Multi-satellite dynamic channel reconstruction method, device, system, equipment and storage medium

Abstract

This application provides a multi-satellite dynamic channel reconstruction method, apparatus, system, device, and storage medium. It constructs a reconstruction time node sequence containing multiple time nodes corresponding to the total reconstruction time. Based on the distribution of this time node sequence, it obtains the dynamic channel parameters of each satellite object at each time node. Then, based on the dynamic channel parameters, it dynamically determines the candidate probe regions for each satellite object at each time node. Finally, it performs multi-satellite dynamic channel reconstruction based on the dynamically adjusted candidate probe regions. This avoids the problems of high computational load and poor real-time performance caused by full screening of all probes, thus improving the real-time performance and accuracy of multi-satellite dynamic channel reconstruction.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a multi-satellite dynamic channel reconstruction method, apparatus, system, device and storage medium. Background Technology

[0002] With the rapid development of low-Earth orbit satellite internet, satellite terminal equipment needs to support multi-satellite collaborative communication, and its air interface performance testing requires simulating dynamically changing multi-satellite channel environments. In typical test environments, the test system needs to simulate the spatial angular distribution characteristics of satellite signal sources using a multi-probe anechoic chamber (MPAC) to verify key performance indicators of the terminal equipment, such as beamforming and multi-satellite signal discrimination capabilities under dynamic channels. However, due to the characteristics of satellite channels, such as multiple cluster signals, dynamic angular changes (e.g., cluster formation and extinction, angular shift), and interference from multiple satellite signal sources, traditional static probe selection methods are difficult to meet the requirements of high-precision, low-complexity dynamic channel reconstruction. Furthermore, in multi-satellite test scenarios, multiple satellite signal sources (e.g., satellites at different orbital altitudes) need to be simulated simultaneously, and each signal source needs to have its probe weights independently configured to distinguish its spatial characteristics. This places higher demands on the real-time performance, resource allocation capabilities, and signal source isolation capabilities of the probe selection algorithm.

[0003] Therefore, existing channel reconstruction schemes suffer from high computational complexity in probe selection and poor real-time performance of dynamic channel reconstruction. Summary of the Invention

[0004] This application provides a method, apparatus, system, device, and storage medium for multi-satellite dynamic channel reconstruction, which achieves low complexity and high precision probe selection for multi-satellite dynamic channel reconstruction.

[0005] In a first aspect, embodiments of this application provide a multi-satellite dynamic channel reconfiguration method, including:

[0006] Obtain the reconstruction time node sequence corresponding to the total reconstruction time. The reconstruction time node sequence includes at least two time nodes within the total reconstruction time. Based on the reconstruction time node sequence, determine the dynamic channel parameters of multiple satellite objects at each time node. Based on the dynamic channel parameters, dynamically determine the candidate probe regions of the satellite objects at each time node. The candidate probe region of the satellite object at a later time node is determined based on the candidate probe region of the satellite object at the previous time node. Based on the candidate probe regions of the satellite objects at each time node, perform multi-satellite dynamic channel reconstruction within the total reconstruction time.

[0007] In one possible implementation, the candidate probe regions for the satellite object at each time node are dynamically determined based on dynamic channel parameters, including: acquiring the candidate probe regions for the satellite object at the first time node; and recursively evolving the candidate probe regions corresponding to the remaining time nodes according to the dynamic channel parameters and the candidate probe regions at the time nodes to obtain the candidate probe regions for the satellite object at each remaining time node.

[0008] In one possible implementation, obtaining the candidate probe region for a satellite object at the first time node includes: for the first time node in the time node sequence, obtaining the channel parameters and feasible probe number range for each cluster of each satellite object; based on the channel parameters, feasible probe number range, and preset reconstruction criteria, obtaining the reconstruction error data for each cluster of each satellite object under different feasible probe numbers; based on the reconstruction error data for each cluster of each satellite object, the cluster power weight, and the maximum number of activatable probes, obtaining the preferred probe allocation set for each satellite object; based on the preferred probe allocation set, determining the spatial distribution boundary of the activated probes for the satellite object, and obtaining the candidate probe region for the satellite object at the first time node based on the spatial distribution boundary.

[0009] In one possible implementation, the spatial distribution boundary of the probes used by the satellite object is determined according to the preferred probe allocation set, and the candidate probe area of ​​the satellite object at the first time node is obtained based on the spatial distribution boundary, including: merging the preferred probe allocation sets of all satellite objects into a unified target probe set according to the preferred probe allocation set; determining the spatial distribution boundary corresponding to the target probe set, and obtaining the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

[0010] In one possible implementation, the candidate probe regions corresponding to the remaining time nodes are recursively evolved according to the dynamic channel parameters and the candidate probe regions of the time nodes to obtain the candidate probe regions corresponding to each remaining time node, including: obtaining the probe selection result corresponding to the previous time node and the dynamic channel parameters corresponding to the current time node; and determining the candidate probe region corresponding to the current time node according to the dynamic channel parameters.

[0011] In one possible implementation, the method further includes: determining the candidate probe area corresponding to the current time node based on dynamic channel parameters, including: determining whether there is cluster birth or death at the current time according to the cluster birth and death judgment rule; if there is no cluster birth or death, correcting the candidate probe area according to the current channel parameters; if there is cluster birth or death, recalculating the candidate probe area according to the initial time logic.

[0012] In one possible implementation, the method further includes: obtaining the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment; verifying the root mean square reconstruction accuracy of the current probe selection scheme based on the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment; if the reconstruction accuracy does not meet the threshold, re-traversing the probe number fluctuation variables to determine a better probe number allocation scheme.

[0013] In one possible implementation, based on the candidate probe regions of the satellite object at each time node, multi-satellite dynamic channel reconstruction is performed within the total reconstruction time, including: obtaining power weight constraints; assigning power weights to probes in the candidate probe regions according to the weight constraints and reconstruction criteria; and allocating signals to probes based on the power weights to complete the channel reconstruction at the current time node.

