Low earth orbit satellite antenna cooperative control tracking method and system based on multi-target task

Abstract

The application provides a low-orbit satellite antenna cooperative control tracking method and system based on multi-target tasks. The method comprises the following steps: determining an executable tracking segment according to a predicted motion state of a target task and a dynamic execution capability of an antenna execution unit; establishing a migration relationship according to a state transition condition between the executable tracking segments and a relay condition of the same target task across the antenna execution units, and forming a multi-target dynamic tracking continuous network; when a main tracking execution unit executes target tracking, decomposing a tracking residual into a target common deviation state and a local deviation state; when a subsequent execution state satisfies the relay condition, making a candidate relay execution unit execute target pre-pointing; when the candidate relay execution unit satisfies a stable tracking condition, executing a main tracking state migration, and updating the multi-target dynamic tracking continuous network and a subsequent tracking continuous path. The application can improve the multi-target task scheduling and tracking matching degree, reduce the cross-antenna relay error, and improve the continuous tracking stability.

Description

Technical Field

[0001] This application relates to the field of satellite communication and ground station antenna control technology, and in particular to a low-orbit satellite antenna cooperative control and tracking method and system based on multi-target missions. Background Technology

[0002] As the scale of low-Earth orbit (LEO) satellite constellations continues to expand, ground control, communication, and data receiving stations need to perform continuous tracking, communication, or telemetry / control tasks on multiple high-speed moving LEO satellite targets under limited antenna resources. LEO satellites are characterized by short transit times, high apparent motion speeds, frequent overlapping of visible windows, and drastic changes in angular velocity near the zenith. This necessitates that ground antennas not only possess high servo tracking capabilities but also dynamically coordinate and rapidly switch between multiple target tasks.

[0003] Existing technologies typically calculate the satellite visibility window based on satellite ephemeris and ground station location, and then allocate tasks between satellites and antennas according to mission priority, visibility time, and antenna idle status. During the execution phase, antenna pointing is corrected through ephemeris guidance, predictive filtering, or signal feedback, and the target is switched to another antenna for continued tracking when the current antenna cannot continue performing its task. Some solutions also employ dual-antenna overlapping operation or multi-beam control to reduce the probability of link interruption during satellite switching.

[0004] However, existing solutions typically separate task scheduling from actual antenna tracking control. The visible window cannot directly reflect the antenna's actual continuous tracking capability in speed, attitude transitions, and high-dynamic regions, easily leading to situations where scheduling results are feasible but continuous tracking fails during execution. Furthermore, different antennas independently form tracking correction states, making it difficult to distinguish between common target trajectory deviations and individual antenna control deviations. Switching between antennas can easily result in error inheritance or the need to re-search for the target. In addition, actual tracking results are often not promptly fed back to subsequent task allocation processes, making it difficult to balance tracking continuity and antenna resource utilization efficiency when multiple target tasks overlap, suddenly insert, or change execution states. Summary of the Invention

[0005] In view of this, embodiments of this application provide a low-orbit satellite antenna cooperative control and tracking method and system based on multi-target tasks, in order to solve the problems of task scheduling and tracking capability disconnection, cross-antenna relay error inheritance, and difficulty in closed-loop updating of tracking status in the prior art.

[0006] A first aspect of this application provides a low-Earth orbit (LEO) satellite antenna cooperative control and tracking method based on multiple target tasks, comprising: acquiring target tasks corresponding to multiple LEO satellites and the execution states of multiple antenna execution units; determining executable tracking segments based on the predicted motion state of the target tasks and the dynamic execution capabilities of the antenna execution units; establishing migration relationships based on state transition conditions between executable tracking segments and relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network; determining a continuous tracking path based on the task state of each target task; determining a main tracking execution unit and candidate relay execution units according to the continuous tracking path; and, in the main tracking execution unit... When performing target tracking, the tracking residual is decomposed into the target common deviation state and the local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state. When the subsequent execution state meets the relay condition, the candidate relay execution unit performs target pre-pointing by combining the target common deviation state and its own local deviation state, and updates the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase. When the candidate relay execution unit meets the stable tracking condition, the main tracking state is transferred, and the multi-target dynamic tracking continuous network and the subsequent tracking continuous path are updated based on the antenna execution state and the actual tracking state after the transfer.

[0007] A second aspect of this application provides a low-Earth orbit satellite antenna cooperative control and tracking system based on multiple target tasks, comprising: an acquisition module, configured to acquire target tasks corresponding to multiple low-Earth orbit satellites and the execution states of multiple antenna execution units, and determine executable tracking segments based on the predicted motion states of the target tasks and the dynamic execution capabilities of the antenna execution units; an establishment module, configured to establish migration relationships based on state transition conditions between executable tracking segments and relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network, and determine a continuous tracking path based on the task states of each target task; and a decomposition module, configured to determine the main tracking execution unit and candidate relay execution units according to the continuous tracking path, and in the main tracking... When the execution unit performs target tracking, it decomposes the tracking residual into the target common deviation state and the local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state. The update module is used to enable the candidate relay execution unit to perform target pre-pointing by combining the target common deviation state and its own local deviation state when the subsequent execution state meets the relay condition, and to update the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase. The execution module is used to perform the main tracking state transition when the candidate relay execution unit meets the stable tracking condition, and to update the multi-target dynamic tracking continuous network and the subsequent tracking continuous path based on the antenna execution state and the actual tracking state after the transition.

[0008] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects:

[0009] By acquiring the target missions corresponding to multiple low-Earth orbit satellites and the execution states of multiple antenna execution units, executable tracking segments are determined based on the predicted motion state of the target missions and the dynamic execution capabilities of the antenna execution units. A migration relationship is established based on the state transition conditions between executable tracking segments and the relay conditions across antenna execution units for the same target mission, forming a multi-target dynamic tracking continuous network. A continuous tracking path is determined based on the mission states of each target mission. The main tracking execution unit and candidate relay execution units are determined according to the continuous tracking path. When the main tracking execution unit performs target tracking, the tracking residual is decomposed into the target common deviation state of the corresponding target mission and the local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state. When the subsequent execution state meets the relay conditions, the candidate relay execution unit performs target pre-pointing by combining the target common deviation state and its own local deviation state, and updates the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase. When the candidate relay execution unit meets the stable tracking conditions, the main tracking state migration is performed, and the multi-target dynamic tracking continuous network and subsequent continuous tracking paths are updated based on the migrated antenna execution state and the actual tracking state. This application can improve the matching degree of multi-target task scheduling and tracking, reduce cross-antenna relay error, and improve the stability of continuous tracking. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating the low-orbit satellite antenna cooperative control and tracking method based on multi-target tasks provided in this application embodiment;

[0012] Figure 2 This is a schematic diagram of the structure of a low-orbit satellite antenna cooperative control and tracking system based on multi-target tasks provided in an embodiment of this application;

[0013] Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0014] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0015] In existing technologies, low-Earth orbit (LEO) satellite ground stations typically calculate the satellite visibility window based on satellite ephemeris, ground station location, and mission time requirements, and allocate satellite mission and antenna resources in conjunction with mission priorities and antenna idle status. During the actual tracking process, ephemeris guidance, predictive filtering, or signal feedback are generally used to correct antenna pointing; when the current antenna cannot continue tracking, the target is switched to another antenna for continued tracking. Some solutions also reduce the risk of link interruption during the switching process by using dual-antenna overlapping operation or multi-beam control.

[0016] However, existing multi-target task scheduling primarily relies on visibility time and resource occupancy status for decision-making, failing to fully consider the actual continuous tracking capabilities of antenna execution units under different attitudes, movement speeds, and high-dynamic regions. This easily leads to situations where task scheduling results meet time constraints, but the actual antennas cannot execute continuously. Furthermore, the correction values ​​generated by different antennas during tracking typically include a mixture of target trajectory prediction bias and antenna control bias. Directly inheriting the correction state during cross-antenna relay can easily introduce additional pointing errors, while re-searching for the target increases the risk of tracking interruption. In addition, the actual tracking status is difficult to feed back to subsequent task paths in a timely manner, resulting in a lack of dynamic adaptability in subsequent task scheduling when multi-target tasks change or antenna execution capabilities decline.

[0017] To address the aforementioned issues, this application first determines executable tracking segments that can be continuously executed by specific antennas based on the predicted motion states of multiple low-Earth orbit satellites corresponding to target missions and the dynamic execution capabilities of multiple antenna execution units. Further, it establishes migration relationships based on the state transition conditions between different executable tracking segments and the relay conditions across antenna execution units for the same target mission, forming a multi-target dynamic tracking continuous network, and determines the corresponding continuous tracking path for each target mission accordingly. During target tracking, based on the residual between the predicted motion state and the actual tracking state, the tracking residual is divided into the target common deviation state for the corresponding target mission and the local deviation state of the current antenna execution unit. This allows the target common deviation state to serve as target correction information shared across antennas, while the local deviation state remains associated with the specific antenna execution unit.

