Optimal avoidance method for satellite laser communication under sunshine or interference light source

Abstract

The invention belongs to the field of satellite laser communication, and particularly relates to an optimal avoidance method for satellite laser communication under a sunshine or interference light source. Comprising the following steps: acquiring satellite historical position information based on a remote control telemetering receiver; establishing adaptive position prediction by adopting a UKF (Unscented Kalman Filter); determining whether a sunshine phenomenon occurs based on the predicted position information; and establishing a target optimization model of the optimal pointing path based on the minimum solar-solar evasion vector. According to the invention, calling of on-satellite computing resources can be avoided or high-precision blind tracking of the target can be realized in a remote control and telemetering unavailable stage, the dependence on the system is reduced, and the stability is improved; according to the method, the planning of a sun-sun avoidance autonomous path at a given angle can be realized, the most suitable pointing vector is found according to the shortest distance and the fastest speed, and the dependence on manpower and satellite computing resources is reduced; the time required for scanning and capturing again under the condition that the link is suddenly disconnected can be shortened by the system according to the predicted result; the method is multiple in application scenes and high in adaptability.

Description

Technical Field

[0001] The present invention belongs to the field of satellite laser communication, and particularly relates to an optimal avoidance method for satellite laser communication under solar eclipse or interference light sources. Background Art

[0002] Satellite laser communication (Gbps or even 100 Gbps) has the advantages of high communication rate, light and miniaturized terminals, low power consumption, good confidentiality, etc. compared with satellite microwave communication (Mbps). Currently, after going through test phases such as early ground verification and on-orbit link verification, it has gradually entered the commercial application stage. For example, SpaceX in the United States has equipped 4 laser communication modules in the Gen2 constellation of its Starlink V1.5 version, which can establish links with the two satellites in front and behind in the same orbit and inter-orbit laser communication satellites. Currently, about 3000 V1.5 version satellites have been launched, and in its V2.0 version, it plans to launch lighter and smaller mini-satellites, equipped with optical inter-satellite link terminals, with an expected communication rate of 100 Gbps. (Detailed introduction to all Starlink satellites, band spectrum, laser inter-satellite link technology, data transmission rate, etc. - CSDN blog). NASA proposed the "Artemis Ⅱ" manned lunar orbiting space program in 2023, which will provide an inter-satellite laser link for 4K video for the Orion satellite in lunar orbit. (Analysis of the development status and trends of satellite laser communication technology). Building the sixth-generation space high-speed information network is the development trend of satellite optical communication technology. Currently, the terminals of satellite laser communication technology are developing towards standardization and modularization, and the inter-satellite link technology is evolving towards networking and building a low-latency and fast network. The link layer is for various payloads such as aircraft, tethered balloons, ships, submarine terminals, missiles, vehicles, etc., and the service targets tend to be sparsely populated places such as deserts, deserts, and the sea surface.

[0003] Capture, pointing, and tracking in the satellite laser link are crucial for the stability of the laser link. Whether a stable link can be established within a short time to achieve high-precision tracking is the key to affecting communication quality. However, there are various factors that affect the link stability, such as vibration, bias error, body installation error, etc. Many scholars already have mature analysis techniques for the analysis of pointing errors caused by vibration, bias error, etc. But the laser communication terminal will also be affected by various stray lights and interference sources when working in space, such as the predictable solar eclipse phenomenon and unpredictable laser (strong light) interference, etc. On the one hand, the solar eclipse will cause the detector saturation phenomenon and then lead to link interruption, and the signal intensity is generally at 10 -6When the sun transit phenomenon occurs, the noise intensity received by the detector is comparable to the signal light intensity, which will result in a very low signal-to-noise ratio. On the other hand, the sun transit will also bring thermal disturbances, especially the internal and external temperature differences on the surface of the Cassegrain primary mirror, which will cause wavefront distortion and lead to pointing errors. Moreover, the influence of thermal disturbances on the optical axis pointing does not only occur during the sun transit. Since the fields of view of the acquisition and tracking optical paths are very small, generally only dozens or hundreds of urad, the angle between the inter-satellite link connection and the line connecting the target satellite and the sun is very small, so the probability of the sun transit occurring is relatively low. However, when approaching the sun transit angle, the thermal disturbance of the primary mirror has already occurred, and then the required true avoidance angle will be much larger than the sun transit angle. Generally, the sun transit lasts for a short time of a few seconds or a long time of a few minutes, and it has a certain regularity. Patent CN119363202A introduces a method and detection device for early calculation of sun transit avoidance, CN118611767A introduces a sun transit avoidance device and method for a ground station device, CN116961733A proposes a sun transit avoidance for an inter-satellite laser link, CN116112061A introduces a design of a sun transit avoidance route, and CN114584198A introduces a medium and method for autonomous sun transit avoidance. The problems to be solved by the above solutions are to realize the prediction of the occurrence of the sun transit, and the processing method is to only judge whether the sun transit will occur. After it occurs, it is necessary to rely on manual operation to achieve avoidance. After manual avoidance, it is necessary to capture the target again, resulting in problems of long time consumption and low automation, reducing the robustness of the link. At the same time, the avoidance accuracy is low, it is difficult to completely prevent the link from being interrupted, and the reliability of the link still cannot be guaranteed.

