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CN111601356A - Wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering system and method - Google Patents

Wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering system and method Download PDF

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CN111601356A
CN111601356A CN202010303459.4A CN202010303459A CN111601356A CN 111601356 A CN111601356 A CN 111601356A CN 202010303459 A CN202010303459 A CN 202010303459A CN 111601356 A CN111601356 A CN 111601356A
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unmanned aerial
aerial vehicle
cluster head
base station
wingman
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CN111601356B (en
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赵太飞
林亚茹
薛蓉莉
王纬轩
张富强
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Shaoxing City Shangyu District Shunxing Electric Power Co ltd
Shenzhen Hongyue Information Technology Co ltd
Yuyao Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Shaoxing Shangyu District Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Xian University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/11—Arrangements specific to free-space transmission, i.e. transmission through air or vacuum
    • H04B10/112—Line-of-sight transmission over an extended range
    • H04B10/1129—Arrangements for outdoor wireless networking of information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/18502—Airborne stations
    • H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/248—Connectivity information update
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
    • H04W84/04—Large scale networks; Deep hierarchical networks
    • H04W84/06—Airborne or Satellite Networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

A wireless ultraviolet light cooperation unmanned aerial vehicle hidden dynamic clustering system and a method thereof are disclosed, wherein each unmanned aerial vehicle body is provided with an ultraviolet light spherical LED array, multitask unmanned aerial vehicles are initially randomly distributed in a designated space, virtual grids are preliminarily divided through the relation between the total bandwidth and a carrier wave, and a virtual cluster head is selected from each virtual grid; the virtual cluster head integrates state information of the wing machines in each grid and transmits the state information to the unmanned aerial vehicle base station, the unmanned aerial vehicle base station masters the global information and transmits a control instruction to each wing machine through the cluster head, and each wing machine realizes position state updating according to the control instruction; then, an optimized secondary soft threshold is introduced to improve the cluster head selection stage, so that the information transmission of the whole network is completed, and the load consumption of communication is reduced; the control commands trigger the wing plane movement system as feedback information, transforming the dynamic network into a relatively static network to adapt to the improved LEACH algorithm. The invention solves the clustering problem of the unmanned aerial vehicle dynamic network, thereby realizing the communication energy balance of the unmanned aerial vehicle.

Description

Wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering system and method
Technical Field
The invention belongs to the field of unmanned aerial vehicle networking communication, and particularly relates to a wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering system and method.
Background
Unmanned aerial vehicle networking is a dynamic real-time network, and real-time reliable communication between unmanned aerial vehicles is particularly important. In a constantly changing battlefield environment, when an unmanned aerial vehicle executes various military tasks, such as supervision, defense and attack tasks, threats such as radio silence, radio monitoring and electronic countermeasure can be met, and the problem of communication safety among the unmanned aerial vehicles becomes severe, so that an ultraviolet light secret communication mode is introduced, an ultraviolet light spherical LED array is carried on the body of the unmanned aerial vehicle, and information is loaded to an ultraviolet light source through modulation to realize information transmission.
Because the ultraviolet communication is carried out by means of ultraviolet light of a day-blind waveband of 200-280 nm, the background noise is low, and atmospheric molecules, dust particles, aerosol and the like in a space environment have a scattering effect on light waves, the limitation that other communication systems need to be directly viewed for communication is broken through, and the ultraviolet communication also has the advantages of being all-weather, strong in anti-interference capability, strong in confidentiality and the like, so that the ultraviolet communication has a wide application scene in a secret communication scene. In addition, the load energy of the drone is very limited, and networking of the drone is very disadvantageous because the energy consumption is almost exhausted, so that the drone fails and network interruption occurs. Therefore, a cluster topology management mechanism of LEACH (Low Energy Adaptive Clustering hierarchy) round robin is introduced, a movement system of a wing plane is triggered through a central feedback signal, a dynamic unmanned plane network is managed into an unmanned plane network moving in stages through a feedback trigger mechanism, and the limitation that the cluster management mechanism is only suitable for a static scene is broken, so that the management and feedback of information of all unmanned planes in an unmanned plane networking are realized, the communication Energy consumption of the unmanned planes is balanced, the survival time of the unmanned plane network is prolonged, and more time is strived for the unmanned planes to perceive the battlefield situation.
Disclosure of Invention
The invention aims to provide a wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering system and a wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering method, which solve the clustering problem of an unmanned aerial vehicle dynamic network, and further realize unmanned aerial vehicle communication energy balance.
The technical scheme adopted by the invention is as follows:
the utility model provides a secret developments clustering system of wireless ultraviolet light cooperation unmanned aerial vehicle, includes that unmanned aerial vehicle and central processing module communicate through the scattering effect of atmosphere to wireless ultraviolet light, all carry on the spherical LED array of ultraviolet light and anticollision induction system on every unmanned aerial vehicle fuselage, the spherical LED array of ultraviolet light comprises 18 single LED, is located the warp and the weft intersection of ball respectively, central processing module is the unmanned aerial vehicle basic station.
