CN111601356B - Wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering system and method - Google Patents
Wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering system and method Download PDFInfo
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Abstract
A wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering system and method, each unmanned aerial vehicle carries with ultraviolet light spherical LED array, the multitasking unmanned aerial vehicle distributes randomly in the appointed space initially, divide the virtual grid preliminarily through the relation of the total bandwidth and carrier, choose the virtual cluster head in each virtual grid; the virtual cluster head fuses the state information of the plane in each grid and transmits the state information to the unmanned aerial vehicle base station, and after the unmanned aerial vehicle base station grasps the global information, the control command is transmitted to each plane through the cluster head, and each plane realizes the position state update according to the control command; then introducing an optimized second-level soft threshold to improve the cluster first-choice stage, completing the information transmission of the whole network, and reducing the load consumption of communication; the control command is used as feedback information to trigger the plane motion system to convert the dynamic network into the static network for the improved LEACH algorithm. The invention solves the clustering problem of the unmanned aerial vehicle dynamic network, thereby realizing the energy balance of unmanned aerial vehicle communication.
Description
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 secret dynamic clustering system and method.
Background
The unmanned aerial vehicle network is a dynamic real-time network, and the real-time reliable communication between unmanned aerial vehicles is particularly important. In a battlefield environment with instantaneous change, when the unmanned aerial vehicle executes various military tasks, such as supervision, defending, hitting tasks and the like, threats such as radio silence, radio interception, electronic countermeasure and the like are faced, so that the communication safety problem among unmanned aerial vehicles becomes severe, an ultraviolet light secret communication mode is introduced, an ultraviolet light spherical LED array is mounted on an unmanned aerial vehicle body, and information is modulated and loaded to an ultraviolet light source to realize information transmission.
Because ultraviolet light communication is carried out by means of ultraviolet light of a solar blind wave band of 200-280 nm, background noise is low, and scattering effects of atmospheric molecules, dust particles, aerosol and the like in a space environment on light waves are achieved, the limitation that other communication systems must directly see communication is broken through by the ultraviolet light communication, and in addition, the ultraviolet light communication has the advantages of being all-weather, high in anti-interference capability, high in confidentiality and the like, and the ultraviolet light communication has a wide application scene in a secret communication scene. In addition, the load energy of the unmanned aerial vehicle is very limited, and the unmanned aerial vehicle is invalid due to the energy consumption, so that the network interruption is very unfavorable to the unmanned aerial vehicle network. Therefore, a LEACH (Low Energy Adaptive Clustering Hierarchy) round-robin clustering topology management mechanism is introduced, a movement system of the unmanned aerial vehicle is triggered through a central feedback signal, a dynamic unmanned aerial vehicle network is managed into a stepwise movement unmanned aerial vehicle network through a feedback trigger mechanism, and the limitation that the clustering management mechanism is only applicable to static scenes is broken, so that management and feedback of information of each unmanned aerial vehicle in the unmanned aerial vehicle network are realized, communication energy consumption of the unmanned aerial vehicle is balanced, the survival time of the unmanned aerial vehicle network is prolonged, and more time is striven for the unmanned aerial vehicle to sense a battlefield situation.
Disclosure of Invention
The invention aims to provide a wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering system and method, which solve the clustering problem of a unmanned aerial vehicle dynamic network, thereby realizing unmanned aerial vehicle communication energy balance.
The technical scheme adopted by the invention is as follows:
the utility model provides a wireless ultraviolet light cooperation unmanned aerial vehicle stealthy developments cluster system, includes unmanned aerial vehicle and central processing module and communicates wireless ultraviolet light's scattering effect through the atmosphere, all carry on ultraviolet light spherical LED array and anti-collision induction system on every unmanned aerial vehicle fuselage, ultraviolet light spherical LED array comprises 18 single LEDs, is located the longitude and latitude junction of ball respectively, central processing module is the unmanned aerial vehicle basic station.
A wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering method comprises the following steps:
step 1: initializing distribution of unmanned aerial vehicles;
step 2: constructing an optimal virtual grid number through the relation between carrier waves and bandwidth, primarily managing the unmanned aerial vehicle in an initial state, selecting a virtual cluster head through the principle that the distance from the virtual centroid is minimum, and carrying out primary data transmission, wherein the method comprises the following specific steps:
the maximum communication radius under the ultraviolet light non-direct view A type communication mode is obtained by OOK modulation, and the communication radius is expressed as:
where α is the path loss index, ζ is the path loss factor, η is the quantum efficiency of the filter and photodetector, R b Information modulation rate, c is light speed, h is Planck constant, lambda is wireless ultraviolet wavelength, P t To transmit optical power, P e The error rate of the system;
the links between clusters are common links, serial communication is realized in the clusters in a TDMA mode, the communication link from the cluster head to the unmanned aerial vehicle base station is a backbone link, the communication capacity meets the parallel communication, and the optimal virtual grid number is obtained as follows:
wherein f c The carrier frequency is used, and B is backbone link communication bandwidth;
dividing m virtual grids, selecting the plane closest to the center of mass of each grid as a virtual cluster head, loading self state information to an ultraviolet spherical LED array by each plane in an OOK modulation mode, sending the ultraviolet spherical LED array to the virtual cluster head, collecting and fusing plane information in the virtual grids by the virtual cluster head, and sending the plane information to an unmanned plane base station, and finishing first data transmission;
step 3: the method comprises the steps of sending the information of the plane in each grid to an unmanned aerial vehicle base station through a virtual cluster head, and making a feedback control instruction by the unmanned aerial vehicle base station according to state information to guide the whole-network plane to make position update, wherein the specific method comprises the following steps:
the virtual cluster head collects and fuses the state information of the plane in the virtual grid and sends the fused information to the unmanned aerial vehicle base station, if the distance d between the virtual cluster head and the unmanned aerial vehicle base station is smaller than or equal to the maximum communication radius r ook The one-hop neighbor node serving as the unmanned aerial vehicle base station sends the fusion information to the unmanned aerial vehicle base station, if d is larger than r ook Then through the rest virtual cluster heads, through multi-hopThe inter-cluster forwarding function sends the fusion information to the unmanned aerial vehicle base station, and the unmanned aerial vehicle base station serving as a central processing module grasps the global unmanned aerial vehicle state information and then sends a central control instruction to guide all the unmanned aerial vehicles to adjust the state distribution;
step 4: aiming at a new wing distribution state, a clustering topology management mechanism of LEACH is introduced, and the maximum iteration round number is set as R max As a network lifetime, the global network is managed in a round-robin working mode, in each round, each wing machine randomly generates a random number, and compared with a threshold election threshold T (n), if the random number is smaller than the threshold election threshold, the current round cluster head is selected, which comprises the following steps:
wherein p is the percentage of the cluster head plane in all the planes, R represents the current number of wheels,the number of the wing machines selected from the cluster head in the round of circulation is represented, and G is a set of the wing machines not selected from the cluster head in the round of circulation;
step 5: the cluster first-choice stage threshold optimization method comprises the following specific steps:
because the formula (3) in the step 4 is a hard threshold election threshold, and the position, node degree, power and energy of the unmanned aerial vehicle in the network are dynamically changed at any time, the soft threshold election threshold is adopted to improve the first election stage of the unmanned aerial vehicle network cluster, and three types of unmanned aerial vehicles are respectively a reconnaissance unmanned aerial vehicle, a defending unmanned aerial vehicle and an attack unmanned aerial vehicle, and the first-level soft threshold election threshold is obtained through the optimization formula (3):
where k=1, 2,3,n 1 、n 2 、n 3 respectively the number T of three unmanned aerial vehicles with the current wheel not disabled k (n)' is a first-level soft threshold election threshold of the kth class unmanned aerial vehicle; considering the factors of the distance from the plane to the unmanned plane base station in the R-th wheel, the residual energy, the node degree and the residual electric quantity, further optimizing the formula (4) to obtain a secondary soft threshold election threshold as follows:
wherein,obtaining a second-level soft threshold election threshold for three task type unmanned aerial vehicles through a formula (5): t (T) k (n) ", wherein w 1 、w 2 、w 3 、w 4 Distance weight factor, energy weight factor, node degree weight factor and electric quantity weight factor, dist respectively i 、E i 、D i Power i The distance from the plane i to the base station of the unmanned plane in the R wheel, the residual energy of the plane i, the node degree of the plane i and the residual electric quantity of the plane i are respectively the k-th unmanned plane>And +.>The average distance from the non-failed plane to the unmanned plane base station of the R wheel of the k-type unmanned plane, the average residual energy of the non-failed plane, the average node degree of the non-failed plane and the average residual electric quantity of the non-failed plane are respectively;
step 6: a stable data transmission phase;
step 7: the control instructions direct the unmanned aerial vehicle status update.
Further, the specific implementation of the step 1 is as follows:
the unmanned aerial vehicle is preliminarily distributed in a given area according to the need and executes tasksAccording to the requirements of different functions, corresponding number of unmanned aerial vehicles are deployed in a given area according to a certain requirement, the unmanned aerial vehicles are randomly distributed in a given space, the reconnaissance unmanned aerial vehicle, the defending unmanned aerial vehicle and the attack unmanned aerial vehicle are respectively N in initial number 1 、N 2 N 3 And carrying the same energy E 0 =300J, each unmanned aerial vehicle is arranged in 20 frames, i.e. N 1 ＝N 2 ＝N 3 The number of the samples is =20, the unmanned aerial vehicle is randomly scattered and distributed in 100 multiplied by 100m in the initial period 3 The unmanned aerial vehicle base station as a central processing module initially hovers at coordinates (50,50,50) and then adjusts position in real time as the network topology changes.