[0014] Secondly, embodiments of this application provide a multi-satellite dynamic channel reconfiguration apparatus, comprising:

[0015] The acquisition module is used to acquire the sequence of reconstruction time nodes corresponding to the total reconstruction time. The sequence of reconstruction time nodes includes at least two time nodes that are within the total reconstruction time.

[0016] The parameter module is used to determine the dynamic channel parameters of the satellite object at each time point based on the reconstructed time point sequence;

[0017] The determination module is used to dynamically determine the candidate probe area of ​​the satellite object at each time node based on the dynamic channel parameters. The candidate probe area of ​​the satellite object at the later time node is determined based on the candidate probe area of ​​the satellite object at the previous time node.

[0018] The reconstruction module is used to perform multi-satellite dynamic channel reconstruction within the total reconstruction time based on the candidate probe areas of the satellite object at each time node.

[0019] In one possible implementation, the determining module is specifically used to: obtain the candidate probe area of ​​the satellite object at the first time node; and recursively evolve the candidate probe areas corresponding to the remaining time nodes according to the dynamic channel parameters and the candidate probe areas of the time nodes to obtain the candidate probe areas of the satellite object at each remaining time node.

[0020] In one possible implementation, when the determining module acquires the candidate probe area for a satellite object at the first time node, it specifically performs the following steps: for the first time node in the time node sequence, acquires the channel parameters and feasible probe number range for each cluster of each satellite object; based on the channel parameters, feasible probe number range, and preset reconstruction criteria, obtains the reconstruction error data for each cluster of each satellite object under different feasible probe numbers; based on the reconstruction error data for each cluster of each satellite object, cluster power weight, and maximum number of activatable probes, obtains the preferred probe allocation set for each satellite object; based on the preferred probe allocation set, determines the spatial distribution boundary of the activated probes for the satellite object, and obtains the candidate probe area for the satellite object at the first time node based on the spatial distribution boundary.

[0021] In one possible implementation, when the determining module determines the spatial distribution boundary of the probes enabled by the satellite object according to the preferred probe allocation set, and obtains the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary, it is specifically used to: merge the preferred probe allocation sets of all satellite objects into a unified target probe set according to the preferred probe allocation set; determine the spatial distribution boundary corresponding to the target probe set, and obtain the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

[0022] In one possible implementation, when the determining module recursively evolves the candidate probe regions corresponding to the remaining time nodes according to the dynamic channel parameters and the candidate probe regions of the time nodes to obtain the candidate probe regions corresponding to the satellite object at each remaining time node, it is specifically used to: obtain the probe selection result corresponding to the previous time node and the dynamic channel parameters corresponding to the current time node; and determine the candidate probe region corresponding to the current time node according to the dynamic channel parameters.

[0023] In one possible implementation, when the determining module determines the candidate probe area corresponding to the current time node based on the dynamic channel parameters, it is specifically used to: determine whether there is a cluster birth or death at the current time according to the cluster birth and death judgment rule; if there is no cluster birth or death, correct the candidate probe area according to the current channel parameters; if there is a cluster birth or death, recalculate the candidate probe area according to the initial time logic.

[0024] In one possible implementation, the determining module is further configured to: obtain the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment; verify the reconstruction accuracy of the current probe selection scheme based on the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment; and if the reconstruction accuracy does not meet the threshold, re-traverse the probe number fluctuation variables to determine a better probe number allocation scheme.

[0025] In one possible implementation, the reconstruction module is specifically used to: obtain power weight constraints; assign power weights to probes within the candidate probe area according to the weight constraints and reconstruction criteria; and allocate signals to probes based on the power weights to complete channel reconstruction at the current time node.

[0026] Thirdly, embodiments of this application provide a multi-satellite dynamic channel reconfiguration system, comprising:

[0027] The first switch array is used to combine the signal sources of multiple multi-satellite objects into a multi-stream signal, and dynamically determine the candidate probe area of ​​the satellite object at each time node according to the dynamic channel parameters of the satellite object. The candidate probe area of ​​the satellite object at the next time node is determined based on the candidate probe area of ​​the satellite object at the previous time node.

[0028] The second switch array is used to dynamically distribute multi-stream signals to probes in the adjusted candidate probe area at each time node in order to perform multi-satellite dynamic channel reconstruction within the total reconstruction time.

[0029] Fourthly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0030] The memory stores instructions that the computer executes;

[0031] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0032] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0033] In a sixth aspect, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0034] The multi-satellite dynamic channel reconstruction method, apparatus, system, device, and storage medium provided in this application embodiment obtain a reconstruction time node sequence corresponding to the total reconstruction time. This sequence includes at least two time nodes within the total reconstruction time. Based on the reconstruction time node sequence, dynamic channel parameters for multiple satellite objects at each time node are determined. Based on the dynamic channel parameters, candidate probe regions for each satellite object at each time node are dynamically determined, where the candidate probe region for a satellite object at a later time node is determined based on the candidate probe region for the satellite object at a previous time node. Multi-satellite dynamic channel reconstruction is then performed within the total reconstruction time based on the candidate probe regions for each satellite object at each time node. By constructing a reconstruction time node sequence containing multiple time nodes corresponding to the total reconstruction time, dynamic channel parameters for each satellite object at each time node are obtained based on the distribution of this time node sequence. Then, candidate probe regions for each satellite object at each time node are dynamically determined based on the dynamic channel parameters. Finally, multi-satellite dynamic channel reconstruction is performed based on the dynamically adjusted candidate probe regions. This avoids the problems of high computational load and poor real-time performance caused by full screening of all probes, thus improving the real-time performance and accuracy of multi-satellite dynamic channel reconstruction. Attached Figure Description

[0035] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0036] Figure 1 A schematic diagram illustrating a multi-satellite dynamic channel reconfiguration scenario provided in this application;

[0037] Figure 2 A flowchart illustrating the multi-satellite dynamic channel reconfiguration method provided in this application. Figure 1 ;

[0038] Figure 3 for Figure 2 A flowchart illustrating the specific implementation of step S103 in the illustrated embodiment;

[0039] Figure 4 for Figure 3 A flowchart illustrating the specific implementation of step S1031 in the illustrated embodiment;

[0040] Figure 5 A schematic diagram of a multi-satellite dynamic channel reconfiguration system provided in an embodiment of this disclosure;

[0041] Figure 6 A schematic diagram of the multi-satellite dynamic channel reconfiguration device provided in this application;

[0042] Figure 7 A schematic diagram of the structure of the electronic device provided in this application.

