Indicates the total number of meta-targets; Step S4.3: Establish the fuel consumption objective function: And set fuel consumption constraints: in, This represents the total weight of fuel consumed by the j-th satellite during its observation mission. Indicates the specific impulse of the thruster. This is the acceleration due to gravity.

5. The responsive synthetic aperture radar constellation imaging method for typhoon observation according to claim 1, characterized in that, Step S5 includes: Step S5.1: Initialize the maneuver pulse sequence population using a multi-objective optimization algorithm. ; Step S5.2: Calculate the objective function value for each individual. ; Step S5.3: Generate a new generation of population through selection, crossover, and mutation operations until the optimization algorithm converges and the Pareto optimal solution set is obtained. .

6. The responsive synthetic aperture radar constellation imaging method for typhoon observation according to claim 1, characterized in that, Step S6 includes: Step S6.1: Process the candidate solution set Sort by task priority and coverage; Step S6.2: Under the condition of ensuring fuel consumption balance and mission timeliness, select the optimal or suboptimal maneuver pulse sequence. .

7. A responsive synthetic aperture radar constellation imaging system for typhoon observation, characterized in that, include: Module M1: Set the observation time window and the set of targets to be observed corresponding to each time window. ;in, Represents the i-th time window The target to be observed is divided into grids to generate meta-observation targets. ;in, Indicates time window The k-th meta-observation target among the targets to be observed, This represents the total number of observed targets in the i-th time window; Module M2: Sets the set of satellites available for mission execution. ,in n Indicates the number of satellites; for each satellite Establish initial orbital state Fuel that can be used to perform observation missions Synthetic Aperture Radar Single Power-On Duration And configured with synthetic aperture radar field of view. ;in, and These represent the near-end downward view and the far-end downward view, respectively, completing the initialization of available constellation resources; Module M3: Extrapolates satellite orbits and obtains constellation pairs for the target region within each observation window. Coverage status; Module M4: Based on the maneuver pulses of each satellite in the constellation A multi-objective optimization model is constructed for coverage and fuel consumption as decision variables, where Indicates the first j The total number of maneuvers a satellite can perform within the mission window; Module M5 uses a multi-objective genetic algorithm to optimize and search for maneuver schemes, obtaining a Pareto optimal solution set: ;in, This indicates the coverage of the target area by the constellation within the time window. This indicates the total fuel consumption of the constellation's satellites; Module M6: For candidate solution sets Compare and select the optimal or second-best maneuver sequence scheme by taking into account task priority, resource consumption balance and time sensitivity. Module M7: Outputs the corresponding coverage results With the maneuver control sequence This generates responsive imaging planning results under limited fuel constraints.

8. The responsive synthetic aperture radar constellation imaging system for typhoon observation according to claim 7, characterized in that, The module M1 includes: when the target data region is not empty, dividing the observation region into grids according to a set resolution to obtain a target set. Otherwise, from the perspective of fuel consumption, the coverage rate can be set directly. maneuver control sequence And trigger module M7; The module M3 includes: calculating each time window. Set of targets to be observed by inner constellation satellites The coverage rate is calculated, and the time-series distribution curve of the coverage rate is output.

9. The responsive synthetic aperture radar constellation imaging system for typhoon observation according to claim 7, characterized in that, The module M4 includes: Module M4.1: Transmits the maneuver pulse sequence of each satellite. As an optimization variable; Module M4.2: Establish the coverage objective function: in, express Metatarget within the time window Covered by any satellite field of view, otherwise ; Indicates the total number of meta-targets; Module M4.3: Establish the fuel consumption objective function: And set fuel consumption constraints: in, This represents the total weight of fuel consumed by the j-th satellite during its observation mission. Indicates the specific impulse of the thruster. This is the acceleration due to gravity.

10. The responsive synthetic aperture radar constellation imaging system for typhoon observation according to claim 7, characterized in that, The module M5 includes: Module M5.1: Initializes the maneuver pulse sequence population using a multi-objective optimization algorithm. ; Module M5.2: Calculate the objective function value for each individual. ; Module M5.3: Generates a new generation of population through selection, crossover, and mutation operations until the optimization algorithm converges, yielding the Pareto optimal solution set. ; The module M6 includes: Module M6.1: For candidate solution sets Sort by task priority and coverage; Module M6.2: Select the optimal or suboptimal maneuver pulse sequence while ensuring fuel consumption balance and mission timeliness. .

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