[0018] When the subsequent execution states in the tracking continuous path meet the relay conditions, this application enables the candidate relay execution unit to form a target pre-pointing state in advance by combining the target common deviation state and its own local deviation state. During the overlapping tracking phase with the main tracking execution unit, the target common deviation state and the locking state of the candidate relay execution unit are updated based on the actual tracking states of the two execution units. After the candidate relay execution unit reaches the stable tracking condition, the main tracking state transition is then performed, and the multi-target dynamic tracking continuous network and subsequent tracking continuous paths are updated based on the antenna execution state and actual tracking state after the transition, thus forming a closed-loop control process from task planning, cooperative tracking, state relay to network update.

[0019] Through the above technical solutions, this application can improve the matching degree between the multi-target task scheduling results and the actual tracking capability of the antenna, reduce the pointing deviation caused by the inheritance of local errors of the equipment during cross-antenna relay, and reduce the tracking gap caused by re-acquiring the target; at the same time, by continuously correcting the dynamic tracking continuous network and subsequent task paths through the actual tracking status, the continuous tracking stability and antenna resource collaborative utilization efficiency under the changing conditions of multi-target tasks can be improved.

[0020] The technical solution of this application will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0021] Figure 1 This is a flowchart illustrating the low-Earth orbit satellite antenna cooperative control and tracking method based on multi-target tasks provided in the embodiment. Figure 1 As shown, the method may specifically include:

[0022] S101: Obtain the target missions corresponding to multiple low-orbit satellites and the execution status of multiple antenna execution units, and determine the executable tracking segments based on the predicted motion status of the target missions and the dynamic execution capabilities of the antenna execution units.

[0023] S102, establish migration relationships based on the state transition conditions between executable tracking segments and the relay conditions of the same target task across antenna execution units, form a multi-target dynamic tracking continuous network, and determine the tracking continuous path based on the task status of each target task;

[0024] S103, determine the main tracking execution unit and candidate relay execution units according to the continuous tracking path. When the main tracking execution unit performs target tracking, decompose the tracking residual into the target common deviation state corresponding to the target task and the local deviation state of the main tracking execution unit according to the residual between the predicted motion state and the actual tracking state.

[0025] S104, when the subsequent execution state meets the relay condition, the candidate relay execution unit combines the target common deviation state and its own local deviation state to perform target pre-pointing, and updates the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase.

[0026] S105, when the candidate relay execution unit meets the stable tracking condition, the main tracking state is transferred, and the multi-target dynamic tracking continuous network and subsequent tracking continuous path are updated according to the antenna execution state and the actual tracking state after the transfer.

[0027] In some embodiments, the execution status of target tasks corresponding to multiple low-Earth orbit satellites and multiple antenna execution units is acquired, and executable tracking segments are determined based on the predicted motion state of the target tasks and the dynamic execution capabilities of the antenna execution units, including:

[0028] Based on the orbital status of the low-Earth orbit satellites corresponding to each target mission and the reference status of the ground station, the predicted motion status of the target mission within the predicted time range is generated.

[0029] The corresponding dynamic execution capability is determined based on the current attitude and motion constraints of each antenna execution unit, and the continuous tracking capability of the antenna execution unit for the target task is predicted.

[0030] The predicted motion state is matched with the dynamic execution capability in a time sequence to identify the effective time interval that meets the target reachability condition and the continuous tracking condition.

[0031] The executable tracking segment between the corresponding target task and the antenna execution unit is determined based on the effective time interval and the state transition margin between adjacent tasks.

[0032] Specifically, the ground station mission management module can read the orbital elements, epoch times, and mission start and end requirements of each low-Earth orbit satellite within the rolling scheduling cycle, and combine this with the ground station's latitude and longitude, elevation, unified time synchronization status, and horizon obstruction model to establish the target mission prediction input. For example, if the ground station currently has tracking missions for satellites A, B, and C simultaneously, the prediction range is set to the next 20 minutes, and the prediction step size is 1 second.

[0033] The positions and velocities of each satellite in the geocentric coordinate system are extrapolated based on their orbital states, and then converted to the local horizontal coordinate system of the ground station to obtain the azimuth, elevation, and their rates of change at each time point. Angular velocity and angular acceleration are calculated by the angle changes between adjacent prediction times. For orbital data with large prediction errors, a prediction confidence range can be generated simultaneously to expand the boundary for subsequent reachability assessment. Taking satellite A as an example, it enters the visible region at 180s and leaves at 760s. Between 430s and 470s, it approaches the zenith, and its predicted azimuth angular velocity increases from 6° / s to 19° / s. Based on this, a predicted motion state including target position, motion changes, and time index is formed.

[0034] For the antenna actuator, the current azimuth attitude, pitch attitude, current rotation speed, drive availability status, and task occupancy status can be periodically collected, and the mechanical limits, maximum rotation speed, maximum acceleration, and settling time in the device configuration can be read. The shortest turning time is calculated based on the angular displacement and motion constraints between the current attitude and the predicted target attitude, and then the continuous tracking capability is determined by combining the target's subsequent angular velocity and angular acceleration.

[0035] For example, if antenna T1 has a current azimuth angle of 120° and an elevation angle of 35°, with a maximum permissible azimuth velocity of 12° / s, and antenna T2 has a maximum permissible azimuth velocity of 22° / s, then after satellite A enters the near-zenith phase, although T1 still meets the geometric visibility conditions, its azimuth drive margin is insufficient, while T2 can still cover this phase. For different attitude regions, dynamic capability correction coefficients can also be established based on historical servo errors. When a certain attitude region has a long-term response lag, the continuous tracking capability of the corresponding region is reduced.

[0036] Subsequently, the predicted motion state and dynamic execution capability are matched time-by-time according to a unified time index. Target reachability conditions may include the target being above the horizon obstruction boundary, the predicted attitude being within the antenna's rotation range, and the RF execution channel being available; continuous tracking conditions can be determined based on the margin between the target angular velocity, target angular acceleration, and the corresponding dynamic capability. Moments that continuously meet the conditions are merged to form an initial valid time interval; if a short-term unexecutable state occurs within the interval, whether to split it is determined based on the allowed interruption duration.

[0037] For example, T1 meets the continuous tracking condition for satellite A from 180s to 428s, and the azimuth velocity requirement exceeds the capacity limit after 429s. Therefore, 180s to 428s is determined as the effective time interval. T2 can cover satellite A from 260s to 760s, thus forming another effective time interval.

[0038] When determining executable tracking segments, it is also necessary to verify the state transition margin between adjacent tasks. Specifically, the termination attitude of the preceding task at the same antenna can be read. The necessary transition duration can be obtained based on the shortest turning time and restabilization time between the termination attitude and the starting attitude of the current target task. This timeframe is then compared with the available interval between the two tasks. If the available interval is insufficient, the starting position of the current effective time interval is compressed backward until the transition requirements are met. If the compressed continuous execution duration is less than the target task requirement, the corresponding interval is discarded.

[0039] For example, T2 is responsible for tracking satellite B before satellite A. Satellite B ends at 240s. It takes 13s for T2 to change from the attitude of satellite B to the attitude predicted by satellite A at 260s, and 4s to re-stabilize. The 20s interval is greater than the necessary 17s transition time. Therefore, the period from 260s to 760s is retained as the executable tracking segment corresponding to satellite A and T2.

[0040] In some examples, to avoid false angular velocity abrupt changes when the azimuth angle crosses 0° or 360°, angle expansion can be performed on the continuous azimuth sequence during the predicted motion state generation stage, and the equivalent angular displacement can be determined in combination with the actual rotation direction of the antenna; for predicted attitudes close to mechanical limits, the remaining turnable angles are converted into attitude margins.

[0041] The dynamic execution capability can also be corrected in real time according to the current load status. For example, when the drive temperature rises or the servo error continuously exceeds the reference range, the allowable angular velocity and angular acceleration are reduced so that the calculated continuous tracking capability reflects the current real state of the device.

[0042] During timing matching, safety boundaries can be set for velocity margin, acceleration margin, and attitude margin respectively. Only when each margin is higher than the corresponding boundary for multiple consecutive prediction times will the effective state of the corresponding time period be maintained, thereby avoiding frequent breakage of executable tracking segments caused by fluctuations at a single sampling point.

