Rotary scanning satellite attitude control efficiency evaluation method and system based on simulation image MTF test

Abstract

The invention discloses a rotary scanning satellite attitude control efficiency evaluation method and system based on a simulation image MTF test, and relates to the field of remote sensing satellite attitude control efficiency evaluation. The problems that a current rotary scanning remote sensing satellite has no real in-orbit image, and there is no effective measurement and evaluation method for the relation among satellite attitude control precision, stability and image quality are solved. The method comprises the following steps: establishing a load attitude controller, a platform attitude controller and a platform position controller to compensate a satellite; a satellite load time domain curve is obtained through simulation according to the compensated satellite and dynamics simulation software; importing the satellite load time domain curve into an image simulation system for simulation imaging; processing the analog image by adopting an inclined edge method to obtain an edge image; and obtaining vertical-rail and along-rail MTFs according to the blade edge image, and evaluating the influence of a control algorithm on the in-rail imaging quality. The method is applied to the field of remote sensing satellite imaging simulation.

Description

Technical Field

[0001] The invention relates to the field of remote sensing satellite attitude control effectiveness evaluation, and in particular to a rotation scanning satellite attitude control effectiveness evaluation method based on simulated image MTF test. Background Art

[0002] In order to solve the problem of the mutual restriction between resolution and width of current optical remote sensing satellites, the patent "A method for rapid rotation of satellites with ultra-wide width swing scanning" proposes a method of vertical rotation scanning of payloads to achieve ultra-wide width detection of thousands of kilometers. Under this new system, the satellite consists of a three-axis stable platform oriented to the earth, a rotating payload and a magnetic suspension bearing. During the on-orbit operation, it is affected by various interference torques such as dynamic and static imbalance of the payload. A large number of scholars have conducted control method research on the dynamic characteristics of such satellites, for example, Payload-oriented control scheme for rotatingpayload satellite considering inertia uncertainties and measurement error, Chinese Journal of Aeronautics, (2023), 36 (10): 335–352 (Payload-centered control strategy for rotating payload satellite considering inertia uncertainties and measurement error), but the current literature almost all measures the effectiveness of attitude control algorithms by comparing the final time domain attitude curve. Due to the lack of real on-orbit data, there is no effective measurement and evaluation method for the relationship between satellite attitude control accuracy, stability and image quality. Summary of the invention

[0003] The present invention solves the problem that there is no real on-orbit image of the current rotating scanning remote sensing satellite, and there is no effective measurement and evaluation method for the relationship between satellite attitude control accuracy, stability and image quality. A rotating scanning satellite attitude control efficiency evaluation method based on simulated image MTF test is proposed. The method comprises:

[0004] S1: Establish a payload attitude controller, a platform attitude controller and a platform position controller to compensate the satellite, including compensating for the imbalance of the rotating load and the vibration interference of the flexible solar wing;

[0005] S2: obtain the satellite payload time domain curve based on the compensated satellite and dynamic simulation software simulation;

[0006] S3: The satellite payload time domain curve is imported into the image simulation system. The image simulation system interpolates the time series according to the current simulation time to obtain the actual attitude of the satellite at the current time, and performs imaging simulation under the current attitude to obtain a simulated image.

[0007] S4: Use the tilted edge method to perform MTF test on the simulated image and obtain the edge image. According to the edge image, obtain the vertical and along-track MTFs to evaluate the impact of the control algorithm on the on-track imaging quality.

[0008] Furthermore, a preferred method is proposed, wherein the load attitude controller is established in step S1, including:

[0009]

[0010] Among them, T p is the load control moment, J z is the moment of inertia tensor of the load system, is the first-order derivative of the desired angular velocity of the load, ω p is the actual angular velocity of the load, is the corresponding cross product antisymmetric matrix, ω pe is the load error angular velocity, R spw D pw is the coupling coefficient between the load flywheel rotation and the load attitude motion, is the fixed axis rotation angular velocity of the load flywheel, q pev is the vector part of the load error quaternion, k p ,d p To control the gain.

[0011] Furthermore, a preferred method is proposed, wherein the step S1 of establishing a platform attitude controller comprises:

[0012]

[0013] Among them, T b is the platform control torque, J s is the moment of inertia tensor of the platform system, is the first-order derivative of the platform's desired angular velocity, ω b is the actual angular velocity of the platform, is the corresponding cross product antisymmetric matrix, ω be is the platform error angular velocity, R swj D wj is the coupling coefficient between the platform flywheel rotation and the platform attitude motion (j=1,2,3), is the fixed-axis rotation angular velocity of the platform flywheel, is a variable, k b and d b To control the gain.

