Satellite network distributed time synchronization control method and system

Abstract

The present application relates to a satellite network distributed time synchronization control method and system, the method comprising: a satellite establishes an inter-satellite measurement link with an adjacent satellite to realize two-way dynamic ranging between satellites; in order to eliminate the influence of the two-way transmission path and its asymmetry, the two-way measurement is converted to epochs using a priori satellite real-time ephemeris to obtain the time deviation of the measurement signal transmission moment; then, the relativistic space-time effect of the inter-satellite measurement is calculated to compensate for the time offset; finally, through a distributed Kalman filter, each satellite uses the inter-satellite time offset estimate obtained by its own satellite node to control the satellite time to be consistent with the adjacent satellite time. Based on the satellite network distributed Kalman consistency protocol, the computational complexity of each satellite node is very small, and real-time computation can be performed on-orbit. The DSS network can realize distributed time synchronization and output time information.

Description

Technical Field

[0001] The present application relates to the technical field of satellite network time synchronization control, and in particular to a satellite network distributed time synchronization control method and system. Background Art

[0002] Satellites are constantly developing towards miniaturization, scale and clustering. Distributed Satellite System (DSS) provides a low-cost, flexible and resilient solution for the booming space applications. Precision time synchronization system has become the core infrastructure of DSS. To achieve precise collaboration and coherent coordination among large-scale distributed satellites, a low-cost and high-precision time synchronization system is required. N The SS system performs timing synchronization, and the time synchronization accuracy is limited. N SS signals are very weak and are easily affected by various electromagnetic interferences, which may lead to failure. The structured time reference transmission method is simple, but the time synchronization accuracy deteriorates with the increase of transmission links, and it cannot adapt well to the dynamic changes of satellite network topology. DSS needs to build a low-cost, high-precision, endogenous and ubiquitous time synchronization control system to provide flexible and elastic time services for large-scale DSS applications. Summary of the invention

[0003] Based on this, it is necessary to provide a satellite network distributed time synchronization control method and system that can solve the distributed synchronization control problem of large-scale satellite network time in response to the above technical problems.

[0004] A satellite network distributed time synchronization control method, the method comprising:

[0005] The DSS network time synchronization system uses inter-satellite links to perform time difference measurement and data transmission. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology.

[0006] Based on the measurement network topology, the satellite establishes an inter-satellite measurement link with the adjacent satellite to obtain the measurement value of the actual inter-satellite transmission delay.

[0007] The prior ephemeris information is used to perform epoch calculation, and the two-way measurement is calculated to the same time to obtain the time difference information between the two dynamic satellite nodes at that time.

[0008] The relativistic space-time effects of intersatellite measurements are calculated, and the time difference information is compensated for the relativistic effects to obtain the estimated value of the intersatellite time difference.

[0009] Each satellite uses a distributed Kalman filter consistency control system based on the inter-satellite time difference estimate of its own satellite node to control the satellite time to be consistent with the adjacent satellite time and output time information.

[0010] In one embodiment, the DSS network time synchronization system uses inter-satellite links to perform time difference measurement and data transmission. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology, including:

[0011] Taking into account the spatiotemporal characteristics of the satellite network, the requirements for inter-satellite data transmission, the inter-satellite time difference measurement performance and transmission direction, the satellite clock accuracy and the on-board processing capability, the optimal strategy network topology is designed based on the preset design goals to support better DSS network time synchronization performance; the preset design goals are: to ensure that each satellite node can be connected using the inter-satellite link, with low satellite link establishment overhead and high algebraic connectivity of the network topology.

[0012] In one embodiment, based on the measurement network topology, a satellite establishes an inter-satellite measurement link with an adjacent satellite to obtain a measurement value of an inter-satellite transmission delay, including:

[0013] The intersatellite measurement link uses dual unidirectional measurements between two satellites.

[0014] According to the timestamp observations of four different system reference times, the dynamic intersatellite measurement model is constructed as follows:

[0015] ;

[0016] ;

[0017] in, It's a satellite m To Satellite n The actual intersatellite transmission delay The measured value of It's a satellite n At system reference time The physical clock deviation is It's a satellite m At system reference time The physical clock deviation is It's a satellite n To Satellite m The actual intersatellite transmission delay The measured value of It's a satellite m At system reference time The physical clock deviation is It's a satellite n At system reference time The physical clock deviation.

[0018] In one embodiment, calculating the relativistic space-time effect of inter-satellite measurement and performing relativistic effect compensation on the time difference information to obtain the inter-satellite time difference estimation value includes:

[0019] The actual orbit, position and velocity of the satellite are obtained by using the real-time ephemeris on board. Based on the inter-satellite precision measurement model of the satellite clock intrinsic time reading, the relativistic effect of the inter-satellite clock time difference information is corrected in real time on orbit to obtain the estimated value of the inter-satellite time difference.

[0020] In one embodiment, each satellite uses a distributed Kalman filter consistency control system according to the estimated value of the inter-satellite time difference of its own satellite node to control the satellite time to be consistent with the adjacent satellite time. The design steps of the distributed Kalman filter in the steps include:

[0021] Establish the system state vector of each satellite node. Each satellite uses the measurement link with the adjacent satellite to obtain the time difference between satellites and establish the satellite node m The measurement vector of .