A hidden dynamic clustering method for a wireless ultraviolet light cooperation unmanned aerial vehicle comprises the following steps:
step 1: unmanned aerial vehicle initialization distribution;
step 2: constructing an optimal virtual grid number through the relationship between carrier waves and bandwidth, carrying out primary management on the unmanned aerial vehicle in an initial state, electing a virtual cluster head through the principle of minimum distance from a virtual center of mass, and carrying out data transmission for one time;
and step 3: the information of the wing plane in each grid is sent to the unmanned aerial vehicle base station through the virtual cluster head, and the unmanned aerial vehicle base station makes a corresponding feedback control instruction according to the state information to guide the whole-network wing plane to primarily make a position update;
and 4, step 4: introducing a LEACH clustering management mechanism, aiming at a new bureaucratic distribution state, introducing a LEACH clustering topology management mechanism, and setting the maximum iteration round number as RmaxAs a network lifetime, the global network is managed in a round-robin manner, in each round a random number is randomly generated by each bureau and compared with a threshold election threshold, and if the random number is smaller than the election threshold, the cluster of the bureau is electedFirstly, carrying out primary treatment;
and 5: optimizing a threshold value in a cluster head election stage;
step 6: a stable data transmission stage;
and 7: and the control instruction guides the unmanned aerial vehicle to update the state.
Further, the specific implementation of step 1 is:
the unmanned aerial vehicles are preliminarily distributed in a given area as required, and the unmanned aerial vehicles with different functions are deployed in the given area according to certain requirements according to the requirements for executing tasks, and are firstly randomly distributed in a given space, so that the initial number of the unmanned aerial vehicles is N respectively by taking reconnaissance unmanned aerial vehicles, defense unmanned aerial vehicles and attack unmanned aerial vehicles as examples1、N2And N3And carrying the same energy E0300J, each drone is set to 20 frames, N1＝N2＝N 320, initially, the unmanned aerial vehicles are randomly scattered and distributed at 100 × 100 × 100m2The unmanned aerial vehicle base station as a central processing module initially hovers at the position with the coordinates of (50,50,50), and then the position is adjusted in real time along with the change of the network topology.
Further, the specific implementation of step 2 is:
the maximum communication radius under the ultraviolet non-direct-view type-A communication mode can be obtained by OOK modulation, and the communication radius can be expressed as:
Figure BDA0002454904430000031
where α is the path loss exponent, ξ is the path loss factor, η is the quantum efficiency of the filter and photodetector, and R isbInformation modulation rate, c is speed of light, h is Planck constant, lambda is wireless ultraviolet wavelength, PtTo emit optical power, PeIs the system error rate;
because the links between clusters are common links, and the communication link from any virtual cluster head to the unmanned aerial vehicle base station is a backbone link; the bandwidth of a common link is limited, so that serial communication is realized in a cluster through a TDMA (time division multiple access) mode, a communication link from a cluster head to an unmanned aerial vehicle base station is a backbone link, the communication capacity is large, and parallel communication can be met, so that the optimal virtual grid number is obtained as follows:
Figure BDA0002454904430000041
wherein f iscIs the carrier frequency, B is the communication bandwidth of the backbone link;
dividing m virtual grids, selecting a wing machine nearest to the centroid of each grid as a virtual cluster head, loading state information of each wing machine to an ultraviolet light spherical LED array by adopting an OOK modulation mode, sending the state information to the virtual cluster head, collecting and fusing the wing machine information in the virtual grids by the virtual cluster head, and sending the information to an unmanned aerial vehicle base station to complete first data transmission.
Further, the specific implementation of step 3 is:
the virtual cluster head collects and fuses state information of the wing plane in the virtual grid, and sends the fused information to the unmanned aerial vehicle base station, and if the distance d from the virtual cluster head to the unmanned aerial vehicle base station is smaller than or equal to the maximum communication radius rookThen the fusion information can be sent to the unmanned aerial vehicle base station as a one-hop neighbor node of the unmanned aerial vehicle base station, if d is larger than rookAnd then, through the rest virtual cluster heads, the fusion information is sent to the unmanned aerial vehicle base station through the multi-hop inter-cluster forwarding function, and the unmanned aerial vehicle base station serving as the central processing module sends out a central control instruction after mastering the state information of the global unmanned aerial vehicle, so as to guide all the wing plane machines to adjust the state distribution.
Further, the specific implementation of step 4 is:
aiming at a new bureaucratic plane distribution state, a clustering topology management mechanism of LEACH is introduced, and the maximum iteration round number is set as RmaxAs the network lifetime, the global network is managed in a round-robin manner, in each round, each bureau generates a random number at random and compares with a threshold election threshold t (n), if the random number is less than the threshold election threshold, then a cluster head in the round is elected, specifically as follows:
Figure BDA0002454904430000051
where p is the percentage of cluster wing machines in all wing machines, R represents the current number of rounds,
Figure BDA0002454904430000052
represents the number of bureaucratic machines elected to a clusterhead in the round robin, and G is the bureaucratic machine set not elected to a clusterhead in the round robin.
