Cluster control method and device for unmanned aerial vehicle networking, electronic equipment and storage medium

Abstract

The application provides a clustering control method and device for unmanned aerial vehicle networking, electronic equipment and storage medium, the method comprising: determining the position information of each unmanned aerial vehicle in the unmanned aerial vehicle networking at the next moment respectively; determining the first unstable communication link at the next moment from the multiple communication links corresponding to the clustering state of the unmanned aerial vehicle networking at the current moment based on the position information of each unmanned aerial vehicle at the next moment; determining the link instability rate at the next moment based on the number of the first unstable communication link at the next moment, the number of the second unstable communication link at the current moment and the total number of the communication links of the unmanned aerial vehicle networking at the current moment; performing clustering control on the unmanned aerial vehicle networking based on the link instability rate at the next moment, the link instability coefficient at the current moment and the position information of each unmanned aerial vehicle at the next moment, and determining the clustering state at the next moment. The application can improve the stability of the unmanned aerial vehicle networking and guarantee the communication quality between the unmanned aerial vehicles in various application scenarios.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle networking, and particularly relates to a clustering control method and device for unmanned aerial vehicle networking, an electronic device and a storage medium. BACKGROUND

[0002] With the development of unmanned aerial vehicle performance, unmanned aerial vehicle networks play an important role in many fields such as emergency rescue, target identification, relay communication and environmental monitoring. In particular, in emergency rescue tasks, it is very important for unmanned aerial vehicles to quickly achieve high-reliability networking.

[0003] The existing technology is mainly an unmanned aerial vehicle networking method applied to a micro-dynamic scene, that is, in an unmanned aerial vehicle system, only a small number of unmanned aerial vehicles move over a large range, and the overall system maintains relative stability. The clustering control of unmanned aerial vehicle networking is based on the current position of the unmanned aerial vehicle.

[0004] However, the existing technology is not applicable to a highly dynamic scene. In a highly dynamic scene, the movement speed and position of the unmanned aerial vehicle change very quickly. The rapid change of speed and position will cause rapid changes in the topology of the unmanned aerial vehicle network. In the case of rapid changes in the topology, it is difficult to accurately control the clustering of the unmanned aerial vehicle network based on the current position of the unmanned aerial vehicle, which further leads to poor stability of the unmanned aerial vehicle network and difficulty in guaranteeing the communication quality between unmanned aerial vehicles. SUMMARY

[0005] The present application provides a clustering control method and device for unmanned aerial vehicle networking, an electronic device and a storage medium to solve the defects in the prior art that it is difficult to accurately control the clustering of the unmanned aerial vehicle network in a highly dynamic scene, which further leads to poor stability of the unmanned aerial vehicle network and difficulty in guaranteeing the communication quality between unmanned aerial vehicles. The present application can improve the stability of the unmanned aerial vehicle network and guarantee the communication quality between unmanned aerial vehicles in various application scenarios.

[0006] The present application provides a clustering control method for unmanned aerial vehicle networking, comprising:

[0007] determining the position information of each unmanned aerial vehicle in the unmanned aerial vehicle network at the next time point respectively;

[0008] determining a first unstable communication link at the next time point from a plurality of communication links corresponding to the clustering state at the current time point of the unmanned aerial vehicle network based on the position information of each unmanned aerial vehicle at the next time point, wherein the plurality of communication links corresponding to the clustering state at the current time point include communication links between cluster head unmanned aerial vehicles of each cluster and super cluster head unmanned aerial vehicles and communication links between intra-cluster unmanned aerial vehicles of each cluster and corresponding cluster head unmanned aerial vehicles;

[0009] determine a link instability rate at the next moment based on the number of first unstable communication links at the next moment, the number of second unstable communication links at the current moment, and the total number of communication links of the UAV network at the current moment, the number of second unstable communication links at the current moment being determined based on a clustering state of the UAV network at the current moment;

[0010] perform clustering control on the UAV network based on the link instability rate at the next moment, a link instability coefficient at the current moment, and the position information of each UAV at the next moment, and determine a clustering state at the next moment, the link instability coefficient being determined based on a clustering control process within a preset historical period from the current moment.

[0011] According to the UAV network clustering control method provided by the application, the first unstable communication link at the next moment is determined from a plurality of communication links corresponding to the clustering state at the current moment of the UAV network based on the position information of each UAV at the next moment.

[0012] For each communication link, the transmission distance of the communication link at the next moment is determined based on the position information of the UAV corresponding to the communication link at the next moment.

[0013] The communication link with a transmission distance greater than a preset transmission distance threshold at the next moment is determined as the first unstable communication link at the next moment.

[0014] According to the UAV network clustering control method provided by the application, the clustering control includes re-clustering control and local adjustment clustering control.

[0015] The clustering control on the UAV network based on the link instability rate at the next moment, the link instability coefficient at the current moment, and the position information of each UAV at the next moment includes:

[0016] In the case that the link instability rate at the next moment is greater than the link instability coefficient at the current moment, the re-clustering control is performed on the UAV network based on the position information of each UAV at the next moment.

[0017] In the case that the link instability rate at the next moment is less than or equal to the link instability coefficient at the current moment, the local adjustment clustering control is performed on the UAV network based on the position information of each UAV at the next moment.

[0018] According to the UAV network clustering control method provided by the application, the re-clustering control on the UAV network based on the position information of each UAV at the next moment includes:

[0019] determine a center point of a region where the UAVs are located at a next time based on position information of the UAVs at the next time, and determine a new super-cluster head UAV as a UAV closest to the center point;

[0020] based on the K-midoids algorithm, divide all the UAVs other than the new super-cluster head UAV into a plurality of new clusters, and determine a cluster head UAV corresponding to each of the new clusters.

[0021] According to the application, a clustering control method for UAV networking is provided, and the local adjustment clustering control for the UAV networking based on position information of the UAVs at a next time includes:

[0022] in a case where a communication link between the cluster head UAV and the super-cluster head UAV exists in the first unstable communication link at the next time, for each cluster, adjust the cluster head UAV in the cluster based on position information of the UAVs in the cluster at the next time;

[0023] in a case where a communication link between the cluster head UAV and the super-cluster head UAV does not exist in the first unstable communication link at the next time, for a first cluster in which a number of unstable communication links in the cluster is greater than or equal to a preset link number threshold, adjust the cluster head UAV in the first cluster based on position information of the UAVs in the first cluster at the next time; and for a second cluster in which the number of unstable communication links in the cluster is less than the preset link number threshold, adjust the communication link in the second cluster based on position information of the UAVs in the second cluster at the next time;

[0024] wherein the unstable communication links in the cluster include first unstable communication links in the cluster at the next time and second unstable communication links in the cluster at the current time.