[0022] According to the system state vector and measurement vector, the state model and measurement model of the Kalman consistency time synchronization control system are established as follows:

[0023] ;

[0024] in, , Respectively represent the satellite nodes at the current time and the previous time m The clock time state vector, Indicates the satellite node at the current time m The time difference measurement vector, , , , represents the system state model noise vector at the current moment, represents the covariance matrix, represents the system observation noise vector at the current moment, m Indicates m Satellite nodes.

[0025] The system state prediction equation is established as:

[0026] ;

[0027] in, Indicates the current satellite m and the prediction vector of the time status of its adjacent satellites, Indicates the satellite at the previous moment m and the estimated vector of the time states of its adjacent satellites.

[0028] The covariance matrix of the system state prediction error is calculated as:

[0029] ;

[0030] in, represents the covariance matrix of the system state prediction error, Represents the system state estimation error covariance matrix.

[0031] According to the current satellite m and the prediction vector of the time state of its adjacent satellites and satellite nodes m The measurement vector of the system is used to establish the system state estimation equation:

[0032] ;

[0033] in, Indicates satellite m and the estimated vector of the time states of its adjacent satellites, represents the Kalman consistency gain matrix, .

[0034] The covariance matrix of the system state estimation error is calculated as:

[0035] .

[0036] The optimal Kalman consistency gain matrix is ​​solved for the covariance matrix of the system state estimation error, and the optimal Kalman consistency gain matrix is ​​obtained as:

[0037] ;

[0038] in, represents the optimal Kalman consistency gain matrix.

[0039] In one embodiment, the system state vector of each satellite node is:

[0040] ;

[0041] in, m Indicates m Satellite nodes, Indicates k The satellite physical clock readings measured Satellite node m The set of adjacent satellite nodes, , M Indicates satellite m The number of intersatellite links.

[0042] In one embodiment, the satellite node m The measurement vector is:

[0043] ;

[0044] in, Indicates the current satellite m To Satellite n The intersatellite time difference observation value, Satellite node m The set of adjacent satellite nodes, Indicates the current satellite m The clock time deviation, Respectively represent the current satellite n The clock time deviation.

[0045] In one embodiment, each satellite uses a distributed Kalman filter consistency control system based on the inter-satellite time difference estimation value of its own satellite node to control the satellite time to be consistent with the adjacent satellite time, including:

[0046] The covariance matrix of the system state prediction error and the satellite m The estimated vector of the time states of its adjacent satellites is initialized.

[0047] According to the satellite m The estimated vector of the time state of its adjacent satellites uses the system state prediction equation to determine the current satellite m and the prediction vector of the time status of its adjacent satellites.

[0048] The covariance matrix of the system state prediction error is used to determine the covariance of the system state prediction error using the state prediction covariance equation.

[0049] The Kalman consistency gain matrix is ​​adjusted according to the covariance of the system state prediction error.

[0050] According to the current satellite m and the prediction vector of the time state of its adjacent satellites, satellite nodes m The measurement vector and the adjusted Kalman consistency gain matrix use the system state estimation equation to determine the satellite at the current moment m and the estimated vector of the time states of its adjacent satellites.

[0051] According to the covariance of the system state prediction error and the adjusted Kalman consistency gain matrix, the covariance matrix of the system state estimation error at the current moment is calculated.

[0052] Update the covariance matrix of the system state prediction error to the covariance matrix of the system state estimation error at the current moment, and update the covariance matrix of the satellite state estimation error at the previous moment to m The estimated vector of the time state of its adjacent satellites is updated to the current satellite m and the estimated vector of the time state of its adjacent satellites, and continue to iterate until the preset stop condition is reached, thereby realizing distributed consistent time synchronization control of the distributed satellite system.

[0053] A satellite network distributed time synchronization control system comprises an inter-satellite measurement and time difference estimation unit, a DSS network time synchronization control unit and a measurement network topology planning unit.

[0054] The inter-satellite measurement and time difference estimation unit comprises a plurality of inter-satellite measurement and time difference estimation sub-units, and each satellite in the distributed satellite system is provided with an inter-satellite measurement and time difference estimation sub-unit.

[0055] The DSS network time synchronization control unit includes a number of distributed Kalman filters, and each satellite in the distributed satellite system is provided with a distributed Kalman filter.

[0056] The measurement network topology planning unit is used to perform time difference measurement and data transmission using inter-satellite links. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology.

[0057] The inter-satellite measurement and time difference estimation subunit is used to establish an inter-satellite measurement link between the satellite and the adjacent satellite based on the measurement network topology to obtain the measurement value of the real inter-satellite transmission delay; use the prior ephemeris information to perform epoch reduction, reduce the two-way measurement to the same time, and obtain the time difference information between the two dynamic satellite nodes at that time; calculate the relativistic space-time effect of the inter-satellite measurement, and compensate the time difference information for the relativistic effect to obtain the inter-satellite time difference estimate.

[0058] The DSS network time synchronization control unit is used for each satellite to use a distributed Kalman filter consistency control system based on the inter-satellite time difference estimation value of its own satellite node to control the satellite time to be consistent with the adjacent satellite time.

