Satellite formation motion prediction optical target accurate tracking method
Patent Information
- Application Number
- CN202611103123.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-23
- Publication Date
- 2026-10-13
AI Technical Summary
[0003]现有的研究成果中激光测量跟踪未考虑编队卫星绕飞大范围相对运动特性，编队卫星在绕飞时，相对位置在短时间内发生显著变化，可能导致光学靶标回光不稳定甚至失锁
（1）本发明提供的一种卫星编队运动预测的光学靶标精确跟踪方法，针对传统激光跟踪算法依赖窄视场探测器、在大运动范围内因无法获取误差信号而被迫采用低精度开环捕获、仅在小范围内能维持高精度跟踪的局限，通过充分利用编队卫星星间高精度GNSS相对定位信息，构建基于统一测量坐标系的测量跟踪控制算法，解决了空间编队绕飞中因相对位置快速变化导致的激光回光失锁问题，实现了基于精确相对状态估计的快速闭环捕获及主动稳定高精度跟踪；
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Figure CN122902726A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a method for precise tracking of optical targets in predicting satellite formation motion, belonging to the field of high-precision satellite formation control and measurement technology. Background Technology
[0002] With the increasing demands for formation control technology, the performance and functionality of a single satellite are gradually becoming insufficient. Distributed satellite formation technology, through the collaborative work of multiple satellites to form specific formations, enables more efficient observation and scientific exploration. High-precision relative state measurement technology is one of the key technologies for improving the flight accuracy of distributed spacecraft formations. Laser technology, due to its high precision, high bandwidth, and strong anti-interference capabilities, can become a key means of inter-satellite measurement and communication, providing the possibility for high-precision relative positioning measurement and data transmission for formation satellites. Target satellites are equipped with optical targets; compared to other measurement methods, laser beams are narrower and have a smaller coverage area, requiring high-precision pointing alignment and tracking.
[0003] Existing research on laser measurement and tracking does not consider the large-scale relative motion characteristics of formation satellites during their orbital flight. During this flight, the relative positions of the satellites change significantly within a short period, potentially leading to unstable optical target reflection or even loss of lock. Traditional tracking designs cannot compensate for these dynamic changes in relative motion and have poor anti-interference capabilities. Summary of the Invention
[0004] The technical problem solved by this invention is to address the various shortcomings of existing traditional tracking design algorithms and propose a new one.
[0005] The present invention solves the above-mentioned technical problem through the following technical solution: A method for accurate optical target tracking based on satellite formation motion prediction includes: The satellite collects relative GNSS measurement information of the target satellite at the current moment, transforms it from the dual-satellite ground-fixed coordinate system to the local satellite formation coordinate system, and obtains the relative position and velocity data of the target satellite at the current moment. A state estimation model is constructed, using relative position and velocity data as state information, to estimate the optimal state of the target satellite using Kalman filtering; Obtain the offset and installation matrix of the antenna or drive mechanism between the local satellite and the target satellite. Calculate the corrected relative state vector and predicted relative state vector between the local satellite and the target satellite at the current moment using the target satellite's Kalman filter optimal state, the offset and installation matrix between the local satellite and the target satellite. Calculate the tracking pointing angle and angular velocity of the local laser relative to the optical target center of the target star based on the current corrected relative state vector between the local satellite and the target star, and the predicted relative state vector; The rotating mechanism is designed based on the optical target's tracking pointing angle and angular velocity to track commands and execute the tracking of the target star.
[0006] Methods for obtaining the relative position and velocity data of a target satellite include: Construct a state estimation model to obtain the predicted state and predicted covariance matrix of the target star at the current moment; The Kalman gain of the target star is calculated using the predicted state and prediction covariance matrix of the target star, and the predicted state and prediction covariance matrix of the target star are updated accordingly. The updated predicted state of the target satellite is taken as the optimal state of the target satellite using Kalman filtering.