[0043] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0044] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0045] First, let me explain the terms used in this application:

[0046] Multi-Probe Anechoic Chamber (MPAC) Method: The multi-probe anechoic chamber method is a test method used to obtain the real communication performance of wireless devices in an outdoor transmission environment. It can accurately simulate the wave characteristics of the target channel by spatial angle without disassembling the device, and complete the over-the-air (OTA) performance test of the entire device's beam and communication capabilities. It has the characteristics of efficient and accurate verification of the device's radiation / reception performance.

[0047] Figure 1 This is a schematic diagram illustrating a multi-satellite dynamic channel reconfiguration scenario provided by this application. The specific application scenario of this application is a multi-satellite communication performance testing scenario for satellite communication equipment. For example, as shown... Figure 1 As shown, firstly, multiple satellite signal simulators are configured to simulate satellite signals, which are then sent to probes connected to the satellite signal simulators via a controller. The probes then transmit the simulated satellite signals in a closed anechoic chamber. Simultaneously, the device under test (DUT) located in the anechoic chamber receives the simulated satellite signals. Based on the data from the simulated satellite signals received by the DUT, the multi-satellite communication performance of the DUT is tested.

[0048] Based on the above scenarios, it is clear that in existing technologies, to accurately reproduce the arrival angle of a real channel, a large number of probes are typically configured in a multi-probe anechoic chamber structure. However, due to the limited resources of the channel simulator, only a few can be selected, i.e., probe selection, which involves activating them and assigning them certain power weights, i.e., probe weighting, to complete channel reconstruction. To select the most suitable probe from all available probes, existing solutions employ computationally intensive processing algorithms, such as the greedy multi-shot algorithm, heuristic algorithms, and machine learning methods. For dynamic channel reconstruction applications, a slicing method is typically used, discretizing the target dynamic channel into multiple moments within the reconstruction time, and reconstructing these moments one by one, thereby achieving OTA performance testing in dynamic environments.

[0049] However, due to the high complexity of the probe selection algorithm, dynamic channel reconstruction currently faces two major problems: high computational complexity and the inability to achieve continuous changes in the reconstructed channel angle and power, which makes it impossible to simultaneously achieve test accuracy and real-time performance.

[0050] The multi-satellite dynamic channel reconstruction method provided in this application constructs a reconstruction time node sequence containing multiple time nodes corresponding to the total reconstruction time. Based on the distribution of this time node sequence, the dynamic channel parameters of each satellite object at each time node are obtained. Then, the candidate probe regions of the satellite object at each time node are dynamically determined based on the dynamic channel parameters. Subsequently, multi-satellite dynamic channel reconstruction is performed based on the dynamically adjusted candidate probe regions. This solves the problem of large computational load and poor real-time performance in the reconstruction process caused by full screening of all probes.

[0051] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0052] Figure 2 A flowchart illustrating the multi-satellite dynamic channel reconfiguration method provided in this application. Figure 1 The method of this embodiment can be applied to electronic devices. In one possible implementation, the terminal device can execute program code deployed locally and / or externally to implement the multi-satellite dynamic channel reconfiguration method provided in this embodiment. In another possible implementation, the electronic device can access external devices and call corresponding functional services to implement the multi-satellite dynamic channel reconfiguration method provided in this embodiment, such as... Figure 2 As shown, exemplarily, the multi-satellite dynamic channel reconstruction method provided in this embodiment includes:

[0053] Step S101: Obtain the reconstruction time node sequence corresponding to the total reconstruction time. The reconstruction time node sequence includes at least two time nodes within the total reconstruction time.

[0054] Step S102: Determine the dynamic channel parameters of multiple satellite objects at each time node based on the reconstructed time node sequence.

[0055] Step S103: Based on the dynamic channel parameters, dynamically determine the candidate probe area of ​​the satellite object at each time node. The candidate probe area of ​​the satellite object at the next time node is determined based on the candidate probe area of ​​the satellite object at the previous time node.

[0056] Step S104: Based on the candidate probe areas of the satellite object at each time node, perform multi-satellite dynamic channel reconstruction within the total reconstruction time.

[0057] For example, refer to Figure 1 The illustrated application scenario diagram shows an electronic device that performs the method provided in this embodiment, for example, a... Figure 1 The controller shown first acquires a preset total reconstruction time T and divides it into multiple time slices (equal or unequal intervals), each time slice corresponding to a time node. These time nodes are then arranged in order to obtain a target dynamic channel reconstruction time node sequence. Next, the number of information sources for the satellite object to be reconstructed is determined. The satellite object refers to the satellite signal simulator used to simulate satellite signals, and the number of information sources is, for example, S. Then, based on the multi-probe anechoic chamber configuration and channel simulator capabilities, the total number of probes M on the probe wall and the probe spacing d are determined. probe And the maximum number of activatable probes K, and based on the reconstruction time node sequence, the dynamic channel parameters are extracted according to the reconstruction criteria, and the dynamic channel parameters of the s-th satellite at time t are obtained as {Ψ s,t}, where s={1,2,…,S}, t={1,2,…,T}. n refers to the nth cluster of satellites.

[0058] Furthermore, in one possible implementation, the dynamic channel parameters include the number of clusters N. s,t Cluster power P s,n,t The horizontal angle reached (AoA) s,n,t Elevation Angle of Arrival (EoA) s,n,t Azimuth Angular Spread of Arrival (ASA) s,n,tElevation Angular Spread of Arrival (ESA) s.n.t wait.