[0004] Practice has confirmed that there can be many avoidance paths for the sun transit, and there must be an optimal path among them. In the case of extremely tight communication time resources, it is very necessary to study the fastest maneuver to achieve sun transit avoidance. Summary of the Invention

[0005] The present invention provides an optimal avoidance method for satellite laser communication under sun transit or interfering light sources to overcome the problems of long time consumption, low automation, low avoidance accuracy, difficulty in completely preventing link interruption, and still unable to guarantee the reliability of the link existing in the prior art.

[0006] To achieve the above object, the present invention proposes the following scheme: An optimal avoidance method for satellite laser communication under sun transit or interfering light sources, comprising the following steps:

[0007] Step 1: Obtain the historical position information of the satellite based on the telemetry and telecommand receiver:

[0008] Step 2: Establish an adaptive position prediction using UKF;

[0009] Step 3: Determine whether the sun transit phenomenon occurs based on the predicted position information;

[0010] Step 4. Establish an objective optimization model for the optimal pointing path based on the minimum sun transit avoidance vector

[0011] including non - linear equality constraints,

[0012] selection of the initial coordinate values,

[0013] Furthermore, the above - mentioned Step 2 includes the following specific steps:

[0014] Step (1). Solve the pointing angle of the satellite laser - link optoelectronic device: Transfer the pointing instruction information in the terminal coordinate system O - X t Y t Z t and the satellite position information in the orbital coordinate system O - X o Y o Z o to the O - X e Y e Z e inertial coordinate system through coordinate transformation;

[0015] Step (2). According to the current position information, adopt an unscented Kalman filter satellite - pointing - angle multi - step prediction strategy based on an adaptive motion model to predict the position information for the next n steps, and obtain the position coordinates of Satellite A and Satellite B for the next n steps.

[0016]

[0017] Furthermore, the above - mentioned Step 2(2) includes the following specific steps:

[0018] Step 1. Read the terminal - pointing - angle data, and generate Sigma points by setting parameters of position, velocity, and acceleration;

[0019] Step 2. Analyze the angular motion characteristics of the laser link, and then conduct azimuth and elevation predictions. After calculating the gain, perform azimuth and elevation angle measurements;

[0020] Step 3. Judge sun transit according to the predicted angle information.

[0021] Furthermore, in the above - mentioned Step 2, taking the relative motion angle, angular velocity, and angular acceleration of the inter - satellite laser link as the basic parameters of the state - transition matrix, establish a state - transition matrix of the inter - satellite laser link based on a non - linear model as:

[0022]

[0023] where φ and are the included angles in the azimuth and elevation directions respectively, and dt is the sampling time interval.

[0024] Furthermore, in the above step 3, a method for introducing a proportional factor of the prediction step length and the data volume, the magnitude of the motion state noise, and the step length adjustment of the jerk is expressed by the formula:

[0025] m = m R + m N + m J (19)

[0026] where m is the prediction step length, and m R = ε i R, where ε i represents the weight, R represents the proportional relationship between the prediction step length and the data volume, and m N = ε 2 N, representing the influence of the noise magnitude on the step length, and m J = ε 3 J, representing the step length change caused by the satellite jerk.

[0027] Compared with the prior art, the advantages of the present invention are as follows:

[0028] 1. The satellite motion trajectory is continuous and predictable. The present invention adopts an adaptive unscented Kalman multi-step prediction algorithm based on the terminal historical attitude and position information, which can realize multi-step position prediction based on the current remote control and telemetry satellite position information, avoid calling on-board computing resources, or achieve high-precision blind tracking of the target during the stage when remote control and telemetry are unavailable, reduce the dependence on the system, and improve its stability.