Further, the specific implementation of step 5 is:
because formula (3) in step 4 is the hard threshold election threshold, and the state of unmanned aerial vehicle in the network, like position, node degree, power and energy etc. are dynamic change at any time, consequently adopt soft threshold election threshold to improve unmanned aerial vehicle network cluster head election stage, owing to have three kinds of unmanned aerial vehicle, be reconnaissance unmanned aerial vehicle, defend against unmanned aerial vehicle and attack unmanned aerial vehicle respectively, can obtain one-level soft threshold election threshold through optimization formula (3) and be:
Figure BDA0002454904430000053
wherein k is 1,2,3,
Figure BDA0002454904430000054
n1、n2、n3the number of three types of unmanned aerial vehicles with current wheels not failed, Tk(n)' is a primary soft threshold election threshold of the kth type unmanned plane; considering factors such as the distance from the bureaucratic plane to the base station of the unmanned aerial vehicle, the residual energy, the node degree, the residual electric quantity and the like, the formula (4) is further optimized to obtain a second-level soft threshold election threshold as follows:
Figure BDA0002454904430000061
wherein,
Figure BDA0002454904430000062
the second level of unmanned aerial vehicles for three task types can be obtained through formula (5)Soft threshold election threshold: t isk(n) ", wherein w1、w2、w3、w4Respectively, distance weight factor, energy weight factor, node degree weight factor, electric quantity weight factor, Disti、Ei、DiAnd PoweriRespectively the distance from a wing plane i to the unmanned aerial vehicle base station in the R-th wheel of the kth type unmanned aerial vehicle, the remaining energy of the wing plane i, the node degree of the wing plane i and the remaining electric quantity of the wing plane i,
Figure BDA0002454904430000063
and
Figure BDA0002454904430000064
the average distance from the unfurled wing plane to the base station of the drone at the R-th wheel, the average remaining energy of the unfurled wing plane, the average degree of nodes of the unfurled wing plane and the average remaining electric quantity of the unfurled wing plane, respectively.
Further, the specific implementation of step 6 is:
the first stage of the LEACH clustering mechanism is a cluster head election stage, after the cluster head election stage is finished, the elected cluster head broadcasts identity information to the whole network, the other wing machines select the wing machine belonging to the closest distance to the elected cluster head through the principle of minimum communication cost and send a request clustering message, when the clustering stage is finished, the cluster head allocates communication time slots for each member in the cluster and then collects and fuses the state information of the members in the cluster, a one-hop sending mode or a multi-hop sending mode can be adopted in the cluster, and the cluster head then sends the information obtained by fusion to an unmanned aerial vehicle base station through a parallel transmission mode.
Further, the specific implementation of step 7 is:
the unmanned aerial vehicle base station receives the fusion data of each cluster head, and can obtain the state information of the global unmanned aerial vehicle, so that the global judgment is made, a central control instruction is sent to each wing plane through the cluster head for retransmission, the central control instruction serves as a feedback signal to trigger the starting of a wing plane movement system, the movement is planned to a corresponding position according to the track of the control instruction, and an airborne anti-collision induction device updates the wing plane positionThe anti-collision provides guarantee; when the updated position state is matched with the feedback signal guide position consistently, the motion system is closed and enters a sleep state, the triggering of the feedback signal at the next moment is waited, the number of rounds R is added with 1 at the moment, and the number of rounds R and the preset life cycle R are judgedmaxIn a relationship between, if R is less than or equal to RmaxTurning to the step 4; if R is not less than RmaxAnd ending the dynamic clustering method and jumping out of the loop.
The invention has the advantages that:
(1) virtual grid division: and introducing an initialized virtual grid division strategy based on a clustering mechanism of LEACH round robin, and preliminarily managing scattered unmanned aerial vehicle states into an ordered state.
(2) The feedback instruction triggers the unmanned aerial vehicle to move: the unmanned aerial vehicle base station transmits the central control instruction to each cluster head through the ultraviolet light source, each cluster head locally transmits to the member unmanned aerial vehicle in each cluster, the unmanned aerial vehicle is guided to move as required, the current state is changed, and the dynamic network is converted into a relatively static network so as to be suitable for a clustering management mechanism.
(3) Determining a soft threshold value in a cluster head election stage: and selecting the unmanned aerial vehicle meeting certain conditions according to the optimized soft threshold value threshold, and using the unmanned aerial vehicle as a cluster head to manage member information in the cluster, so that the energy consumption of the network can be effectively balanced.
Drawings
Fig. 1 is a flow chart of a wireless ultraviolet light cooperative unmanned aerial vehicle covert dynamic clustering method;
FIG. 2 is an ultraviolet light spherical LED array;
figure 3 is a schematic diagram of ultraviolet light non-direct-view class a communication;
fig. 4 is a schematic diagram of virtual grid division of a drone network;
FIG. 5 is a schematic diagram of a simulation of a second level soft threshold improvement cluster election phase;
fig. 6 is a schematic diagram of a control instruction directing the update of the state of the drone.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Aiming at the problem of network communication energy consumption of unmanned aerial vehicles threatened by information security, a wireless ultraviolet light cooperation unmanned aerial vehicle covert dynamic clustering system and method are provided.
The utility model provides a secret developments clustering system of wireless ultraviolet light cooperation unmanned aerial vehicle, includes that unmanned aerial vehicle and central processing module communicate through the scattering effect of atmosphere to wireless ultraviolet light, all carries on the spherical LED array of ultraviolet light and anticollision induction system on every unmanned aerial vehicle fuselage, and the spherical LED array of ultraviolet light comprises 18 single LEDs, is located the warp and the weft intersection of ball respectively, central processing module is the unmanned aerial vehicle basic station.