[0059] Furthermore, after obtaining the dynamic channel parameters, the candidate probe regions for the satellite object at each time node are dynamically determined based on these parameters. That is, at each time node, the candidate probe regions are calculated based on the current dynamic channel parameters of each satellite object. This process can be achieved by first calculating an initial candidate probe region, and then, based on this initial region, calculating a contour offset to obtain the candidate probe region for the next time node, thus realizing dynamic adjustment of the candidate probe regions. Specifically, as shown... Figure 3 As shown, the specific implementation of step S103 includes:

[0060] Step S1031: Obtain the candidate probe area of ​​the satellite object at the first time node;

[0061] Step S1032: Based on the dynamic channel parameters and the candidate probe regions at each time node, the candidate probe regions corresponding to the remaining time nodes are recursively evolved to obtain the candidate probe regions corresponding to the satellite object at each remaining time node.

[0062] For example, firstly, the candidate probe regions of the satellite object at the first time node are obtained. In one possible implementation, a multi-shot algorithm using a greedy algorithm for the candidate probe regions at the first time node is used for calculation. Then, based on the same algorithm, the candidate probe regions corresponding to the remaining time nodes are recursively evolved to obtain the candidate probe regions of the satellite object at each remaining time node. In another possible implementation, such as... Figure 4 As shown, the specific implementation of step S1031 includes:

[0063] Step S1031-1: For the first time node in the time node sequence, obtain the channel parameters and feasible probe number range for each cluster of each satellite object.

[0064] Step S1031-2: Based on the channel parameters, the range of feasible probe numbers, and the preset reconstruction criteria, obtain the reconstruction error data of each cluster of each satellite object under different feasible probe numbers.

[0065] Step S1031-3: Based on the reconstruction error data of each cluster of each satellite object, the cluster power weight, and the maximum number of activatable probes, obtain the preferred probe allocation set for each satellite object;

[0066] Step S1031-4: Based on the preferred probe allocation set, determine the spatial distribution boundary of the probes enabled by the satellite object, and obtain the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

[0067] In one possible implementation, step S1031-4 is specifically implemented by: merging the preferred probe allocation sets of all satellite objects into a unified target probe set according to the preferred probe allocation set; determining the spatial distribution boundary corresponding to the target probe set; and obtaining the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

[0068] Furthermore, in one possible implementation, step S104 specifically includes:

[0069] Step S1041: Obtain the power weight constraints;

[0070] Step S1042: Assign power weights to the probes in the candidate probe area according to the weight constraints and reconstruction criteria;

[0071] Step S1043: Distribute the signal to the probe based on power weight to complete the channel reconstruction at the current time node.

[0072] For example, the channel reconstruction for the first time point can be completed through the above steps.

[0073] The following section provides a detailed explanation of the process for determining the candidate probe area and the channel reconstruction process at the first time point:

[0074] For example, firstly, the candidate probe regions for each satellite object at the first time node are obtained, i.e., as the initial case, for all times t={1,2,…,T}, the nth cluster of the s-th satellite is selected (AoA s,n,t EoA s,n,t As the center of the candidate probe area, according to ASA s,n,t The ESAs.nt parameter determines the candidate probe area range D for each satellite signal source. s,n,t Specifically, the candidate probe area range D, encompassing both horizontal and vertical ranges. s,n,t The calculation methods for the horizontal and vertical ranges are shown in equations (1) and (2):

[0075] (1)

[0076] (2)

[0077] Where a1, a2, b1, and b2 are scaling factors, which are applied to different probe spacings d. probe It can have different values. dfluc As a floating factor, the range of the candidate probe area is appropriately expanded according to different target solution accuracies, and its actual value is related to d. probe related.

[0078] The above D s,n,t The index of the probe within the candidate probe area can be further determined based on the probe spacing of the anechoic chamber used, which will facilitate algorithm implementation. After the above calculations, the set of coordinates within the candidate probe area can be determined as shown in equation (3):

[0079] (3)

[0080] Furthermore, D can be determined based on the distribution that PAS follows. s,n,t The outline shape. In one possible implementation, when generating PAS using the Cluster Delay Line (CDL) in a standardized channel model such as 3GPP TR 38.901, the projection of this region in the vertical direction should be rectangular or elongated.

[0081] Furthermore, the intersection of the nth and n'th sets is shown in equation (4):

[0082] (4)

[0083] The above-mentioned method for merging the target probe set involves determining the candidate probe region based on the spatial distribution boundary corresponding to the target probe set. Specifically, for D... s,n,t ∩D s,n’,t ≠ The two sets are merged into D. s,n,t ∪D s,n’,t Probe selection is performed. Further, D is calculated. s,t ∩D s’,t , s={1,2,…,S}, s'≠s. For D s,t ∩D s’,t ≠ The probe sets of the two satellites are merged into D. s,t ∪D s’,t When selecting probes as a signal source, it's important to note that despite signal source merging, different satellite signal simulators are still required for testing due to varying network connections. Furthermore, it's necessary to determine the required number of probes for each satellite signal source and ensure the number of active probes does not exceed a preset value.

[0084] Among them, the reconstruction criteria include the spatial correlation criterion of the PFS method. Taking the spatial correlation criterion of the PFS method as an example, firstly, the spatial correlation of the target space is calculated according to the following formula (5):

[0085] (5)

[0086] Where j represents the imaginary part, z represents the wavenumber, z = 2π / λ, and λ is the signal wavelength; r u and r v Let u and v be the position vectors of the virtual sampling antenna. For space angle Let P(·) be a unit vector, and let P(·) be the power angular spectrum (PAS), satisfying... .

[0087] Furthermore, the reconstructed spatial correlation can be expressed as shown in equation (6):

[0088] (6)

[0089] Among them, w k,t Let w be the power weight of the k-th probe at time t. k,t A value ≠ 0 indicates that the probe is activated. Φ k Let be the unit vector of the spatial angle of the k-th probe.

[0090] For each time step, the probe weight vector of the s-th signal source The optimization problem can be expressed as shown in equations (7) and (8):

[0091] (7)

[0092] (8)

[0093] For an initial time t1, for each cluster of each satellite signal source across all feasible probes... In the case of reconstruction error, the reconstruction error is calculated according to the selected reconstruction criterion, i.e., in equation (7). .