[0043] Through the above processing, each executable tracking segment is associated with the target task, antenna execution unit, start and end time, and dynamic capability margin, providing an executable foundation for the subsequent construction of a multi-target dynamic tracking continuous network.

[0044] In some embodiments, a migration relationship is established based on the state transition conditions between executable tracking segments and the relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network. The continuous tracking path is determined based on the task state of each target task, including:

[0045] The target task, antenna execution unit, and corresponding executable tracking segment are associated to form an execution node;

[0046] The state transition conditions are determined based on the attitude transition capabilities between adjacent execution nodes, and the relay conditions are determined based on the overlapping tracking states between execution nodes corresponding to the same target task.

[0047] Establish migration relationships for execution nodes that meet the corresponding conditions to form a multi-target dynamic tracking continuous network;

[0048] Based on the task status and execution continuity of each target task, the corresponding tracking continuous path is determined from the multi-target dynamic tracking continuous network.

[0049] Specifically, after obtaining the executable tracking segments corresponding to each target task and each antenna execution unit, each set of target tasks, antenna execution units and executable time range can be associated to form an execution node, and the target identifier, antenna identifier, start and end time, start attitude, end attitude, dynamic capability margin and task completion amount can be recorded for the execution node.

[0050] For example, if satellite A is executable by antenna T1 from 180s to 428s and by antenna T2 from 260s to 760s, then nodes A-T1-1 and A-T2-1 are formed respectively; if satellite B is executable by T1 from 500s to 820s, then node B-T1-1 is formed. Execution nodes represent the actual execution status of a target task that can be continuously undertaken by a specific antenna within a corresponding time range, rather than simply indicating that the satellite is visible.

[0051] For adjacent execution nodes with the same antenna undertaking different target tasks, the shortest attitude transition time can be calculated based on the antenna attitude at the termination of the previous node and the predicted target attitude at the start of the next node. This shortest transition time is then added to the time required for drive deceleration, reverse rotation, and restabilization to form the necessary transition time. The necessary transition time is compared with the available time interval between the two execution nodes. If the available time interval is not less than the necessary transition time, and the transition process does not pass through mechanical limits or other unreachable attitude areas, the state transition condition is deemed met.

[0052] For example, when T1 completes tracking satellite A, its azimuth angle is 246° and its elevation angle is 52°. The initial attitude of the corresponding node for satellite B is 285° and 31°. Based on T1's current velocity and drive constraints, the attitude transition requires 8 seconds, and stabilization requires 3 seconds. Since there is a 72-second idle time between the two nodes, a cross-task migration relationship can be established between A-T1-1 and B-T1-1. If the necessary transition time exceeds the available interval, the two nodes will not establish a migration relationship.

[0053] For execution nodes of the same target task undertaken by different antenna execution units, the ability to form a relay is determined based on the time overlap range of the two executable tracking segments. First, the start and end times of the overlap are determined, and then the minimum relay preparation time is calculated by combining the time required for the candidate relay antenna to complete pre-pointing, target acquisition, and lock confirmation. When the overlap time covers the minimum relay preparation time, and both antennas maintain a dynamic capability margin sufficient to meet the continuous tracking conditions during the overlap phase, the relay conditions are deemed met.

[0054] For example, A-T1-1 and A-T2-1 have a 168-second overlap from 260s to 428s. T2 requires 15s to complete pre-turning and stabilization, and 8s to confirm target acquisition and lock-on. Therefore, the relay can be completed before T1 exits continuous tracking capability, establishing a relay migration relationship between the two nodes. If the overlap time is insufficient, or if the candidate relay antenna enters a high-dynamic-risk area after the overlap, no corresponding relationship is established.

[0055] Furthermore, after completing the condition checks between all execution nodes, the execution nodes are treated as network nodes. Directed migration relationships are established between nodes that meet the state transition or relay conditions, forming a multi-target dynamic tracking continuous network. The migration direction is determined according to the execution time sequence, and each migration relationship can be associated with transition margin, relay margin, and continuity state. For example, A-T1-1 can migrate to A-T2-1, or it can migrate to B-T1-1 after completion. The network simultaneously retains relay paths for the same target and switching paths for different target tasks. No connections are established for nodes that cannot migrate directly, structurally preventing subsequent path planning from producing physically unexecutable antenna scheduling results.

[0056] In some examples, when determining a continuous tracking path, path selection constraints can be determined based on the priority status of each target task, remaining execution requirements, and permissible interruption status. The duration of execution nodes and migration relationships can then be used to search for a node sequence that covers the task requirements. For example, if satellite A is a high-priority continuous tracking task requiring minimal interruption from 180s to 700s, then A-T1-1 to A-T2-1 can be selected as the continuous tracking path, with T1 handling the initial tracking and then migrating to T2 in the overlapping section. If satellite B allows for short-term interruptions, then B-T1-1 or other executable nodes can be selected from the remaining nodes to form the corresponding path without affecting the continuity of satellite A. If multiple candidate paths meet the task requirements, the path with fewer migrations, higher dynamic capability margin, and lower subsequent resource consumption conflicts can be prioritized.

[0057] During operation, the network can be locally updated based on changes in the executable time range corresponding to the execution nodes. For example, if the real-time drive state of T2 decreases, causing the effective end time of A-T2-1 to be advanced from 760s to 620s, the corresponding execution node will be shortened synchronously, and its subsequent migration relationship will be re-verified. If the original continuous tracking path can no longer cover the remaining tasks of satellite A, an alternative path that meets the relay conditions between the current node and other antenna execution nodes will be searched. Thus, the multi-target dynamic tracking continuous network not only describes the static task allocation relationship but also reflects the actual motion capability of the antenna, cross-task attitude transitions, and timing constraints between cross-antenna relays of the same target, providing a continuous and executable path basis for the determination of the subsequent main tracking execution unit and candidate relay execution units.

[0058] In some embodiments, determining the main tracing execution unit and candidate relay execution units according to the tracing continuous path includes:

[0059] Based on the task execution status corresponding to the current execution node in the tracking continuous path, determine the main tracking execution unit responsible for tracking the current target;

[0060] Identify the target location where the tracking capability of the main tracking execution unit decreases along the continuous tracking path;

[0061] Identify the successor execution node that can cover the target location and has a relay migration relationship with the current execution node;

[0062] Based on the executable continuous state and relay preparation state of the successor execution node, candidate relay execution units are determined from the corresponding antenna execution units.

[0063] Specifically, after forming the continuous tracking path corresponding to each target task, the antenna execution unit that should be responsible for target tracking at the current moment can be determined according to the time sequence of the execution nodes in the path, the task completion status, and the node validity status. For example, the continuous tracking path corresponding to satellite A includes nodes A-T1-1, A-T2-1, and A-T3-1 in sequence, where A-T1-1 corresponds to 180s to 428s, A-T2-1 corresponds to 260s to 760s, and A-T3-1 corresponds to 600s to 900s.

[0064] At the current time of 300s, A-T1-1 has entered the effective execution phase and T1 maintains target lock. The cumulative task completion is consistent with the path plan. Therefore, T1 is designated as the current main tracking execution unit, and A-T1-1 is marked as the current execution node. If the current execution node is within the planned time range, but the corresponding antenna loses lock, experiences a drive anomaly, or its dynamic capability degrades to an unexecutable state, then this node will not continue to be used as the main tracking basis. Instead, a successor node will be searched along the path.

[0065] Furthermore, once the main tracking execution unit is determined, it can continuously predict subsequent tracking capabilities based on the remaining time range of the current execution node. Specifically, it can perform rolling matching between the predicted motion state of the target and the dynamic execution capabilities updated in real time by the main tracking execution unit, calculate the attitude margin, motion margin, and continuous locking margin corresponding to each prediction moment, and identify the position where the capability degradation condition is first reached.

[0066] The capability degradation condition does not require the antenna to have lost its tracking ability; it can be triggered in advance when the dynamic margin approaches its limit. For example, if the maximum available azimuth velocity for T1 is 12° / s, and satellite A's predicted azimuth velocity increases rapidly after 410s, exceeding the corresponding capability limit at 429s, the system can determine 405s as the starting point of the tracking capability degradation and 425s as the target position where the relay needs to be completed, thus reserving sufficient pre-pointing and locking time for candidate antennas. The same method can be used to determine the future target position when mechanical limits are approaching, servo errors continue to increase, or link locking margin decreases.

[0067] Furthermore, after identifying the target location, the system queries subsequent execution nodes that have a relay migration relationship with the current execution node along the current tracking continuous path. For each subsequent execution node, it verifies whether its executable time range covers the target location and confirms that the corresponding relay migration relationship is still valid in the current device state.