Fig. 1 is a flow chart of a hidden dynamic clustering method for a wireless ultraviolet light cooperative unmanned aerial vehicle, wherein multitask unmanned aerial vehicles are initially randomly distributed in a designated space, virtual grids are preliminarily divided through the relation between total bandwidth and carrier waves, and a virtual cluster head is selected from each virtual grid; the virtual cluster head fuses state information of the wing machines in each grid and transmits the state information to the unmanned aerial vehicle base station, the unmanned aerial vehicle base station masters the global information and transmits a control instruction to each wing machine through the cluster head, and each wing machine realizes position state updating according to the control instruction; and then, an optimized secondary soft threshold is introduced to improve the cluster head selection stage, so that the information transmission of the whole network is completed, and the load consumption of communication is reduced. The control commands trigger the wing plane movement system as feedback information, transforming the dynamic network into a relatively static network to adapt to the improved LEACH algorithm.
An implementation step of a wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering method comprises the following steps:
step 1: unmanned aerial vehicle initialization distribution
The unmanned aerial vehicles are preliminarily distributed in a given area as required, and the unmanned aerial vehicles with different functions are deployed in the given area according to certain requirements according to the requirements for executing tasks, and are firstly randomly distributed in a given space, so that the initial number of the unmanned aerial vehicles is N respectively by taking reconnaissance unmanned aerial vehicles, defense unmanned aerial vehicles and attack unmanned aerial vehicles as examples1、N2And N3And carrying the same energy E0300J, each drone is set to 20 frames, N1＝N2＝N 320, initially the unmanned aerial vehicle is scattered randomly100×100×100m2The unmanned aerial vehicle base station as a central processing module initially hovers at the position with the coordinates of (50,50,50), and then the position is adjusted in real time along with the change of the network topology. Every unmanned aerial vehicle fuselage all carries on the spherical LED array of ultraviolet light to increase single LED's transmitting power in order to enlarge transmission radius, and then adapt to the demand of space transmission. Ultraviolet spherical LED arrays are shown in FIG. 2, each spherical LED array is composed of 18 single LEDs and is respectively positioned at the intersection of the warp and the weft;
step 2: partitioning of virtual grids
The maximum communication radius under the ultraviolet non-direct-view a-class communication mode can be obtained by OOK modulation, which is shown in fig. 3, wherein
Figure BDA0002454904430000091
And
Figure BDA0002454904430000092
elevation angle, theta, respectivelyTAngle of divergence, θRFor receiving angle of view, TxAnd RxRespectively representing a transmitting end and a receiving end. The communication radius at this time can be expressed as:
Figure BDA0002454904430000093
wherein α is path loss exponent, ξ is path loss factor, and the elevation angle is determined as the elevation angle of transmission and reception
Figure BDA0002454904430000094
And
Figure BDA0002454904430000095
all take 90 degrees, divergence angle thetaTAnd a reception angle of view thetaRRespectively, 17 °, 30 °, α ═ 1.23, ξ ═ 1.6 × 109And η is the quantum efficiency, R, of the filters and photodetectorsbInformation modulation rate, c is speed of light, h is Planck constant, lambda is wireless ultraviolet wavelength, PtTo emit optical power, PeIs the system error rate. As the links between the clusters are ordinary links, and the communication link from any virtual cluster head to the unmanned aerial vehicle base station is a backbone link. Because the bandwidth of the common link is limited, serial communication is realized in the cluster in a TDMA mode, a communication link from the cluster head to the unmanned aerial vehicle base station is a backbone link, and the parallel communication can be met due to large communication capacity. Therefore, the optimal virtual grid number can be obtained as follows:
Figure BDA0002454904430000101
wherein f iscIs the carrier frequency and B is the backbone link communication bandwidth.
Dividing m virtual grids, selecting a wing plane nearest to the centroid of each grid as a virtual cluster head, loading state information of each wing plane to an ultraviolet spherical LED array and sending the state information to the virtual cluster head in an OOK (on-off keying) modulation mode, and collecting and fusing the wing plane information in the virtual grids by the virtual cluster head and sending the information to an unmanned aerial vehicle base station to complete first data transmission. Fig. 4 is a plan top view of virtual grid division, and the projection coordinates of the initial position of the drone base station on the xoy plane are (50, 50).
And step 3: inter-cluster information forwarding for virtual cluster heads
The virtual cluster head collects and fuses state information of the wing plane in the virtual grid, and sends the fused information to the unmanned aerial vehicle base station, and if the distance d from the virtual cluster head to the unmanned aerial vehicle base station is smaller than or equal to the maximum communication radius rookThen the fusion information can be sent to the unmanned aerial vehicle base station as a one-hop neighbor node of the unmanned aerial vehicle base station, if d is larger than rookAnd then, through the rest virtual cluster heads, the fusion information is sent to the unmanned aerial vehicle base station through the multi-hop inter-cluster forwarding function, and the unmanned aerial vehicle base station serving as the central processing module sends out a central control instruction after mastering the state information of the global unmanned aerial vehicle, so as to guide all the wing plane machines to adjust the state distribution.