[0094] Based on the calculated error results, select The probe allocation set with the minimum reconstruction error is determined under the following conditions. Since the angular difference between the two satellites is usually significant, and signal source merging was performed in the aforementioned steps, the following conditions are met. .

[0095] Furthermore, after completing the calculation of the candidate probe region for the first time node, probe evolution is performed for the remaining reconstruction time. Specifically, the specific implementation of step S1032 includes:

[0096] Step S1032-1: Obtain the probe selection result corresponding to the previous time node and the dynamic channel parameters corresponding to the current time node;

[0097] Step S1032-2: Determine the candidate probe area corresponding to the current time node based on the dynamic channel parameters.

[0098] For example, in determining the candidate probe area corresponding to the current time node, the candidate probe area is determined based on the existence of cluster birth and death, thereby obtaining a more accurate candidate probe area. Specifically, the specific implementation of step S1032-2 includes: judging whether there is cluster birth and death at the current time according to the cluster birth and death judgment rule; if there is no cluster birth and death, the candidate probe area is corrected according to the current channel parameters; if there is cluster birth and death, the candidate probe area is recalculated according to the initial time logic.

[0099] Furthermore, in one possible implementation, this embodiment also includes the step of:

[0100] Step S1033: Obtain the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment;

[0101] Step S1034: Based on the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment, verify the reconstruction accuracy of the current probe selection scheme;

[0102] Step S1035: If the reconstruction accuracy does not meet the threshold, re-traverse the probe number fluctuation variable to determine a better probe number allocation scheme.

[0103] For example, the following describes the process of recursively evolving the candidate probe regions corresponding to the remaining time nodes. First, in D... s,n,t Probe selection is performed under the inherently selected channel reconstruction criterion to obtain... ,according to The probe distribution was used to determine the edge region as the updated D. s,n,t The shape of this region is related to the distribution that PAS follows.

[0104] Next, it is determined whether cluster birth or death has occurred. If no cluster birth or death has occurred, the range of the candidate probes is corrected according to AoA, EoA, ASA, and ESA. The specific implementation method is shown in formula (9) and formula (10):

[0105] (9)

[0106] (10)

[0107] in, , The scaling factor is determined by the angular deviation from the probe position and is also affected by the probe spacing d. probe The impact. This is the evolution correction factor, determined by the solution accuracy.

[0108] When clusters are generated or destroyed, the distribution range of candidate probes is calculated using the initial time point (considered as the initial time node). The root mean square (RMS) reconstruction accuracy is verified during probe selection, and its definition is shown in equation (11).

[0109] (11)

[0110] Where Q represents the number of sampling pairs. When the reconstruction accuracy does not meet the set threshold ε0, the probe number allocation and calculation need to be re-performed. The probe number allocation and calculation can be performed based on the aforementioned initial time (initial time node), or it can be done by setting a floating variable N for the probe number. fluc Thus, for K s,t {K s,t-1 -K fluc ,K s,t-1 -K fluc +1,…,K s,t-1 +K fluc The process involves iterating through the data to determine a better allocation scheme for the number of probes.

[0111] After the above steps, a multi-satellite dynamic reconstruction channel that meets the accuracy requirements can be obtained, namely, the multi-satellite dynamic reconstruction channel of the target dynamic channel.

[0112] In this embodiment, a reconstruction time node sequence corresponding to the total reconstruction time is obtained. This sequence includes at least two time nodes within the total reconstruction time. Based on the reconstruction time node sequence, dynamic channel parameters for multiple satellite objects at each time node are determined. Based on these dynamic channel parameters, candidate probe regions for each satellite object at each time node are dynamically determined. The candidate probe region for a satellite object at a later time node is determined based on the candidate probe region for the satellite object at the previous time node. Multi-satellite dynamic channel reconstruction is then performed based on the candidate probe regions for each satellite object at each time node within the total reconstruction time. By constructing a reconstruction time node sequence containing multiple time nodes corresponding to the total reconstruction time, dynamic channel parameters for each satellite object at each time node are obtained based on this sequence. Then, candidate probe regions for each satellite object at each time node are dynamically determined based on these dynamic channel parameters. Finally, multi-satellite dynamic channel reconstruction is performed based on the dynamically adjusted candidate probe regions. This avoids the problems of high computational load and poor real-time performance caused by full screening of all probes, thus improving the real-time performance and accuracy of multi-satellite dynamic channel reconstruction.

[0113] The following is another embodiment of the multi-satellite dynamic channel reconfiguration method provided in this application. The method flow includes:

[0114] 1. Slice the total reconstruction time T into slices, including uniform slicing and non-uniform slicing strategies, to obtain each time slice {1,2,…,T}.

[0115] 2. Determine the dynamic channel parameters for each satellite during the total reconfiguration time, including the number of clusters N. s,t Cluster power P s,n,t The horizontal angle reached (AoA) s,n,t Elevation Angle of Arrival (EoA) s,n,t Azimuth Angular Spread of Arrival (ASA) s,n,t Elevation Angular Spread of Arrival (ESA) s.n.t wait.

[0116] 3. For the initial time t1, for each cluster of each satellite signal source, across all feasible probes... Under the given circumstances, the reconstruction error is calculated based on the selected reconstruction criteria.

[0117] 4. Perform power weighting on the multiple clusters of channels, and then select the appropriate cluster based on the calculated error results. The probe allocation set with the minimum reconstruction error is determined under the following conditions. Note that since the angular difference between the two satellites is usually significant, They are easily satisfied.

[0118] 5. Regarding The multiple signal sources are processed based on the signal source merging method described in the previous embodiments.

[0119] 6. Based on the probe selection results in step 5 Define the enabled probe boundaries for each satellite signal source.

[0120] 7. Perform probe evolution at each {t2,…,T} time point.

[0121] 8. Based on the previous time step, select the candidate probe area range. When there is no cluster birth or death, correct the candidate probe range according to AoA, EoA, ASA, and ESA. When there is cluster birth or death, use it as the initial time step to calculate the candidate probe distribution range.

