Parabolic antenna pointing tracking method in inter-satellite communication scene

Abstract

The invention relates to the field of satellite communication, and discloses a parabolic antenna pointing tracking method in an inter-satellite communication scene, and the method comprises the following steps: carrying out the attitude initialization, dynamic prediction, error compensation and closed-loop control, and achieving the high-precision satellite tracking of an antenna. The method adapts to large dynamic changes of target satellites and ensures stable and reliable communication; the invention discloses a parabolic antenna pointing tracking system in an inter-satellite communication scene. The system comprises an antenna angle sensor module, a signal receiving module, a prediction module, an error compensation module and a closed-loop control module. According to the method, orbit prediction, an extrapolation algorithm, adaptive control and a closed-loop feedback mechanism are fused, and high-precision and high-robustness antenna satellite tracking is realized. The method can adapt to large dynamic change of a target satellite, reduces dependence on real-time position information, still keeps stable communication under the condition of orbit sudden change or data missing, and improves system reliability and engineering practicability.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication, and particularly to a method for pointing and tracking a parabolic antenna in an inter-satellite communication scenario. Background Art

[0002] In a satellite communication system, precise pointing control of an antenna is crucial for ensuring stable inter-satellite communication. In the prior art, many solutions rely only on orbit prediction and simple open-loop control to achieve antenna pointing. These methods usually cannot respond in real time to the dynamic changes of the target satellite's orbit, resulting in the accumulation of pointing errors, especially when the satellite orbit is unstable or changing rapidly. Although some systems have also introduced error correction techniques, most solutions do not consider how to combine prediction and feedback in real time, making it difficult to achieve rapid response.

[0003] In addition, some existing antenna pointing control methods generally have the phenomenon of fixed control gain and lack of adaptive adjustment. In the case of rapid orbit changes, fixed control gains often cannot fully adapt to the high-speed movement of the satellite, resulting in insufficiently sensitive control responses and even error amplification. For the high-precision requirements in complex orbit environments, the prior art fails to provide a sufficiently flexible adjustment mechanism, and unstable control effects are likely to occur.

[0004] Furthermore, although there are some trajectory tracking methods based on prediction in the prior art, most rely on rough orbit models and do not accurately handle orbit error correction and real-time update of future trajectories. The orbit environment is complex and difficult to predict, and some solutions do not fully consider external disturbances or accurate modeling, resulting in a decrease in the accuracy of antenna pointing control under complex orbit conditions. For the application scenarios of high-precision inter-satellite communication, the prior art is difficult to effectively avoid pointing instability caused by orbit changes; therefore, the present invention proposes a method for pointing and tracking a parabolic antenna in an inter-satellite communication scenario to solve the deficiencies of the prior art. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a method for pointing and tracking a parabolic antenna in an inter-satellite communication scenario, which solves the problems of unstable antenna pointing accuracy and lagging control response under dynamic orbit change conditions.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A method for pointing and tracking a parabolic antenna in an inter-satellite communication scenario, comprising the following steps: S1. Obtain the initial attitude, orbit information of the satellite and the position information of the target satellite, and initialize the antenna pointing parameters; S2. According to the initial attitude, orbit information of the satellite and the position information of the target satellite, collect the antenna angle sensor data and the received signal strength in real time; S3. Based on the data of the acquisition antenna angle sensor, the historical antenna pointing data, and the information on the change of the target satellite's position, use the algorithm extrapolation technology to predict the future position of the target satellite and the corresponding antenna pointing angle; S4. Compare the predicted future position of the target satellite and the corresponding antenna pointing angle with the antenna angle and signal strength collected in real time, calculate the pointing error and perform error compensation to obtain the corrected antenna pointing parameters; S5. According to the corrected antenna pointing parameters, adjust the antenna control system in real time to implement closed-loop control for continuously tracking the target satellite and ensuring that the antenna always points to the target.

[0007] The present invention also provides a parabolic antenna pointing and tracking system in an inter-satellite communication scenario, including: An antenna angle sensor module for collecting antenna angle data in real time; A signal receiving module for collecting the signal strength data of the target satellite; A prediction module for predicting the future position of the target satellite and the antenna pointing angle according to the satellite orbit model and historical data; an error compensation module for calculating and correcting the antenna pointing error; A closed-loop control module for adjusting the antenna attitude in real time according to the corrected pointing parameters to continuously track the target satellite.