And 4, step 4: introducing LEACH clustering management mechanism
Aiming at a new bureaucratic plane distribution state, a clustering topology management mechanism of LEACH is introduced, and the maximum iteration round number is set as RmaxAs network lifetime, in turnsThe global network is managed in a cyclic manner, in each round, each bureaucratic party randomly generates a random number and compares it with a threshold election threshold t (n), when the random number is less than the election threshold, the cluster head of the round is elected, as follows:
Figure BDA0002454904430000111
where p is the percentage of cluster wing machines in all wing machines, R represents the current number of rounds,
Figure BDA0002454904430000112
represents the number of bureaucratic machines elected to a clusterhead in the round robin, and G is the bureaucratic machine set not elected to a clusterhead in the round robin.
And 5: threshold optimization in cluster election phase
Because formula (3) is the hard threshold election threshold, and the state (position, node degree, power and energy etc.) of unmanned aerial vehicle is dynamic change at any time in the network, consequently adopt soft threshold election threshold to improve unmanned aerial vehicle network cluster election stage, owing to have three kinds of unmanned aerial vehicles, be reconnaissance unmanned aerial vehicle, defend unmanned aerial vehicle and attack unmanned aerial vehicle respectively, can obtain one-level soft threshold election threshold through optimizing formula (3) and do:
Figure BDA0002454904430000113
wherein k is 1,2,3,
Figure BDA0002454904430000121
n1、n2、n3the number of three types of unmanned aerial vehicles with current wheels not failed, Tk(n)' is a primary soft threshold election threshold of the kth type unmanned plane; considering factors such as the distance from the bureaucratic plane to the base station of the unmanned aerial vehicle, the residual energy, the node degree, the residual electric quantity and the like, the formula (4) is further optimized to obtain a second-level soft threshold election threshold as follows:
Figure BDA0002454904430000122
wherein,
Figure BDA0002454904430000123
the second-level soft threshold election threshold for the unmanned aerial vehicle of three task types can be obtained through the formula (5): t isk(n) ". Wherein w1、w2、w3、w4Respectively, distance weight factor, energy weight factor, node degree weight factor, electric quantity weight factor, Disti、Ei、DiAnd PoweriThe distance from a wing plane i to the base station of the unmanned plane in the R-th wheel, the remaining energy of the wing plane i, the node degree of the wing plane i, and the remaining electric quantity of the wing plane i, respectively.
Figure BDA0002454904430000124
And
Figure BDA0002454904430000125
the average distance between a wing plane not in failure at the R-th wheel to the base station of the drone, the average remaining energy of the wing plane not in failure, the average degree of nodes of the wing plane not in failure and the average remaining electric quantity of the wing plane not in failure, respectively. The soft threshold is adopted to simulate special scenes to verify the effectiveness of the optimization scheme, namely three types of unmanned aerial vehicles based on task allocation are simplified into one type of unmanned aerial vehicle: the reconnaissance unmanned aerial vehicle can verify the simulation result from the aspects of energy consumption and death node number of the network as shown in fig. 5. Simulation results show that the soft threshold optimization scheme BEAD-LEACH can effectively balance network energy consumption by optimizing a cluster head election stage and prolong the life cycle of a network.
Step 6: stable data transmission phase
The first stage of the LEACH clustering mechanism is a cluster head election stage, after the cluster head election stage is finished, the elected cluster head broadcasts identity information to the whole network, the remaining wing machines select the wing machine belonging to the closest distance to the elected cluster head through the principle of minimum communication cost as the cluster head and send a request cluster entering message, after the cluster forming stage is finished, the cluster head allocates communication time slots for each member in the cluster and then collects and fuses the state information of the members in the cluster, and a one-hop sending mode or a multi-hop sending mode can be adopted in the cluster. And the cluster head transmits the information obtained by fusion to the unmanned aerial vehicle base station in a parallel transmission mode.
And 7: control instruction guides unmanned aerial vehicle state to be updated
Fig. 6 is a schematic diagram of a control instruction guiding a state update of an unmanned aerial vehicle, where a base station of the unmanned aerial vehicle receives fusion data of each cluster head, and can obtain state information of a global unmanned aerial vehicle, so as to make a judgment on the global situation, send a central control instruction to be transmitted to each wing plane again via the cluster head, where the central control instruction serves as a feedback signal to trigger a wing plane movement system to start up, plan movement to a corresponding position according to a trajectory of the control instruction, and an airborne anti-collision sensing device provides a guarantee for anti-collision when a wing plane position is updated. And when the updated position state is consistent with the position guided by the feedback signal, closing the motion system, entering a sleep state, and waiting for triggering of the feedback signal at the next moment. The central control instruction is used as feedback information to trigger a wing plane movement system, the unmanned plane is guided to move as required to change the current state, a dynamic network is converted into a relatively static network, and the limitation that LEACH is used for the static network is broken. At this time, the number of rounds R is added with 1, and the number of rounds R and the preset lifetime R are determinedmaxIn a relationship between, if R is less than or equal to RmaxTurning to the step 4; if R is not less than RmaxAnd ending the dynamic clustering method and jumping out of the loop.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and that the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are within the scope of the invention.