[0014] Furthermore, a preferred embodiment is proposed, in which the platform position controller in step S1 comprises:

[0015]

[0016] Among them, F ms is the platform position control force, M s is the platform quality, X e is the position control error, k,μ are controller parameters, is the interference observation value.

[0017] Furthermore, a preferred method is proposed, wherein step S3 comprises:

[0018] For the attitude angle curve of the current working condition, 50 groups of time series with a duration of 30ms are randomly selected within the stable phase time interval and imported into the simulation system in csv format. One group of time series is selected with the maximum angular velocity modulus as the starting point;

[0019] The simulation software is used to interpolate the time series according to the current simulation time to obtain the actual attitude of the satellite at the current time, and imaging simulation is performed under the current attitude to obtain a simulated image.

[0020] Furthermore, a preferred embodiment is proposed, wherein the time interval of the stable phase is 20s to 80s.

[0021] Furthermore, a preferred method is proposed, wherein step S4 comprises:

[0022] Set a checkerboard target model with a side length of 10 km at the specified latitude and longitude position of the earth model;

[0023] The two sides of the target form angles with the along-track direction and the vertical-track direction of the satellite respectively;

[0024] The vertical and along-track MTFs are obtained by extracting the edge images at the junction of the black area and the white area in two directions of the target.

[0025] The influence of the control algorithm on the on-track imaging quality is evaluated based on the vertical and along-track MTF.

[0026] Based on the same inventive concept, the present invention also proposes a rotating scanning satellite attitude control effectiveness evaluation system based on simulated image MTF test, the system comprising:

[0027] A compensation unit is used to establish a payload attitude controller, a platform attitude controller and a platform position controller to compensate the satellite, including compensation for the imbalance of the rotating load and the vibration interference of the flexible solar wing;

[0028] A time domain curve acquisition unit is used to acquire a satellite payload time domain curve according to the compensated satellite and the dynamics simulation software simulation;

[0029] The imaging simulation unit is used to import the satellite payload time domain curve into the image simulation system. The image simulation system interpolates the time series according to the current simulation time to obtain the actual satellite attitude at the current time, and performs imaging simulation under the current attitude to obtain a simulated image.

[0030] The evaluation unit is used to perform MTF test on the simulated image by using the inclined edge method to obtain the edge image; obtain the vertical track and along track MTF according to the edge image, and evaluate the influence of the control algorithm on the on-track imaging quality.

[0031] Based on the same inventive concept, the present invention also proposes a computer device, including a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to any one of the above-mentioned methods.

[0032] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test as described in any of the above items are executed.

[0033] The present invention is beneficial in that:

[0034] Traditional evaluation methods usually rely on real on-orbit images, but due to the high cost and difficulty of obtaining these images, they are difficult to be widely used in actual operations. The present invention proposes a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test, which uses simulated images instead of real images for testing, thus solving the problem of no real on-orbit images and enabling effective evaluation and optimization in the design and development stages.

[0035] In order to solve the problem that the relationship between the accuracy, stability and imaging quality of existing satellite attitude control systems is complex and difficult to quantify, the present invention establishes a payload attitude controller, a platform attitude controller and a platform position controller to accurately compensate for the satellite attitude, and performs simulation based on these compensation results, so as to comprehensively evaluate the impact of these control systems on imaging quality.

[0036] Aiming at the problem that rotating scanning remote sensing satellites may encounter dynamic interferences such as load imbalance and flexible solar wing vibration during operation, which may affect image quality, the present invention designs a compensator. Therefore, these actual dynamic effects can be taken into account in the simulation, thereby providing a performance evaluation that is closer to reality.

[0037] Furthermore, the present invention also uses the tilted edge method to perform MTF (modulation transfer function) testing, which can quantify the spatial frequency response characteristics of the image in detail, obtain the MTF values ​​in the vertical and along-track directions, and accurately evaluate the specific impact of the control algorithm on the imaging quality. By importing the satellite payload time domain curve into the image simulation system for dynamic simulation, the closeness of the simulated image generation process and the actual imaging situation improves the accuracy of the evaluation. This method uses the MTF test results as an evaluation index, which can provide a quantitative basis for the optimization of the control algorithm, help improve the attitude control system, and improve the final imaging quality.

[0038] The present invention designs a rotating scanning satellite attitude control effectiveness evaluation method based on simulated image MTF (modulation transfer function) test, which can effectively evaluate the final impact of various types of control methods on the on-orbit imaging quality, effectively support satellite control system design and optimization, and has high academic value and engineering significance.