[0068] For example, A-T2-1 covers the period from 260s to 760s and has already established a relay migration relationship with A-T1-1, so it can be considered a candidate successor node. Although A-T3-1 can track satellite A after 600s, it cannot cover the target position at 425s, so it cannot undertake this relay. If multiple successor execution nodes cover the target position, the available preparation time from the current time to the target position and the duration for which they can continuously undertake the task after the target position can be compared.

[0069] The executable duration of a subsequent execution node can be determined based on the remaining executable time after the target position, changes in dynamic capability margin, and the occupancy of subsequent tasks. For example, T2 can continue tracking for 335 seconds after 425 seconds, and the corresponding motion margin remains stable; another execution unit, T4, can also cover 425 seconds, but needs to take on a higher priority task at 500 seconds. Therefore, T2 has a better executable duration as its subsequent execution node. The relay preparation state can be determined based on the transition time from the current attitude of the subsequent execution unit to the target's pre-pointing attitude, the stabilization time, and the expected target acquisition time. If T2 is currently idle, it takes 12 seconds to transition from its current attitude to the predicted position of satellite A at 390 seconds, 8 seconds for stabilization and target acquisition, and there are still 35 seconds to go before the predetermined relay target position, then it has a sufficient relay preparation state.

[0070] When multiple successor execution nodes simultaneously meet the requirements for continuous execution and relay preparation, the antenna execution unit with the larger preparation margin, longer continuous execution time, and lower subsequent task conflict can be prioritized as the candidate relay execution unit. If the first priority successor node experiences a decrease in driving capability during preparation, other successor nodes in the tracking continuous path are reread and an alternative selection is performed without changing the effective tracking status of the current main tracking execution unit. For example, if T2 experiences a servo anomaly during the pre-turning phase, it can continue to determine whether there are execution nodes in T3 or other path branches that can promptly cover the subsequent target position. The candidate relay execution unit is only updated after the alternative node meets the relay conditions.

[0071] In actual control, the primary tracking execution unit and the candidate relay execution unit can maintain their current role states separately. The primary tracking role maintains closed-loop tracking of satellite A, while the candidate relay role only enters the pre-turning, acquisition preparation, or overlapping tracking states, without prematurely releasing the primary tracking resources due to the candidate relationship. Once the candidate relay execution unit subsequently completes stable locking and meets the state transition conditions, it then enters the primary tracking state.

[0072] Through the above implementation method, the position where the current antenna’s future capability decline can be identified in advance based on the continuous tracking path, and candidate relay execution units can be selected from the successor execution nodes that have been verified to have a physical relay relationship. This allows the relay decision to be driven by both the actual continuous tracking capability and the preparation margin, reducing the tracking interruption caused by temporarily searching for a replacement antenna after the near loss of lock.

[0073] In some embodiments, when the main tracking execution unit performs target tracking, the tracking residual is decomposed into a target common deviation state corresponding to the target task and a local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state, including:

[0074] The actual tracking state of the target task formed by the main tracking execution unit is obtained and matched with the corresponding predicted motion state to generate tracking residuals;

[0075] Based on the temporal changes of the tracking residuals and the consistency status across execution units, the target shared deviation component and the execution unit specific deviation component in the tracking residuals are determined.

[0076] State estimation is performed on the two types of deviation components respectively to generate the target common deviation state of the target task and the local deviation state of the main tracking execution unit.

[0077] Based on the subsequent actual tracking status, update the target common deviation status of the corresponding target task and the local deviation status of the main tracking execution unit respectively.

[0078] Specifically, after the main tracking execution unit enters the stable tracking phase, it can acquire the actual tracking status corresponding to the current target task according to a unified sampling period and time-align it with the predicted motion status at the same time. The actual tracking status can be formed by antenna servo feedback, target angle measurement results, and link locking feedback, and is used to characterize the target's actual azimuth position, elevation position, and corresponding trend of change. The predicted motion status is generated by combining the orbit extrapolation results with the ground station reference status.

[0079] In some examples, taking satellite A being tracked by antenna T1 as an example, at 320s, the predicted azimuth angle is 146.20° and the elevation angle is 48.35°. After tracking feedback, the actual target positions are obtained as 146.32° and 48.29°, resulting in instantaneous tracking residuals of 0.12° in the azimuth direction and -0.06° in the elevation direction. The same processing is performed on consecutive sampling times to form a residual time series associated with the target task and the current antenna execution unit.

[0080] To avoid mixing orbit prediction bias and antenna control bias, the residuals can be decomposed based on their variation characteristics over continuous time periods and the consistency of residuals generated by different antennas for the same target. First, the residual sequence generated during continuous tracking of satellite A in T1 is smoothed and its trend extracted to identify stable components that continuously change with satellite motion and local fluctuation components related to antenna attitude changes. When satellite A was previously tracked by T2, or is currently in the overlapping tracking phase of T1 and T2, the residual sequence generated by T2 for the same time interval can be read, and the direction, magnitude, and duration of residual changes between the two execution units can be compared.

[0081] If both T1 and T2 exhibit azimuth deviations with consistent direction and similar amplitude in multiple consecutive sampling periods, the corresponding deviation is given a higher weight as a target shared deviation component. If a certain deviation only appears in T1 and repeats as T1 enters a specific azimuth range or undergoes a change in rotation direction, the corresponding part is determined as a deviation component specific to the execution unit.

[0082] For example, both T1 and T2 exhibited a sustained positive azimuth residual of approximately 0.08° to 0.11° during overlapping tracking of satellite A, while the elevation residuals showed a slow decreasing trend. The portion shared by both antennas can be considered a shared deviation of the predicted orbit position relative to the actual target position. Meanwhile, T1 exhibited an additional periodic negative residual of approximately 0.04° after the azimuth angle exceeded 150°, while T2 did not show a corresponding change. Furthermore, historical operational data for T1 indicates a slight hysteresis in this attitude region; this portion can be considered a deviation specific to the execution unit corresponding to T1. For phases lacking synchronous observations from other antennas, the residual components can be recursively determined by combining historical cross-antenna tracking results of the same target with the current historical antenna calibration status, rather than directly assigning all residuals to any single state.

[0083] Furthermore, after obtaining the two types of deviation components, target deviation estimation state and antenna local deviation estimation state can be established separately. The target shared deviation component is recursively fused according to temporal continuity and the consistency of multiple execution units to generate the target common deviation state corresponding to the current target mission of satellite A, and associated with the estimated value, change trend and confidence level. The execution unit-specific deviation component is combined with the current attitude range, motion direction and historical local deviation records of T1 to estimate the state and generate the local deviation state corresponding to T1. The target common deviation state is associated with the target mission of satellite A and can be provided to other execution units in subsequent cross-antenna relay; the local deviation state of T1 is only associated with T1 and is used to correct its own control input to avoid the inherent error of the equipment being transmitted to the candidate relay execution unit.

[0084] As the main tracking process continues, each time a new actual tracking state is obtained, the current residual is recalculated and matched with the existing deviation state. When the direction of change of the newly added residual and the target common deviation state is consistently consistent, and is verified in subsequent cross-execution unit observations, the confidence level of the corresponding target common deviation state is increased and the deviation estimate is updated. When the newly added residual only appears continuously in T1 and has a stable correlation with the execution state of T1 itself, the local deviation state of T1 is updated. If a certain deviation component no longer appears in multiple consecutive sampling periods, the effective weight of the corresponding state is gradually reduced to avoid the long-term influence of historical deviations on the current tracking.

[0085] Through the above implementation method, the actual tracking residual can be continuously decomposed into a target common deviation state that can be shared across execution units and a local deviation state that is only used for correction of a single device, providing mutually independent state basis for the pre-pointing and overlapping tracking verification of subsequent candidate relay execution units.

[0086] In some embodiments, the target shared bias component and execution unit specific bias component in the tracking residual are determined based on the temporal changes of the tracking residual and the consistency status across execution units, including:

[0087] Determine the state of residual change based on the tracking residual formed during the continuous tracking phase of the same target task;

[0088] Obtain the tracking residuals formed by different antenna execution units for the same target task, and determine the consistency of changes between the corresponding residuals;

[0089] The residuals that are consistent across execution units and change continuously with the target motion are identified as target-shared bias components, while the residuals that are associated with the execution state of the corresponding antenna execution unit and lack consistency across execution units are identified as execution unit-specific bias components.

[0090] Specifically, a tracking residual sequence arranged according to a unified time base can be established for the same target task, and the changing state of the residual during the target motion process can be identified using a continuous analysis window. The tracking residual can be obtained by subtracting the actual tracking state from the predicted motion state, and residual components can be formed according to the azimuth and pitch directions respectively.