Claims (9)

1.一种无线紫外光协作无人机隐秘动态分簇系统，其特征在于，包括无人机与中央处理模块通过大气对无线紫外光的散射作用进行通信，所述每个无人机机身上均搭载紫外光球形LED阵列和防碰撞感应装置，所述紫外光球形LED阵列由18个单颗LED构成，分别位于球的经线和纬线交汇处，所述中央处理模块为无人机基站。1. a wireless ultraviolet light cooperative unmanned aerial vehicle stealth dynamic clustering system, is characterized in that, comprises unmanned aerial vehicle and central processing module to communicate by the scattering effect of wireless ultraviolet light by atmosphere, and described each unmanned aerial vehicle body Both are equipped with an ultraviolet spherical LED array and an anti-collision sensing device. The ultraviolet spherical LED array is composed of 18 single LEDs, which are respectively located at the intersection of the warp and latitude of the ball. The central processing module is a drone base station. 2.一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，包括以下步骤：2. a wireless ultraviolet cooperative unmanned aerial vehicle secret dynamic clustering method, is characterized in that, comprises the following steps: 步骤1：无人机初始化分布；Step 1: UAV initialization distribution; 步骤2：通过载波与带宽的关系构造出最优虚拟栅格数，对初始状态的无人机进行初步管理，通过距虚拟质心距离最小的原则选举虚拟簇首，先进行一次数据传输；Step 2: Construct the optimal number of virtual grids based on the relationship between the carrier and the bandwidth, conduct preliminary management of the UAV in the initial state, elect the virtual cluster head according to the principle of the smallest distance from the virtual center of mass, and perform a data transmission first; 步骤3：通过虚拟簇首将各栅格中的僚机信息发送至无人机基站，并由无人机基站根据状态信息作出相应反馈控制指令，指引全网僚机初步作出位置更新；Step 3: Send the wingman information in each grid to the UAV base station through the virtual cluster head, and the UAV base station will make corresponding feedback control commands according to the status information, and guide the entire network wingman to make a preliminary position update; 步骤4：引入LEACH分簇管理机制，针对新的僚机分布状态，引入LEACH的分簇拓扑管理机制，设置最大迭代轮数为Rmax作为网络生存期，以轮循工作方式管理全局网络，在每一轮中，每个僚机会随机产生随机数，并且与阈值选举门限比较，如果随机数小于选举门限则当选本轮簇首；Step 4: Introduce the LEACH clustering management mechanism. For the new wingman distribution status, introduce the LEACH clustering topology management mechanism, set the maximum number of iteration rounds to Rmax as the network lifetime, and manage the global network in a round-robin manner. In a round, each wingman will randomly generate a random number and compare it with the threshold election threshold. If the random number is less than the election threshold, it will be elected as the cluster head of the current round; 步骤5：簇首选举阶段阈值优化；Step 5: Optimize the threshold in the cluster head election stage; 步骤6：稳定的数据传输阶段；Step 6: Stable data transmission stage; 步骤7：控制指令引导无人机状态更新。Step 7: The control command guides the UAV status update. 3.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤1的具体做法为：3. a kind of wireless ultraviolet light cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 1 is: 无人机按需初步分布在给定区域，按照执行任务的需求，不同功能的无人机按照一定需求部署相应数量于给定区域，首先在给定空间随机分布，以侦察无人机、防守无人机以及攻击无人机为例，三类无人机的初始数目分别为N1、N2以及N3，并携带同等能量E0＝300J，每种无人机分别设置成20架，即N1＝N2＝N3＝20，初始时无人机随机散落分布在100×100×100m2的空间区域，无人机基站作为中央处理模块初始悬停于坐标为(50,50,50)处，之后随着网络拓扑的变化，实时调整位置。UAVs are initially distributed in a given area as needed. According to the needs of performing tasks, UAVs with different functions are deployed in a corresponding number in a given area according to certain requirements. First, they are randomly distributed in a given space to scout UAVs and defend them. Take drones and attack drones as examples, the initial numbers of three types of drones are N 1 , N 2 and N 3 respectively, and carry the same energy E 0 =300J, each type of drone is set to 20, respectively. That is, N 1 =N 2 =N 3 =20, the UAVs are randomly scattered in a space area of 100×100×100m 2 at the beginning, and the UAV base station as the central processing module initially hovers at the coordinates (50,50, 50), and then adjust the position in real time as the network topology changes. 4.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤2的具体做法为：4. a kind of wireless ultraviolet light cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 2 is: 采用OOK调制可以得到在紫外光非直视A类通信方式下的最大通信半径，通信半径可以表示为：The OOK modulation can be used to obtain the maximum communication radius under the non-direct line-of-sight type A communication mode of ultraviolet light, and the communication radius can be expressed as:
Figure FDA0002454904420000021
Figure FDA0002454904420000021