[0122] 9. Set a threshold ε0 and verify the RMS reconstruction accuracy of the reconstructed channel. If the reconstruction accuracy does not meet the set threshold ε0, the probe number allocation and calculation need to be re-performed. The probe number allocation and calculation can be performed based on the calculation at the first moment mentioned above, or by setting a floating variable N for the probe number. fluc Thus, for K s,t {K s,t-1 -K fluc ,K s,t-1 -K fluc +1,…,K s,t-1 +K fluc The process involves iterating through the data to determine a better allocation scheme for the number of probes.

[0123] 10. Based on the selected reconstruction criteria, perform probe weighting to complete multi-satellite channel reconstruction.

[0124] Figure 5 This is a schematic diagram of a multi-satellite dynamic channel reconfiguration system provided in an embodiment of this disclosure, as shown below. Figure 5 As shown, it includes a first switch array, which is used to merge the signal sources of multiple multi-satellite objects into a multi-stream signal, and dynamically determine the candidate probe area of ​​the satellite object at each time node according to the dynamic channel parameters of the satellite object. The candidate probe area of ​​the satellite object at the later time node is determined based on the candidate probe area of ​​the satellite object at the previous time node.

[0125] The second switch array is used to dynamically distribute multi-stream signals to probes within the adjusted candidate probe area at each time node in order to perform multi-satellite dynamic channel reconstruction within the total reconstruction time.

[0126] Further, optionally, the multi-satellite dynamic channel reconstruction system also includes a channel simulator, which is connected to the first and second switch arrays respectively. The multi-satellite dynamic channel reconstruction system corresponds to the controller in the embodiment shown in the figure. The first switch array is also connected to satellite signal simulators p1, p2, ..., pn; the second switch array is connected to a probe in the anechoic chamber for performing air interface performance testing on the device under test.

[0127] The first switch array enables the merging of multiple satellite signal sources, facilitating probe selection. It sends the merged multi-satellite signal sources as a multi-stream signal to a channel simulator, generating signals that have undergone channel fading. The first switch array allocates and maps the number of available probes based on the channel characteristics experienced by each target source's transmitted signal. It narrows down and confirms the probe selection interval based on the target channel characteristics. Specifically, based on the probe selection results from the previous moment, the switch array allocates the probe selection interval for the next moment according to the target channel characteristics. The first switch array inputs the probe selection results to a second switch array, which then distributes the signal to the activated probes. With the support of these functions, the first switch array enables rapid probe selection for multiple signal sources in dynamic channel environments.

[0128] Furthermore, based on the aforementioned multi-satellite dynamic channel reconstruction system, this embodiment provides a multi-satellite dynamic channel reconstruction method, including:

[0129] Determine the number of satellite information sources that need to be reconstructed. At the same time, the total number of probes on the probe wall is determined based on the MPAC configuration and channel simulator capabilities used. probe spacing and the maximum number of activatable probes .

[0130] The reconstruction duration is determined to be The target dynamic channel is determined, and the target channel parameters are extracted according to the reconstruction criteria to obtain the first... One satellite in The target channel parameters at time are .

[0131] Reconstruction criteria include, but are not limited to, the electric field similarity criterion for the Plane Wave Synthesis (PWS) method and the spatial correlation and power angular spectrum similarity (PSP) criteria for the Pre-Faded Signal Synthesis (PFS) method.

[0132] Target channel parameters Including the number of clusters Cluster power Horizontal angle pitch angle Horizontal reach angle expansion and pitch reach angle expansion wait.

[0133] As an initial case, for all times No. The first satellite Selected clusters As the center of the candidate probe area, according to and Determine the candidate probe area range for each satellite signal source. As for the horizontal and vertical ranges, we have:

[0134]

[0135]

[0136] in , , and The scaling factor is used for different... It can have different values. As a floating factor, the range of the candidate probe area is appropriately expanded according to different target solution accuracies, and its actual value is related to... related.

[0137] The above The index of the probes within the candidate probe area can be further determined based on the probe spacing of the anechoic chamber used, which will facilitate the algorithm implementation.

[0138] The above calculations can determine the set of coordinates within the area of ​​the candidate probes:

[0139]

[0140] Furthermore, the above can be determined based on the distribution that PAS follows. The outline shape. As an example, when generating PAS using the Cluster Delay Line (CDL) in the standardized channel model such as 3GPP TR 38.901, the projection of this region in the vertical direction should be rectangular or elongated.

[0141] Further calculations:

[0142]

[0143] for The two sets are merged into Probe selection processing is performed.

[0144] Further calculation ,for The probe sets of the two satellites were merged into one. The probe is selected and processed as a single signal source. It should be noted that despite signal source merging, in actual testing, different satellite signal simulators still need to be connected due to the different networks accessed.

[0145] Furthermore, it is necessary to determine the number of probes required for each satellite signal source and maintain the number of active probes within a preset value.

[0146] As an example, the spatial correlation criterion using the PFS method is illustrated below:

[0147] Calculate the target space correlation:

[0148]

[0149] Where j represents the imaginary part, z is the wavenumber, z = 2π / λ, and λ is the signal wavelength. and For virtual sampling antenna pairs and The position vector, For space angle unit vector, The power angular spectrum (PAS) satisfies... .

[0150] The reconstructed spatial correlation can be expressed as:

[0151]

[0152] in, for Time of the first The power weight of each probe, when This indicates that the probe is not activated. For the first A unit vector of spatial angles of each probe.

[0153] For each moment, the first Probe weight vector of each signal source The optimization problem can be written as:

[0154]

[0155]

[0156] For the initial time For each cluster of each satellite signal source, across all feasible probes Under the given circumstances, the reconstruction error is calculated based on the selected reconstruction criterion. That is, the calculation... .

[0157] Based on the calculated error results, select The probe allocation set with the minimum reconstruction error is determined under the following conditions. Since the angular difference between the two satellites is usually significant, and signal source merging was performed in the aforementioned steps, the following conditions are met. .

[0158] Furthermore, regarding the remaining reconstruction time Probe evolution is carried out.