[0025] According to the application, a clustering control method for UAV networking is provided, and the adjustment of the cluster head UAV in the cluster based on position information of the UAVs in the cluster at a next time includes:

[0026] determine distances of the UAVs in the cluster from the super-cluster head UAV at the next time based on position information of the UAVs in the cluster at the next time;

[0027] determine a new cluster head UAV corresponding to the cluster as a UAV closest to the super-cluster head UAV in the cluster at the next time.

[0028] According to the application, a clustering control method for UAV networking is provided, and the adjustment of the communication link in the second cluster based on position information of the UAVs in the second cluster at a next time includes:

[0029] determine a non-cluster head unmanned aerial vehicle corresponding to the second sub-cluster unstable communication link as a target unmanned aerial vehicle corresponding to the second sub-cluster;

[0030] For each target unmanned aerial vehicle, based on the position information of each unmanned aerial vehicle in the second sub-cluster at the next time, determine the unmanned aerial vehicle closest to the target unmanned aerial vehicle; and construct a communication link between the closest unmanned aerial vehicle and the target unmanned aerial vehicle.

[0031] The application also provides a clustering control device for unmanned aerial vehicle networking, comprising:

[0032] A position module is configured to determine position information of each unmanned aerial vehicle in the unmanned aerial vehicle network at the next time, respectively.

[0033] A link module is configured to determine a first unstable communication link at the next time from a plurality of communication links corresponding to a current time clustering state of the unmanned aerial vehicle network based on the position information of each unmanned aerial vehicle at the next time, wherein the plurality of communication links corresponding to the current time clustering state include communication links between cluster head unmanned aerial vehicles of each sub-cluster and super cluster head unmanned aerial vehicles, and communication links between intra-cluster unmanned aerial vehicles of each sub-cluster and corresponding cluster head unmanned aerial vehicles.

[0034] A determination module is configured to determine a link instability rate at the next time based on a number of the first unstable communication links at the next time, a number of second unstable communication links at the current time, and a total number of communication links of the unmanned aerial vehicle network at the current time, wherein the number of second unstable communication links at the current time is determined based on a clustering state of the unmanned aerial vehicle network at the current time.

[0035] A clustering control module is configured to perform clustering control on the unmanned aerial vehicle network based on the link instability rate at the next time, a link instability coefficient at the current time, and the position information of each unmanned aerial vehicle at the next time, to determine a clustering state at the next time, wherein the link instability coefficient is determined based on a clustering control process within a preset historical period from the current time.

[0036] The application also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the clustering control method for unmanned aerial vehicle networking as described above.

[0037] The application also provides a non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program is executable on a processor to implement the clustering control method for unmanned aerial vehicle networking as described above.

[0038] The application further provides a computer program product comprising a computer program which, when executed by a processor, implements the clustering control method for the UAV network as described in any of the above.

[0039] The application provides a clustering control method and device for a UAV network, an electronic device, and a storage medium. The method includes determining position information of each UAV in the UAV network at a next time point, determining a first unstable communication link at the next time point from a plurality of communication links corresponding to a clustering state of the UAV network at a current time point based on the position information of each UAV at the next time point, determining a link instability rate at the next time point based on a number of the first unstable communication links at the next time point, a number of second unstable communication links at the current time point, and a total number of communication links of the UAV network at the current time point, and finally performing clustering control on the UAV network at the next time point based on the link instability rate at the next time point, a link instability coefficient at the current time point, and the position information of each UAV at the next time point to determine a clustering state at the next time point. In a highly dynamic scenario, even if the topology of the UAV network changes rapidly, the clustering control method can still determine the clustering state at the next time point according to the link instability rate at the next time point and the position information of each UAV at the next time point, so that the clustering state of the UAV network is adjusted according to the predicted position information of each UAV at the next time point and the instability of the communication link, thereby improving the stability of the UAV network and ensuring the communication quality between UAVs in various application scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0041] Figure 1 is a flowchart of the clustering control method for the UAV network provided by the embodiments of the application;

[0042] Figure 2 is a flowchart of the clustering control method for the UAV network provided by the embodiments of the application;

[0043] Figure 3 is a structural diagram of the clustering control device for the UAV network provided by the embodiments of the application;

[0044] Figure 4 is a structural diagram of the electronic device provided by the embodiments of the application. DETAILED DESCRIPTION

[0045] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the present application. Obviously, the described embodiments are only some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall into the protection scope of the present application.

[0046] In view of the above problems in the prior art, the present application provides a clustering control method for unmanned aerial vehicle networking, Figure 1 is a flowchart of the clustering control method for unmanned aerial vehicle networking provided by the embodiments of the present application, as shown in the figure, the clustering control method for unmanned aerial vehicle networking comprises the following steps: Figure 1

[0047] Step 110: respectively determine the position information of each unmanned aerial vehicle in the unmanned aerial vehicle network at the next time.

[0048] Specifically, the position information of each unmanned aerial vehicle at the next time can be determined based on the speed information and the position information of each unmanned aerial vehicle in the unmanned aerial vehicle network at the current time.

[0049] Exemplarily, the speed information and the position information of the unmanned aerial vehicle i at the time t can be represented by the following formula:

[0050]

[0051]

[0052] wherein, and respectively represent the speed vector in the x-axis direction, the speed vector in the y-axis direction and the speed vector in the z-axis direction, and respectively represent the position coordinate in the x-axis direction, the position coordinate in the y-axis direction and the position coordinate in the z-axis direction, I represents the set of all unmanned aerial vehicles in the unmanned aerial vehicle network, and T represents the set of all time from the execution of the task to the end of the task of the unmanned aerial vehicle.

[0053] Further, the position information of the unmanned aerial vehicle i at the time t+1 can be determined by the following formula:

[0054]

[0055] wherein, Δt represents the time interval from the time t to the time t+1.