[0091] For example, taking satellite A as the target mission, antenna T1 continuously tracks satellite A from 300s to 420s, obtaining the actual tracking status every 1s. The actual azimuth and elevation angles at each moment are compared with the corresponding predicted values, forming 120 sets of tracking residuals. For a continuous analysis window of 10s, the mean, slope, and fluctuation of the residuals within the window can be calculated, and the direction and magnitude of change between adjacent windows can be matched. If a residual maintains the same direction of change in multiple continuous windows and the fluctuation is lower than the preset stability boundary, it is determined to be a continuously changing state; if the residual changes abruptly only at a few sampling points or the direction of change frequently reverses, the effectiveness of the corresponding residual as a stable deviation is reduced.

[0092] For example, the azimuth residual generated by T1 from 330s to 380s gradually increases from 0.07° to 0.12°, maintaining a positive change within the continuous window, while the pitch residual slowly changes from -0.03° to -0.06°. These residuals can be marked as a stable, continuously changing state. Simultaneously, T1 exhibits an instantaneous azimuth residual of 0.25° around 365s, but recovers to its original range in the next sampling period. This abnormal change can be suppressed as a short-term disturbance and does not directly participate in the determination of the target shared deviation component or the execution unit-specific deviation component. In practical applications, effective weights can be assigned to residual samples based on the link locking status. When the target is in a weakly locked or briefly unlocked state, the participation level of that sampling point is reduced accordingly.

[0093] In some examples, when there are continuous historical observations or currently overlapping observations from two or more antenna execution units for the same target mission, the tracking residuals corresponding to different execution units can be extracted according to a unified target time index and time aligned. Taking satellite A as an example, T1 and T2 have a 60-second overlapping tracking interval from 350s to 410s. After alignment, the azimuth and elevation residuals of the two execution units at the same sampling time are compared to determine whether the direction of residual change is consistent, whether the difference in the magnitude of change is within the allowable range, and whether the consistent change continues to meet the corresponding time requirements.

[0094] If the azimuth residual of T1 increases from 0.09° to 0.13°, and the azimuth residual of T2 increases from 0.08° to 0.12° during the same period, and both sets of residuals maintain the same direction of change for 30 consecutive seconds, then they are determined to have a high degree of consistency in change. If T1 exhibits additional periodic negative fluctuations, while T2 does not show corresponding fluctuations, then this part is marked as a local change lacking consistency across execution units.

[0095] Furthermore, the correlation between residuals and antenna execution states can be used to distinguish between the two types of deviations. For residuals that appear simultaneously in T1 and T2, have similar directions of change, and change continuously with the motion of satellite A, their source can be considered independent of specific execution units. Therefore, the residual portion jointly maintained by multiple execution units is determined as the target shared deviation component. For example, during the period from 350s to 410s, both T1 and T2 have positive azimuth offsets of approximately 0.08° to 0.12°. The common variation portion of the two sets of residuals can be taken as the target shared deviation component corresponding to satellite A, used to characterize the common offset of the predicted trajectory relative to the actual target motion state.

[0096] Residuals that appear only in a single antenna actuator and are repeatedly correlated with the attitude range, motion direction, or servo response state of that actuator are identified as actuator-specific bias components. For example, if after the azimuth angle of T1 enters the range of 145° to 160°, a local residual of approximately -0.04° appears in multiple tracking tasks, while T2 does not show a corresponding change in the same time period, and the amplitude of this local residual changes with the rotation direction of T1, then this part is identified as the actuator-specific bias component corresponding to T1. Residuals that lack consistency across actuators and do not exhibit stable device correlation can be temporarily reserved as pending determination and assigned after obtaining subsequent continuous observations.

[0097] In the actual judgment process, the credibility of the consistent state across execution units and the degree of correlation of execution states can be formed separately, and updated recursively according to the continuous observation results. When a newly added antenna execution unit forms a residual consistent with the existing shared changes for the same target, the credibility of the target shared deviation component is increased; when a certain local residual appears repeatedly in multiple different target tasks of the same antenna, the credibility of the deviation component specific to the corresponding execution unit is increased.

[0098] This embodiment utilizes the temporal continuity of residuals, common changes across execution units, and the correlation of device states simultaneously to avoid classifying errors based solely on single residual amplitudes, thereby providing a stable data foundation for the independent estimation of subsequent target common deviation states and local deviation states.

[0099] In some embodiments, the candidate relay execution unit performs target pre-pointing by combining the target common deviation state and its own local deviation state, and updates the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase, including:

[0100] The predicted motion state of the corresponding target task is corrected based on the common deviation state of the target, and a pre-direction state is generated by combining the local deviation state of the candidate relay execution unit.

[0101] According to the pre-pointing state, the candidate relay execution unit is controlled to enter the target acquisition range and obtain the corresponding actual tracking state;

[0102] During the overlapping tracking phase with the main tracking execution unit, the consistency of the actual tracking states of the two execution units is verified.

[0103] The target common deviation state is corrected based on the verification results, and the locking state of the candidate relay execution unit is updated.

[0104] Specifically, when the tracking of a continuous path indicates that the main tracking execution unit is about to enter a region of decreased dynamic capability, and a candidate relay execution unit has been identified, the predicted motion state corresponding to the current target task, the target common deviation state, and the local deviation state maintained by the candidate relay execution unit itself can be read to generate a pre-pointing state for the candidate relay. Taking the relay of satellite A from antenna T1 to antenna T2 as an example, at 390s, the predicted azimuth angle of satellite A is 168.40° and the elevation angle is 62.30°. The target common deviation state indicates that the current predicted trajectory has a positive azimuth offset of 0.10° and a negative elevation offset of 0.05°. The historical local deviation state of T2 indicates that there is a 0.03° azimuth compensation in the current attitude region.

[0105] In some examples, the predicted position of satellite A can be corrected first using the target common deviation state, and then the antenna execution error can be compensated using the local deviation state of T2 itself, to obtain the pre-pointing position corresponding to T2 and the subsequent continuous pre-pointing trajectory. The target common deviation is used to correct the actual motion position of the target, while the local deviation only affects the control process of T2 itself, avoiding the transmission of the T1 device error to T2.

[0106] The candidate relay execution unit completes attitude transfer in advance according to the pre-pointing state and enters the target acquisition phase after reaching the vicinity of the target's predicted position. The acquisition range can be determined based on the uncertainty associated with the target's common deviation state. When the confidence level of the target's common deviation is high, the search area is narrowed; when the confidence level decreases, the acquisition boundary is appropriately expanded. For example, based on the current state, the azimuth acquisition range of satellite A at 395s is determined to be 169.05° to 169.25°, and the elevation acquisition range is determined to be 63.10° to 63.28°. After T2 reaches the center pre-pointing position, scanning is only performed within this local range, and the target direction is determined by combining the changes in the received signal. When the signal strength exceeds the acquisition threshold and remains stable for multiple consecutive sampling periods, the actual tracking state corresponding to T2 is acquired, and the pre-pointing control is switched to closed-loop tracking control.

[0107] During the overlapping tracking phase where both T1 and T2 can stably observe satellite A, the actual tracking states of the two execution units can be aligned according to a unified time reference and then compared with the corrected predicted motion states. Specifically, the direction and duration of the actual azimuth changes, pitch changes, and corresponding tracking residual changes can be compared, and the consistency of the observation results can be determined by combining the target lock feedback from both paths. For example, if from 400s to 420s, both T1 and T2 detect a continuous positive azimuth offset of approximately 0.03° relative to the corrected predicted trajectory for satellite A, and the offset trends of the two paths are consistent, then this common change is determined to still belong to the target common trajectory correction part; if only T2 shows a short-term additional deviation of 0.04°, while T1 does not show a corresponding change, then it is processed in conjunction with T2's own local deviation state and is not directly incorporated into the target common deviation state.

[0108] Consistency verification can also be continuously judged in conjunction with the reliability of the state. If the deviation between the actual tracking state of T2 and T1 continues to decrease, and the common changes of the two observations remain within the allowable consistency range, the reliability of the verification corresponding to T2 is gradually increased; if the residual of T2 continues to deviate from T1 and exceeds the allowable range, the candidate state is maintained, and the pre-pointing or local compensation of T2 is readjusted to avoid premature completion of the relay. For single-point anomalies caused by short-term signal fading, suppression can be carried out based on the continuous sampling results before and after, and the reliability of the verification is reduced only after the anomaly persists for a set time.

[0109] Based on the verification results generated during the overlapping tracking phase, the stable residuals jointly observed by T1 and T2 can be used to correct the target common deviation state corresponding to satellite A. For example, if both execution units continuously exhibit a positive azimuth offset of 0.03°, this common offset is fused into the original target common deviation state according to the current confidence level, making the subsequent target predicted trajectory closer to the actual motion trajectory. Simultaneously, the locking state of T2 is updated based on the continuous acquisition duration of T2, the actual tracking residual changes, and the degree of consistency with the observation results of T1.