[0159] First of all, Probe selection is performed under the inherently selected channel reconstruction criterion to obtain... ,according to The probe distribution was used to determine its edge region as the updated [data / data]. The shape of this region is related to the distribution that PAS follows.

[0160] Next, it is determined whether cluster birth and death have occurred. If no cluster birth and death have occurred, the candidate probe range is corrected based on AoA, EoA, ASA, and ESA, as follows:

[0161]

[0162]

[0163] in, , The scaling factor is determined by the angular deviation from the probe position and is also affected by the probe spacing. The impact. This is the evolution correction factor, determined by the solution accuracy.

[0164] When clusters are generated or destroyed, the distribution range of candidate probes is calculated using the initial time as the time point.

[0165] When selecting a probe, the root mean square (RMS) reconstruction accuracy is verified, defined as:

[0166]

[0167] in This refers to the number of sample pairs. When the reconstruction accuracy does not meet the set threshold... If necessary, the number of probes needs to be reassigned and recalculated.

[0168] The allocation and calculation of the number of probes can be performed based on the calculation at the first moment mentioned above, or by setting a floating variable for the number of probes. Thus, for K s,t {K s,t-1 -K fluc ,K s,t-1 -K fluc +1,…,K s,t-1 +K fluc The process involves iterating through the data to determine a better allocation scheme for the number of probes.

[0169] After the above steps, a multi-satellite dynamic reconfiguration channel that meets the accuracy requirements can be obtained.

[0170] It should be noted that the meanings of the symbols appearing in the formulas in the above embodiments are consistent throughout the entire specification and can be understood by referring to the content of the entire specification; those not explained are general symbols known to those skilled in the art, such as ∑, etc., and can be understood by referring to the general understanding in this technical field, and will not be elaborated here.

[0171] Figure 6 This is a schematic diagram of the multi-satellite dynamic channel reconfiguration device provided in this application, as shown below. Figure 6 As shown, the multi-satellite dynamic channel reconstruction device 30 provided in this embodiment includes:

[0172] The acquisition module 301 is used to acquire the reconstruction time node sequence corresponding to the total reconstruction time. The reconstruction time node sequence includes at least two time nodes that are within the total reconstruction time.

[0173] The parameter module 302 is used to determine the dynamic channel parameters of the satellite object at each time node based on the reconstructed time node sequence;

[0174] The determination module 303 is used to dynamically determine the candidate probe area of ​​the satellite object at each time node based on the dynamic channel parameters. The candidate probe area of ​​the satellite object at the later time node is determined based on the candidate probe area of ​​the satellite object at the previous time node.

[0175] Reconstruction module 304 is used to perform multi-satellite dynamic channel reconstruction within the total reconstruction time based on the candidate probe areas of the satellite object at each time node.

[0176] In one possible implementation, the determining module 303 is specifically used to: obtain the candidate probe area of ​​the satellite object at the first time node; and recursively evolve the candidate probe areas corresponding to the remaining time nodes according to the dynamic channel parameters and the candidate probe areas of the time nodes to obtain the candidate probe areas corresponding to the satellite object at each remaining time node.

[0177] In one possible implementation, when determining the candidate probe area of ​​a satellite object at the first time node, the determining module 303 is specifically used to: for the first time node in the time node sequence, obtain the channel parameters and feasible probe number range of each cluster of each satellite object; based on the channel parameters, feasible probe number range, and preset reconstruction criteria, obtain the reconstruction error data of each cluster of each satellite object under different feasible probe numbers; based on the reconstruction error data of each cluster of each satellite object, the cluster power weight, and the maximum number of active probes, obtain the preferred probe allocation set of each satellite object; based on the preferred probe allocation set, determine the spatial distribution boundary of the probes activated by the satellite object, and obtain the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

[0178] In one possible implementation, when determining the spatial distribution boundary of the probes used by the satellite object according to the preferred probe allocation set, and obtaining the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary, the determining module 303 is specifically used to: merge the preferred probe allocation sets of all satellite objects into a unified target probe set according to the preferred probe allocation set; determine the spatial distribution boundary corresponding to the target probe set, and obtain the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

[0179] In one possible implementation, when the determining module 303 recursively evolves the candidate probe regions corresponding to the remaining time nodes according to the dynamic channel parameters and the candidate probe regions of the time nodes to obtain the candidate probe regions of the satellite object at each remaining time node, it is specifically used to: obtain the probe selection result corresponding to the previous time node and the dynamic channel parameters corresponding to the current time node; and determine the candidate probe region corresponding to the current time node according to the dynamic channel parameters.

[0180] In one possible implementation, when determining the candidate probe area corresponding to the current time node based on the dynamic channel parameters, the determining module 303 is specifically used to: determine whether there is a cluster birth or death at the current time according to the cluster birth and death judgment rule; if there is no cluster birth or death, correct the candidate probe area according to the current channel parameters; if there is a cluster birth or death, recalculate the candidate probe area according to the initial time logic.

[0181] In one possible implementation, the determining module 303 is further configured to: obtain the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment; verify the reconstruction accuracy of the current probe selection scheme based on the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment; if the reconstruction accuracy does not meet the threshold, re-traverse the probe number fluctuation variables to determine a better probe number allocation scheme.

[0182] In one possible implementation, the reconstruction module 304 is specifically used to: obtain power weight constraints; assign power weights to probes in the candidate probe area according to the weight constraints and reconstruction criteria; and allocate signals to probes based on the power weights to complete the channel reconstruction at the current time node.

[0183] The multi-satellite dynamic channel reconstruction device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0184] Figure 7 A schematic diagram of the structure of the electronic device provided in this application. Figure 7 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0185] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0186] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0187] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0188] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0189] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0190] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0191] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0192] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0193] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0194] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0195] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0196] In addition, the functional units in the various embodiments of the present invention 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.