[0008] The present invention provides a parabolic antenna pointing and tracking method in an inter-satellite communication scenario. It has the following beneficial effects: 1. The present invention adopts an antenna pointing control strategy based on the fusion of orbit prediction and extrapolation algorithms, achieving the technical effect of high-precision dynamic tracking of the target satellite. Compared with the existing method that relies on a single sensor input and performs static error correction, it effectively solves the problems of antenna response lag and large pointing deviation under the condition of rapid satellite movement.

[0009] 2. By introducing an adaptive control and rolling prediction mechanism, the system can flexibly cope with the large dynamic displacement of the target satellite and achieve continuous and stable pointing adjustment. This solution is different from the traditional fixed-value tracking method and solves the problem of tracking unlocking when the orbit changes violently, improving the dynamic adaptability of the overall control system.

[0010] 3. By constructing an antenna pointing compensation mechanism for multi-source information fusion, even when the position data of the target satellite is missing or updated with a delay, the system can still achieve approximate accurate tracking by extrapolating the historical trajectory, thus achieving the effect of maintaining communication ability under the condition of incomplete information. Different from the existing technology that highly depends on the orbit update frequency, this solution greatly reduces the system's dependence on external input and improves the practical stability.

[0011] 4. The present invention uses closed-loop feedback combined with filter compensation control to maintain the stability and uninterruption of the communication link even when there are command angle disturbances or sudden orbit jumps. Compared with the traditional open-loop position prediction control method, this method solves the pain point of being vulnerable to orbit anomalies and resulting in communication link disconnection, making inter-satellite microwave communication more robust and engineering applicable. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a flowchart of the method of the present invention; Figure 2 is a system architecture diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0014] Please refer to Figure 1 , an embodiment of the present invention provides a method for pointing and tracking a parabolic antenna in an inter-satellite communication scenario, including the following steps: S1. Obtain the initial attitude, orbit information, and target satellite position information of the satellite, and initialize the antenna pointing parameters; In the embodiment of the present invention, the core task of step S1 is to obtain the initial attitude, orbit information, and position information of the target satellite of the satellite, and initialize the antenna pointing parameters based on this. This step provides the basic data for subsequent precise tracking and error compensation of the satellite pointing. Accurate initial data is the key to ensuring that the antenna can always stably align with the target satellite.

[0015] First, in this embodiment, the initial attitude information of the satellite is usually obtained by relying on the inertial measurement unit (IMU) carried by the satellite itself. The IMU can collect attitude information such as the pitch angle, roll angle, and yaw angle of the satellite in real time. Specifically, the IMU will provide the rotation angle and orientation data of the satellite in three-dimensional space. These attitude information provide important references for subsequent antenna pointing adjustments. In some embodiments, the satellite can also carry a star sensor to further improve the attitude accuracy, and the star sensor can use stars as a reference for precise attitude measurement.

[0016] The orbital information of the satellite is obtained through the satellite's orbital calculation model. Generally, the orbital information includes, but is not limited to, parameters such as the orbital radius, eccentricity, orbital inclination, longitude of the ascending node, argument of perigee, true anomaly, etc. The accurate acquisition of orbital information is crucial for subsequent prediction of the target satellite's position. In some embodiments, the calculation of these orbital elements uses the classical Newton - Raphson iteration method or other numerical integration methods. Through these methods, the orbital position of the satellite at different time points can be accurately predicted and support for calculating the antenna pointing angle can be provided.

[0017] The position information of the target satellite depends on the satellite's real - time positioning system. In some embodiments, the position data of the target satellite can be obtained in real time through an inter - satellite positioning system or through real - time data transmission provided by a ground control station to this satellite. The position information of the target satellite provides a basis for setting the initial pointing angle.

[0018] In this embodiment, the initial pointing angle of the antenna is determined by the relative position relationship between the target satellite and the satellite. Specifically, the pointing of the antenna is jointly determined by the elevation angle and the azimuth angle, and these two angles determine the orientation of the antenna. To calculate the initial pointing angle of the antenna, geometric calculations can be performed based on the spatial coordinates of the target satellite and the spatial coordinates of this satellite.

[0019] In this calculation, the following formula can be used to determine the elevation angle and azimuth angle of the antenna: where: θ ε is the elevation angle (ElevationAngle) between the target satellite and this satellite, that is, the angle of the antenna in the vertical direction; z satcllite is the height coordinate of the current position of the satellite; z target is the height coordinate of the current position of the target satellite; r satcllite is the distance from the target satellite to the center of the earth; r target is the distance from the target satellite to the center of the earth.