[0007] The state estimation model is as follows:
[0008]
[0009] In the formula, This refers to the target star's state at the previous moment. The target star's predicted state is given by n, where n is the star's orbital angular velocity and t is the calculation step size. The target star covariance matrix at the previous time step. Predict the covariance matrix for the target star. The covariance matrix of the 6×6 dimensional diagonal state equation is... Let be the state transition matrix.
[0010] The Kalman gain of the target star The calculation method is as follows:
[0011] In the formula, The observation equation matrix, , It is a 6×6 dimensional diagonal measurement covariance matrix; Update the predicted status of the target star and predicting covariance matrix The method is as follows:
[0012] In the formula, This provides information on relative position and velocity measurements.
[0013] The offset between the local satellite and the target satellite is calculated based on the position offset vector of the GNSS antenna center relative to the local satellite and the target satellite in the local satellite coordinate system. , Then, based on the corresponding stellar measurement rotation matrices M1 and M2 of the local and target stars, respectively, the calculation method is as follows: .
[0014] The relative state vector between the local star and the target star after correction at the current moment Predicting the relative state vector The calculation method is as follows:
[0015]
[0016] .
[0017] The optical target tracking pointing angle and angular velocity relative to the target star are calculated based on the inverse mapping of the relative state vector, using the following method:
[0018]
[0019] In the formula, The pitch angle at the current moment. The azimuth angle at the current moment. To predict the pitch angular velocity at a given moment, To predict the azimuth angular velocity at a given time.
[0020] The method for designing the tracking command of the rotating mechanism based on the optical target's tracking pointing angle and angular velocity is as follows:
[0021]
[0022]
[0023] In the formula, It is a 2×2 positive definite diagonal control gain matrix. , For pitch angle error and azimuth angle error, This refers to the actual pitch and azimuth angles of the drive mechanism. This is the two-dimensional tracking and control command for the current moment.
[0024] During the generation of tracking commands for the rotating mechanism, the pointing angle and angular velocity of the optical target relative to the target star are used to compensate for the position difference between the rotating components of the local satellite and the phase center of the GNSS antenna.
[0025] The advantages of this invention compared to the prior art are: (1) The present invention provides a method for precise tracking of optical targets based on satellite formation motion prediction. It addresses the limitations of traditional laser tracking algorithms, which rely on narrow field-of-view detectors, are forced to adopt low-precision open-loop acquisition due to the inability to obtain error signals within a large range of motion, and can only maintain high-precision tracking within a small range. By making full use of the high-precision GNSS relative positioning information between the formation satellites, a measurement tracking control algorithm based on a unified measurement coordinate system is constructed. This solves the problem of laser backlight loss of lock caused by rapid changes in relative position during the flight of space formations, and realizes rapid closed-loop acquisition and active stable high-precision tracking based on accurate relative state estimation. (2) In view of the problem that traditional laser tracking algorithms cannot cope with the interference and changes in relative motion and the lag in predicted angular velocity caused by the deterioration of Kalman prediction filter performance, the present invention introduces angle outer loop feedback in angular velocity feedforward control, which effectively compensates for the motion dynamic error caused by high-speed fly-around, and realizes high-precision and high-robust continuous tracking of target stars in complex interference environment. Attached Figure Description
[0026] Figure 1 This is a schematic diagram of the formation satellite coordinate system provided by the present invention; Figure 2 A flowchart illustrating the invention tracking principle provided for this invention. Detailed Implementation
[0027] A method for precise tracking of an optical target based on satellite formation motion prediction includes the following design steps: (1) Collecting GNSS measurement information of the local satellite relative to the target satellite and converting it into the formation coordinate system to obtain relative position and velocity data; (2) Using the relative position and velocity in the formation coordinate system as state information, performing optimal state estimation of the target satellite using Kalman filtering; (3) Measuring the part correction between the local satellite and the target satellite, and using it to calculate the tracking pointing angle and pointing angular velocity relative to the target satellite after characterization by relevant parameters; (4) Using the tracking pointing angle and pointing angular velocity to generate laser tracking motion control commands for tracking control of the target satellite.