[0059] The above-mentioned satellite network distributed time synchronization control method and system include: the satellite establishes an inter-satellite measurement link with an adjacent satellite to realize two-way dynamic ranging between satellites; in order to eliminate the influence of the two-way transmission path and its asymmetry, the two-way measurement is converted to epochs using a priori satellite real-time ephemeris to obtain the time deviation of the measurement signal transmission moment; then, the relativistic space-time effect of the inter-satellite measurement is calculated to compensate for the time offset; finally, through a distributed Kalman filter, each satellite uses the inter-satellite time offset estimate obtained by its own satellite node to control the satellite time to be consistent with the adjacent satellite time. Based on the satellite network distributed Kalman consistency protocol, the calculation amount of each satellite node is very small, and real-time calculation can be performed on orbit. The DSS network can realize distributed time synchronization and output time information. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A schematic diagram of a flow chart of a satellite network distributed time synchronization control method in one embodiment;

[0061] Figure 2 A schematic diagram of a dual unidirectional measurement process of an intersatellite link in an embodiment;

[0062] Figure 3 A schematic diagram of a distributed Kalman filter synchronization control process in one embodiment;

[0063] Figure 4 1 is a structural block diagram of a satellite network distributed time synchronization control system in one embodiment. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0065] In one embodiment, Figure 1 As shown, a satellite network distributed time synchronization control method is provided, the method comprising the following steps:

[0066] Step 100: The DSS network time synchronization system uses inter-satellite links to perform time difference measurement and data transmission. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology.

[0067] Specifically, the DSS network time synchronization system is composed of onboard time and frequency synchronization modules, inter-satellite link payloads and ground support systems distributed on each satellite.

[0068] The topology of the measurement network directly affects the time synchronization performance of the DSS network.

[0069] Step 102: Based on the measurement network topology, the satellite establishes an inter-satellite measurement link with an adjacent satellite to obtain a measurement value of the actual inter-satellite transmission delay.

[0070] Step 104: Use the prior ephemeris information to perform epoch calculation, calculate the two-way measurement to the same time, and obtain the time difference information between the two dynamic satellite nodes at that time.

[0071] Step 106: Calculate the relativistic space-time effect of the inter-satellite measurement, and perform relativistic effect compensation on the time difference information to obtain the estimated value of the inter-satellite time difference.

[0072] Specifically, when measuring time and frequency in large-scale space, based on the absolute view of space and time and classical Newtonian mechanics, the time observation accuracy is The distributed satellite system operates in the Earth's gravitational field. The long-distance measurement between satellites and the high-speed movement of satellites lead to obvious relativistic effects, which will have a great impact on high-precision time and frequency measurements. It is necessary to analyze the high-dynamic long-distance intersatellite clock time and frequency measurement characteristics of the distributed satellite system under the framework of relativity.

[0073] Step 108: Each satellite uses a distributed Kalman filter consistency control system according to the inter-satellite time difference estimation value of its own satellite node to control the satellite time to be consistent with the adjacent satellite time and output the time information.

[0074] Specifically, the DSS time synchronization network can use distributed Kalman filter consistency control to achieve distributed time synchronization. It uses the measurement of time differences between satellites to achieve consistency in the logical time of all satellites. Since it is impossible to make absolute observations of each satellite time, all intersatellite link measurements are relative differences in satellite time. Therefore, this time synchronization system is different from the traditional Kalman time synchronization system.

[0075] In the above satellite network distributed time synchronization control method, the method includes: the satellite establishes an inter-satellite measurement link with the adjacent satellite to realize two-way dynamic ranging between satellites; in order to eliminate the influence of the two-way transmission path and its asymmetry, the two-way measurement is converted to epochs using the a priori satellite real-time ephemeris to obtain the time deviation of the measurement signal transmission time; then, the relativistic space-time effect of the inter-satellite measurement is calculated to compensate for the time offset; finally, through a distributed Kalman filter, each satellite uses the inter-satellite time offset estimate obtained by its own satellite node to control the satellite time to be consistent with the adjacent satellite time. Based on the satellite network distributed Kalman consistency protocol, the calculation amount of each satellite node is very small, and real-time calculation can be performed on orbit. The DSS network can realize distributed time synchronization and output time information.

[0076] In one of the embodiments, step 100 includes: considering the spatiotemporal characteristics of the satellite network, the inter-satellite data transmission requirements, the inter-satellite time difference measurement performance and transmission direction, the satellite clock accuracy and the on-board processing capability, designing the optimal strategy network topology based on the preset design goals, and supporting better DSS network time synchronization performance; the preset design goals are: ensuring that each satellite node can be connected using the inter-satellite link, and the satellite link establishment overhead is small and the network topology algebraic connectivity is large.

[0077] In one embodiment, step 102 includes: the inter-satellite measurement link uses dual unidirectional measurement between two satellites; and constructs a dynamic inter-satellite measurement model based on the acquired timestamp observation values ​​of four different system reference times:

[0078] (1)

[0079] (2)

[0080] in, It's a satellite m To Satellite n The actual intersatellite transmission delay The measured value of It's a satellite n At system reference time The physical clock deviation is It's a satellite m At system reference time The physical clock deviation is It's a satellite n To Satellite m The actual intersatellite transmission delay The measured value of It's a satellite m At system reference time The physical clock deviation is It's a satellite n At system reference time The physical clock deviation.

[0081] Specifically, the intersatellite measurement link uses two-way and one-way measurements between two satellites, such as Figure 2 As shown in the figure, the satellite moves at high speed during the measurement process, and the two-way transmission path is asymmetric. , , and Get four timestamps respectively , , and In a measurement process, it is considered Since intersatellite measurement signals are transmitted over long distances, the signal transmission time and reception time are not equal, that is, and Due to the high-speed dynamic motion of satellites, the actual transmission delay of the two-way intersatellite link is also not equal, that is, .