[0020] This formula describes the geometric relationship between the satellite and the target satellite and can calculate the elevation angle between the two. It should be noted that the angle value calculated by this formula is only the elevation angle, and for the calculation of the azimuth angle, it can be further deduced based on the relative azimuth information between the satellite and the target satellite.

[0021] When calculating the azimuth angle, it is usually necessary to combine the relative positions of this satellite and the target satellite in the plane coordinate system and use the following formula to calculate: where: θa is the azimuth angle, i.e., the angle of the antenna in the horizontal direction; x satellite , y satellite are the abscissa and ordinate of the satellite in the plane coordinate system of the Earth's surface; x targct , y target are the abscissa and ordinate of the target satellite in the plane coordinate system of the Earth's surface.

[0022] This formula calculates the angle between the satellite and the target satellite in the horizontal direction to obtain the azimuth angle of the antenna, thus completely determining the angle of the antenna pointing.

[0023] After obtaining the position information, orbital information of the target satellite and the attitude data of the satellite itself, the initial pointing parameters of the antenna can be calculated through the above formula. The pointing parameters mainly include the elevation angle and the azimuth angle. On this basis, through the adjustment of the antenna control system, it can ensure that the antenna always points to the target satellite and provide stable signal transmission.

[0024] By acquiring and processing these initial data, this embodiment can ensure that the initial pointing of the antenna is accurate and stable, providing a solid foundation for subsequent error compensation and predictive adjustment.

[0025] It should be noted that the orbital information of the satellite and the position information of the target satellite are not fixed, but change with the evolution of time and orbit. Therefore, real-time data transmission and dynamic tracking technologies are required to obtain this information. For example, continuous satellite orbit tracking can be carried out through the inter-satellite navigation system or the ground control station to timely obtain the latest orbital parameters and the position of the target satellite to ensure the dynamic adjustment of the antenna pointing.

[0026] In some embodiments, the calculation of satellite orbital elements not only needs to consider the standard Earth gravity model, but also needs to consider external perturbation factors such as solar radiation pressure and lunar gravity. These factors will cause slight changes in the satellite orbit, thus affecting the accuracy of the antenna pointing. Therefore, in satellite orbit prediction, an accurate orbit calculation method including these perturbation effects can be used to further improve the accuracy of the antenna pointing.

[0027] S2. According to the initial attitude, orbital information of the satellite and the position information of the target satellite, collect the data of the antenna angle sensor and the received signal strength in real time; In the embodiments of the present invention, the main task of step S2 is to collect antenna angle sensor data and received signal strength in real time according to the initial satellite attitude, orbital information, and target satellite position information. The purpose of this step is to monitor the relative motion state between the satellite and the target satellite in real time, ensure that the antenna pointing is always accurate, and evaluate the accuracy of the antenna pointing according to the received signal strength. This process is a dynamic feedback loop that provides the necessary basis for the precise tracking and adjustment of the antenna by accurately collecting and analyzing the relative position changes between the satellite and the target satellite and the received signal strength.

[0028] In some embodiments, antenna angle sensors (such as inertial measurement units IMU, gyroscopes, star sensors, electronic compasses, etc.) are used to measure the attitude changes of the satellite in real time. The attitude information of the satellite usually includes pitch angle, roll angle, yaw angle, etc. Star sensors are relatively common high-precision sensors that can measure the satellite's attitude in real time by comparing the position changes of stars in the sky, thereby providing high-precision satellite attitude data. In addition, an inertial measurement unit (IMU) combined with a gyroscope can detect the dynamic changes of the satellite and provide continuous attitude feedback information to further enhance the accuracy of antenna tracking.

[0029] The orbital information of the satellite is the basis for obtaining the relative position changes of the satellite. Usually, this orbital information includes the orbital elements of the satellite, such as orbital radius, eccentricity, orbital inclination, etc. Using these orbital elements, the accurate position of the satellite at any moment can be calculated. However, due to the fact that the satellite orbit is subject to external perturbations (such as solar radiation pressure, earth's gravity, etc.), the actual position of the satellite in the orbit may deviate. Therefore, it is necessary to regularly monitor and update the satellite's orbital state to obtain accurate orbital positions and dynamic change information.

[0030] The relative position changes of the target satellite are also an important data source in this step. The real-time position of the target satellite can be obtained through the inter-satellite communication system, the real-time positioning system of the target satellite, or the updated data from the ground control station. These data can be updated in real time by various methods, such as based on high-precision inter-satellite navigation or ground tracking data.