[0056] ​It should be noted that the unmanned aerial vehicle networking described in the present application although at each time corresponds to a different clustering state, but in any clustering state, the unmanned aerial vehicle networking includes a super cluster head unmanned aerial vehicle, and the unmanned aerial vehicles other than the super cluster head unmanned aerial vehicle are divided into multiple clusters, each cluster includes a corresponding cluster head unmanned aerial vehicle and at least one intra-cluster unmanned aerial vehicle. The clustering state of the unmanned aerial vehicle networking at the initial time can be predetermined. Each unmanned aerial vehicle in the unmanned aerial vehicle networking can carry multiple FSO (Free Space Optical Communication) transceivers, and the unmanned aerial vehicles can build communication links through the FSO transceivers. Because the FSO transceivers have the characteristics of point-to-point transmission, the number of FSO transceivers carried by each unmanned aerial vehicle needs to be the same, and because the cluster heads of each cluster need to build communication links with the super cluster head respectively, the number of clusters should not be greater than the number of FSO transceivers. Building communication links between unmanned aerial vehicles through FSO transceivers has the following advantages: (1) large bandwidth, FSO transceivers can carry up to 2000THz of communication bandwidth, and large bandwidth can guarantee the realization of high-speed communication. (2) Strong anti-interference ability, FSO transceivers limit the transmission power in a narrow area and provide good spatial isolation, which can significantly reduce the interference of other signals. (3) Low cost, FSO transceivers do not need to build pipelines compared with optical fibers, which can effectively reduce the cost. (4) Easy to deploy, communication links can be built in a short time through FSO transceivers, and the disconnection of the communication links is also very easy.

[0057] Step 120: determining a first unstable communication link at the next time from the multiple communication links corresponding to the clustering state of the unmanned aerial vehicle networking at the current time based on the position information of each unmanned aerial vehicle at the next time, the multiple communication links corresponding to the clustering state at the current time including the communication links between the cluster head unmanned aerial vehicles of each cluster and the super cluster head unmanned aerial vehicle and the communication links between the intra-cluster unmanned aerial vehicles of each cluster and the corresponding cluster head unmanned aerial vehicle.

[0058] Specifically, the first unstable communication link at the next time can be determined from the multiple communication links corresponding to the clustering state of the unmanned aerial vehicle networking at the current time based on the position information of each unmanned aerial vehicle at the next time, the multiple communication links corresponding to the clustering state at the current time including the communication links between the cluster head unmanned aerial vehicles of each cluster and the super cluster head unmanned aerial vehicle and the communication links between the intra-cluster unmanned aerial vehicles of each cluster and the corresponding cluster head unmanned aerial vehicle.

[0059] In one embodiment, the determination of the first unstable communication link at the next time from the multiple communication links corresponding to the clustering state of the unmanned aerial vehicle networking at the current time based on the position information of each unmanned aerial vehicle at the next time includes:

[0060] For each of the communication links, a transmission distance of the communication link at a next time is determined based on position information of a UAV corresponding to the communication link at the next time.

[0061] A communication link with a transmission distance at the next time greater than a preset transmission distance threshold is determined as a first unstable communication link at the next time.

[0062] Specifically, the stability r of the communication link between the UAVs can be represented by the following formula:

[0063]

[0064] wherein, P(U≥I th ) represents a probability that a light signal intensity U of a light signal received by the communication link is greater than a preset light signal intensity threshold I th , erf() represents an error function, I0 represents an average light signal intensity of the light signal received by the communication link in a case without turbulence, σ x represents a standard deviation of the logarithmic intensity, and a square of the standard deviation of the logarithmic intensity, i.e., a variance of the logarithmic intensity can be determined by the following formula:

[0065]

[0066] wherein, π represents a circular constant, λ represents a wavelength of the light signal received by the communication link, represents a refractive index structure parameter factor, and L represents the transmission distance of the communication link.

[0067] As described above, the stability of the communication link between the UAVs depends only on the transmission distance of the communication link, and thus whether the communication link is stable and reliable can be determined by the transmission distance of the communication link.

[0068] For each of the communication links, a transmission distance of the communication link at a next time can be determined based on position information of a UAV corresponding to the communication link at the next time.

[0069] For example, a UAV corresponding to a certain communication link is UAV i and UAV j, and a transmission distance L i,j of the communication link at a time t+1 can be represented by the following formula:

[0070]

[0071] wherein, and respectively represent an x-axis direction position coordinate, a y-axis direction position coordinate and a z-axis direction position coordinate of UAV i at the time t+1, and respectively represent the position coordinates of the x-axis direction, the y-axis direction and the z-axis direction of the UAV j at the time t+1.

[0072] Further, the transmission distance at the next time can be compared with a preset transmission distance threshold, and the communication link with the transmission distance at the next time greater than the preset transmission distance threshold is determined as the first unstable communication link at the next time. The preset transmission distance threshold can be set according to requirements, and the embodiments of the present application do not make specific limitations here.

[0073] In the above embodiments, for each communication link, the transmission distance at the next time of the communication link is determined based on the position information of the UAV corresponding to the communication link at the next time, and the first unstable communication link can be accurately determined based on the comparison of the transmission distance at the next time of the communication link with the preset transmission distance threshold.

[0074] Step 130: determining the link instability rate at the next time based on the number of the first unstable communication links at the next time, the number of the second unstable communication links at the current time and the total number of the communication links of the UAV network at the current time, wherein the number of the second unstable communication links at the current time is determined based on the clustering state of the UAV network at the current time.

[0075] Specifically, the link instability rate at the next time can be determined based on the number of the first unstable communication links at the next time, the number of the second unstable communication links at the current time and the total number of the communication links of the UAV network at the current time.

[0076] For example, the link instability rate at the next time η can be determined by the following formula:

[0077]

[0078] wherein, l ins represents the number of the first unstable communication links at the next time, l mark represents the number of the second unstable communication links at the current time, l all represents the total number of the communication links of the UAV network at the current time.

[0079] The number of the second unstable communication links at the current time is determined based on the clustering state of the UAV network at the current time. The second unstable communication link at the current time is the unstable communication link marked after the local adjustment clustering control of the UAV network in the historical period. The second unstable communication link is essentially the communication link between the intra-cluster UAVs. For example, after the local adjustment clustering control of the UAV network at t-2, the communication link between UAV a and UAV b is determined as the second unstable communication link, and after the local adjustment clustering control of the UAV network at t-1, the communication link between UAV c and UAV d is determined as the second unstable communication link. Therefore, the second unstable communication link at t is the communication link between UAV a and UAV b and the communication link between UAV c and UAV d, and the number of the second unstable communication links at t is 2. It is easy to understand that the number of the second unstable communication links at the current time can be zero.

[0080] It should be noted that in the process of determining the first unstable communication link at the next time from the plurality of communication links corresponding to the clustering state of the UAV network at the current time described in step 120, since the second unstable communication link has been marked as an unstable communication link, it is not necessary to determine the stability of each second unstable communication link according to the position information of the UAV at the next time. Therefore, the plurality of communication links do not include the second unstable communication link.