 其中，α为路径损耗指数，ξ为路径损耗因子，η为滤光片和光电探测器的量子效率，Rb信息调制速率，c为光速，h为普朗克常数，λ为无线紫外光波长，Pt为发射光功率，Pe为系统误码率；where α is the path loss index, ξ is the path loss factor, η is the quantum efficiency of the filter and photodetector, R b is the information modulation rate, c is the speed of light, h is Planck's constant, and λ is the wavelength of wireless ultraviolet light , P t is the transmitted optical power, and P e is the system bit error rate; 由于簇内之间的链路为普通链路，而任意虚拟簇首至无人机基站的通信链路为骨干链路；普通链路带宽有限，因此簇内通过TDMA方式实现串行通信，簇首至无人机基站的通信链路为骨干链路，通信容量大可以满足并行通信，因此可以得到最佳虚拟栅格数为：Since the links between clusters are ordinary links, and the communication link from any virtual cluster head to the UAV base station is the backbone link; the bandwidth of ordinary links is limited, so serial communication is realized in the cluster through TDMA, and the cluster The first communication link to the UAV base station is the backbone link, and the communication capacity is large enough to meet parallel communication. Therefore, the optimal number of virtual grids can be obtained as:
Figure FDA0002454904420000031
Figure FDA0002454904420000031
 其中，fc为载波频率，B为骨干链路通信带宽；Among them, f c is the carrier frequency, and B is the communication bandwidth of the backbone link; 划分m个虚拟栅格并选出与每个栅格质心最近僚机作为虚拟簇首，每个僚机采用OOK调制方式，将自身的状态信息加载至紫外光球形LED阵列发送至虚拟簇首，虚拟簇首对虚拟栅格中的僚机信息进行收集融合，并发送至无人机基站，先完成第一次数据传输。Divide m virtual grids and select the wingman closest to the centroid of each grid as the virtual cluster head. Each wingman uses the OOK modulation method to load its own state information into the ultraviolet spherical LED array and send it to the virtual cluster head. First, collect and fuse the wingman information in the virtual grid, and send it to the UAV base station, and complete the first data transmission first. 5.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤3的具体做法为：5. a kind of wireless ultraviolet cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 3 is: 虚拟簇首将虚拟栅格中的僚机状态信息收集融合，并将融合信息发送给无人机基站，若虚拟簇首至无人机基站的距离d小于或等于最大通信半径rook，则可以作为无人机基站的一跳邻居节点将融合信息发送至无人机基站，如果d＞rook，则通过其余虚拟簇首，经过多跳簇间转发功能将融合信息发送至无人机基站，作为中央处理模块的无人机基站掌握全局无人机状态信息后，发出中央控制指令，指引所有僚机调整状态分布。The virtual cluster head collects and fuses the wingman status information in the virtual grid, and sends the fusion information to the UAV base station. If the distance d from the virtual cluster head to the UAV base station is less than or equal to the maximum communication radius r ook , it can be used as The one-hop neighbor node of the UAV base station sends the fusion information to the UAV base station. If d > r ook , the fusion information is sent to the UAV base station through the multi-hop inter-cluster forwarding function through the remaining virtual cluster heads, as After the UAV base station of the central processing module grasps the global UAV status information, it issues a central control command to guide all wingmen to adjust the status distribution. 6.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤4的具体做法为：6. a kind of wireless ultraviolet light cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 4 is: 针对新的僚机分布状态，引入LEACH的分簇拓扑管理机制，设置最大迭代轮数为Rmax作为网络生存期，以轮循工作方式管理全局网络，在每一轮中，每个僚机会随机产生随机数，并且与阈值选举门限T(n)比较，如果随机数小于阈值选举门限则当选本轮簇首，具体如下：In view of the new wingman distribution state, the clustering topology management mechanism of LEACH is introduced, and the maximum number of iteration rounds is set as Rmax as the network lifetime, and the global network is managed in a round-robin manner. In each round, each wingman will be randomly generated. The random number is compared with the threshold election threshold T(n). If the random number is less than the threshold election threshold, it will be elected as the cluster head of this round, as follows:
Figure FDA0002454904420000041
Figure FDA0002454904420000041
 其中p是簇首僚机在所有僚机中所占的百分比，R代表当前轮数，
Figure FDA0002454904420000042
代表这一轮循环中当选过簇首的僚机个数，G是这一轮循环中未当选过簇首的僚机集合。where p is the percentage of the cluster head wingman among all wingmen, R is the current number of rounds,
Figure FDA0002454904420000042
Represents the number of wingmen who have been elected as cluster heads in this round, and G is the set of wingmen who have not been elected as cluster heads in this round. 7.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤5的具体做法为：7. a kind of wireless ultraviolet light cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 5 is: 由于步骤4公式(3)为硬阈值选举门限，而网络中无人机的状态，如位置、节点度、功率以及能量等是随时动态变化的，因此采用软阈值选举门限对无人机网络簇首选举阶段进行改进，由于有三类无人机，分别为侦察无人机、防守无人机以及攻击无人机，通过优化公式(3)可以得到一级软阈值选举门限为：Since formula (3) in step 4 is the hard threshold election threshold, and the status of the UAVs in the network, such as position, node degree, power and energy, changes dynamically at any time, the soft threshold election threshold is used for the UAV network cluster. Improvements are made in the first election stage. Since there are three types of UAVs, namely, reconnaissance UAVs, defensive UAVs and attack UAVs, the first-level soft threshold election threshold can be obtained by optimizing formula (3):