[0031] In the embodiments, the antenna angle sensor can not only capture the attitude data of the satellite, but also obtain the pointing error and dynamic changes of the antenna in real time. By analyzing the angular difference between the antenna pointing and the target satellite, the antenna can be adjusted in real time to ensure that it always maintains accurate alignment with the target satellite.

[0032] Received signal strength is one of the important parameters for evaluating the pointing accuracy of an antenna. During inter-satellite communication, the strength of the received signal is closely related to the distance between satellites, the alignment accuracy of the antenna, and environmental factors (such as atmospheric disturbances, solar activities, etc.). Generally speaking, the received signal strength is inversely proportional to the square of the relative distance between satellites. By monitoring the change in received signal strength, the relative position of the satellite can be estimated, and the real-time accuracy of the antenna pointing can be judged.

[0033] There is a relationship between the change in received signal strength and the relative position of the satellite and the antenna pointing error. Specifically, the received signal strength (P r ) is closely related to factors such as the relative distance (d) between satellites and the antenna gains (G t and G r ). According to the free space transmission model, the received signal strength can be expressed by the following formula: Where: P r is the received signal strength; P t is the power of the transmitted signal; G t is the transmitting antenna gain; G r is the receiving antenna gain; λ is the signal wavelength; d is the relative distance between the satellite and the target satellite.

[0034] This formula reveals the relationship between the signal strength and the relative position between satellites. The change in signal strength reflects the change in the distance between satellites and the error in antenna pointing. By monitoring the received signal strength in real time, the change in the relative position of the satellite and the accuracy error of the antenna pointing can be evaluated. If the signal strength weakens, it may mean that the alignment accuracy between the antenna and the target satellite has decreased, and adjustment is required at this time.

[0035] By collecting antenna angle sensor data and received signal strength in real time, the relative position between the satellite and the target satellite can be accurately evaluated at each moment, and the antenna pointing can be adjusted in a timely manner according to the change in signal strength. This method ensures that the antenna can always accurately point to the target satellite and provides stable signal reception.

[0036] In the embodiments of the present invention, by collecting antenna angle sensor data and received signal strength in real time, the relative position between the satellite and the target satellite and the pointing accuracy of the antenna can be evaluated in real time. In some embodiments, the adjustment of the antenna pointing not only depends on the data provided by the attitude sensor, but also needs to consider the influence of external disturbances (such as solar wind, earth gravity, etc.) on the satellite orbit. In order to effectively handle these disturbances, the system can adopt a dynamic compensation algorithm or an orbit correction model to ensure the stable pointing of the antenna.

[0037] In addition, the received signal strength data collected in real time can also be used to evaluate the antenna pointing error, and then optimize the antenna pointing accuracy. The monitoring of the signal strength combined with the antenna angle sensor data can provide dynamic feedback for the real-time position update of the target satellite and the antenna pointing accuracy, and automatically correct the antenna pointing according to this feedback, maximizing the signal quality and communication efficiency.

[0038] S3. Based on the data collected by the antenna angle sensor, the historical antenna pointing data, and the information on the change of the target satellite's position, use the algorithm extrapolation technology to predict the future position of the target satellite and the corresponding antenna pointing angle; In step S2, the real-time acquisition and dynamic feedback control of the satellite attitude, antenna angle, and received signal strength are realized, and a relatively complete input information basis has been formed. Based on this, in step S3, the algorithm extrapolation technology is further introduced, combined with the aforementioned collected data and the satellite orbit prediction model, to dynamically predict the future position of the target satellite and the corresponding antenna pointing angle, so as to implement a control strategy of advance adjustment, ensuring the continuity and accuracy stability of the inter-satellite communication link. A close linkage in data flow and control logic is formed between step S3 and step S2. The former takes the latter as the information input source, and the latter adjusts according to the future state predicted by S3, which is a composite control architecture with a feed-forward nature.

[0039] In this embodiment, the algorithm extrapolation technology takes the collected antenna angle sensor data, historical antenna pointing data, and the historical orbit change information of the target satellite as inputs, and fuses the orbit dynamics modeling and the optimal control algorithm for future state prediction. This prediction process is not limited to the single-point deduction in time, but a short-term orbit extrapolation technology based on continuous time-domain modeling, combined with system state feedback to achieve dynamic self-update.

[0040] In a possible implementation manner, the target satellite orbit change information can be composed of the following six orbital elements (Kepler elements): Semi-major axis a; Eccentricity e; Inclination i; Right ascension of the ascending node Ω; Argument of perigee ω; Mean anomaly M.