[0028] A method for precise optical target tracking based on satellite formation motion prediction, comprising the following steps: The satellite collects relative GNSS measurement information of the target satellite from the two-satellite ground-fixed coordinate system and transforms it to the local satellite formation coordinate system to obtain the relative position and velocity data of the target satellite. A state estimation model is constructed, using relative position and velocity data as state information, to estimate the optimal state of the target satellite using Kalman filtering; Obtain the positional offset between the local satellite and the target satellite, and use the target satellite's optimal Kalman filter state and the positional offset between the local satellite and the target satellite to calculate the corrected relative state vector between the local satellite and the target satellite at the current moment, and the predicted relative state vector. Calculate the optical target tracking pointing angle and angular velocity relative to the target star based on the current corrected relative state vector between the local satellite and the target satellite and the predicted relative state vector; The rotating mechanism is designed based on the optical target's tracking pointing angle and angular velocity to track commands and execute the tracking of the target star.
[0029] Methods for obtaining the relative position and velocity data of a target satellite include: Construct a state estimation model to obtain the predicted state and predicted covariance matrix of the target star at the current moment; The Kalman gain of the target star is calculated using the predicted state and prediction covariance matrix of the target star, and the predicted state and prediction covariance matrix of the target star are updated accordingly. The updated predicted state of the target satellite is taken as the optimal state of the target satellite using Kalman filtering.
[0030] The state estimation model is as follows:
[0031]
[0032] In the formula, This refers to the target star's state at the previous moment. The target star's predicted state is given by n, where n is the star's orbital angular velocity and t is the calculation step size. The target star covariance matrix at the previous time step. Predict the covariance matrix for the target star. The covariance matrix of the 6×6 dimensional diagonal state equation is... Let be the state transition matrix.
[0033] Kalman gain of the target star The calculation method is as follows:
[0034] In the formula, The observation equation matrix, , It is a 6×6 dimensional diagonal measurement covariance matrix; Update the predicted status of the target star and predicting covariance matrix The method is as follows:
[0035] In the formula, This provides information on relative position and velocity measurements.
[0036] The offset between the local satellite and the target satellite is calculated based on the position offset vectors of the GNSS antenna center relative to the local and target satellites in the local coordinate system. , Then, based on the corresponding stellar measurement rotation matrices M1 and M2 of the local and target stars, respectively, the calculation method is as follows: .
[0037] The relative state vector between the local and target stars after correction at the current moment Predicting the relative state vector The calculation method is as follows:
[0038]
[0039] .
[0040] The calculation methods for the optical target tracking pointing angle and angular velocity relative to the target star are as follows:
[0041]
[0042] In the formula, The pitch angle, It is the azimuth angle. The pitch angular velocity, This represents the azimuth angular velocity.
[0043] The method for designing the tracking command of the rotating mechanism based on the optical target's tracking pointing angle and angular velocity is as follows:
[0044]
[0045]
[0046] In the formula, It is a 2×2 positive definite diagonal control gain matrix. , For pitch angle error and azimuth angle error, This refers to the actual pitch and azimuth angles of the drive mechanism. This is the current two-dimensional tracking control command.
[0047] The above scheme obtains the corresponding pointing angle based on the inter-satellite GNSS relative information between the transmitting and receiving satellites. Since the installation of the rotating component is not aligned with the phase center of the GNSS antenna, a position offset conversion is required, and control commands for the rotating component are obtained from GNSS measurement information.