[0039] The present invention is applied to the field of remote sensing satellite imaging simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flow chart of a method for evaluating the effectiveness of attitude control of a rotating scanning satellite based on a simulated image MTF test as described in Implementation Example 1;

[0041] Figure 2 This is a schematic diagram of a three-dimensional simulation scene according to the eleventh embodiment;

[0042] Figure 3 is a curve diagram of load attitude angular deviation and angular velocity deviation according to the eleventh embodiment, wherein: Figure 3 (a) is the load attitude angle deviation curve, Figure 3 (b) is the angular velocity deviation curve;

[0043] Figure 4 A schematic diagram of the generation of a simulated image of a checkerboard target and the extraction of a blade edge according to the eleventh embodiment;

[0044] Figure 5 This is a graph showing the results of 50 MTF random tests of the same blade edge image described in Implementation Example 11 under the conditions of the same ROI size and random position;

[0045] Figure 6 This is a graph of the vertical-to-track and along-track MTF test results according to the eleventh embodiment, wherein: Figure 6 (a) is the vertical track result diagram, Figure 6 (b) is the MTF test result along the track. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0047] Implementation method 1, see Figure 1 The present embodiment is described as follows. The present embodiment describes a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test, the method comprising:

[0048] S1: Establish a payload attitude controller, a platform attitude controller and a platform position controller to compensate the satellite, including compensating for the imbalance of the rotating load and the vibration interference of the flexible solar wing;

[0049] S2: obtain the satellite payload time domain curve based on the compensated satellite and dynamic simulation software simulation;

[0050] S3: The satellite payload time domain curve is imported into the image simulation system. The image simulation system interpolates the time series according to the current simulation time to obtain the actual attitude of the satellite at the current time, and performs imaging simulation under the current attitude to obtain a simulated image.

[0051] S4: Use the tilted edge method to perform MTF test on the simulated image and obtain the edge image. According to the edge image, obtain the vertical and along-track MTFs to evaluate the impact of the control algorithm on the on-track imaging quality.

[0052] Traditional evaluation methods usually rely on real on-orbit images, but due to the high cost and difficulty of obtaining these images, they are difficult to be widely used in actual operations. The method described in this embodiment uses simulated images instead of real images for testing, which solves the problem of no real on-orbit images, allowing effective evaluation and optimization in the design and development stage.

[0053] In this implementation, the problem that the relationship between the accuracy, stability and imaging quality of existing satellite attitude control systems is complex and difficult to quantify is addressed. By establishing a payload attitude controller, a platform attitude controller and a platform position controller, the satellite attitude is accurately compensated, and simulation is performed based on these compensation results. This allows a comprehensive evaluation of the impact of these control systems on imaging quality.

[0054] In this implementation, a compensator is designed to address the problem that rotating scanning remote sensing satellites may encounter dynamic interference such as load imbalance and flexible solar wing vibration during operation, which may affect image quality. Therefore, these actual dynamic effects can be taken into account in the simulation, thereby providing a performance evaluation that is closer to reality.

[0055] Furthermore, the tilted edge method is also used in this embodiment to perform MTF (modulation transfer function) testing, which can quantify the spatial frequency response characteristics of the image in detail, obtain the MTF values ​​in the vertical and along-track directions, and accurately evaluate the specific impact of the control algorithm on the imaging quality. By importing the satellite payload time domain curve into the image simulation system for dynamic simulation, the closeness of the simulated image generation process and the actual imaging situation improves the accuracy of the evaluation. This method uses the MTF test results as an evaluation indicator, which can provide a quantitative basis for the optimization of the control algorithm, help improve the attitude control system, and improve the final imaging quality.

[0056] Embodiment 2: This embodiment further limits the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in Embodiment 1. The step S1 of establishing a payload attitude controller includes:

[0057]

[0058] Among them, T p is the load control moment, J z is the moment of inertia tensor of the load system, is the first-order derivative of the desired angular velocity of the load, ω p is the actual angular velocity of the load, is the corresponding cross product antisymmetric matrix, ω pe is the load error angular velocity, R spw D pw is the coupling coefficient between the load flywheel rotation and the load attitude motion, is the fixed axis rotation angular velocity of the load flywheel, q pev is the vector part of the load error quaternion, k p ,d p To control the gain.

[0059] In this implementation, a payload attitude controller is designed to define parameters such as payload control torque and moment of inertia tensor, which can accurately control the attitude of the satellite and ensure that the system accurately adjusts the attitude of the payload. The introduction of the moment of inertia tensor and the vector part of the error quaternion can better describe and compensate for the deviation of the satellite attitude and improve the accuracy of attitude control. By calculating the payload error angular velocity and adjusting the control gain, the attitude error can be corrected in real time to ensure the stability and control accuracy of the satellite in a dynamic environment.