[0029] 2. The present invention adopts an intelligent optimization algorithm, which can realize the planning of the autonomous path for sun outage avoidance at a given angle, and find the most suitable pointing vector according to the shortest distance and the fastest speed. The non-linear state transition matrix is closer to the actual situation than the linear state transition matrix, and can achieve the purpose of autonomous planning, greatly reducing the dependence on manual and satellite computing resources.

[0030] 3. The present invention can predict the satellite position in the future multi-steps, thereby predicting the sun outage, and adjust the turntable pointing to avoid direct sunlight according to the avoidance position obtained by the optimization algorithm. Therefore, the prediction result can guide the acquisition and tracking of satellite laser communication, and can systematically reduce the time required for re-scanning and acquisition when the link is suddenly disconnected.

[0031] 4. The present invention has a wide range of application scenarios and strong adaptability: this method can be used under various stray light and interference light sources, such as predictable sun outage phenomena and unpredictable laser (strong light) interference conditions. Brief Description of the Drawings

[0032] Figure 1This is a descriptive diagram of the laser pointing that requires four coordinate systems when the present invention performs aiming;

[0033] Figure 2 This is a flowchart of the laser communication link pointing angle prediction based on UKF of the present invention;

[0034] Figure 3 This is a schematic diagram of the sun outage avoidance optical axis pointing process of the present invention;

[0035] Figure 4 This is a flowchart of the sun outage optimization avoidance process of the present invention.

[0036] Figure 5 This is an example diagram of the simulation results of the optimal avoidance pointing position under different avoidance angles and turntable maneuvering states

[0037] Figure 5 (a) is an example diagram of the simulation results of the azimuth axis;

[0038] Figure 5 (b) is an example diagram of the simulation results of the pitch axis;

[0039] Figure 6 This is a prediction result diagram of the azimuth angle and pitch angle of the inter-satellite laser link by respectively using the typical Kalman filter and the unscented Kalman filter:

[0040] Figure 6 (a) is an example of the prediction result of the pointing angle of the typical Kalman filter optoelectronic tracking device, and the information diagram of the azimuth axis of the filter prediction;

[0041] Figure 6 (b) is an example of the prediction result of the pointing angle of the typical Kalman filter optoelectronic tracking device, and the information diagram of the pitch axis of the filter prediction;

[0042] Figure 6 (c) is an example of the prediction result of the pointing angle of the adaptive unscented Kalman filter optoelectronic tracking device, and the information diagram of the azimuth axis of the UKF filter prediction;

[0043] Figure 6 (d) is an example of the prediction result of the pointing angle of the adaptive unscented Kalman filter optoelectronic tracking device, and the information diagram of the pitch axis of the UKF filter prediction. Specific embodiments

[0044] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, which are only used to illustrate the present invention, but not to limit the scope of the present invention.

[0045] A system adopted by an optimal avoidance method for satellite laser communication under solar eclipse or interference light sources, including a laser communication terminal for realizing beam collimation and transceiver, a two-dimensional turntable for executing avoidance strategies, an on-board computer for calculating the optimal path to formulate avoidance strategies, a satellite platform for carrying the laser communication payload, an attitude measurement device for measuring the current attitude information of the satellite, and a remote control and telemetry signal receiver for receiving the current position of the satellite.

[0046] Coordinate system description: As Figure 1 shown, four coordinate systems are required to participate in the description of laser pointing when the method of the present invention is aiming, which are respectively:

[0047] Communication terminal coordinate system O-X t Y t Z t Take the center of the communication terminal and the satellite installation surface as the coordinate system O point, O z is perpendicular to the installation surface and points outwards, OX and OY are perpendicular to each other, and when PAT rotates, it rotates around OX in the azimuth direction α and around OY in the pitch direction by an angle β.

[0048] Satellite body coordinate system O-X s Y s Z s Take the center of mass as the O point, the forward direction as the OX axis, that is, the spin axis, the perpendicular line OY of the longitudinal symmetry plane as the pitch axis, and OZ is perpendicular to OX and OY as the yaw axis;

[0049] Satellite orbit coordinate system O-X o Y o Z o ; Take the center of mass of the satellite as the O point, the line connecting the center of mass and the geocenter E as OZ and pointing to the geocenter, the satellite orbit velocity direction as OX, and the OY axis as the normal of the orbit plane;

[0050] Equatorial inertial coordinate system O-X e Y e Z e Take the center of the earth as the O point, OX points to the vernal equinox, OZ points to the earth's axis of rotation, and the OY axis is formed according to the right-hand rule.