[0081] Step 140: performing clustering control on the UAV network based on the link instability rate at the next time, the link instability coefficient at the current time, and the position information of each UAV at the next time, to determine the clustering state at the next time; the link instability coefficient is determined based on the clustering control process in the preset historical period from the current time.

[0082] Specifically, the clustering control of the UAV network can be performed based on the link instability rate at the next moment, the link instability coefficient at the current moment, and the position information of each UAV at the next moment, and the clustering state of the UAV network at the next moment is determined. The link instability coefficient is determined based on the clustering control process within a preset historical period from the current moment. The preset historical period can include a first preset historical period and a second preset historical period. In the case that the re-clustering control of the UAV is performed at each moment within the first preset historical period from the current moment, the link instability coefficient at the last moment can be reduced by a preset adjustment step to obtain the link instability coefficient at the current moment. In the case that the local adjustment clustering control of the UAV is performed at each moment within the second historical period from the current moment, the link instability coefficient at the last moment can be increased by a preset adjustment step to obtain the link instability coefficient at the current moment. The length of the second preset historical period is greater than the length of the first preset historical period, and the preset adjustment step can be set as needed, for example, it can be 10%. It is easy to understand that the value of the link instability coefficient at the initial moment can also be preset, for example, it can be set to 50%.

[0083] In one embodiment, the clustering control includes re-clustering control and local adjustment clustering control.

[0084] The clustering control of the UAV network based on the link instability rate at the next moment, the link instability coefficient at the current moment, and the position information of each UAV at the next moment includes:

[0085] In the case that the link instability rate at the next moment is greater than the link instability coefficient at the current moment, the re-clustering control of the UAV network is performed based on the position information of each UAV at the next moment.

[0086] In the case that the link instability rate at the next moment is less than or equal to the link instability coefficient at the current moment, the local adjustment clustering control of the UAV network is performed based on the position information of each UAV at the next moment.

[0087] Specifically, Figure 2 is a flowchart of the clustering control of the UAV network provided by the embodiment of the present application, as Figure 2 shown, the clustering control of the UAV network can include re-clustering control and local adjustment clustering control. In the case that the link instability rate at the next moment η is greater than the link instability coefficient at the current moment η0, i.e. η>η0, it indicates that the instability of the UAV network communication link at the next moment is high, and then the re-clustering control of the UAV network can be performed based on the position information of each UAV at the next moment.

[0088] In a case that the link instability rate at the next moment is less than or equal to the link instability coefficient at the current moment, i.e. η≤η0, it is indicated that the instability of the UAV networking communication link at the next moment is low, and thus it is not necessary to perform the re-clustering control on the UAV networking, and the local adjustment clustering control can be performed on the UAV networking based on the position information of each UAV at the next moment.

[0089] In the above embodiment, the re-clustering control or the local adjustment clustering control is determined based on the comparison between the link instability rate at the next moment and the link instability coefficient at the current moment, and different clustering control modes can be determined according to the stability of the UAV networking communication link at the next moment, so that the calculation resources are reasonably utilized on the basis of accurately clustering the UAV networking.

[0090] In one embodiment, the re-clustering control on the UAV networking based on the position information of each UAV at the next moment comprises:

[0091] determining a center point of a region where the UAV networking is located at the next moment based on the position information of each UAV at the next moment, and determining a UAV closest to the center point as a new super cluster head UAV;

[0092] based on the K-midoids algorithm, dividing all the UAVs other than the new super cluster head UAV into a plurality of new clusters, and determining a cluster head UAV corresponding to each new cluster.

[0093] Specifically, in a case that the link instability rate at the next moment is greater than the link instability coefficient at the current moment, a center point of a region where the UAV networking is located at the next moment can be determined based on the position information of each UAV at the next moment, and a UAV closest to the center point is determined as a new super cluster head UAV.

[0094] For example, the center point M of the region where the UAV networking is located at the next moment mid which can be expressed by the following formula:

[0095]

[0096] wherein x max , y max and z max represent the maximum x-axis direction position coordinate, the maximum y-axis direction position coordinate and the maximum z-axis direction position coordinate in the position information of all the UAVs at the next moment, respectively, x min , y min and z minrespectively represent the minimum x-axis direction position coordinate, the minimum y-axis direction position coordinate and the minimum z-axis direction position coordinate in the position information of all unmanned aerial vehicles at the next moment.

[0097] Further, all unmanned aerial vehicles except the new super cluster head unmanned aerial vehicle can be divided into multiple new clusters based on the K-midoids algorithm, and the cluster head unmanned aerial vehicles corresponding to each new cluster are determined, wherein the K value in the K-midoids algorithm is the predicted number of new clusters, for example, the predicted number of new clusters can be the same as the number of FSO transceivers on the unmanned aerial vehicle. Alternatively, since the number of unmanned aerial vehicles included in each new cluster divided based on the K-midoids algorithm can not be balanced, part of the unmanned aerial vehicles in the new cluster with the largest number of unmanned aerial vehicles can be allocated to the new cluster with the smallest number of unmanned aerial vehicles, so that the number of unmanned aerial vehicles included in each new cluster is smaller.

[0098] In the above embodiment, the center point of the area where the unmanned aerial vehicle network is located at the next moment is determined based on the position information of each unmanned aerial vehicle at the next moment, and the unmanned aerial vehicle closest to the center point is determined as the new super cluster head unmanned aerial vehicle. Since the newly determined super cluster head unmanned aerial vehicle is close to the center of the area where the unmanned aerial vehicle network is located, the stability of the communication link between each new cluster head unmanned aerial vehicle and the super cluster head unmanned aerial vehicle is higher after the new cluster is divided. Further, based on the K-midoids algorithm, all unmanned aerial vehicles in the unmanned aerial vehicle network except the new super cluster head unmanned aerial vehicle are divided into multiple new clusters, and the cluster head unmanned aerial vehicles corresponding to each new cluster are determined. Based on the characteristics of the K-midoids algorithm, the division of the new cluster and the selection of the cluster head unmanned aerial vehicle are more excellent.

[0099] In one embodiment, the local adjustment clustering control of the unmanned aerial vehicle network based on the position information of each unmanned aerial vehicle at the next moment comprises:

[0100] In the case where the communication link between the cluster head unmanned aerial vehicle and the super cluster head unmanned aerial vehicle exists in the first unstable communication link at the next moment, for each cluster, the cluster head unmanned aerial vehicle in the cluster is adjusted based on the position information of each unmanned aerial vehicle in the cluster at the next moment.