[0110] In some examples, the lock state can be gradually transitioned from the capture state to the tracking confirmation state and the stable lock state. The stable lock state is determined only when the T2 tracking time meets the requirements, the tracking residual remains within the allowable range, and the consistency across execution units meets the requirements.

[0111] Through the above implementation method, the candidate relay execution unit can complete target pre-capture, status verification and lock confirmation before the main tracking execution unit is released, providing reliable conditions for the subsequent main tracking status transition.

[0112] In some embodiments, during the overlapping tracking phase with the main tracking execution unit, a consistency check is performed on the actual tracking states of the two execution units, including:

[0113] The actual tracking states of the main tracking execution unit and the candidate relay execution unit are matched with the corrected predicted motion states to obtain the corresponding tracking deviations;

[0114] The degree of consistency across execution units is determined based on the correlation status of changes in the corresponding tracking deviations between the two execution units.

[0115] The verification result is determined based on the consistency across execution units and the continuous locking status of candidate successor execution units, and the common deviations that meet the consistency conditions are used to correct the target common deviation status.

[0116] Specifically, after both the main tracking execution unit and the candidate relay execution unit have entered the effective tracking range of the same target task, a unified time index can be established to match the actual tracking states formed by the two execution units at the same sampling time with the current corrected predicted motion states. The corrected predicted motion states can be obtained by superimposing the original predicted motion states with the current target common deviation states, and are used to represent the target reference states after some common trajectory errors have been eliminated.

[0117] For example, taking the relay tracking of satellite A from antenna T1 to antenna T2 as an example, a 30-second overlapping tracking interval is set from 400s to 430s, with a sampling period of 1s. At 405s, the corrected predicted azimuth angle is 172.36° and the elevation angle is 66.18°. T1 obtains the actual azimuth angle of 172.39° and the elevation angle of 66.16°, and T2 obtains the actual azimuth angle of 172.40° and the elevation angle of 66.15°. Then, the azimuth tracking deviation and elevation tracking deviation corresponding to T1 and T2 can be obtained respectively, and two sets of tracking deviation sequences can be formed in chronological order.

[0118] To avoid signal jitter at a single sampling moment affecting consistency judgment, the changing states of two sets of tracking deviations can be extracted within a continuous analysis window. Specifically, the mean deviation, direction of change, rate of change, and fluctuation range within the corresponding window can be calculated, and it can be determined whether the tracking deviations of the two execution units have a synchronous change relationship. For example, during the period from 405s to 415s, the azimuth tracking deviation of T1 increases from 0.03° to 0.06°, and that of T2 increases from 0.04° to 0.07°. Both sets of deviations maintain a positive growth, and the difference in change between adjacent moments remains within 0.02°, thus determining that the two have a strong correlation in change. If T2 experiences a momentary deviation of 0.15° at a certain moment, and subsequent sampling quickly recovers, this deviation is treated as a short-term disturbance and its participation weight is reduced, without directly reducing the overall cross-execution unit consistency.

[0119] In some examples, the consistency across execution units can be determined by comprehensively considering the directional consistency, amplitude similarity, and duration of consistency between the two sets of tracking deviations. The consistency state is calculated separately for the azimuth and pitch directions, and then combined with the current actual lock-on effectiveness to form the overall consistency level. For example, if T1 and T2 show consistent azimuth deviation changes over 15 seconds with an average amplitude difference of 0.01° and an average pitch deviation amplitude difference of 0.015°, and both execution units maintain effective target lock, then the current cross-execution unit consistency level can be determined as a high consistency state. If the two sets of deviations are in opposite directions, or the amplitude difference continues to widen, the consistency level is reduced, and it is further determined whether the candidate relay execution unit has local pointing anomalies or has not yet stably entered the target center region.

[0120] The continuous locking status of a candidate relay execution unit can be determined based on the target acquisition duration, the stability of the tracking deviation, and changes in the locking feedback. For example, if T2 maintains target lock for 20 seconds without re-searching and the tracking deviation gradually converges, it forms a valid continuous locking status. If the locking feedback is interrupted multiple times, or the actual tracking position frequently deviates from the allowable error range, it remains in a pending confirmation state. Using the consistency across execution units and the continuous locking status together to determine the verification result can avoid mistakenly concluding that a candidate relay execution unit has stable relay capability simply because two antennas have similar deviations in a short period of time.

[0121] When the consistency across execution units reaches a preset consistency condition and T2 maintains a continuous and effective lock state, a common deviation can be extracted from the two sets of tracking deviations. Common deviations can be determined based on the portion that is in the same direction, has similar amplitude, and persists. For example, if, during the period from 410s to 425s, both T1 and T2 exhibit a persistent positive azimuth deviation of approximately 0.04° to 0.06° and an elevation deviation of approximately -0.02°, then the corresponding common portion will be used as new common correction information, and a recursive update will be performed based on the reliability of the original target common deviation state. Additional deviations existing only in T1 or T2 will not participate in this target common deviation state correction, preventing the local error of a single antenna from propagating to other execution units.

[0122] If a decrease in consistency occurs during the verification process, the current tracking state of the main tracking execution unit can be maintained, and the overlap observation time can be extended. Local compensation or target center correction can then be re-executed for the candidate relay execution units. For example, if T2 consistently exhibits a fixed additional deviation of approximately 0.05° relative to T1, but their common trend remains consistent, this fixed additional deviation can be preferentially attributed to the local deviation state of T2, and the tracking deviation of T2 can be recalculated. Only when the cross-execution unit consistency and continuous locking state after recalibration simultaneously meet the conditions will a verification result be generated.

[0123] Through the above implementation method, the dual execution units in the overlapping tracking stage can jointly observe and distinguish the real common changes of the target from the local errors of a single device, and continuously correct the common deviation state of the target, providing a reliable basis for the state consistency of the subsequent main tracking state transition.

[0124] In some embodiments, when a candidate relay execution unit meets the stable tracking condition, a main tracking state transition is performed, and the multi-target dynamic tracking continuous network and subsequent tracking continuous paths are updated according to the antenna execution state and the actual tracking state after the transition, including:

[0125] Determine whether the stable tracking condition is met based on the locking status and continuous tracking status of the candidate relay execution unit;

[0126] When the stable tracking conditions are met, the candidate relay execution unit is converted into a new main tracking execution unit, and the original main tracking execution unit is released;

[0127] The corresponding execution node and migration relationship are corrected based on the antenna execution status and actual tracking status after migration.

[0128] The subsequent tracking path for the affected target task is redefined based on the updated multi-target dynamic tracking continuous network.

[0129] Specifically, after the candidate relay execution unit completes pre-pointing, target acquisition, and overlapping tracking verification, it can be determined whether the conditions for transitioning to the main tracking state are met based on its current lock state and continuous tracking state. The lock state can be determined based on the candidate relay execution unit's continuous acquisition results of the target signal, the tracking deviation convergence state, and the overlapping tracking consistency results; the continuous tracking state can be determined based on the candidate relay execution unit's attitude following capability, dynamic capability margin, and target link maintenance state within a continuous time range.

[0130] For example, taking the relay tracking of satellite A from antenna T1 to antenna T2, T2 completes target acquisition at 410s and maintains overlapping tracking with T1 from 410s to 430s. If T2 maintains effective lock for 20 consecutive seconds, with azimuth tracking deviation stable within 0.03° and elevation tracking deviation stable within 0.02°, and the motion margin in the subsequent prediction time still meets the continuous tracking requirements, then T2 is determined to meet the stable tracking conditions. If a re-search occurs during T2, the tracking deviation continues to increase, or the subsequent dynamic capability is insufficient, then the candidate state is maintained, and the main tracking migration is not performed.

[0131] When T2 meets the stable tracking conditions, the target common deviation state and T2 local deviation state corresponding to the current migration time can be frozen first. Then, the role state of T2 can be changed from candidate relay state to main tracking state, so that T2 can take over the subsequent target tracking control, deviation update and link maintenance. At the same time, T1 can be changed from main tracking state to release state. After confirming that T2 continuously outputs valid tracking results, the main tracking control of T1 on satellite A can be stopped.

[0132] In some examples, to avoid short-term gaps during state transitions, a limited confirmation hold time can be set. For example, after T2 transitions to the primary tracking state, it continues to track for 5 seconds using T1. If T2 remains stable within this time, T1 is released; if T2 encounters an anomaly, the release action is revoked and T1 resumes its primary tracking task. After the transition is complete, the current primary tracking execution unit of satellite A is updated to T2, and the transition time, execution nodes before and after the transition, and the corresponding actual tracking states are recorded.