[0051] An optimal avoidance method for satellite laser communication under solar eclipse or interference light sources includes the following steps:

[0052] Step 1: Obtain the historical position information of the satellite based on the remote control and telemetry receiver:

[0053] Step 2: Establish an adaptive position prediction using UKF

[0054] Step 3: Determine whether a solar eclipse occurs based on the predicted position information

[0055] Step 4. Establish an objective optimization model for the optimal pointing path based on the minimum solar eclipse avoidance vector

[0056] including linear equality constraints,

[0057] selection of initial coordinate values,

[0058] Embodiment: An optimal avoidance method for satellite laser communication under solar eclipse or interfering light sources. Refer to Figure 1 , taking Satellite A and Satellite B as examples, specifically including the following steps:

[0059] Step 1. Obtain the historical position information of the satellite based on the telemetry and telecommand receiver:

[0060] The on-board computer obtains the historical position information of Satellite A and Satellite B received by the telemetry and telecommand signal receiver.

[0061] Step 2. Establish an adaptive position prediction using UKF, including the following steps:

[0062] Step (1) Solve the pointing angle of the optoelectronic device of the satellite laser link: Transform the pointing command information in the terminal coordinate system O-X t Y t Z t and the satellite position information in the orbital coordinate system O-X o Y o Z o to the O-X e Y e Z e in the inertial coordinate system through coordinate transformation.

[0063] Step (2) According to the current position information, adopt an unscented Kalman filter (UKF: Unscented Kalman Filter) satellite pointing angle multi-step prediction strategy based on an adaptive motion model to predict the position information for the next n steps. The specific process is as Figure 2 shown:

[0064] Step 1. Read the terminal pointing angle data and generate Sigma points by setting parameters such as position, velocity, and acceleration:

[0065]

[0066] where λ = α 2 (n + κ) - n is the scaling factor. The larger the value, the farther away from the state mean. n is the state dimension, denotes the Cholesky decomposition.

[0067] Combined with the Sigma point weights, in this embodiment, the mean weights of each point With variance weights They are respectively:

[0068]

[0069] For the Gaussian model, in this embodiment, conventional selection is adopted, β = 2, κ = 3 - n, α satisfies 0 ≤ α ≤ 1, and the predicted sigma points are:

[0070]

[0071] where f(·) represents a non - linear transformation.

[0072] Furthermore, calculate the predicted mean and covariance of the sigma points:

[0073]

[0074] The above process is the generation and prediction process of the sigma sampling points in UKF.

[0075] Step 2: Analyze the angular motion characteristics of the laser link, so as to perform azimuth and elevation prediction. After calculating the gain, perform azimuth and elevation angle measurement.

[0076] First, a state transition matrix for the angular motion of the link needs to be established. The specific method is as follows:

[0077] For the inter - satellite laser link, a relatively high prediction accuracy is required to reduce the time required for reacquisition and improve the capture probability. Generally, the uncertainty region caused by factors such as pointing error, attitude control error, and orbit determination error is on the order of mrad. Therefore, the prediction accuracy of UKF for the trajectory cannot be higher than mrad. And a main factor affecting the prediction accuracy of the UKF trajectory is to determine an appropriate state transition matrix (i.e., the motion model). For the pointing angle of the inter - satellite laser link, it was previously considered that its motion state conforms to a linear model. In fact, when the inter - satellite link is aiming ahead, its sampling frequency is time - varying (2L / c, where c is the speed of light and L is the inter - satellite distance), and the angular accelerations of the azimuth and elevation angles are time - varying. Therefore, the present invention uses the relative motion angle, angular velocity, and angular acceleration of the inter - satellite laser link as the basic parameters of the state transition matrix, and establishes a state transition matrix of the inter - satellite laser link based on a non - linear model:

[0078]

[0079] where φ and are respectively the angles in the azimuth and elevation directions, and dt is the sampling time interval.

[0080] The observation matrix is the angles of the azimuth and elevation axes:

[0081]

[0082] The covariance of the one-step prediction result is:

[0083] P(k + 1,k) = F(k)P(k|k)F T (k) + G(k)Q(k)G T (k)(15)

[0084] Q(k) is the process covariance matrix, and the update equation for the prediction result is:

[0085]

[0086] is the UKF gain. represents the update of the prediction result, the prediction of the next state under the prior information at step K, is the residual.