[0041] Generally, these orbital elements are gradually perturbed by the perturbing forces (such as solar gravity, the non-spherical gravitational field of the earth, solar radiation pressure, etc.) over time. Therefore, in the extrapolation modeling process, the following form of the orbit dynamics state equation is usually adopted: Where: x(t) is the system state vector, usually including the change of orbital elements, attitude change, and antenna pointing error, etc.; Denote the time derivative of the state; A(t) is the state transition matrix representing the internal structure of the system; B(t) is the control input matrix; u(t) is the control input vector representing the action input of the antenna servo system.

[0042] As an option, to achieve an optimized prediction of the future state, this embodiment introduces the Linear Quadratic Regulator (LQR) method to determine the rapid decay of the system state (i.e., the antenna pointing error) on the premise of minimizing the control cost. Its objective is to minimize the following cost function: where: J is the total cost function representing the optimization objective of the system; x(t) is the system state vector, usually representing the antenna pointing error and its variation; u(t) is the control input vector representing the control signal required to adjust the antenna pointing; Q is a symmetric positive semi-definite weight matrix, usually used to weight the system state; R is a symmetric positive definite weight matrix, usually used to weight the control input.

[0043] In a specific implementation, the state vector x(t) can be expressed as: where: θ e (t) is the antenna pointing angle error; is the rate of change of the antenna pointing angle error; δ r (t) is the relative position error of the target satellite; is the rate of change of the relative position error.

[0044] Based on the above state expression, the control input u(t) can include the control quantities of the antenna actuator, such as: where: τ az (t) is the control torque of the azimuth servo motor; τ el (t) is the control torque of the elevation servo motor. Specifically, in one implementation, the feedback gain matrix K can be obtained by solving the Riccati equation, and then the optimal control law is obtained: u(t) = -Kx(t); This control strategy will automatically adjust the antenna control input according to the system state to ensure that even when non-linear disturbances occur during the movement of the target satellite, the antenna pointing can be predictively adjusted in advance, thereby improving the tracking robustness.

[0045] In some embodiments, the Extended Kalman Filter (EKF) or the Unscented Kalman Filter (UKF) can be introduced to enhance the state observation accuracy and further optimize the robustness of orbit extrapolation, which is particularly applicable to scenarios where the target satellite has an uncertain state model.

[0046] As another implementation, the orbit prediction part can also be completed by an orbit extrapolation method based on least squares fitting, and a time series model (such as the ARIMA model) can be combined to model and correct the historical orbit error to enhance the long-term prediction ability. Through the regression analysis of the received signal strength change data, the error term in the orbit prediction model can also be assisted to be corrected to achieve multi-source data fusion prediction.

[0047] In addition, in some embodiments, to improve the stability in a high-dynamic environment, a multi-objective optimization control structure can be designed, and multiple constraint terms, including response time, moment of inertia constraint, actuator saturation constraint, etc., can be introduced under the LQR framework to improve the engineering adaptability of the entire system.

[0048] S4. Compare the predicted future position of the target satellite and the corresponding antenna pointing angle with the antenna angle and signal strength collected in real time, calculate the pointing error and perform error compensation to obtain the corrected antenna pointing parameters; After the antenna pointing prediction in step S3 is completed, step S4 is introduced to solve the pointing deviation problem caused by orbit perturbation, attitude drift or observation error between the prediction model and the actual operation. Although the extrapolation mechanism based on orbit dynamics and optimal control can perform feedforward compensation to a certain extent, due to the uncertainty of the space environment and the nonlinear characteristics of the system itself, prediction offset still inevitably exists. Therefore, step S4 further introduces an error compensation mechanism, constructs a state estimation system with the extended Kalman filter as the core, and combines the dynamic change information of the orbit and attitude to achieve high-precision correction of the antenna pointing through an adaptive adjustment method. This step logically follows step S3, is a closed-loop correction of the prediction result, and is a key link to improve the robustness and practicality of the system.

[0049] In this embodiment, the error compensation strategy first estimates the true state of the satellite based on the extended Kalman filter algorithm (EKF). Considering the nonlinear characteristics of the on-board attitude system and orbit model, it is difficult to obtain an effective estimate using the linear Kalman filter method, so EKF is required to linearize the state to enhance the accuracy of state estimation.

[0050] In a possible implementation, the state update equation of the extended Kalman filter is defined as follows: Where, is the state estimate value at the k-th moment; is the state prediction value at the (k - 1)-th moment; is the observation value at the k-th moment; is the Kalman gain matrix; is the observation matrix.