[0133] Furthermore, after the master tracking state transition is complete, the relevant execution nodes in the multi-target dynamic tracking continuous network can be corrected based on the latest antenna execution states of T1 and T2. For the original execution node A-T1-1, the actual end time can be updated to the release time of T1, and the task completion status can be updated based on the completed tracking duration; for A-T2-1, the actual takeover time can be written into the node state, and the remaining executable range can be recalculated based on the current attitude, motion margin, and subsequent locking state of T2.

[0134] For example, if the original A-T2-1 prediction could be executed up to 760s, but after migration, an increase in the T2 drive temperature was detected, reducing the allowable azimuth velocity, then its effective end time can be corrected to 710s. If T1 returns to an idle state after release, the executable tracking segments corresponding to other target tasks are reassessed based on its current position and the latest dynamic execution capabilities, and the corresponding execution nodes are adjusted synchronously.

[0135] While correcting the execution nodes, it is also necessary to re-verify the migration relationships associated with the affected nodes. For subsequent relay relationships with the same target as A-T2-1 as the preceding node, the relay conditions can be re-determined based on the overlap between the corrected end time and other candidate execution nodes; for other target tasks that T1 may undertake after release, the state transition conditions can be re-determined based on the shortest transition time from its current release posture to the starting posture of the subsequent target.

[0136] For example, if satellite B was originally planned to be handled by T3, but T1 releases it early at 435 seconds, it can complete the initial attitude conversion of satellite B before 500 seconds. In this case, a new migration relationship can be added between the satellite B execution node corresponding to T1 and the current network. Conversely, if an existing migration relationship loses sufficient conversion margin due to a delay in the actual tracking end time, the corresponding migration relationship should be deleted or temporarily disabled.

[0137] Based on the updated multi-target dynamic tracking continuous network, the search for subsequent tracking continuous paths for affected target missions can begin again from the current moment. For satellite A, priority can be given to searching for execution nodes that can continue to cover the remaining tasks, starting from the new primary tracking execution node A-T2-1. If the executable time after T2 correction is insufficient to complete the task, then a successor node that meets the relay conditions with A-T2-1 is selected to continue forming a path. For satellite B or satellite C missions that have gained additional resources due to the release of T1, the execution continuity and resource conflict status of the original path and the new available path are re-compared, and only the local paths affected by the migration are adjusted to avoid unnecessary replanning of all missions.

[0138] Through the above implementation methods, the main tracking state migration results can be fed back to the execution node, migration relationship and subsequent path in a timely manner, realizing closed-loop linkage between the actual antenna execution state and the multi-target task scheduling state, improving the stability of continuous tracking after the relay and the adaptability of subsequent resource allocation.

[0139] The following are system embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the system embodiments of this application, please refer to the method embodiments of this application.

[0140] Figure 2 This is a schematic diagram of the structure of a low-orbit satellite antenna cooperative control and tracking system based on multi-target tasks provided in an embodiment of this application. Figure 2As shown, the system includes:

[0141] The acquisition module 201 is used to acquire the target missions corresponding to multiple low-orbit satellites and the execution status of multiple antenna execution units, and to determine the executable tracking segments based on the predicted motion status of the target missions and the dynamic execution capabilities of the antenna execution units.

[0142] Module 202 is used to establish migration relationships based on the state transition conditions between executable tracking segments and the relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network, and determining the tracking continuous path based on the task status of each target task.

[0143] The decomposition module 203 is used to determine the main tracking execution unit and candidate relay execution units according to the continuous tracking path. When the main tracking execution unit performs target tracking, it decomposes the tracking residual into the target common deviation state corresponding to the target task and the local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state.

[0144] The update module 204 is used to enable the candidate relay execution unit to perform target pre-pointing by combining the target common deviation state and its own local deviation state when the subsequent execution state meets the relay conditions, and to update the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase.

[0145] The execution module 205 is used to perform the main tracking state transition when the candidate relay execution unit meets the stable tracking conditions, and to update the multi-target dynamic tracking continuous network and the subsequent tracking continuous path according to the antenna execution state after the transition and the actual tracking state.

[0146] In some embodiments, Figure 2 The acquisition module 201 generates the predicted motion state of the target mission within the predicted time range based on the orbital state of the low-orbit satellite corresponding to each target mission and the reference state of the ground station; determines the corresponding dynamic execution capability based on the current attitude and motion constraints of each antenna execution unit, and predicts the continuous tracking capability of the antenna execution unit for the target mission; performs time-series matching between the predicted motion state and the dynamic execution capability to identify the effective time interval that satisfies the target reachability condition and the continuous tracking condition; and determines the executable tracking segment between the corresponding target mission and the antenna execution unit based on the effective time interval and the state transition margin between adjacent missions.

[0147] In some embodiments, Figure 2The establishment module 202 associates the target task, antenna execution unit and corresponding executable tracking segment to form execution nodes; determines the state transition conditions based on the attitude conversion capability between adjacent execution nodes, and determines the relay conditions based on the overlapping tracking states between execution nodes corresponding to the same target task; establishes migration relationships for execution nodes that meet the corresponding conditions to form a multi-target dynamic tracking continuous network; and determines the corresponding tracking continuous path from the multi-target dynamic tracking continuous network based on the task status and execution continuity of each target task.

[0148] In some embodiments, Figure 2 The decomposition module 203 determines the main tracking execution unit responsible for tracking the current target based on the task execution status corresponding to the current execution node in the tracking continuous path; identifies the target location where the subsequent tracking capability of the main tracking execution unit decreases along the tracking continuous path; determines the successor execution node that can cover the target location and has a relay migration relationship with the current execution node; and determines the candidate relay execution unit from the corresponding antenna execution units based on the executable continuous status and relay preparation status of the successor execution node.

[0149] In some embodiments, Figure 2 The decomposition module 203 obtains the actual tracking state formed by the main tracking execution unit for the target task and matches it with the corresponding predicted motion state to generate tracking residuals. Based on the temporal changes of the tracking residuals and the consistent state across execution units, it determines the target shared deviation component and the execution unit specific deviation component in the tracking residuals. It performs state estimation on the two types of deviation components respectively to generate the target common deviation state of the corresponding target task and the local deviation state of the main tracking execution unit. Based on the subsequent actual tracking state, it updates the target common deviation state of the corresponding target task and the local deviation state of the main tracking execution unit respectively.

[0150] In some embodiments, Figure 2 The decomposition module 203 determines the residual change state based on the tracking residual formed during the continuous tracking phase of the same target task; it acquires the tracking residual formed by different antenna execution units for the same target task and determines the consistency state of change between the corresponding residuals; it identifies the residuals that have cross-execution unit consistency and change continuously with the target movement as target shared deviation components, and identifies the residuals that are associated with the execution state of the corresponding antenna execution unit and lack cross-execution unit consistency as execution unit specific deviation components.

[0151] In some embodiments, Figure 2The update module 204 corrects the predicted motion state of the corresponding target task according to the target common deviation state, and generates a pre-pointing state by combining the local deviation state of the candidate relay execution unit; controls the candidate relay execution unit to enter the target acquisition range according to the pre-pointing state, and obtains the corresponding actual tracking state; in the overlapping tracking stage with the main tracking execution unit, performs consistency verification on the actual tracking states of the two execution units; corrects the target common deviation state according to the verification result, and updates the locking state of the candidate relay execution unit.

[0152] In some embodiments, Figure 2 The update module 204 matches the actual tracking states of the main tracking execution unit and the candidate relay execution unit with the corrected predicted motion states to obtain the corresponding tracking deviations; determines the cross-execution unit consistency based on the change correlation state between the corresponding tracking deviations of the two execution units; determines the verification result based on the cross-execution unit consistency and the continuous locking state of the candidate relay execution unit, and uses the common deviations that meet the consistency conditions to correct the target common deviation state.

[0153] In some embodiments, Figure 2 The execution module 205 determines whether the stable tracking conditions are met based on the locking state and continuous tracking state of the candidate relay execution unit. When the stable tracking conditions are met, the candidate relay execution unit is converted into a new main tracking execution unit, and the original main tracking execution unit is released. The corresponding execution node and migration relationship are corrected based on the antenna execution state after migration and the actual tracking state. The subsequent tracking continuous path of the affected target task is re-determined based on the updated multi-target dynamic tracking continuous network.

[0154] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments.

[0155] Figure 3 This is a schematic diagram of the electronic device 3 provided in an embodiment of this application. Figure 3 As shown, the electronic device 3 of this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, it implements the steps in the various method embodiments described above. Alternatively, when the processor 301 executes the computer program 303, it implements the functions of each module / unit in the various system embodiments described above.