[0048] The following description, in conjunction with the accompanying drawings and preferred embodiments, provides further details: In the current embodiment, the relative relationship between the local satellite and the target satellite is as follows: Figure 1 As shown, the instruction control principle is as follows: Figure 2 As shown, using GNSS relative measurement information, Kalman filtering optimal state estimation obtains inter-satellite relative position and velocity data, corrects the installation parameters of onboard sensors and rotating mechanisms, and obtains the target pointing angle and angular velocity of the local satellite's laser relative to the target satellite. The target pointing angle and angular velocity, combined with the actual pointing angle information of the laser driver, generate laser tracking motion closed-loop control commands through a position feedback controller. Simultaneously, addressing the prediction angular velocity lag problem caused by the degraded performance of the Kalman predictive filter under high-speed fly-around relative motion, the system introduces feedforward angular velocity commands on top of the position outer-loop feedback control. By real-time correction of position deviations, it effectively compensates for delay errors, thereby significantly improving target tracking performance.
[0049] The specific process of this embodiment is as follows: (1) Use the original measurement information of the two-star ground-fixed system output by the GNSS system on the local star and convert it into the formation coordinate system to obtain the relative position and velocity information of the target star under the main star formation system; (2) Perform Kalman filtering on the relative position and velocity information of the current frame to estimate the optimal state and obtain the filtered state information. ; (3) Perform part correction between the local satellite measurement reference point and the target satellite tracking reference point, and calculate the current tracking pointing angle and the predicted pointing angular velocity; (4) Calculate the laser tracking motion control command by combining the predicted pointing angular velocity and the state feedback command of the drive mechanism; The specific calculation steps for the optimal state estimation of the target satellite using Kalman filtering include: (2-1) State and covariance prediction
[0050]
[0051] In the formula, This refers to the state at the previous moment. For the predicted state, n is the angular velocity of the principal star's orbit, and t is the calculation step size. Let be the covariance matrix of the previous time step. To predict the covariance matrix, The covariance matrix of the 6×6 dimensional diagonal state equation is... This is the state transition matrix; The state transition matrix is:
[0052] (2-2) Calculate the Kalman gain
[0053] In the formula, The observation equation matrix, , It is a 6×6 dimensional diagonal measurement covariance matrix; (2-3) Update status information and covariance
[0054] In the formula, Information on relative position and velocity measurements; In step (3), the specific calculation steps for the location correction between the GNSS measurement reference point and the tracking reference point include:
[0055] To correct the current relative state vector between stars, This is the corrected inter-satellite predicted relative state vector; This represents the current state information obtained from the Kalman filter. , M1 and M2 are the position offset vectors of the GNSS antenna center relative to the tracking reference point in the coordinate system of the primary and secondary satellites, respectively, and the satellite measurement rotation matrices of the primary and secondary satellites, respectively.
[0056] In step (3), the specific calculation method for obtaining the optical target tracking pointing angle and angular velocity is as follows:
[0057]
[0058] The specific calculation method for obtaining the tracking command of the rotating mechanism is as follows:
[0059] in, It is a 2×2 positive definite diagonal control gain matrix. , For pitch and azimuth errors, , This indicates the actual pitch and azimuth angles of the drive mechanism. This is the current two-dimensional tracking control command. This embodiment addresses the limitations of traditional laser tracking algorithms, which rely on open-loop acquisition, are prone to lock-loss, and have poor anti-interference capabilities under large-scale, rapid relative motion. It proposes a tracking scheme based on high-precision GNSS relative positioning and a composite control strategy using a formation coordinate system. By introducing an extended Kalman filter, high-precision relative position and velocity states are obtained while effectively filtering out high-frequency measurement noise and suppressing noise amplification. This solves the problem of backlight instability caused by drastic changes in relative position during large-scale flight maneuvers, achieving accurate tracking across the entire space range. Simultaneously, a velocity feedforward + position outer-loop feedback control architecture is constructed. Position feedback is used to compensate for dynamic errors caused by filter lag in real time, thus achieving highly robust and high-precision closed-loop stable tracking under high-speed, high-interference conditions.
[0060] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.
[0061] The contents not described in detail in this specification are common knowledge to those skilled in the art.