[0082] It is assumed here that the intersatellite transceiver equipment zero value and antenna phase center deviation have been corrected. Based on the four timestamp observations, the intersatellite measurement equation can be modeled as shown in formula (1) and formula (2).

[0083] Satellites can obtain ephemeris information, including satellite orbit, position speed, clock time difference, frequency deviation and clock drift. Through this prior information, the actual transmission delay between satellites can be estimated. and , so that the time difference information between two dynamic satellite nodes can be calculated by using one inter-satellite link measurement .

[0084] In one embodiment, step 106 includes: using the on-board real-time ephemeris to obtain the actual orbit, position and speed of the satellite, and based on the inter-satellite precision measurement model of the satellite clock intrinsic time reading, completing the on-orbit real-time correction of the relativistic effect of the inter-satellite clock time difference information to obtain the inter-satellite time difference estimate.

[0085] Specifically, according to the theory of relativity, the transformation from Euclidean space to Riemannian spacetime, the intersatellite dynamic time and frequency measurement involves the characteristics of satellite-borne clocks and electromagnetic signal transmission characteristics.

[0086] For the characteristics of satellite clocks in Riemannian spacetime, based on the geocentric inertial coordinate system (ECI) under the relativistic system, the gravitational redshift caused by gravitational potential and the time dilation effect caused by high-speed motion are analyzed, and the influence of the third celestial body outside the Earth's space is considered, mainly including the gravitational influence of the moon and the sun, which is reflected in the influence of tidal forces. In the geocentric inertial coordinate system, the satellite clock is affected by gravitational potential and high-speed motion, and can quantitatively analyze the Earth's gravity (including The reference coordinate time of the onboard clock is quantitatively calculated from the intrinsic time of the onboard clock, which is used for dynamic time measurement between satellites.

[0087] For the measurement signal transmission in Riemann spacetime, in the geocentric inertial coordinate system (ECI), the main focus is on analyzing the variation of the Riemann spacetime interval based on the laser / radio wave measurement signal transmission, and quantitatively calculating the influence of the gravitational potential at a certain orbital altitude.

[0088] In summary, the actual orbit, position and velocity of the satellite can be obtained by using the on-board real-time ephemeris, and the inter-satellite precision measurement model based on the satellite clock intrinsic time reading can complete the on-orbit real-time correction of the relativistic effect of the inter-satellite clock time difference measurement.

[0089] In one embodiment, the design steps of the distributed Kalman filter in step 108 include: establishing a system state vector for each satellite node, each satellite uses a measurement link with an adjacent satellite to obtain the time difference between satellites, and establishing a satellite node m According to the system state vector and measurement vector, the state model and measurement model of the Kalman consistency time synchronization control system are established as follows:

[0090] (3)

[0091] in, , Respectively represent the satellite nodes at the current time and the previous time m The clock time state vector, Indicates the satellite node at the current time m The time difference measurement vector, , , , represents the noise vector of the system state model at the current moment, which obeys the zero-mean Gaussian distribution. Represents the system state model noise vector at the current moment The covariance matrix of represents the system observation noise vector at the current moment, which obeys the zero-mean Gaussian distribution. Represents the system observation noise vector at the current moment The covariance matrix of m Indicates m Satellite nodes.

[0092] The system state prediction equation is established as:

[0093] (4)

[0094] in, Indicates the current satellite m and the prediction vector of the time status of its adjacent satellites, Indicates the satellite at the previous moment m and the estimated vector of the time states of its adjacent satellites.

[0095] The covariance matrix of the system state prediction error is calculated as:

[0096] (5)

[0097] in, represents the covariance matrix of the system state prediction error, Represents the system state estimation error covariance matrix.

[0098] According to the current satellite m and the prediction vector of the time state of its adjacent satellites and satellite nodes m The measurement vector of the system is used to establish the system state estimation equation:

[0099] (6)

[0100] in, Indicates satellite m and the estimated vector of the time states of its adjacent satellites, represents the Kalman consistency gain matrix, .

[0101] The covariance matrix of the system state estimation error is calculated as:

[0102] (7)

[0103] The optimal Kalman consistency gain matrix is ​​solved for the covariance matrix of the system state estimation error, and the optimal Kalman consistency gain matrix is ​​obtained as:

[0104] (8)

[0105] in, represents the optimal Kalman consistency gain matrix.

[0106] In summary, the five equations of Kalman consistency control for system time synchronization from formula (4) to formula (8) are as follows: Figure 3 As shown, DSS distributed consistency time synchronization control can be achieved.

[0107] In one embodiment, the system state vector of each satellite node is:

[0108] (9)

[0109] in, m Indicates m Satellite nodes, Indicates k The satellite physical clock readings measured Satellite node m The set of adjacent satellite nodes, , M Indicates satellite m The number of intersatellite links (i.e.M Satellites have established inter-satellite measurement links.

[0110] In one embodiment, the satellite node m The measurement vector is:

[0111] (10)

[0112] in, Indicates the current satellite m To Satellite n The intersatellite time difference observation value, Satellite node m The set of adjacent satellite nodes, Indicates the current satellite m The clock time deviation, Respectively represent the current satellite n The clock time deviation.