[0101] in the case that the communication link between the cluster head UAV and the super cluster head UAV does not exist in the first unstable communication link at the next moment, for a first cluster in which the number of unstable communication links within the cluster is greater than or equal to a preset link quantity threshold, adjusting the cluster head UAV in the first cluster based on the position information of each UAV in the first cluster at the next moment; for a second cluster in which the number of unstable communication links within the cluster is less than the preset link quantity threshold, adjusting the communication link in the second cluster based on the position information of each UAV in the second cluster at the next moment;

[0102] The unstable communication link within the cluster includes a first unstable communication link within the cluster at the next moment and a second unstable communication link within the cluster at the current moment.

[0103] Specifically, in the case that the communication link between the cluster head UAV and the super cluster head UAV exists in the first unstable communication link at the next moment, it is indicated that the cluster head UAV may have fallen behind, and for each cluster, the cluster head UAV in the cluster can be adjusted based on the position information of each UAV in the cluster at the next moment. It is easy to understand that in the above case, the super cluster head and the cluster do not change, and only the cluster head UAV corresponding to each cluster may change.

[0104] In the case that the communication link between the cluster head UAV and the super cluster head UAV does not exist in the first unstable communication link at the next moment, for a cluster in which the number of unstable communication links within the cluster is greater than or equal to a preset link quantity threshold, the cluster can be determined as a first cluster, and in the above case, it is indicated that there may be multiple intra-cluster UAVs and the cluster head UAV of the first cluster with unstable communication links. The cluster head UAV in the first cluster can be adjusted based on the position information of each UAV in the first cluster at the next moment. For a cluster in which the number of unstable communication links within the cluster is less than the preset link quantity threshold, the cluster can be determined as a second cluster, and in the above case, it is indicated that there may be only a small number of intra-cluster UAVs and the cluster head UAV of the second cluster with unstable communication links. The communication link in the second cluster can be adjusted based on the position information of each UAV in the second cluster at the next moment. The unstable communication link within the cluster includes a first unstable communication link within the cluster at the next moment and a second unstable communication link within the cluster at the current moment. The preset link quantity threshold can be set as needed, for example, it can be half of the number of FSO transceivers on the UAV.

[0105] In the above embodiments, different adjustments are made to each cluster for different situations, which can reasonably utilize computing resources.

[0106] In an embodiment, the adjusting the cluster head unmanned vehicle in the cluster based on the position information of each unmanned vehicle in the cluster at the next moment in time comprises:

[0107] determining distances of each unmanned vehicle in the cluster from the super cluster head unmanned vehicle at the next moment in time based on the position information of each unmanned vehicle in the cluster at the next moment in time;

[0108] determining the unmanned vehicle closest to the super cluster head unmanned vehicle in the cluster at the next moment in time as the new cluster head unmanned vehicle corresponding to the cluster.

[0109] Specifically, for each cluster, the distance of each unmanned vehicle in the cluster from the super cluster head unmanned vehicle at the next moment in time can be determined based on the position information of each unmanned vehicle in the cluster at the next moment in time, and then the unmanned vehicle closest to the super cluster head unmanned vehicle in the cluster at the next moment in time can be determined as the new cluster head unmanned vehicle corresponding to the cluster.

[0110] For example, the distance of the unmanned vehicle a from the super cluster head unmanned vehicle in the cluster S at the next moment in time can be determined to be the shortest based on the position information of each unmanned vehicle in the cluster S at the next moment in time, and the unmanned vehicle a can be determined as the new cluster head unmanned vehicle corresponding to the cluster S.

[0111] It is easy to understand that the cluster head unmanned vehicle in the first cluster can be adjusted based on the position information of each unmanned vehicle in the first cluster at the next moment in time by a method similar to the above method, i.e., the distance of each unmanned vehicle in the first cluster from the super cluster head unmanned vehicle at the next moment in time can be determined based on the position information of each unmanned vehicle in the first cluster at the next moment in time, and then the unmanned vehicle closest to the super cluster head unmanned vehicle in the first cluster at the next moment in time can be determined as the new cluster head unmanned vehicle corresponding to the first cluster.

[0112] In the above embodiment, for each cluster, the unmanned vehicle closest to the super cluster head unmanned vehicle in the cluster at the next moment in time is determined as the new cluster head unmanned vehicle corresponding to the cluster, which can increase the stability of the overall communication link of the unmanned vehicle networking by adjusting only the cluster head unmanned vehicle.

[0113] In an embodiment, the adjusting the communication link in the second cluster based on the position information of each unmanned vehicle in the second cluster at the next moment in time comprises:

[0114] determining a non-cluster head unmanned vehicle corresponding to an unstable communication link in the second cluster as a target unmanned vehicle corresponding to the second cluster;

[0115] for each target unmanned vehicle, determining an unmanned vehicle closest to the target unmanned vehicle based on the position information of each unmanned vehicle in the second cluster at the next moment in time, and constructing a communication link between the unmanned vehicle closest to the target unmanned vehicle and the target unmanned vehicle.

[0116] Specifically, for each second sub-cluster, the non-cluster head unmanned vehicle corresponding to the unstable communication link in the second sub-cluster can be determined as the target unmanned vehicle corresponding to the second sub-cluster, and then for each target unmanned vehicle, the unmanned vehicle closest to the target unmanned vehicle can be determined based on the position information of each unmanned vehicle in the second sub-cluster at the next moment, and a communication link can be constructed between the unmanned vehicle closest and the target unmanned vehicle. And due to the characteristics of FSO point-to-point transmission, that is, only one FSO transceiver can construct a communication link, if the unmanned vehicle closest to the target unmanned vehicle does not have redundant FSO transceivers, the target unmanned vehicle can construct a communication link with the second closest unmanned vehicle. Wherein, in the process of determining the non-cluster head unmanned vehicle corresponding to the unstable communication link in the second sub-cluster as the target unmanned vehicle corresponding to the second sub-cluster, the non-cluster head unmanned vehicle is the non-cluster head unmanned vehicle that does not exist between the cluster head unmanned vehicle in the second sub-cluster.

[0117] Further, if the unmanned vehicle closest to the target unmanned vehicle corresponding to the second sub-cluster are both non-cluster head unmanned vehicles, the communication link between the two needs to be determined as the second unstable communication link.