[0060] Taking into account the coupling effect between the flywheel and the attitude motion of the payload, the attitude control is more comprehensive, which can handle the influence of the flywheel on the attitude and improve the dynamic compensation capability of the system. The introduction of the fixed-axis rotation angular velocity of the flywheel can better adjust the contribution of the flywheel to the attitude control and enhance the stability of the attitude control system. Through precise controller design and parameter setting, various dynamic disturbances (such as imbalance and vibration) in the rotating scanning satellite can be effectively compensated, thereby improving the quality and clarity of the final image.

[0061] By adjusting the control gain, the attitude control strategy can be optimized, the system response speed and stability can be improved, and the satellite can maintain efficient attitude control during the rotation scanning process. After considering these detailed parameters in the simulation environment, the simulation results can be closer to reality, thus providing a more accurate basis for the optimization of the control algorithm.

[0062] Implementation method 3: This implementation method further limits the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in implementation method 1. The step S1 of establishing a platform attitude controller includes:

[0063]

[0064] Among them, T b is the platform control torque, J s is the moment of inertia tensor of the platform system, is the first-order derivative of the platform's desired angular velocity, ω b is the actual angular velocity of the platform, is the corresponding cross product antisymmetric matrix, ω be is the platform error angular velocity, R swj D wj is the coupling coefficient between the platform flywheel rotation and the platform attitude motion (j=1,2,3), is the fixed-axis rotation angular velocity of the platform flywheel, is a variable, k b and d b To control the gain.

[0065] The platform attitude controller described in this embodiment introduces a fixed-time extended state observer, which does not rely on the mathematical model of the disturbance and realizes the observation of the disturbance torque by expanding the one-dimensional state variable. To estimate the first derivative of the quaternion vector part of the platform error variable To estimate the generalized interference D, define e 2 =Z 2 -D, design disturbance observer

[0066]

[0067] Among them, T b is the platform control torque, J s is the moment of inertia tensor of the platform system, is the first-order derivative of the platform's desired angular velocity, ω b is the actual angular velocity of the platform ( is the corresponding cross product antisymmetric matrix), ω be is the platform error angular velocity, R swj D wj is the coupling coefficient between the platform flywheel rotation and the platform attitude motion (j=1,2,3), is the fixed-axis rotation angular velocity of the platform flywheel, (q be0 is the scalar part of the platform error quaternion, I is the unit matrix), λ 1 ,λ 2 ,λ 3 is the observer gain, then Z 2 It will converge to D in a fixed time. On this basis, the platform attitude controller is

[0068]

[0069] Embodiment 4: This embodiment further limits the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in Embodiment 1. In step S1, the platform position controller includes:

[0070]

[0071] Among them, F ms is the platform position control force, M s is the platform quality, X e is the position control error, k,μ are controller parameters, is the interference observation value.

[0072] In this implementation, a sliding mode control method based on an adaptive RBF neural network disturbance observer is adopted, and the controller is in the form of

[0073]

[0074] Among them, F ms is the platform position control force, M s is the platform quality, X e is the position control error, k,μ are controller parameters, is the interference observation value, satisfying

[0075]

[0076] in, is the estimated value of the network weight, h is the output of the network hidden layer, and ρ is the learning rate parameter.

[0077] Embodiment 5: This embodiment further limits the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in Embodiment 1. Step S3 includes:

[0078] For the attitude angle curve of the current working condition, 50 groups of time series with a duration of 30ms are randomly selected within the stable phase time interval and imported into the simulation system in csv format. One group of time series is selected with the maximum angular velocity modulus as the starting point;

[0079] The simulation software is used to interpolate the time series according to the current simulation time to obtain the actual attitude of the satellite at the current time, and imaging simulation is performed under the current attitude to obtain a simulated image.

[0080] In this embodiment, 50 groups of time series with a duration of 30ms are randomly selected, including a time series with the maximum angular velocity modulus as the starting point, which can more comprehensively cover the different states of satellite attitude changes. This selection method that combines randomness and pertinence helps to better simulate various attitude conditions that may occur in actual work. In particular, selecting the maximum angular velocity modulus as the starting point can ensure that the test is performed under critical attitude conditions, thereby improving the accuracy of the evaluation and the sensitivity to extreme situations. Using simulation software to interpolate the time series to obtain the actual attitude of the satellite at the current moment can make the simulation results closer to the actual situation. Interpolation can reduce the error caused by insufficient time resolution and improve the accuracy of the simulated image.