[0087] Step 3, perform sun outage judgment based on the predicted angle information:

[0088] Judgment is "No", continue to predict the movement, update the state transition matrix to generate new sigma points: In the non-linear transformation, the state update process is the same as the ordinary Kalman algorithm. First, the state transition matrix (Φ k，k-1 ) and the observation matrix (H) need to be determined. The state transition matrix describes the evolution mode of the system state, while the observation matrix maps the system state to the observation space. In addition, there are two covariance matrices: the prediction covariance matrix (P) and the observation covariance matrix (R). The prediction covariance matrix describes the uncertainty of the predicted system state, while the observation covariance matrix describes the uncertainty of the observed value. The core equations of the Kalman filter are the one-step prediction equation and the observation equation.

[0089] x k+1 = Φ k+1,k x(k) + w(k) (11)

[0090] z k+1 = hx k+1 + v k+1 (12)

[0091] where z(K) is the observed value, x(k) is the one-step prediction state, Φ k+1，k is the one-step state transition matrix of the system, w(k) is the system noise, h represents the observation matrix, and v(k + 1) is the measurement noise sequence.

[0092] Substitute the new set of sigma points into the observation equation to obtain the predicted observed quantity:

[0093]

[0094] The covariance of the system is updated as follows:

[0095] P = (I - K k+1 h k+1 )P k+1,k (18)

[0096] For multi-step prediction, the state and error are no longer updated. Only past data is used to predict multiple steps into the future. However, through simulation based on the above model, it is found that the length of past data should not be too long or too short. If it is too short, the amount of data is insufficient for the system to make accurate predictions. If it is too long, the cumulative error is large, resulting in an increase in error. On the other hand, the prediction accuracy is also related to the motion state of the inter-satellite laser link, such as system position noise, jerk, etc. In this paper, a variable-step multi-step prediction method based on past data and angular velocity characteristics is adopted, that is, a step size adjustment method that introduces the proportional factor of the prediction step size and the amount of data, the magnitude of the motion state noise, and jerk. The formula is expressed as:

[0097] m = m R + m N + m J (19)

[0098] where m is the prediction step size, and m R = ε i R, ε i represents the weight, R represents the proportional relationship between the prediction step size and the amount of data, m N = ε 2 N, represents the influence of the noise magnitude on the step size, m J = ε 3 J, represents the change in the step size due to satellite jerk.

[0099] If the determination is "yes", the position coordinates of satellite A and satellite B in the next n steps are obtained respectively.

[0100]

[0101] As Figure 6 shown, Figure 6 (a) and Figure 6 (b) are traditional Kalman filters, Figure 6 (c) and Figure 6(d) is the unscented Kalman filter. In the simulation, 10-step prediction is adopted. By analyzing the prediction results, it can be seen that whether it is the traditional Kalman or the unscented Kalman filter, their one-step predictions can maintain a high prediction accuracy. The prediction of the traditional Kalman filter can basically reach an accuracy of about 0.001 - 0.002°, while the UKF is higher. For multi-step predictions, as the prediction step length increases, the prediction accuracies of both methods decrease to a certain extent. However, the UKF has a higher multi-step prediction accuracy compared to the typical Kalman filter. This can be seen from the prediction of the pitch angle of the Kalman filter. Its multi-step prediction accuracy deteriorates as the step length increases, while the UKF can maintain within the range of 0.02 - 0.05 in both azimuth and pitch directions for multi-step predictions, meeting the requirements of the laser communication link for the size of the uncertain region.

[0102] Step 3: Determine whether solar eclipse occurs based on the predicted position information:

[0103] As Figure 3 shown in the schematic diagram of avoiding solar eclipse in satellite optical communication, S is the sun, B is the target satellite, A is the transmitting satellite, B' is the direction of avoiding solar eclipse, θ is the angle between the optical axis from A to B and the line connecting A and the sun, θ' is the minimum avoidance angle. Assume that the positions of each point in the ecliptic coordinate system are P A , P B , the position of point B' is unknown, and the motion vector of satellite B relative to satellite A is The vector of point B relative to point A is The vector of the sun relative to point A is:

[0104] When the angle between the line connecting satellite A and satellite B predicted and the line connecting satellite A and the sun is less than the solar eclipse determination threshold, it can be determined that a solar eclipse has occurred. This process can be expressed as:

[0105]

[0106] where θ AS is the angle between the line connecting the home satellite and the target satellite and the line connecting the home satellite and the sun, and can be expressed as:

[0107]

[0108] θ T is the size of the threshold field of view angle.