[0113] In one embodiment, step 108 includes: calculating the covariance matrix of the system state prediction error and the satellite m and the estimated vector of the time state of its adjacent satellites are initialized; according to the satellite at the previous moment m The estimated vector of the time state of its adjacent satellites uses the system state prediction equation to determine the current satellite m and the prediction vector of the time state of its adjacent satellites; according to the covariance matrix of the system state prediction error, the state prediction covariance equation is used to determine the covariance of the system state prediction error; according to the covariance of the system state prediction error, the Kalman consistency gain matrix is ​​adjusted; according to the current satellite m and the prediction vector of the time state of its adjacent satellites, satellite nodes m The measurement vector and the adjusted Kalman consistency gain matrix use the system state estimation equation to determine the satellite at the current moment m and the estimated vector of the time state of its adjacent satellites; calculate the covariance matrix of the system state estimation error at the current moment according to the covariance of the system state prediction error and the adjusted Kalman consistency gain matrix; update the covariance matrix of the system state prediction error to the covariance matrix of the system state estimation error at the current moment, and replace the satellite at the previous moment with the covariance matrix of the system state prediction error. m The estimated vector of the time state of its adjacent satellites is updated to the current satellite m The estimated vector of the time state of its adjacent satellites is used to continue iterating until the preset stop condition is reached, thus realizing the distributed consistency time synchronization control of the distributed satellite system. The distributed Kalman filter synchronization control process is as follows: Figure 3 shown.

[0114] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0115] In one embodiment, Figure 4 As shown, in order to achieve high-precision and flexible time synchronization of satellite constellations, a satellite network distributed time synchronization control system is provided, which includes an inter-satellite measurement and time difference estimation unit, a DSS network time synchronization control unit and a measurement network topology planning unit.

[0116] The inter-satellite measurement and time difference estimation unit comprises a plurality of inter-satellite measurement and time difference estimation sub-units, and each satellite in the distributed satellite system is provided with an inter-satellite measurement and time difference estimation sub-unit.

[0117] The DSS network time synchronization control unit includes a number of distributed Kalman filters, and each satellite in the distributed satellite system is provided with a distributed Kalman filter.

[0118] The measurement network topology planning unit is used to perform time difference measurement and data transmission using inter-satellite links. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology.

[0119] The inter-satellite measurement and time difference estimation subunit is used to establish an inter-satellite measurement link between a satellite and an adjacent satellite based on the measurement network topology to obtain the measurement value of the real inter-satellite transmission delay; use the prior ephemeris information to perform epoch reduction on the two-way measurement to obtain the real inter-satellite transmission delay; obtain the time difference information between two dynamic satellite nodes based on the measurement value of the real inter-satellite transmission delay and the real inter-satellite transmission delay; calculate the relativistic space-time effect of the inter-satellite measurement, and compensate the time difference information for the relativistic effect to obtain the estimated value of the inter-satellite time difference.

[0120] The DSS network time synchronization control unit is used for each satellite to use a distributed Kalman filter consistency control system based on the inter-satellite time difference estimation value of its own satellite node to control the satellite time to be consistent with the adjacent satellite time.

[0121] Specifically, in order to achieve high-precision and flexible time synchronization of satellite constellations, a distributed time synchronization control framework for satellite networks was established, and the time deviation measurement of distributed inter-satellite measurement links and distributed Kalman filter synchronization control were used to achieve precise time synchronization of satellite networks.

[0122] Unlike ground-based wireless sensor networks, satellites are widely distributed in space and move very fast. This will lead to huge transmission delays and relativistic effects, which is not conducive to high-precision inter-satellite measurement. In order to achieve high-precision and flexible time synchronization of satellite constellations, it is necessary to establish a time synchronization framework for distributed space networks, such as Figure 4 As shown, it includes an inter-satellite measurement and time difference estimation unit, a DSS network time synchronization control unit, and a measurement network topology planning unit.

[0123] Each satellite needs to solve two main problems: intersatellite measurement and time offset estimation, and DSS network time synchronization control. The former mainly completes intersatellite bidirectional measurement in a dynamic space environment and estimates the time offset between two satellites. In order to achieve high-precision estimation, it is necessary to consider the high-speed movement of satellites, long-distance transmission and relativistic effects. The satellite establishes an intersatellite measurement link with the adjacent satellite to achieve two-way dynamic ranging between satellites. In order to eliminate the influence of the two-way transmission path and its asymmetry, the two-way measurement is epoch-reduced using the prior satellite real-time ephemeris to obtain the time offset of the measurement signal transmission time. Then, the relativistic space-time effect of intersatellite measurement is calculated to compensate for the time offset. The latter is a distributed Kalman filter. Each satellite uses the intersatellite time offset estimation obtained by its own satellite node to control the satellite time to be consistent with the adjacent satellite time. Based on the satellite network distributed Kalman consistency protocol, the calculation amount of each satellite node is very small, and it can be calculated in real time on orbit. The DSS network can achieve distributed time synchronization and output time information.

[0124] At the same time, the stability and time synchronization performance of the system are also closely related to the network topology. For satellite constellations, the topology is usually designed in advance before the satellite is launched, and no real-time calculation is required on orbit. Therefore, the measurement topology planning can be completed in advance when the satellite network system is designed, instead of being processed in real time on orbit. When operating on orbit, the satellite only needs less computing resources to monitor changes in intersatellite links and network topology.

[0125] In one of the embodiments, the measurement network topology planning unit is also used to consider the spatiotemporal characteristics of the satellite network, inter-satellite data transmission requirements, inter-satellite time difference measurement performance and transmission direction, satellite clock accuracy and on-board processing capabilities, and to design the optimal strategy network topology based on preset design goals to support better DSS network time synchronization performance; the preset design goals are: to ensure that each satellite node can be connected using inter-satellite links, and that the satellite link establishment overhead is small and the network topology algebraic connectivity is large.