[0081] By interpolating and simulating the current attitude, images at different time points can be obtained, which helps to evaluate the satellite's imaging capabilities in dynamic situations rather than relying solely on static analysis. Importing data in csv format can be easily processed and analyzed in the simulation system. The popularity and ease of use of the csv format help improve the efficiency of data processing and reduce the complexity caused by format conversion. Automated testing through simulation software can reduce human intervention and improve the efficiency and consistency of the test process. At the same time, software interpolation and simulation can automatically generate a large number of test results, which is suitable for large-scale testing needs.

[0082] By performing imaging simulation at the current attitude, the satellite's attitude control performance can be evaluated more accurately, and the image quality in the actual operating environment can be effectively predicted and evaluated. Performing evaluation within the stable phase can reduce the error caused by drastic attitude changes, making the evaluation results more stable and reliable. By performing a detailed analysis of the attitude angle curve, we can have a deeper understanding of the impact of satellite attitude changes on imaging quality, thus providing a basis for optimizing control algorithms and improving system performance.

[0083] Implementation method 6: This implementation method is a further limitation of the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in implementation method 5, wherein the stable phase time interval is 20s to 80s.

[0084] The stabilization phase time interval is set to 20 seconds to 80 seconds, which can ensure that the satellite operates stably within this time range, thereby obtaining more accurate MTF test data. This time interval allows the system to reach a certain stability, making the test results more representative and reducing the interference of transient effects on the test results. The longer stabilization phase provides enough time to observe the performance of the satellite's attitude control system under various conditions, thereby improving the accuracy of the evaluation.

[0085] The time limit of the stabilization phase can effectively reduce the interference in the dynamic process and avoid the noise and errors that may be introduced by MTF testing under rapid dynamic changes. The time range of 20 seconds to 80 seconds is usually enough for the system to enter a stable state, but not too long to introduce new change factors. This helps to accurately evaluate the attitude control effect of the satellite in a real environment.

[0086] The stable phase within the time interval can make the test process more efficient. Setting a reasonable time range can avoid too long a test cycle, saving computing resources and data processing time. Optimizing the test time can make the satellite's attitude control performance evaluation more efficient, thereby improving the feasibility and economy of the test in actual operation.

[0087] By setting the stable phase time interval, it can be ensured that during the evaluation process, the satellite attitude control system has reached the stable state of its designed performance. This helps to obtain more reliable evaluation results, because these results reflect the actual performance of the system under stable working conditions and reduce errors caused by unstable factors in a short period of time.

[0088] Fixed stabilization time intervals help standardize the test process so that results can be compared between different tests. Whether testing multiple satellite systems or the same satellite at different times, setting consistent time intervals ensures uniform test conditions, thereby improving comparability and consistency of results.

[0089] In actual satellite operations, attitude control systems usually need to remain stable within a certain time frame to meet various mission requirements. By setting a reasonable stabilization phase time, we can simulate the environmental conditions in actual operations, ensure that the evaluation method is closer to the actual application scenario, and thus better reflect the true performance of the satellite attitude control system.

[0090] Embodiment 7: This embodiment further limits the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in Embodiment 1. Step S4 includes:

[0091] Set a checkerboard target model with a side length of 10 km at the specified latitude and longitude position of the earth model;

[0092] The two sides of the target form angles with the along-track direction and the vertical-track direction of the satellite respectively;

[0093] The vertical and along-track MTFs are obtained by extracting the edge images at the junction of the black area and the white area in two directions of the target.

[0094] The influence of the control algorithm on the on-track imaging quality is evaluated based on the vertical and along-track MTF.

[0095] In this embodiment, a checkerboard target model with a side length of 10 km is selected to simulate the imaging of large-scale targets in an actual on-orbit environment. This large-scale target can effectively simulate the actual conditions of satellite on-orbit observation, thereby more accurately reflecting the actual imaging performance of the satellite system. The two sides of the target form angles with the along-track direction and the vertical-track direction of the satellite, respectively. This setting makes it possible to extract images in two directions and obtain the MTF in the vertical-track direction and the along-track direction. This directional evaluation method helps to identify and analyze the imaging quality of the satellite in different directions, especially the resolution and image clarity in different directions.

[0096] By extracting the image of the intersection of the target in two directions to obtain the MTF, the edge features of the target in these directions can be effectively captured. This method helps to accurately measure the MTF in different directions. Through the MTF data in the vertical and along-track directions, the effect of the control algorithm can be comprehensively evaluated. This MTF-based evaluation method can help optimize the satellite attitude control algorithm to improve the on-orbit imaging quality and ensure that the satellite imaging system can provide high-quality data in actual missions.