[0197] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0198] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0199] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A multi-satellite dynamic channel reconfiguration method, characterized in that, include: Obtain the sequence of reconstruction time nodes corresponding to the total reconstruction time, wherein the sequence of reconstruction time nodes includes at least two time nodes located within the total reconstruction time. Based on the reconstructed time node sequence, the dynamic channel parameters of multiple satellite objects at each of the time nodes are determined; Based on the dynamic channel parameters, the candidate probe regions for the satellite object at each time node are dynamically determined. The candidate probe regions are candidate probe regions with spatial distribution boundaries. The candidate probe region for the satellite object at a later time node is determined based on the candidate probe region for the satellite object at the previous time node. Furthermore, in the process of determining the candidate probe region corresponding to the current time node, the cluster birth and death judgment rule is used to determine whether there is a cluster birth or death at the current moment. If there is no cluster birth or death, the candidate probe region is corrected according to the current channel parameters. If clusters emerge or disappear, the candidate probe area is recalculated according to the logic at the initial time. Based on the candidate probe regions of the satellite object at each of the aforementioned time points, multi-satellite dynamic channel reconstruction is performed within the total reconstruction time.

2. The method according to claim 1, characterized in that, The step of dynamically determining the candidate probe area of ​​the satellite object at each of the aforementioned time nodes based on the dynamic channel parameters includes: Obtain the candidate probe area of ​​the satellite object at the first time node; Based on the dynamic channel parameters and the candidate probe regions at the time nodes, the candidate probe regions corresponding to the remaining time nodes are recursively evolved to obtain the candidate probe regions corresponding to the satellite object at each remaining time node.

3. The method according to claim 2, characterized in that, The acquisition of the candidate probe area for the satellite object at the first time point includes: For the first time node in the time node sequence, obtain the channel parameters and feasible probe number range for each cluster of the satellite objects; Based on the channel parameters, the range of feasible probe numbers, and the preset reconstruction criteria, the reconstruction error data of each cluster of each satellite object under different feasible probe numbers are obtained; Based on the reconstruction error data of each cluster of each satellite object, the cluster power weight, and the maximum number of activatable probes, the preferred probe allocation set for each satellite object is obtained; Based on the preferred probe allocation set, the spatial distribution boundary of the probes enabled by the satellite object is determined, and the candidate probe area of ​​the satellite object at the first time node is obtained based on the spatial distribution boundary.

4. The method according to claim 3, characterized in that, The step of determining the spatial distribution boundary of the activated probes for the satellite object based on the preferred probe allocation set, and obtaining the candidate probe area for the satellite object at the first time node based on the spatial distribution boundary, includes: The preferred probe allocation sets of all satellite objects are merged into a unified target probe set according to the preferred probe allocation set. Determine the spatial distribution boundary corresponding to the target probe set, and obtain the candidate probe area of ​​the satellite object at the first time node based on the spatial distribution boundary.

5. The method according to claim 2, characterized in that, The step of recursively evolving the candidate probe regions corresponding to the remaining time nodes based on the dynamic channel parameters and the candidate probe regions at the time nodes to obtain the candidate probe regions for the satellite object at each remaining time node includes: Obtain the probe selection result corresponding to the previous time node and the dynamic channel parameters corresponding to the current time node; Based on the dynamic channel parameters, the candidate probe area corresponding to the current time node is determined.

6. The method according to claim 5, characterized in that, Also includes: Obtain the current candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range; Based on the candidate probe area, reconstruction accuracy threshold, and probe number fluctuation range at the current moment, verify the reconstruction accuracy of the current probe selection scheme; If the reconstruction accuracy does not meet the threshold, the probe number fluctuation variable is re-traversed to determine a better probe number allocation scheme.

7. The method according to claim 1, characterized in that, The step of performing multi-satellite dynamic channel reconstruction within the total reconstruction time based on the candidate probe regions of the satellite object at each of the aforementioned time nodes includes: Obtain the power weight constraints; Assign power weights to the probes within the candidate probe region according to the weight constraints and reconstruction criteria; The signal is allocated to the probe based on the power weight, and the channel reconstruction at the current time node is completed.

8. A multi-satellite dynamic channel reconfiguration device, characterized in that, include: The acquisition module is used to acquire the sequence of reconstruction time nodes corresponding to the total reconstruction time, wherein the sequence of reconstruction time nodes includes at least two time nodes located within the total reconstruction time. The parameter module is used to determine the dynamic channel parameters of the satellite object at each of the reconstructed time nodes based on the reconstructed time node sequence. The determination module is used to dynamically determine the candidate probe regions of the satellite object at each time node based on the dynamic channel parameters. The candidate probe regions are candidate probe regions with spatial distribution boundaries. The candidate probe regions of the satellite object at a later time node are determined based on the candidate probe regions of the satellite object at the previous time node. Furthermore, in the process of determining the candidate probe regions corresponding to the current time node, the module determines whether cluster birth or death occurs at the current time according to the cluster birth and death judgment rules. If no cluster birth or death occurs, the candidate probe regions are corrected according to the current channel parameters; if cluster birth or death occurs, the candidate probe regions are recalculated according to the initial time logic. The reconstruction module is used to perform multi-satellite dynamic channel reconstruction within the total reconstruction time based on the candidate probe areas of the satellite object at each of the time nodes.

9. A multi-satellite dynamic channel reconfiguration system, characterized in that, include: The first switch array is used to merge the signal sources of multiple multi-satellite objects into a multi-stream signal, and dynamically determine the candidate probe regions of the satellite objects at each time node according to the dynamic channel parameters of the satellite objects. The candidate probe regions are candidate probe regions with spatial distribution boundaries. The candidate probe region of the satellite object at a later time node is determined based on the candidate probe region of the satellite object at the previous time node. In the process of determining the candidate probe region corresponding to the current time node, the cluster birth and death judgment rule is used to determine whether there is a cluster birth and death at the current time. If there is no cluster birth and death, the candidate probe region is corrected according to the current channel parameters. If there is a cluster birth and death, the candidate probe region is recalculated according to the initial time logic. The second switch array is used to dynamically allocate the multi-stream signal to the probes in the adjusted candidate probe area at each time node in order to perform multi-satellite dynamic channel reconstruction within the total reconstruction time.

10. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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