[0126] In one embodiment, the inter-satellite measurement and time difference estimation subunit is also used for the inter-satellite measurement link to use dual one-way measurement between two satellites; according to the acquired timestamp observation values ​​of four different system reference times, a dynamic inter-satellite measurement model is constructed as follows:

[0127] ;

[0128] ;

[0129] in, It's a satellite m To Satellite n The actual intersatellite transmission delay The measured value of It's a satellite n At system reference time The physical clock deviation is It's a satellite m At system reference time The physical clock deviation is It's a satellite n To Satellite m The actual intersatellite transmission delay The measured value of It's a satellite m At system reference time The physical clock deviation is It's a satellite n At system reference time The physical clock deviation.

[0130] In one of the embodiments, the inter-satellite measurement and time difference estimation subunit is also used to obtain the actual orbit, position and speed of the satellite using the real-time ephemeris on the satellite, and to complete the on-orbit real-time correction of the relativistic effect of the inter-satellite clock time difference information based on the inter-satellite precision measurement model of the satellite clock intrinsic time reading, so as to obtain the inter-satellite time difference estimate.

[0131] In one embodiment, the design steps of the distributed Kalman filter in the DSS network time synchronization control unit include: establishing a system state vector for each satellite node, each satellite uses a measurement link with an adjacent satellite to obtain the time difference between satellites, and establishing a satellite node m According to the system state vector and measurement vector, the state model and measurement model of the Kalman consistency time synchronization control system are established as follows:

[0132] ;

[0133] in, , Respectively represent the satellite nodes at the current time and the previous time m The clock time state vector, Indicates the satellite node at the current time m The time difference measurement vector, , , , represents the system state model noise vector at the current moment, represents the covariance matrix, represents the system observation noise vector at the current moment, m Indicates m Satellite nodes.

[0134] The system state prediction equation is established as:

[0135] ;

[0136] in, Indicates the current satellite m and the prediction vector of the time status of its adjacent satellites, Indicates the satellite at the previous moment m and the estimated vector of the time states of its adjacent satellites.

[0137] The covariance matrix of the system state prediction error is calculated as:

[0138] ;

[0139] in, represents the covariance matrix of the system state prediction error, Represents the system state estimation error covariance matrix.

[0140] According to the current satellite m The prediction vector of the time state of its adjacent satellites and the satellite nodes m The measurement vector of the system is used to establish the system state estimation equation:

[0141] ;

[0142] in, Indicates satellite m and the estimated vector of the time states of its adjacent satellites, represents the Kalman consistency gain matrix, .

[0143] The covariance matrix of the system state estimation error is calculated as:

[0144] .

[0145] The optimal Kalman consistency gain matrix is ​​solved for the covariance matrix of the system state estimation error, and the optimal Kalman consistency gain matrix is ​​obtained as:

[0146] ;

[0147] in, represents the optimal Kalman consistency gain matrix.

[0148] In one embodiment, the system state vector of each satellite node in the DSS network time synchronization control unit is:

[0149] ;

[0150] in, m Indicates m Satellite nodes, Indicates k The satellite physical clock readings measured Satellite node m The set of adjacent satellite nodes, , M Indicates satellite m The number of intersatellite links.

[0151] In one embodiment, the satellite node in the DSS network time synchronization control unit m The measurement vector is:

[0152] ;

[0153] in, Indicates the current satellite m To Satellite n The intersatellite time difference observation value, Satellite node m The set of adjacent satellite nodes, Indicates the current satellite m The clock time deviation, Respectively represent the current satellite n The clock time deviation.

[0154] In one embodiment, the DSS network time synchronization control unit is also used to calculate the covariance matrix of the system state prediction error and the satellite m and the estimated vector of the time state of its adjacent satellites are initialized; according to the satellite at the previous moment m The estimated vector of the time state of its adjacent satellites uses the system state prediction equation to determine the current satellite mand the prediction vector of the time state of its adjacent satellites; according to the covariance matrix of the system state prediction error, the state prediction covariance equation is used to determine the covariance of the system state prediction error; according to the covariance of the system state prediction error, the Kalman consistency gain matrix is ​​adjusted; according to the current satellite m and the prediction vector of the time state of its adjacent satellites, satellite nodes m The measurement vector and the adjusted Kalman consistency gain matrix use the system state estimation equation to determine the satellite at the current moment m and the estimated vector of the time state of its adjacent satellites; calculate the covariance matrix of the system state estimation error at the current moment according to the covariance of the system state prediction error and the adjusted Kalman consistency gain matrix; update the covariance matrix of the system state prediction error to the covariance matrix of the system state estimation error at the current moment, and replace the satellite at the previous moment with the covariance matrix of the system state prediction error. m The estimated vector of the time state of its adjacent satellites is updated to the current satellite m and the estimated vector of the time state of its adjacent satellites, and continue to iterate until the preset stop condition is reached, thereby realizing distributed consistent time synchronization control of the distributed satellite system.