[0097] Using such a target model in a simulation environment can accurately simulate and verify the performance of the satellite system in the actual orbit environment. This approach helps reduce risks in actual launch and on-orbit operations and improves the efficiency and reliability of performance verification.

[0098] Setting targets at designated latitude and longitude positions on the model enables testing under different geographical conditions. This flexible configuration allows testing of imaging performance under different orbital conditions, ensuring that the satellite system can adapt to a variety of actual operating environments.

[0099] Embodiment 8: A rotating scanning satellite attitude control effectiveness evaluation system based on simulated image MTF test described in this embodiment includes:

[0100] A compensation unit is used to establish a payload attitude controller, a platform attitude controller and a platform position controller to compensate the satellite, including compensation for the imbalance of the rotating load and the vibration interference of the flexible solar wing;

[0101] A time domain curve acquisition unit is used to acquire a satellite payload time domain curve according to the compensated satellite and the dynamics simulation software simulation;

[0102] The imaging simulation unit is used to import the satellite payload time domain curve into the image simulation system. The image simulation system interpolates the time series according to the current simulation time to obtain the actual satellite attitude at the current time, and performs imaging simulation under the current attitude to obtain a simulated image.

[0103] The evaluation unit is used to perform MTF test on the simulated image by using the inclined edge method to obtain the edge image; obtain the vertical track and along track MTF according to the edge image, and evaluate the influence of the control algorithm on the on-track imaging quality.

[0104] Implementation method 9. This implementation provides a computer device, characterized in that it includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to any one of implementation methods 1 to 7.

[0105] Embodiment 10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test as described in any one of embodiments 1 to 7 are executed.

[0106] Implementation method 11: See Figures 2 to 6 This embodiment provides a specific example of the method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test described in the first embodiment, and is also used to explain the second to seventh embodiments, specifically:

[0107] In order to verify the effectiveness of the control strategy of the rotating scanning remote sensing satellite, satellite image simulation is carried out under the conditions of considering the real earth, satellite and camera characteristics, and MTF evaluation is performed by generating images containing simulated target edges. Specifically, it includes three parts: ground object observation geometry generation based on a strict imaging model, attitude control algorithm time domain curve simulation and import, simulated target imaging test and MTF evaluation. The implementation methods of each part are as follows:

[0108] (1) Geometry generation of ground object observation based on imaging model

[0109] According to the image simulation method in patent CN117786934A "Rotational scanning remote sensing satellite imaging characteristics simulation and image generation method, device and storage medium", a three-dimensional scene including the earth-satellite-payload is established based on the OpenSceneGraph (OSG) three-dimensional rendering engine. The graphics rendering pipeline of the OSG engine is used to complete the strict mapping from the ground object coordinates to the pixel coordinates to obtain the simulated image. The simulation process and scene are respectively as follows: Figure 2 As shown. At this time, the coordinates of the sub-satellite point in the geographic coordinate system G are [G 1 G 2 G 3 ] T After the ground object point has gone through seven coordinate transformation processes, including the ground-fixed coordinate system E, inertial coordinate system I, orbital coordinate system B, body coordinate system S, camera installation coordinate system C and image plane coordinate system P, the coordinates of its corresponding image point in the image plane system are

[0110]

[0111] Among them, M BA It is the homogeneous coordinate transformation matrix from system A to system B (A can be G, E, I, B, S, C, and B can be E, I, B, S, C, P).

[0112] The imaging model also gives the image motion compensation parameters such as the integration time and drift angle of the TDI camera. The simulation system adjusts the simulation step size and the camera installation matrix according to the parameters given at each moment to obtain a series of original images after single exposure. Subsequently, different rows of images corresponding to the same ground scene in the original image are extracted, and the superimposed image is used as one row of the simulation image. These images are spliced ​​together to obtain the final simulation image.

[0113] (2) Simulation and import of time domain curve of attitude control algorithm

[0114] This embodiment designs a disturbance observer for the case where the satellite is simultaneously disturbed by the large inertia rotation load imbalance and the flexible solar wing vibration. The controller of this embodiment is divided into the following three parts:

[0115] 1. Load attitude controller: Based on the high-precision identification and compensation of the unbalanced amount of the rotating load, a model-based PD attitude feedback controller is designed:

[0116]

[0117] Among them, T p is the load control moment, J z is the moment of inertia tensor of the load system, is the first-order derivative of the desired angular velocity of the load, ω p is the actual angular velocity of the load ( is the corresponding cross product antisymmetric matrix), ω pe is the load error angular velocity, R spw D pw is the coupling coefficient between the load flywheel rotation and the load attitude motion, is the fixed axis rotation angular velocity of the load flywheel, q pev is the vector part of the load error quaternion, k p ,d p To control the gain.