[0109] Step 4: Establish an objective optimization model for the optimal pointing path based on minimizing the solar eclipse avoidance vector:

[0110] See Figure 4, when it is determined that solar eclipse occurs, avoidance is required. The angle between the line connecting the satellite position B' after avoidance and satellite A and the line connecting the sun and satellite A can be expressed as:

[0111]

[0112] Assume that the instantaneous motion vector of the turntable from B to B' is Then the actual rotation vector magnitude of the PAT system can be expressed as the sum of the instantaneous motion vector of satellite B relative to A in the orbital direction and the vector of the A terminal PAT turntable from B to B'. This process can be expressed as:

[0113]

[0114] According to the vector and the vector the vector between B' and A after avoidance can be obtained as Then the angle between B'A and SA after avoidance can be obtained as:

[0115]

[0116] When θ > θ', the avoidance requirement is met. Assume that the angular velocity of the PAT turntable rotation in each direction is equal, and the angular velocities in the azimuth direction and the pitch direction are θ Az and θ El , then

[0117]

[0118] The above problem can be reduced to a path optimization problem, that is, under certain conditions (inequality constraints), the objective is minimized. This process can be expressed as:

[0119]

[0120] Referring to Figure 5 , the simulation results of the optimal avoidance pointing position under different avoidance angles and turntable maneuvering states can be seen, indicating that the most suitable pointing vector can be successfully found according to the shortest distance and the fastest speed.

[0121] The above content is only to illustrate the technical idea of the present invention, and the protection scope of the present invention cannot be limited thereby. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. An optimal avoidance method for satellite laser communication under solar eclipse or interfering light source, characterized by: The following steps are involved: Step 1: Obtain satellite historical position information based on remote control telemetry receiver: Step 2: Use UKF to establish adaptive position prediction; Step 3: determining whether a solar eclipse occurs based on the predicted position information; Step 4: Establish a target optimization model based on the optimal pointing path with the smallest solar eclipse avoidance vector Contains nonlinear equality constraints, Selection of initial coordinate values, 2. The optimal avoidance method for satellite laser communication under solar eclipse or strong light according to claim 1, characterized in that: The step 2 includes the following specific steps: Step (1) Solve the pointing angle of the optoelectronic device of the satellite laser link: transform the terminal coordinate system OX t Y t Z t The pointing instruction information and orbital coordinate system OX o Y o Z o The satellite position information under is converted to OX e Y e Z e In inertial coordinate system; Step (ii) Based on the current position information, the unscented Kalman filter satellite pointing angle multi-step prediction strategy based on the adaptive motion model is used to predict the position information of the next n steps, and obtain the position coordinates of star A and star B in the next n steps.

3. The optimal avoidance method for satellite laser communication under solar eclipse or interfering light source according to claim 1 is characterized by: The step 2 (ii) comprises the following specific steps: Step 1: Read the terminal pointing angle data and generate Sigma points by setting the parameters of position, velocity and acceleration; Step 2: Analyze the angular motion characteristics of the laser link to predict the azimuth and elevation, and measure the azimuth and elevation angles by calculating the gain; Step 3: Determine the solar eclipse based on the predicted angle information.

4. The optimal avoidance method for satellite laser communication under solar eclipse or interfering light source according to claim 3 is characterized by: In step 2, the relative motion angle, angular velocity and angular acceleration of the intersatellite laser link are used as the basic parameters of the state transfer matrix, and the intersatellite laser link state transfer matrix based on the nonlinear model is established as follows: where φ and are the angles between azimuth and elevation, and dt is the sampling time interval.

5. The optimal avoidance method for satellite laser communication under solar eclipse or interfering light source according to claim 4, characterized in that: In step 3, the proportional factor between the prediction step length and the data volume, the noise level of the motion state and the step length adjustment method of the jerk are introduced, and the formula is expressed as follows: m=m R +m N +m J (19) Where m is the prediction step length, R =ε i R, ε i represents the weight, R represents the proportional relationship between the prediction step length and the amount of data, m N =ε2N, indicating the effect of noise on step size, m J =ε3J, which indicates the change in step size due to the rapid motion of the satellite.

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