[0051] The Kalman gain matrix K k is calculated as follows: where: P k∣k-1 is the predicted state covariance matrix; R k is the observation noise covariance matrix; is the transpose of the observation matrix.

[0052] Meanwhile, the state prediction is completed by the following non - linear system model: where: f(·) is the system state transition function; u k-1 is the control input at the previous moment; w k-1 is the process noise vector, assumed to be zero - mean Gaussian white noise.

[0053] In practical applications, the state vector can be expressed as: where: θ e (k) is the antenna pointing angle error; is the change rate of the pointing angle error; δ r (k) is the relative position error of the target satellite; is the change rate of the relative position error; b gyro (k) is the gyroscope drift deviation (modeled as a slow variable in the system).

[0054] In some embodiments, the observation vector z k includes the antenna angular velocity measured by sensors such as IMU or angular position encoders, as well as the processed relative position information, and its model is expressed as: where: v k is the observation noise, following a Gaussian distribution with covariance R k ; H k is the observation matrix, and its form can be determined according to the observation content. For example, H k = [I 0] indicates that some states can be directly observed.

[0055] To further address the antenna pointing error caused by orbit changes, this embodiment introduces an adaptive error compensation algorithm. This algorithm dynamically corrects the pointing control parameters based on the relative position information of the target satellite and the change characteristics of the received signal strength. In some typical implementations, the antenna compensation angle Δθ(t) can be modeled using the following expression: Where: Δθ(t) is the compensation angle at the current moment; δ r (t) is the current target satellite relative position error vector modulus; is the received signal strength change rate; ∈ bias (t) is the estimated value of the measurement deviation in the system; α, β, γ are adaptive adjustment coefficients, which can be dynamically updated according to real-time error feedback.

[0056] In actual deployment, in order to prevent the filter from diverging, the linearized Jacobian matrix F of the state transfer matrix needs to be k and the observation matrix H k Perform dynamic updates and set the initial covariance matrix P 0 to match the initial uncertainty of the system.

[0057] In addition, in order to improve the system's ability to cope with sudden attitude disturbances (such as attitude control propulsion or external force), in some embodiments, a multi-model switching strategy can be combined to set different parameter filters for different disturbance intensities, and adaptively switch according to the size of the error residual to enhance the system's dynamic response capability.

[0058] In some cases, the system can also introduce a regulation mechanism based on model prediction error to adjust the Q k , R k The matrix is ​​adjusted online to make it more consistent with the error statistical characteristics under real-time working conditions, so as to reduce the impact of modeling errors on estimation accuracy.

[0059] S5. According to the corrected antenna pointing parameters, the antenna control system is adjusted in real time to implement closed-loop control to continuously track the target satellite and ensure that the antenna always points to the target; In step S4, the system corrects the state of the antenna pointing angle prediction result through the extended Kalman filter and adaptive error compensation method, and obtains a relatively accurate state estimate. However, in order to ensure that the antenna can achieve continuous, stable and high-precision pointing control in the dynamically changing environment of the target satellite, it is not enough to rely solely on static correction. Therefore, in step S5, a closed-loop control mechanism is further introduced, and the corrected pointing angle parameters are input into the servo control system through the feedback path, and the pointing strategy is continuously updated according to the orbital evolution characteristics to achieve the purpose of dynamic real-time control.

[0060] This step is closely connected with the previous steps, taking over the orbit prediction output in step S3 and integrating the state estimation results in step S4 to provide dynamic correction instructions for the final servo control system. At the same time, it ensures the robustness and responsiveness of the system operation under the condition of continuous change of the target orbit. It is a key component in building a complete intersatellite communication pointing and tracking control chain.

[0061] In this embodiment, the antenna control system adopts a closed-loop feedback structure to achieve real-time tracking and adjustment of the pointing angle. The system takes the corrected command angle as the input, obtains the current antenna pointing angle feedback value in real time, constructs a control error through the difference, and generates a servo control signal according to a certain control law.

[0062] In a possible implementation, the control system adopts the following structure: θ ctrl (t) = θ pred (t) + Δθ corr (t); e(t) = θ ctrl (t) - θ meas (t); Where: θ ctrl (t) is the current control command angle, which is composed of the predicted angle and the error correction angle; θ prcd (t) is the target antenna pointing angle calculated by the orbit prediction algorithm; Δθ corr (t) is the error correction angle output in step S4; θ meas (t) is the antenna angle sensor data collected in real time; e(t) is the current control error; u(t) is the control signal output to the servo execution unit; K P (t), K I (t), K D (t) are the time-related proportional, integral, and differential control gains respectively; is the integral term of the error, representing the accumulation of the error over time; is the derivative term of the error, representing the error change rate and capable of predicting the future trend of the error.