[0118] 2. Platform attitude controller: introduce a fixed-time extended state observer, which does not rely on the mathematical model of the disturbance and realizes the observation of the disturbance torque by expanding the one-dimensional state variable. To estimate the first derivative of the quaternion vector part of the platform error variable To estimate the generalized interference D, define e 2 =Z 2 -D, design disturbance observer:

[0119]

[0120] Among them, T b is the platform control torque, J s is the moment of inertia tensor of the platform system, is the first-order derivative of the platform's desired angular velocity, ω b is the actual angular velocity of the platform ( is the corresponding cross product antisymmetric matrix), ω be is the platform error angular velocity, R swj D wj is the coupling coefficient between the platform flywheel rotation and the platform attitude motion (j=1,2,3), is the fixed-axis rotation angular velocity of the platform flywheel, (q be0 is the scalar part of the platform error quaternion, I is the unit matrix), λ 1 ,λ 2 ,λ3 is the observer gain, then Z 2 It will converge to D in a fixed time. On this basis, the platform attitude controller is

[0121]

[0122] 3. Platform position controller: It adopts sliding mode control method based on adaptive RBF neural network disturbance observer. The controller form is

[0123]

[0124] Among them, F ms is the platform position control force, M s is the platform quality, X e is the position control error, k,μ are controller parameters, is the interference observation value, satisfying

[0125]

[0126] in, is the estimated value of the network weight, h is the output of the network hidden layer, and ρ is the learning rate parameter.

[0127] Next, the payload attitude control performance is verified when the satellite is disturbed by the flexible solar wing and the imbalance is compensated. The results are as follows: Figure 3 As shown in the figure, the horizontal axis of each figure is time (unit s), and the vertical axis is ° (left figure) and ° / s (right figure). It can be seen that after imbalance compensation, the attitude angle control accuracy is maintained at about ±0.001°, and the angular velocity control error is within ±4×10 -4 Within ° / s, the flexible interference of the solar wing is effectively isolated.

[0128] After obtaining the above time domain curve, it needs to be imported into the image simulation system. Due to the high-speed rotation of the satellite payload, the imaging time of the target edge area is only a few milliseconds. Therefore, during the test, 50 groups of 30ms time series are randomly selected for the attitude angle curve of this working condition within the stable phase time interval (20s to 80s), and imported into the image simulation system in csv format. One group selects the time series with the maximum angular velocity modulus as the starting point. During simulation, the software interpolates the time series according to the current simulation time to obtain the actual attitude of the satellite at that time, and performs imaging simulation under this attitude.

[0129] (3) Simulated target imaging test and MTF evaluation

[0130] The MTF test of the simulated image adopts the inclined edge method. A checkerboard target model with a side length of 10 km is set at the specified latitude and longitude position of the earth model (the DN value of the black part is 0, and the DN value of the white part is 255). At this time, the two sides of the target form a small angle with the along-track direction and the vertical-track direction of the satellite respectively. By extracting the edge image at the junction of the black area and the white area in the two directions of the target, the vertical-track and along-track MTF can be tested, as shown in Figure 2. Figure 4 shown.

[0131] When testing MTF, each group selects a region of interest (ROI) with exactly the same position and size in the simulated image. However, since the image shift caused by posture deviation is relatively random and inevitable (the image shift is about 10 pixels when the posture angle deviation is 0.001°), there will be a certain deviation in the position of the corresponding edge area during the MTF test, which will cause fluctuations in the MTF results. Perform 50 random MTF tests on a certain edge image. The ROI size of each test is the same, but the center point of the area moves randomly within a circle with a radius of 10 pixels. At this time, the test results will fluctuate by about 3%, such as Figure 5 shown.

[0132] Next, the target MTF test is carried out under the conditions of satellite orbit altitude of 500km, side viewing angle of 65°, camera focal length of 5m, pixel size of 10μm, and integration level of 96. The ROI of 800 rows × 300 columns starting from the upper left of the simulation image is selected during the MTF test. The test results are as follows: Figure 6 As shown. It can be found that the change in MTF under the above working conditions does not exceed 3% compared with the condition without attitude deviation. At this time, for the local image used for MTF testing, the attitude angle error affects the direction of the optical axis, which in turn causes the position deviation of the edge area. Therefore, there is a situation in which the MTF of some directions is higher than the condition without attitude deviation; and the factor causing image blur (MTF) is the attitude angular velocity error. Since the error under this condition is very small (the corresponding theoretical MTF decreases>0.9999), its impact on image quality is not obvious. Even considering the above deviations, the requirement of MTF>0.95 is still met, which means that the load attitude deviation has no effect on the imaging quality under the aforementioned attitude control strategy, proving the effectiveness of the control method of this embodiment.