[0118] For example, for the cluster S, the cluster S includes the cluster head UAV P and the cluster internal UAVs a, b and c, the unstable communication link in the cluster S is the communication link between the cluster internal UAV a and the cluster internal UAV b, the cluster internal UAV a can be determined as the target UAV, and the cluster internal UAV b cannot be determined as the target UAV because the communication link between the cluster internal UAV b and the cluster head UAV P is stable. Further, the cluster internal UAV c closest to the cluster internal UAV a in the cluster S is determined, a communication link is constructed between the cluster internal UAV a and the cluster internal UAV c, and the communication link is determined as the second unstable communication link. For another example, for the cluster S, the cluster S includes the cluster head UAV P and the cluster internal UAVs a, b and c, the unstable communication link in the cluster S is the communication link between the cluster internal UAV a and the cluster internal UAV b, the cluster internal UAV a can be determined as the target UAV, and the cluster internal UAV b cannot be determined as the target UAV because the communication link between the cluster internal UAV b and the cluster head UAV P is stable. Further, the cluster internal UAV c closest to the cluster internal UAV a in the cluster S is determined, a communication link is constructed between the cluster internal UAV a and the cluster internal UAV c, and the communication link is determined as the second unstable communication link. For another example, for the cluster S, the cluster S includes the cluster head UAV P and the cluster internal UAVs a, b and c, the unstable communication link in the cluster S is the communication link between the cluster internal UAV a and the cluster internal UAV b, the cluster internal UAV a can be determined as the target UAV, and the cluster internal UAV b cannot be determined as the target UAV because the communication link between the cluster internal UAV b and the cluster head UAV P is stable. Further, the cluster internal UAV c closest to the cluster internal UAV a in the cluster S is determined, a communication link is constructed between the cluster internal UAV a and the cluster internal UAV c, and the communication link is determined as the second unstable communication link.

[0119] In the above embodiment, the non-cluster head UAV corresponding to the second cluster unstable communication link is determined as the target UAV corresponding to the second cluster, and further, for each target UAV, the UAV closest to the target UAV is determined, a communication link is constructed between the closest UAV and the target UAV, which can ensure the problem of the corresponding communication link with a small adjustment of the UAV networking.

[0120] The application provides a clustering control method for a UAV network, which comprises the following steps: determining the position information of each UAV in the UAV network at the next moment, respectively; determining the first unstable communication link at the next moment from the plurality of communication links corresponding to the clustering state of the UAV network at the current moment based on the position information of each UAV at the next moment; determining the link instability rate at the next moment based on the number of the first unstable communication link at the next moment, the number of the second unstable communication link at the current moment and the total number of the communication links of the UAV network at the current moment; and finally performing clustering control on the UAV network based on the link instability rate at the next moment, the link instability coefficient at the current moment and the position information of each UAV at the next moment to determine the clustering state at the next moment. The technical scheme of the application can perform clustering control on the UAV network based on the link instability rate at the next moment and the position information of each UAV at the next moment to determine the clustering state at the next moment even if the topology of the UAV network changes rapidly in a highly dynamic scene, so that the clustering state of the UAV network is adjusted according to the predicted position information of each UAV at the next moment and the instability of the communication link, thereby improving the stability of the UAV network and ensuring the communication quality between UAVs in various application scenarios.

[0121] The clustering control device for a UAV network provided by the application will be described below, and the clustering control device for a UAV network described below can be correspondingly referred to the clustering control method for a UAV network described above.

[0122] Figure 3 is a structural schematic diagram of the clustering control device for a UAV network provided by the embodiment of the application, as Figure 3 shown, the clustering control device for a UAV network 300 comprises:

[0123] a position module 310 configured to determine the position information of each UAV in the UAV network at the next moment, respectively;

[0124] a link module 320 configured to determine the first unstable communication link at the next moment from the plurality of communication links corresponding to the clustering state of the UAV network at the current moment based on the position information of each UAV at the next moment, wherein the plurality of communication links corresponding to the clustering state at the current moment comprise the communication link between the cluster head UAV of each cluster and the super cluster head UAV and the communication link between the intra-cluster UAV of each cluster and the corresponding cluster head UAV;

[0125] The determining module 330 is configured to determine a link instability rate at the next moment based on the number of the first unstable communication links at the next moment, the number of the second unstable communication links at the current moment, and the total number of the communication links of the UAV network at the current moment, wherein the number of the second unstable communication links at the current moment is determined based on the clustering state of the UAV network at the current moment.

[0126] The clustering control module 340 is configured to perform clustering control on the UAV network based on the link instability rate at the next moment, a link instability coefficient at the current moment, and the position information of each UAV at the next moment, and determine a clustering state at the next moment, wherein the link instability coefficient is determined based on the clustering control process within a preset historical period from the current moment.

[0127] In an embodiment, the link module 320 is specifically configured to:

[0128] For each communication link, determine a transmission distance of the communication link at the next moment based on the position information of the UAV corresponding to the communication link at the next moment.

[0129] Determine a communication link with a transmission distance greater than a preset transmission distance threshold at the next moment as the first unstable communication link at the next moment.

[0130] In an embodiment, the clustering control includes re-clustering control and local adjustment clustering control, and the clustering control module 340 is specifically configured to:

[0131] When the link instability rate at the next moment is greater than the link instability coefficient at the current moment, perform the re-clustering control on the UAV network based on the position information of each UAV at the next moment.

[0132] When the link instability rate at the next moment is less than or equal to the link instability coefficient at the current moment, perform the local adjustment clustering control on the UAV network based on the position information of each UAV at the next moment.

[0133] In an embodiment, the clustering control module 340 is specifically further configured to:

[0134] Determine a center point of an area where the UAV network is located at the next moment based on the position information of each UAV at the next moment, and determine a UAV closest to the center point as a new super cluster head UAV.

[0135] Divide all the UAVs other than the new super cluster head UAV into a plurality of new clusters based on a K-midoids algorithm, and determine a cluster head UAV corresponding to each new cluster.

[0136] In an embodiment, the clustering control module 340 is specifically further configured to:

[0137] In the case that the communication link between the cluster head UAV and the super cluster head UAV exists in the first unstable communication link at the next moment, for each cluster, based on the position information of each UAV in the cluster at the next moment, adjusting the cluster head UAV in the cluster;

[0138] In the case that the communication link between the cluster head UAV and the super cluster head UAV does not exist in the first unstable communication link at the next moment, for a first cluster in which the number of unstable communication links within the cluster is greater than or equal to a preset link number threshold, based on the position information of each UAV in the first cluster at the next moment, adjusting the cluster head UAV in the first cluster; for a second cluster in which the number of unstable communication links within the cluster is less than the preset link number threshold, based on the position information of each UAV in the second cluster at the next moment, adjusting the communication link in the second cluster;

[0139] Wherein, the unstable communication link within the cluster includes a first unstable communication link within the cluster at the next moment and a second unstable communication link within the cluster at the current moment.