[0063] As an option, an adaptive gain adjustment strategy can be further introduced to enhance the system's response ability to orbit changes. For example, the proportional gain can be updated in real time according to the target satellite orbit change rate, as follows: Where: K P0 is the initial value of the proportional gain; λ is the adjustment coefficient used to control the influence degree of the orbit speed on the gain; is the change rate of the target satellite position vector.

[0064] This strategy can effectively address the pointing mutation problem caused by rapid orbit changes and improve the stability and real-time responsiveness of the system.

[0065] In this embodiment, to achieve the forward-looking pointing adjustment of the antenna control, the system periodically performs a rolling prediction on the future trajectory of the target satellite and generates an antenna control command sequence for a future period of time.

[0066] In general, trajectory prediction can calculate the future position of the target satellite based on the following relationship: Where: is the predicted future position of the target satellite; r sat (t) is the current position of the target satellite; v rel (t) is the relative velocity vector; a rel (t) is the relative acceleration vector, which can be derived from the orbital dynamics model; Δt is the prediction time step.

[0067] Furthermore, according to the position relationship between the antenna and the target satellite, the predicted value of the antenna pointing angle is calculated: Where: θ pred (t + Δt) is the predicted pointing angle of the target satellite, that is, the pointing angle at time t + Δt; is the projection of the predicted position of the target satellite in the antenna coordinate system; arctan2(·) is the two-parameter arctangent function, which ensures the accuracy of angle calculation in all quadrants.

[0068] In order to avoid severe disturbances to the control system caused by sudden orbital changes, in some embodiments, the command angle can be smoothed over time, such as using a first-order lag filter, and the expression is as follows: Where: α is the filtering coefficient, and its value range is (0, 1); is the smoothed control angle command at the current moment; θ cmd (t) is the unfiltered control angle.

[0069] To ensure the closed-loop response of the control system, the antenna system continuously collects angle sensor data and forms a complete feedback path, sending the actual pointing angle back to the main control unit to participate in the next control error calculation.

[0070] Specifically, the sensor value θ meas (t) collected by the system is transmitted to the controller in real time, compared with the target pointing angle θ ctrl (t), the control error e(t) is updated, and a new servo control signal is formed.

[0071] In some embodiments, this feedback path can also monitor the tolerance of the current pointing state in combination with the residual criterion. When the error e(t) exceeds the set tolerance, the system can trigger a quick correction or re-planning strategy, thereby ensuring that the system pointing is always within the controllable range.

[0072] Please refer toFigure 2 , the present invention also provides a parabolic antenna pointing and tracking system in an inter-satellite communication scenario, including: an antenna angle sensor module, which is used to collect the current attitude angle data of the antenna in real time, including information such as azimuth angle and elevation angle, and upload the collection results to the main control system for subsequent error analysis and closed-loop control calculation to ensure that the system always obtains accurate attitude feedback; A signal receiving module, which is used to collect the signal strength, level change and possible modulation information from the target satellite as an auxiliary judgment basis for pointing accuracy. When the signal strength drops abnormally, it can be used as one of the criteria for pointing deviation to improve the system's perception ability of non-orbit anomalies; A prediction module, which based on the satellite orbit dynamics model, historical flight data and the current time state, makes a rolling prediction of the future trajectory of the target satellite, and at the same time calculates the ideal pointing angle sequence that the antenna should respond to, providing support for advance control. This module supports multi-step prediction and dynamic update to adapt to the high-dynamic orbit environment; An error compensation module, which is used to calculate the error amount between the predicted pointing angle and the actual antenna attitude in real time, and combines the received signal strength information to correct the error by using methods such as filtering, adaptive adjustment, and Kalman prediction, and outputs the corrected command angle to improve the pointing accuracy; A closed-loop control module, which is used to drive the servo actuator to adjust the antenna attitude in real time according to the corrected target pointing angle. This module continuously receives the sensor feedback data to form a closed-loop control loop, and has a fault tolerance criterion and a tracking state judgment mechanism to ensure stable and continuous target tracking ability under various orbit dynamic change conditions.