[0133] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure rather than to limit its protection scope. Although the present disclosure has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present disclosure, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the disclosed claims to be approved.

Claims

1. A method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test, characterized in that: The method comprises: S1: Establish a payload attitude controller, a platform attitude controller and a platform position controller to compensate the satellite, including compensating for the imbalance of the rotating load and the vibration interference of the flexible solar wing; S2: obtain the satellite payload time domain curve based on the compensated satellite and dynamic simulation software simulation; S3: The satellite payload time domain curve is imported into the image simulation system. The image simulation system interpolates the time series according to the current simulation time to obtain the actual attitude of the satellite at the current time, and performs imaging simulation under the current attitude to obtain a simulated image. S4: Use the tilted edge method to perform MTF test on the simulated image and obtain the edge image. According to the edge image, obtain the vertical and along-track MTFs to evaluate the impact of the control algorithm on the on-track imaging quality.

2. The method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to claim 1, characterized in that: The step S1 of establishing a load attitude controller includes: Among them, T p is the load control moment, J z is the moment of inertia tensor of the load system, is the first-order derivative of the desired angular velocity of the load, ω p is the actual angular velocity of the load, is the corresponding cross product antisymmetric matrix, ω pe is the load error angular velocity, R spw D pw is the coupling coefficient between the load flywheel rotation and the load attitude motion, is the fixed axis rotation angular velocity of the load flywheel, q pev is the vector part of the load error quaternion, k p ,d p To control the gain.

3. The method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to claim 1, characterized in that: In step S1, a platform attitude controller is established. include: Among them, T b is the platform control torque, J s is the moment of inertia tensor of the platform system, is the first-order derivative of the platform's desired angular velocity, ω b is the actual angular velocity of the platform, is the corresponding cross product antisymmetric matrix, ω be is the platform error angular velocity, R swj D wj is the coupling coefficient between the platform flywheel rotation and the platform attitude motion (j=1,2,3), is the fixed-axis rotation angular velocity of the platform flywheel, is a variable, k b and d b To control the gain.

4. The method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to claim 1, characterized in that: The platform position controller in step S1 includes: Among them, F ms is the platform position control force, M s is the platform quality, X e is the position control error, k,μ are controller parameters, is the interference observation value.

5. The method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to claim 1, characterized in that: The step S3 comprises: For the attitude angle curve of the current working condition, 50 groups of time series with a duration of 30ms are randomly selected within the stable phase time interval and imported into the simulation system in csv format. One group of time series is selected with the maximum angular velocity modulus as the starting point; The simulation software is used to interpolate the time series according to the current simulation time to obtain the actual attitude of the satellite at the current time, and imaging simulation is performed under the current attitude to obtain a simulated image.

6. The method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to claim 5, characterized in that: The stable phase time interval is 20s to 80s.

7. The method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to claim 1, characterized in that: The step S4 comprises: Set a checkerboard target model with a side length of 10 km at the specified latitude and longitude position of the earth model; The two sides of the target form angles with the along-track direction and the vertical-track direction of the satellite respectively; The vertical and along-track MTFs are obtained by extracting the edge images at the junction of the black area and the white area in two directions of the target. The influence of the control algorithm on the on-track imaging quality is evaluated based on the vertical and along-track MTF.

8. A rotating scanning satellite attitude control effectiveness evaluation system based on simulated image MTF test, characterized in that: The system comprises: A compensation unit is used to establish a payload attitude controller, a platform attitude controller and a platform position controller to compensate the satellite, including compensation for the imbalance of the rotating load and the vibration interference of the flexible solar wing; A time domain curve acquisition unit is used to acquire a satellite payload time domain curve according to the compensated satellite and the dynamics simulation software simulation; The imaging simulation unit is used to import the satellite payload time domain curve into the image simulation system. The image simulation system interpolates the time series according to the current simulation time to obtain the actual satellite attitude at the current time, and performs imaging simulation under the current attitude to obtain a simulated image. The evaluation unit is used to perform MTF test on the simulated image by using the inclined edge method to obtain the edge image; obtain the vertical track and along track MTF according to the edge image, and evaluate the influence of the control algorithm on the on-track imaging quality.

9. A computer device, characterized in that: The invention comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of a method for evaluating the attitude control effectiveness of a rotating scanning satellite based on a simulated image MTF test as described in any one of claims 1 to 7.

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