Claims
1. A method for precise optical target tracking based on satellite formation motion prediction, characterized in that... include: The satellite collects relative GNSS measurement information of the target satellite at the current moment, transforms it from the dual-satellite ground-fixed coordinate system to the local satellite formation coordinate system, and obtains the relative position and velocity data of the target satellite at the current moment. A state estimation model is constructed, using relative position and velocity data as state information, to estimate the optimal state of the target satellite using Kalman filtering; Obtain the offset and installation matrix of the antenna or drive mechanism between the local satellite and the target satellite. Calculate the corrected relative state vector and predicted relative state vector between the local satellite and the target satellite at the current moment using the target satellite's Kalman filter optimal state, the offset and installation matrix between the local satellite and the target satellite. Calculate the tracking pointing angle and angular velocity of the local laser relative to the optical target center of the target star based on the current corrected relative state vector between the local satellite and the target star, and the predicted relative state vector; The rotating mechanism is designed based on the optical target's tracking pointing angle and angular velocity to track commands and execute the tracking of the target star.
2. The method for precise optical target tracking based on satellite formation motion prediction according to claim 1, characterized in that: Methods for obtaining the relative position and velocity data of a target satellite include: Construct a state estimation model to obtain the predicted state and predicted covariance matrix of the target star at the current moment; The Kalman gain of the target star is calculated using the predicted state and prediction covariance matrix of the target star, and the predicted state and prediction covariance matrix of the target star are updated accordingly. The updated predicted state of the target satellite is taken as the optimal state of the target satellite using Kalman filtering.
3. The method for precise optical target tracking based on satellite formation motion prediction according to claim 2, characterized in that: The state estimation model is as follows: In the formula, This refers to the target star's state at the previous moment. The target star's predicted state is given by n, where n is the star's orbital angular velocity and t is the calculation step size. Let be the target star covariance matrix at the previous time step. Predict the covariance matrix for the target star. The covariance matrix of the 6×6 dimensional diagonal state equation is... Let be the state transition matrix.
4. The method for precise optical target tracking based on satellite formation motion prediction according to claim 3, characterized in that: The Kalman gain of the target star The calculation method is as follows: In the formula, The observation equation matrix, , It is a 6×6 dimensional diagonal measurement covariance matrix; Update the predicted status of the target star and predicting covariance matrix The method is as follows: In the formula, This provides information on relative position and velocity measurements.
5. The method for precise optical target tracking based on satellite formation motion prediction according to claim 4, characterized in that: The offset between the local satellite and the target satellite is calculated based on the position offset vector of the GNSS antenna center relative to the local satellite and the target satellite in the local satellite coordinate system. , Then, based on the corresponding stellar measurement rotation matrices M1 and M2 of the local and target stars, respectively, the calculation method is as follows: .
6. The method for precise optical target tracking based on satellite formation motion prediction according to claim 5, characterized in that: The relative state vector between the local satellite and the target satellite after correction at the current moment Predicting the relative state vector The calculation method is as follows: 。 7. The method for precise optical target tracking based on satellite formation motion prediction according to claim 6, characterized in that: The optical target tracking pointing angle and angular velocity relative to the target star are calculated based on the inverse mapping of the relative state vector, using the following method: In the formula, The pitch angle at the current moment. The azimuth angle at the current moment. To predict the pitch angular velocity at a given moment, To predict the azimuth angular velocity at a given time.
8. The method for precise optical target tracking based on satellite formation motion prediction according to claim 7, characterized in that: The method for designing the tracking command of the rotating mechanism based on the optical target's tracking pointing angle and angular velocity is as follows: In the formula, It is a 2×2 positive definite diagonal control gain matrix. , For pitch angle error and azimuth angle error, This refers to the actual pitch and azimuth angles of the drive mechanism. This is the two-dimensional tracking and control command for the current moment.
9. The method for precise optical target tracking based on satellite formation motion prediction according to claim 8, characterized in that: During the generation of tracking commands for the rotating mechanism, the pointing angle and angular velocity of the optical target relative to the target star are used to compensate for the position difference between the rotating components of the local satellite and the phase center of the GNSS antenna.