Figure FDA0002454904420000043
Figure FDA0002454904420000043
 其中k＝1,2,3，
Figure FDA0002454904420000044
n1、n2、n3分别为当前轮未失效的三类无人机数量，Tk(n)′为第k类无人机的一级软阈值选举门限；考虑第R轮中僚机至无人机基站的距离、剩余能量、节点度以及剩余电量等因素，对公式(4)进一步优化得到二级软阈值选举门限为：where k=1,2,3,
Figure FDA0002454904420000044
n 1 , n 2 , and n 3 are the number of three types of UAVs that have not failed in the current round, respectively, and T k (n)′ is the first-level soft threshold election threshold for the k-th UAV; Factors such as the distance, remaining energy, node degree, and remaining power of the UAV base station are further optimized by formula (4) to obtain the second-level soft threshold election threshold:
Figure FDA0002454904420000051
Figure FDA0002454904420000051
 其中，
Figure FDA0002454904420000052
通过公式(5)可以得到针对三种任务类型无人机的二级软阈值选举门限：Tk(n)″，其中w1、w2、w3、w4分别为距离权重因子、能量权重因子、节点度权重因子以及电量权重因子，Disti、Ei、Di以及Poweri分别为第k类无人机在第R轮中僚机i到无人机基站的距离、僚机i的剩余能量、僚机i的节点度以及僚机i的剩余电量，
Figure FDA0002454904420000053
以及
Figure FDA0002454904420000054
分别为第k类无人机在第R轮未失效僚机至无人机基站的平均距离、未失效僚机的平均剩余能量、未失效僚机的平均节点度以及未失效僚机的平均剩余电量。in,
Figure FDA0002454904420000052
By formula (5), the secondary soft threshold selection threshold for three types of UAVs can be obtained: T k (n)”, where w 1 , w 2 , w 3 , and w 4 are the distance weight factor and energy weight, respectively factor, node degree weight factor and power weight factor, Dist i , E i , D i and Power i are the distance from wingman i to the base station of the drone and the remaining energy of wingman i in the R round of the k-th UAV, respectively , the node degree of wingman i and the remaining power of wingman i,
Figure FDA0002454904420000053
as well as
Figure FDA0002454904420000054
are the average distance from the non-failed wingman to the base station of the k-th type of UAV in the R round, the average remaining energy of the non-failed wingman, the average node degree of the non-failed wingman, and the average remaining power of the non-failed wingman. 8.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤6的具体做法为：8. a kind of wireless ultraviolet cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 6 is: LEACH分簇机制的第一阶段为簇首选举阶段，待簇首选举阶段结束后，当选的簇首向整个网络广播身份信息，其余僚机通过通信代价最小原则选择从属于与之距离最近的僚机作为簇首，并发送请求入簇消息，待成簇阶段结束，簇首为每个簇内成员分配通信时隙、之后收集并融合簇内成员状态信息，簇内可以采用一跳发送方式或多跳发送方式，簇首再将融合所得信息通过并行传输方式传送至无人机基站。The first stage of the LEACH clustering mechanism is the cluster head election stage. After the cluster head election stage is over, the elected cluster head broadcasts the identity information to the entire network, and the rest of the wingmen select the wingman with the closest distance to it through the principle of minimum communication cost. The cluster head sends a request to join the cluster. When the clustering phase ends, the cluster head allocates a communication time slot for each member in the cluster, and then collects and fuses the status information of the members in the cluster. One-hop transmission or multi-hop transmission can be used in the cluster. The cluster head then transmits the information obtained from the fusion to the UAV base station through parallel transmission. 9.根据权利要求2所述的一种无线紫外光协作无人机隐秘动态分簇方法，其特征在于，所述步骤7的具体做法为：9. a kind of wireless ultraviolet light cooperative unmanned aerial vehicle secret dynamic clustering method according to claim 2, is characterized in that, the concrete practice of described step 7 is: 无人机基站收到各个簇首的融合数据，可以得到全局无人机的状态信息，从而对全局做出判断，发送中央控制指令经由簇首再次传输至各个僚机，中央控制指令作为反馈信号触发僚机运动系统启动，按照控制指令的航迹规划运动至对应位置，机载的防碰撞感应装置为僚机位置更新时的防碰撞提供了保障；当更新的位置状态与反馈信号指引位置达到匹配一致后，运动系统关闭并进入睡眠状态，等待下一时刻反馈信号的触发，而此时轮数R加1，判断轮数R与预设生存期Rmax之间的关系，若R≤Rmax，转至步骤4；若R≥Rmax动态分簇方法结束，跳出循环。The UAV base station receives the fusion data of each cluster head, and can obtain the status information of the global UAV, so as to make a global judgment, and send the central control command to be transmitted to each wingman again through the cluster head, and the central control command is triggered as a feedback signal. The wingman motion system is activated, and moves to the corresponding position according to the track plan of the control command. The on-board anti-collision sensing device provides a guarantee for the anti-collision when the wingman position is updated; when the updated position state and the feedback signal guide position are matched and consistent , the motion system shuts down and enters the sleep state, waiting for the trigger of the feedback signal at the next moment, and at this time, the number of rounds R is increased by 1, and the relationship between the number of rounds R and the preset lifetime Rmax is judged. If R≤Rmax , turn Go to step 4; if the R≥R max dynamic clustering method ends, jump out of the loop.
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