[0155] For the specific definition of the satellite network distributed time synchronization control system, please refer to the definition of the satellite network distributed time synchronization control method above, which will not be repeated here. Each module in the above-mentioned satellite network distributed time synchronization control system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0156] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A satellite network distributed time synchronization control method, characterized in that: The method comprises: The DSS network time synchronization system uses inter-satellite links to measure time differences and transmit data. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology; Based on the measurement network topology, the satellite establishes an inter-satellite measurement link with an adjacent satellite to obtain a measurement value of the inter-satellite transmission delay; The prior ephemeris information is used to perform epoch calculation, and the two-way measurement is calculated to the same time to obtain the time difference information between the two dynamic satellite nodes at that time; Calculating the relativistic space-time effect of intersatellite measurement, and performing relativistic effect compensation on the time difference information to obtain an estimated value of the intersatellite time difference; Each satellite uses a distributed Kalman filter consistency control system based on the inter-satellite time difference estimation value of its own satellite node to control the satellite time to be consistent with the adjacent satellite time and output time information; Among them, the design steps of the distributed Kalman filter include: Establish the system state vector of each satellite node. Each satellite uses the measurement link with the adjacent satellite to obtain the time difference between satellites and establish the satellite node m The measurement vector of According to the system state vector and the measurement vector, the state model and measurement model of the Kalman consistency time synchronization control system are established as follows: ； in, , Respectively represent the satellite nodes at the current time and the previous time m The clock time state vector, Indicates the satellite node at the current time m The time difference measurement vector, , , , represents the system state model noise vector at the current moment, represents the covariance matrix, represents the system observation noise vector at the current moment, m Indicates m Satellite nodes; The system state prediction equation is established as: ； in, Indicates the current satellite m and the prediction vector of the time status of its adjacent satellites, Indicates the satellite at the previous moment m and the estimated vector of the time states of its adjacent satellites; The covariance matrix of the system state prediction error is calculated as: ； in, represents the covariance matrix of the system state prediction error, represents the system state estimation error covariance matrix; According to the current satellite m The prediction vector of the time state of its adjacent satellites and the satellite nodes m The measurement vector of the system is used to establish the system state estimation equation: ； in, Indicates satellite m and the estimated vector of the time states of its adjacent satellites, represents the Kalman consistency gain matrix, ; The covariance matrix of the system state estimation error is calculated as; ； The optimal Kalman consistency gain matrix is ​​solved for the covariance matrix of the system state estimation error, and the optimal Kalman consistency gain matrix is ​​obtained as: ； in, represents the optimal Kalman consistency gain matrix; Among them, each satellite uses a distributed Kalman filter consistency control system based on the inter-satellite time difference estimation value of its own satellite node to control the satellite time to be consistent with the adjacent satellite time and output time information, including: The covariance matrix of the system state prediction error and the satellite m Initialize the estimated vector of the time state of its adjacent satellites; According to the satellite m The estimated vector of the time state of its adjacent satellites uses the system state prediction equation to determine the current satellite m and the prediction vector of the time status of its adjacent satellites; According to the covariance matrix of the system state prediction error, the state prediction covariance equation is adopted to determine the covariance of the system state prediction error; Adjusting the Kalman consistency gain matrix according to the covariance of the system state prediction error; According to the current satellite m and the prediction vector of the time state of its adjacent satellites, satellite nodes m The measurement vector and the adjusted Kalman consistency gain matrix use the system state estimation equation to determine the satellite at the current moment m and the estimated vector of the time states of its adjacent satellites; Calculate the covariance matrix of the system state estimation error at the current moment according to the covariance of the system state prediction error and the adjusted Kalman consistency gain matrix; Update the covariance matrix of the system state prediction error to the covariance matrix of the system state estimation error at the current moment, and update the covariance matrix of the satellite state estimation error at the previous moment m The estimated vector of the time state of its adjacent satellites is updated to the current satellite m The estimated vector of the time state of its adjacent satellites is continued to iterate until the preset stop condition is reached, thereby realizing the distributed consistency time synchronization control of the distributed satellite system and outputting the time information.

2. The satellite network distributed time synchronization control method according to claim 1, characterized in that: The DSS network time synchronization system uses inter-satellite links to measure time differences and transmit data. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology, including: Taking into account the spatiotemporal characteristics of the satellite network, the requirements for inter-satellite data transmission, the inter-satellite time difference measurement performance and transmission direction, the satellite clock accuracy and the on-board processing capability, the optimal strategy network topology is designed based on the preset design goals to support better DSS network time synchronization performance; the preset design goals are: to ensure that each satellite node can be connected using the inter-satellite link, and the satellite link establishment overhead is small and the network topology algebraic connectivity is large.

3. The satellite network distributed time synchronization control method according to claim 1, characterized in that: Based on the measurement network topology, the satellite establishes an inter-satellite measurement link with an adjacent satellite to obtain a measurement value of the inter-satellite transmission delay, including: The intersatellite measurement link uses dual one-way measurements between two satellites; According to the timestamp observations of four different system reference times, the dynamic intersatellite measurement model is constructed as follows: ； ； in, It's a satellite m To Satellite n The actual intersatellite transmission delay The measured value of It's a satellite n At system reference time The physical clock deviation is It's a satellite m At system reference time The physical clock deviation is It's a satellite n To Satellite m The actual intersatellite transmission delay The measured value of It's a satellite m At system reference time The physical clock deviation is It's a satellite n At system reference time The physical clock deviation.