[0140] In an embodiment, the clustering control module 340 is specifically further configured to:

[0141] Based on the position information of each UAV in the cluster at the next moment, determining the distances of each UAV in the cluster from the super cluster head UAV at the next moment;

[0142] Determining the UAV closest to the super cluster head UAV in the cluster at the next moment as the new cluster head UAV corresponding to the cluster.

[0143] In an embodiment, the clustering control module 340 is specifically further configured to:

[0144] Determining the non-cluster head UAV corresponding to the unstable communication link within the second cluster as the target UAV corresponding to the second cluster;

[0145] For each of the target UAVs, based on the position information of each UAV in the second cluster at the next moment, determining the UAV closest to the target UAV; and constructing a communication link between the closest UAV and the target UAV.

[0146] The application provides a clustering control device for a UAV network, which determines the position information of each UAV in the UAV network at the next moment, determines the first unstable communication link at the next moment from the multiple communication links corresponding to the clustering state of the UAV network at the current moment based on the position information of each UAV at the next moment, determines the link instability rate at the next moment based on the number of the first unstable communication link at the next moment, the number of the second unstable communication link at the current moment and the total number of the communication links of the UAV network at the current moment, and finally performs clustering control on the UAV network based on the link instability rate at the next moment, the link instability coefficient at the current moment and the position information of each UAV at the next moment to determine the clustering state at the next moment. In a highly dynamic scene, even if the topology of the UAV network changes rapidly, the clustering control device can still determine the clustering state at the next moment according to the link instability rate at the next moment and the position information of each UAV at the next moment, so that the clustering state of the UAV network is adjusted according to the predicted position information of each UAV at the next moment and the instability of the communication link, thereby improving the stability of the UAV network and ensuring the communication quality between UAVs in various application scenarios.

[0147] Figure 4 An example of a schematic diagram of a physical structure of an electronic device is shown in Figure 4 The electronic device can include a processor 410, a communications interface 420, a memory 430 and a communications bus 440, wherein the processor 410, the communications interface 420 and the memory 430 can communicate with each other through the communications bus 440. The processor 410 can call the logical instructions in the memory 430 to execute the clustering control method for the UAV network, which includes the following steps:

[0148] Determine the position information of each UAV in the UAV network at the next moment, respectively;

[0149] Determine the first unstable communication link at the next moment from the multiple communication links corresponding to the clustering state of the UAV network at the current moment based on the position information of each UAV at the next moment, wherein the multiple communication links corresponding to the clustering state at the current moment include the communication links between the cluster head UAVs of each cluster and the super cluster head UAVs and the communication links between the intra-cluster UAVs of each cluster and the corresponding cluster head UAVs;

[0150] determine a link instability rate at the next moment based on the number of first unstable communication links at the next moment, the number of second unstable communication links at the current moment and the total number of communication links of the UAV network at the current moment, the number of second unstable communication links at the current moment being determined based on a clustering state of the UAV network at the current moment;

[0151] perform clustering control on the UAV network based on the link instability rate at the next moment, a link instability coefficient at the current moment and the position information of each UAV at the next moment to determine a clustering state at the next moment, the link instability coefficient being determined based on a clustering control process within a preset historical period from the current moment.

[0152] In addition, the logical instructions in the memory 430 described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0153] On the other hand, the present application also provides a computer program product, the computer program product comprising a computer program, the computer program being stored on a non-transitory computer readable storage medium, and the computer program being executable by a processor to cause a computer to perform the clustering control method of the UAV network provided by the above-mentioned methods, the method comprising:

[0154] determine the position information of each UAV in the UAV network at the next moment respectively;

[0155] determine first unstable communication links at the next moment from a plurality of communication links corresponding to the clustering state of the UAV network at the current moment based on the position information of each UAV at the next moment, the plurality of communication links corresponding to the clustering state at the current moment including communication links between cluster head UAVs of each cluster and super cluster head UAVs and communication links between intra-cluster UAVs of each cluster and corresponding cluster head UAVs;

[0156] determine a link instability rate at the next moment based on the number of the first unstable communication links at the next moment, the number of the second unstable communication links at the current moment, and the total number of the communication links of the UAV network at the current moment, the number of the second unstable communication links at the current moment being determined based on the clustering state of the UAV network at the current moment;

[0157] perform clustering control on the UAV network based on the link instability rate at the next moment, a link instability coefficient at the current moment, and the position information of each of the UAVs at the next moment, and determine a clustering state at the next moment, the link instability coefficient being determined based on the clustering control process within a preset historical period from the current moment.

[0158] In another aspect, the present application also provides a non-transitory computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the clustering control method of the UAV network provided by the above method, the method comprising:

[0159] determine the position information of each of the UAVs at the next moment in the UAV network respectively;

[0160] determine the first unstable communication links at the next moment from a plurality of communication links corresponding to the clustering state at the current moment in the UAV network based on the position information of each of the UAVs at the next moment, the plurality of communication links corresponding to the clustering state at the current moment including the communication links between the cluster head UAVs of each cluster and the super cluster head UAVs and the communication links between the intra-cluster UAVs of each cluster and the corresponding cluster head UAVs;

[0161] determine a link instability rate at the next moment based on the number of the first unstable communication links at the next moment, the number of the second unstable communication links at the current moment, and the total number of the communication links of the UAV network at the current moment, the number of the second unstable communication links at the current moment being determined based on the clustering state of the UAV network at the current moment;

[0162] perform clustering control on the UAV network based on the link instability rate at the next moment, a link instability coefficient at the current moment, and the position information of each of the UAVs at the next moment, and determine a clustering state at the next moment, the link instability coefficient being determined based on the clustering control process within a preset historical period from the current moment.