[0156] Electronic device 3 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 3 may include, but is not limited to, processor 301 and memory 302. Those skilled in the art will understand that... Figure 3This is merely an example of electronic device 3 and does not constitute a limitation on electronic device 3. It may include more or fewer components than shown, or different components.

[0157] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0158] The memory 302 can be an internal storage unit of the electronic device 3, such as a hard disk or memory of the electronic device 3. The memory 302 can also be an external storage device of the electronic device 3, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 3. The memory 302 can also include both internal and external storage units of the electronic device 3. The memory 302 is used to store computer programs and other programs and data required by the electronic device.

[0159] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0160] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a readable storage medium (e.g., a computer-readable storage medium). Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which may be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0161] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A low-Earth orbit satellite antenna cooperative control and tracking method based on multi-target tasks, characterized in that, include: The system acquires the target missions corresponding to multiple low-Earth orbit satellites and the execution status of multiple antenna execution units, and determines the executable tracking segments based on the predicted motion state of the target missions and the dynamic execution capabilities of the antenna execution units. The migration relationship is established based on the state transition conditions between executable tracking segments and the relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network, and the tracking continuous path is determined according to the task state of each target task. The main tracking execution unit and candidate relay execution units are determined according to the continuous tracking path. When the main tracking execution unit performs target tracking, the tracking residual is decomposed into the target common deviation state corresponding to the target task and the local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state. When the subsequent execution state meets the relay condition, the candidate relay execution unit combines the target common deviation state and its own local deviation state to perform target pre-pointing, and updates the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase. When the candidate relay execution unit meets the stable tracking conditions, the main tracking state transition is performed, and the multi-target dynamic tracking continuous network and subsequent tracking continuous path are updated according to the antenna execution state after the transition and the actual tracking state.

2. The method according to claim 1, characterized in that, The process of acquiring the target missions corresponding to multiple low-Earth orbit satellites and the execution status of multiple antenna execution units, and determining executable tracking segments based on the predicted motion state of the target missions and the dynamic execution capabilities of the antenna execution units, includes: Based on the orbital status of the low-Earth orbit satellites corresponding to each target mission and the reference status of the ground station, the predicted motion status of the target mission within the predicted time range is generated. The corresponding dynamic execution capability is determined based on the current attitude and motion constraints of each antenna execution unit, and the continuous tracking capability of the antenna execution unit for the target task is predicted. The predicted motion state is matched with the dynamic execution capability in a time sequence to identify the effective time interval that meets the target reachability condition and the continuous tracking condition. The executable tracking segment between the corresponding target task and the antenna execution unit is determined based on the effective time interval and the state transition margin between adjacent tasks.

3. The method according to claim 1, characterized in that, The process of establishing migration relationships based on state transition conditions between executable tracking segments and relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network, and determining the tracking continuous path based on the task state of each target task includes: The target task, antenna execution unit, and corresponding executable tracking segment are associated to form an execution node; The state transition conditions are determined based on the attitude transition capabilities between adjacent execution nodes, and the relay conditions are determined based on the overlapping tracking states between execution nodes corresponding to the same target task. Establish migration relationships for execution nodes that meet the corresponding conditions to form a multi-target dynamic tracking continuous network; Based on the task status and execution continuity of each target task, the corresponding tracking continuous path is determined from the multi-target dynamic tracking continuous network.

4. The method according to claim 1, characterized in that, The step of determining the main tracking execution unit and candidate relay execution units according to the continuous tracking path includes: Based on the task execution status corresponding to the current execution node in the tracking continuous path, determine the main tracking execution unit responsible for tracking the current target; Identify the target location where the tracking capability of the main tracking execution unit decreases along the continuous tracking path; Identify the successor execution node that can cover the target location and has a relay migration relationship with the current execution node; Based on the executable continuous state and relay preparation state of the successor execution node, candidate relay execution units are determined from the corresponding antenna execution units.

5. The method according to claim 4, characterized in that, When the main tracking execution unit performs target tracking, based on the residual between the predicted motion state and the actual tracking state, the tracking residual is decomposed into the target common deviation state corresponding to the target task and the local deviation state of the main tracking execution unit, including: The actual tracking state of the target task formed by the main tracking execution unit is obtained and matched with the corresponding predicted motion state to generate tracking residuals; Based on the temporal changes of the tracking residuals and the consistency status across execution units, the target shared deviation component and the execution unit specific deviation component in the tracking residuals are determined. State estimation is performed on the two types of deviation components respectively to generate the target common deviation state of the target task and the local deviation state of the main tracking execution unit. Based on the subsequent actual tracking status, update the target common deviation status of the corresponding target task and the local deviation status of the main tracking execution unit respectively.

6. The method according to claim 5, characterized in that, The step of determining the target-shared deviation component and execution-unit-specific deviation component in the tracking residual based on the temporal changes and cross-execution-unit consistency status includes: Determine the state of residual change based on the tracking residual formed during the continuous tracking phase of the same target task; Obtain the tracking residuals formed by different antenna execution units for the same target task, and determine the consistency of changes between the corresponding residuals; The residuals that are consistent across execution units and change continuously with the target motion are identified as target-shared bias components, while the residuals that are associated with the execution state of the corresponding antenna execution unit and lack consistency across execution units are identified as execution unit-specific bias components.

7. The method according to claim 1, characterized in that, The step of enabling candidate relay execution units to perform target pre-pointing by combining the target common deviation state and their own local deviation state, and updating the target common deviation state and the locking state of candidate relay execution units during the overlapping tracking phase, includes: The predicted motion state of the corresponding target task is corrected based on the common deviation state of the target, and a pre-direction state is generated by combining the local deviation state of the candidate relay execution unit. According to the pre-pointing state, the candidate relay execution unit is controlled to enter the target acquisition range and obtain the corresponding actual tracking state; During the overlapping tracking phase with the main tracking execution unit, the consistency of the actual tracking states of the two execution units is verified. The target common deviation state is corrected based on the verification results, and the locking state of the candidate relay execution unit is updated.

8. The method according to claim 7, characterized in that, During the overlapping tracking phase with the main tracking execution unit, the consistency verification of the actual tracking states of the two execution units includes: The actual tracking states of the main tracking execution unit and the candidate relay execution unit are matched with the corrected predicted motion states to obtain the corresponding tracking deviations; The degree of consistency across execution units is determined based on the correlation status of changes in the corresponding tracking deviations between the two execution units. The verification result is determined based on the consistency across execution units and the continuous locking status of candidate successor execution units, and the common deviations that meet the consistency conditions are used to correct the target common deviation status.

9. The method according to claim 1, characterized in that, When a candidate relay execution unit meets the stable tracking condition, the main tracking state transition is performed, and the multi-target dynamic tracking continuous network and subsequent tracking continuous paths are updated according to the antenna execution state and actual tracking state after the transition, including: Determine whether the stable tracking condition is met based on the locking status and continuous tracking status of the candidate relay execution unit; When the stable tracking conditions are met, the candidate relay execution unit is converted into a new main tracking execution unit, and the original main tracking execution unit is released; The corresponding execution node and migration relationship are corrected based on the antenna execution status and actual tracking status after migration. The subsequent tracking path for the affected target task is redefined based on the updated multi-target dynamic tracking continuous network.

10. A low-orbit satellite antenna cooperative control and tracking system based on multi-target missions, characterized in that, include: The acquisition module is used to acquire the target missions corresponding to multiple low-orbit satellites and the execution status of multiple antenna execution units, and to determine the executable tracking segments based on the predicted motion status of the target missions and the dynamic execution capabilities of the antenna execution units. A module is established to establish migration relationships based on the state transition conditions between executable tracking segments and the relay conditions across antenna execution units for the same target task, forming a multi-target dynamic tracking continuous network, and determining the continuous tracking path based on the task status of each target task; The decomposition module is used to determine the main tracking execution unit and candidate relay execution units according to the continuous tracking path. When the main tracking execution unit performs target tracking, it decomposes the tracking residual into the target common deviation state corresponding to the target task and the local deviation state of the main tracking execution unit based on the residual between the predicted motion state and the actual tracking state. The update module is used to enable the candidate relay execution unit to perform target pre-pointing by combining the target common deviation state and its own local deviation state when the subsequent execution state meets the relay conditions, and to update the target common deviation state and the locking state of the candidate relay execution unit during the overlapping tracking phase. The execution module is used to perform the main tracking state transition when the candidate relay execution unit meets the stable tracking conditions, and to update the multi-target dynamic tracking continuous network and subsequent tracking continuous path according to the antenna execution state after the transition and the actual tracking state.

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