[0073] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A parabola antenna pointing tracking method in an intersatellite communication scenario, characterized in that: The following steps are involved: S1. Obtain the satellite's initial attitude, orbit information and target satellite position information, and initialize the antenna pointing parameters; S2, collecting antenna angle sensor data and received signal strength in real time according to the satellite initial attitude, orbit information and target satellite position information; S3, based on the collected antenna angle sensor data, historically collected antenna pointing data and target satellite position change information, use algorithm extrapolation technology to predict the future position of the target satellite and the corresponding antenna pointing angle; S4, comparing the predicted future position of the target satellite and the corresponding antenna pointing angle with the antenna angle and signal strength collected in real time, calculating the pointing error and performing error compensation to obtain the corrected antenna pointing parameters; S5. According to the corrected antenna pointing parameters, the antenna control system is adjusted in real time to implement closed-loop control to continuously track the target satellite and ensure that the antenna always points to the target.

2. The method for tracking the pointing direction of a parabola antenna in an intersatellite communication scenario according to claim 1, characterized in that: The real-time acquisition of antenna angle sensor data includes dynamic information of satellite attitude changes, orbital deviations and relative positions of target satellites, and the received signal strength data is used to evaluate the relative positions of target satellites and the real-time accuracy of antenna pointing.

3. The method for tracking the pointing direction of a parabola antenna in an intersatellite communication scenario according to claim 1, characterized in that: The algorithm extrapolation technology combines historical data with the satellite orbit dynamics model and adopts an optimal control method to predict the future orbit and antenna pointing angle of the target satellite. The optimal control method includes a linear quadratic adjustment method, and its cost function is used to minimize the weighted square error of the system state and the control input.

4. The method for tracking the pointing direction of a parabola antenna in an intersatellite communication scenario according to claim 3, characterized in that: The linear quadratic adjustment method defines the cost function by the following mathematical formula: Where: J is the total cost function; x(t) is the system state vector; u(t) is the control input vector; Q is the symmetric semi-positive definite weight matrix; R is the symmetric positive definite weight matrix.

5. The method for tracking the pointing direction of a parabola antenna in an intersatellite communication scenario according to claim 1, characterized in that: The error compensation includes using an extended Kalman filter algorithm to estimate the true state of the satellite, and using the estimated state to correct the pointing direction of the antenna. The state update formula of the extended Kalman filter is: in, is the estimated value of the state at the kth moment; is the state prediction value at the k-1th moment; is the observed value at the kth moment; is the Kalman gain matrix; is the observation matrix.

6. The method for tracking the pointing direction of a parabola antenna in an intersatellite communication scenario according to claim 1, characterized in that: The error compensation includes dynamically adjusting antenna pointing parameters through an adaptive algorithm according to the satellite orbit model and the relative position information of the target satellite, so as to compensate for the pointing error caused by the dynamic change of the satellite orbit.

7. The method for tracking the pointing direction of a parabola antenna in an intersatellite communication scenario according to claim 1, characterized in that: The closed-loop control includes inputting the corrected antenna pointing parameters into the antenna control system through a feedback loop, adjusting the rotation angle of the antenna in real time, and continuously updating the pointing parameters according to the satellite orbit changes.

8. A parabola antenna pointing tracking system in an inter-satellite communication scenario, applied to a parabola antenna pointing tracking method in an inter-satellite communication scenario as claimed in any one of claims 1 to 7, characterized in that: include: Antenna angle sensor module, used to collect antenna angle data in real time; A signal receiving module is used to collect signal strength data of the target satellite; A prediction module is used to predict the future position of the target satellite and the antenna pointing angle based on the satellite orbit model and historical data; An error compensation module, used to calculate and correct antenna pointing errors; The closed-loop control module is used to adjust the antenna attitude in real time according to the corrected pointing parameters and continuously track the target satellite.

9. The parabola antenna pointing tracking system in an intersatellite communication scenario according to claim 8, characterized in that: The prediction module comprises: A satellite orbit prediction unit, used to calculate the future position of the target satellite based on the satellite's orbit model and historical data; An antenna pointing prediction unit is used to predict the corresponding antenna pointing angle according to the future position of the target satellite; The data fusion unit is used to fuse the orbit prediction and antenna pointing prediction data.

10. The parabola antenna pointing tracking system in an intersatellite communication scenario according to claim 8, characterized in that: The closed-loop control module comprises: A pointing error calculation unit, used to calculate the error between the real-time antenna pointing and the predicted antenna pointing; A control signal generating unit, used to generate a control signal required for correcting the antenna pointing; The adjustment execution unit is used to adjust the rotation angle of the antenna according to the control signal and track the position of the target satellite in real time.

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