4. The satellite network distributed time synchronization control method according to claim 1, characterized in that: Calculating the relativistic space-time effect of intersatellite measurement and performing relativistic effect compensation on the time difference information to obtain an estimated value of the intersatellite time difference, including: The actual orbit, position and velocity of the satellite are obtained by using the real-time ephemeris on board. Based on the inter-satellite precision measurement model of the satellite clock intrinsic time reading, the relativistic effect of the inter-satellite clock time difference information is corrected in real time on orbit to obtain the estimated value of the inter-satellite time difference.

5. The satellite network distributed time synchronization control method according to claim 1, characterized in that: The system state vector of each satellite node is: ； in, m Indicates m Satellite nodes, Indicates k The satellite clock readings measured Satellite node m The set of adjacent satellite nodes, , M Indicates satellite m The number of intersatellite links.

6. The satellite network distributed time synchronization control method according to claim 1, characterized in that: Satellite Node m The measurement vector is: ； in, Indicates the current satellite m To Satellite n The intersatellite time difference observation value, Satellite node m The set of adjacent satellite nodes, Indicates the current satellite m The clock time deviation, Respectively represent the current satellite n The clock time deviation.

7. A satellite network distributed time synchronization control system, characterized in that: The system comprises an inter-satellite measurement and time difference estimation unit, a DSS network time synchronization control unit and a measurement network topology planning unit; The inter-satellite measurement and time difference estimation unit includes a plurality of inter-satellite measurement and time difference estimation sub-units, and each satellite in the distributed satellite system is provided with an inter-satellite measurement and time difference estimation sub-unit; The DSS network time synchronization control unit includes a plurality of distributed Kalman filters, and each satellite in the distributed satellite system is provided with a distributed Kalman filter; The measurement network topology planning unit is used to perform time difference measurement and data transmission using inter-satellite links. The entire network is composed of multiple inter-satellite links connecting various satellite nodes to form a measurement network topology; The inter-satellite measurement and time difference estimation subunit is used to establish an inter-satellite measurement link between a satellite and an adjacent satellite based on the measurement network topology to obtain a measurement value of the real inter-satellite transmission delay; Using a priori ephemeris information to perform epoch reduction, the two-way measurement is reduced to the same time, and the time difference information between the two dynamic satellite nodes at that time is obtained; the relativistic space-time effect of the inter-satellite measurement is calculated, and the relativistic effect compensation is performed on the time difference information to obtain the inter-satellite time difference estimation value; The DSS network time synchronization control unit is used for each satellite to use a distributed Kalman filter consistency control system according to the inter-satellite time difference estimation value of its own satellite node, control the satellite time to be consistent with the adjacent satellite time, and output time information; The design steps of the distributed Kalman filter in the DSS network time synchronization control unit include: Establish the system state vector of each satellite node. Each satellite uses the measurement link with the adjacent satellite to obtain the time difference between satellites and establish the satellite node m The measurement vector of According to the system state vector and the measurement vector, the state model and measurement model of the Kalman consistency time synchronization control system are established as follows: ； in, , Respectively represent the satellite nodes at the current time and the previous time m The clock time state vector, Indicates the satellite node at the current time m The time difference measurement vector, , , , represents the system state model noise vector at the current moment, represents the covariance matrix, represents the system observation noise vector at the current moment, m Indicates m Satellite nodes; The system state prediction equation is established as: ； in, Indicates the current satellite m and the prediction vector of the time status of its adjacent satellites, Indicates the satellite at the previous moment m and the estimated vector of the time states of its adjacent satellites; The covariance matrix of the system state prediction error is calculated as: ； in, represents the covariance matrix of the system state prediction error, represents the system state estimation error covariance matrix; According to the current satellite m The prediction vector of the time state of its adjacent satellites and the satellite nodes m The measurement vector of the system is used to establish the system state estimation equation: ； in, Indicates satellite m and the estimated vector of the time states of its adjacent satellites, represents the Kalman consistency gain matrix, ; The covariance matrix of the system state estimation error is calculated as; ； The optimal Kalman consistency gain matrix is ​​solved for the covariance matrix of the system state estimation error, and the optimal Kalman consistency gain matrix is ​​obtained as: ； in, represents the optimal Kalman consistency gain matrix; The DSS network time synchronization control unit is also used to include: the covariance matrix of the system state prediction error and the satellite at the previous moment m and the estimated vector of the time state of its adjacent satellites are initialized; according to the satellite at the previous moment m The estimated vector of the time state of its adjacent satellites uses the system state prediction equation to determine the current satellite m and the prediction vector of the time state of its adjacent satellites; according to the covariance matrix of the system state prediction error, the state prediction covariance equation is used to determine the covariance of the system state prediction error; according to the covariance of the system state prediction error, the Kalman consistency gain matrix is ​​adjusted; according to the current satellite m and the prediction vector of the time state of its adjacent satellites, satellite nodes m The measurement vector and the adjusted Kalman consistency gain matrix use the system state estimation equation to determine the satellite at the current moment m and the estimated vector of the time state of its adjacent satellites; calculate the covariance matrix of the system state estimation error at the current moment according to the covariance of the system state prediction error and the adjusted Kalman consistency gain matrix; update the covariance matrix of the system state prediction error to the covariance matrix of the system state estimation error at the current moment, and update the covariance matrix of the satellite at the previous moment m The estimated vector of the time state of its adjacent satellites is updated to the current satellite m The estimated vector of the time state of its adjacent satellites is continued to iterate until the preset stop condition is reached, thereby realizing the distributed consistency time synchronization control of the distributed satellite system and outputting the time information.

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