[0163] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0164] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and the necessary general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0165] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A clustering control method for unmanned aerial vehicle networking, characterized in that, The method comprises the steps of: respectively determining position information of each unmanned aerial vehicle in the next time in the unmanned aerial vehicle networking; determining a first unstable communication link in the next time from a plurality of communication links corresponding to a current time clustering state of the unmanned aerial vehicle networking based on the position information of each unmanned aerial vehicle in the next time, wherein the plurality of communication links corresponding to the current time clustering state comprise communication links between cluster head unmanned aerial vehicles of each cluster and super cluster head unmanned aerial vehicles and communication links between intra-cluster unmanned aerial vehicles of each cluster and corresponding cluster head unmanned aerial vehicles; determining a link instability rate in the next time based on a number of the first unstable communication links in the next time, a number of second unstable communication links in the current time and a total number of communication links of the unmanned aerial vehicle networking in the current time, wherein the number of the second unstable communication links in the current time is determined based on the clustering state of the unmanned aerial vehicle networking in the current time; controlling clustering of the unmanned aerial vehicle networking based on the link instability rate in the next time, a link instability coefficient in the current time and the position information of each unmanned aerial vehicle in the next time to determine a clustering state in the next time, wherein the link instability coefficient is determined based on a clustering control process in a preset historical period from the current time; the step of determining the first unstable communication link in the next time from the plurality of communication links corresponding to the current time clustering state of the unmanned aerial vehicle networking based on the position information of each unmanned aerial vehicle in the next time comprises the steps of: for each communication link, determining a transmission distance of the communication link in the next time based on position information of an unmanned aerial vehicle corresponding to the communication link in the next time; determining a communication link with a transmission distance greater than a preset transmission distance threshold in the next time as the first unstable communication link in the next time; the clustering control comprises re-clustering control and local adjustment clustering control; the step of controlling clustering of the unmanned aerial vehicle networking based on the link instability rate in the next time, the link instability coefficient in the current time and the position information of each unmanned aerial vehicle in the next time comprises the steps of: in a case where the link instability rate in the next time is greater than the link instability coefficient in the current time, performing the re-clustering control of the unmanned aerial vehicle networking based on the position information of each unmanned aerial vehicle in the next time; in a case where the link instability rate in the next time is less than or equal to the link instability coefficient in the current time, performing the local adjustment clustering control of the unmanned aerial vehicle networking based on the position information of each unmanned aerial vehicle in the next time. 2.The method of claim 1, wherein, the step of performing the re-clustering control of the unmanned aerial vehicle networking based on the position information of each unmanned aerial vehicle in the next time comprises the steps of: determining a center point of an area in which the unmanned aerial vehicle networking is located in the next time based on the position information of each unmanned aerial vehicle in the next time, and determining an unmanned aerial vehicle closest to the center point as a new super cluster head unmanned aerial vehicle; dividing all unmanned aerial vehicles other than the new super cluster head unmanned aerial vehicle into a plurality of new clusters based on a K-midoids algorithm, and determining cluster head unmanned aerial vehicles corresponding to each new cluster. 3.The method of claim 1, wherein, The local adjustment clustering control of the unmanned aerial vehicle networking based on the position information of each unmanned aerial vehicle at the next moment comprises: In the case that the communication link between the cluster head unmanned aerial vehicle and the super cluster head unmanned aerial vehicle exists in the first unstable communication link at the next moment, for each cluster, the cluster head unmanned aerial vehicle in the cluster is adjusted based on the position information of each unmanned aerial vehicle in the cluster at the next moment; In the case that the communication link between the cluster head unmanned aerial vehicle and the super cluster head unmanned aerial vehicle does not exist in the first unstable communication link at the next moment, for the first cluster in which the number of unstable communication links in the cluster is greater than or equal to a preset link quantity threshold, the cluster head unmanned aerial vehicle in the first cluster is adjusted based on the position information of each unmanned aerial vehicle in the first cluster at the next moment; for the second cluster in which the number of unstable communication links in the cluster is less than the preset link quantity threshold, the communication link in the second cluster is adjusted based on the position information of each unmanned aerial vehicle in the second cluster at the next moment; Wherein, the unstable communication link in the cluster includes the first unstable communication link in the cluster at the next moment and the second unstable communication link in the cluster at the current moment. 4.The method of claim 3, wherein, The adjustment of the cluster head unmanned aerial vehicle in the cluster based on the position information of each unmanned aerial vehicle in the cluster at the next moment comprises: The distance of each unmanned aerial vehicle in the cluster from the super cluster head unmanned aerial vehicle at the next moment is determined based on the position information of each unmanned aerial vehicle in the cluster at the next moment; The unmanned aerial vehicle closest to the super cluster head unmanned aerial vehicle in the cluster at the next moment is determined as the new cluster head unmanned aerial vehicle corresponding to the cluster. 5.The method of claim 3, wherein, The adjustment of the communication link in the second cluster based on the position information of each unmanned aerial vehicle in the second cluster at the next moment comprises: The non-cluster head unmanned aerial vehicle corresponding to the unstable communication link in the second cluster is determined as the target unmanned aerial vehicle corresponding to the second cluster; For each target unmanned aerial vehicle, the unmanned aerial vehicle closest to the target unmanned aerial vehicle is determined based on the position information of each unmanned aerial vehicle in the second cluster at the next moment; a communication link is constructed between the closest unmanned aerial vehicle and the target unmanned aerial vehicle. 6.A clustering control device for unmanned aerial vehicle networking, characterized by comprising: Comprise: A position module for determining the position information of each unmanned aerial vehicle in the unmanned aerial vehicle networking at the next moment respectively; A link module for determining the first unstable communication link at the next moment from a plurality of communication links corresponding to the clustering state of the unmanned aerial vehicle networking at the current moment based on the position information of each unmanned aerial vehicle at the next moment, the plurality of communication links corresponding to the clustering state at the current moment comprising the communication link between the cluster head unmanned aerial vehicle of each cluster and the super cluster head unmanned aerial vehicle and the communication link between the intra-cluster unmanned aerial vehicle of each cluster and the corresponding cluster head unmanned aerial vehicle; A determination module for determining the link instability rate at the next moment based on the number of the first unstable communication link at the next moment, the number of the second unstable communication link at the current moment and the total number of communication links of the unmanned aerial vehicle networking at the current moment, the number of the second unstable communication link at the current moment being determined based on the clustering state of the unmanned aerial vehicle networking at the current moment; The clustering control module is configured to perform clustering control on the UAV network based on the link instability rate at the next time, the link instability coefficient at the current time, and the position information of each UAV at the next time, and determine a clustering state at the next time; the link instability coefficient is determined based on a clustering control process within a preset historical period from the current time; The link module is specifically configured to: For each communication link, determine a transmission distance of the communication link at the next time based on position information of a UAV corresponding to the communication link at the next time; determine a communication link with a transmission distance greater than a preset transmission distance threshold at the next time as a first unstable communication link at the next time; The clustering control includes re-clustering control and local adjustment clustering control, and the clustering control module is specifically configured to: when the link instability rate at the next time is greater than the link instability coefficient at the current time, perform the re-clustering control on the UAV network based on the position information of each UAV at the next time; when the link instability rate at the next time is less than or equal to the link instability coefficient at the current time, perform the local adjustment clustering control on the UAV network based on the position information of each UAV at the next time.

7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the clustering control method of the UAV network according to any one of claims 1 to 5 when executing the program.

8. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program implements the clustering control method of the UAV network according to any one of claims 1 to 5 when executed by the processor.

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