Further, the specific implementation of the step 6 is as follows:
the first stage of the LEACH clustering mechanism is a cluster first-choice lifting stage, after the cluster first-choice lifting stage is finished, the selected cluster head broadcasts identity information to the whole network, other auxiliary machines select a slave machine closest to the selected auxiliary machine as the cluster head through a communication cost minimum principle, and send a request-to-enter cluster message, after the clustering stage is finished, the cluster head distributes communication time slots for each member in the cluster, then collects and fuses member state information in the cluster, a one-hop transmission mode or a multi-hop transmission mode is adopted in the cluster, and the cluster head transmits fused information to an unmanned aerial vehicle base station through a parallel transmission mode.
Further, the specific implementation of the step 7 is as follows:
the unmanned aerial vehicle base station receives the fusion data of each cluster head, obtains the state information of the global unmanned aerial vehicle, makes judgment on the global, sends a central control instruction to each auxiliary plane again through the cluster head, and uses the central control instruction as a feedback signal to trigger the auxiliary plane motion system to start, and moves to the corresponding position according to the track planning of the control instruction, so that an onboard anti-collision sensing device provides a guarantee for anti-collision during the updating of the auxiliary plane position; when the updated position state is matched with the feedback signal guiding position, the motion system is closed and enters a sleep state, the feedback signal is triggered at the next moment, the number of rounds R is increased by 1, and the number of rounds R and the preset lifetime R are judged max The relation between R and R is smaller than or equal to R max Turning to step 4; if R is greater than or equal to R max And (5) ending the dynamic clustering method and jumping out of the circulation.
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 primarily managing scattered unmanned aerial vehicle states into ordered states.
(2) The feedback instruction triggers the unmanned aerial vehicle to move: the unmanned aerial vehicle base station transmits a central control instruction to each cluster head through an ultraviolet light source, each cluster head is locally transmitted to member unmanned aerial vehicles in each cluster, the unmanned aerial vehicles are guided to move as required, the current state is changed, and a dynamic network is converted into a relatively static network so as to be suitable for a cluster management mechanism.
(3) Determination of cluster first-choice stage soft threshold: and selecting unmanned aerial vehicles meeting certain conditions as cluster heads according to the optimized soft threshold 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 spherical LED array;
FIG. 3 is a schematic illustration of UV light non-direct view type A communication;
FIG. 4 is a schematic diagram of a virtual grid division of a network of unmanned aerial vehicles;
FIG. 5 is a schematic diagram of a simulation of a preferred lift phase of a two-level soft threshold improvement cluster;
fig. 6 is a schematic diagram of control instruction guided drone status update.
Detailed Description
The invention will be described in detail below with reference to the drawings and the detailed description.
Aiming at the problem of network communication energy consumption of unmanned aerial vehicle which threatens information security, a wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering system and a method are provided.
The utility model provides a wireless ultraviolet light cooperation unmanned aerial vehicle stealthy developments cluster system, includes that unmanned aerial vehicle communicates through the scattering effect of atmosphere to wireless ultraviolet light with central processing module, all carries on ultraviolet light spherical LED array and anticollision induction system on every unmanned aerial vehicle fuselage, and ultraviolet light spherical LED array comprises 18 single LEDs, is located the warp and the weft junction of ball respectively, central processing module is the unmanned aerial vehicle basic station.
Fig. 1 is a flow chart of a secret dynamic clustering method of a wireless ultraviolet light cooperation unmanned aerial vehicle, wherein a multi-task unmanned aerial vehicle is randomly distributed in a designated space initially, virtual grids are initially divided through the relation between total bandwidth and carrier waves, and virtual cluster heads are selected from each virtual grid; the virtual cluster head fuses the state information of the plane in each grid and transmits the state information to the unmanned plane base station, and after the unmanned plane base station grasps the global information, the control command is transmitted to each plane through the cluster head, and each plane realizes the position state update according to the control command; and then, introducing an optimized second-level soft threshold to improve the cluster first-choice stage, completing the information transmission of the whole network, and reducing the load consumption of communication. The control command is used as feedback information to trigger the plane motion system to convert the dynamic network into the static network for the improved LEACH algorithm.
The implementation steps of the wireless ultraviolet light cooperation unmanned aerial vehicle secret dynamic clustering method are as follows:
step 1: unmanned aerial vehicle initialization distribution
Unmanned aerial vehicles are preliminarily distributed in a given area according to the requirement of executing tasks, unmanned aerial vehicles with different functions are deployed in corresponding numbers in the given area according to certain requirements, are randomly distributed in a given space, and the initial numbers of three unmanned aerial vehicles are N respectively, taking a reconnaissance unmanned aerial vehicle, a defending unmanned aerial vehicle and an attack unmanned aerial vehicle as examples 1 、N 2 N 3 And carrying the same energy E 0 =300J, each unmanned aerial vehicle is arranged in 20 frames, i.e. N 1 ＝N 2 ＝N 3 The number of the samples is =20, the unmanned aerial vehicle is randomly scattered and distributed in 100 multiplied by 100m in the initial period 3 The unmanned aerial vehicle base station as a central processing module initially hovers at coordinates (50,50,50) and then adjusts position in real time as the network topology changes. Each unmanned aerial vehicle body is provided with an ultraviolet spherical LED array, so that the emission power of a single LED is increased to enlarge the transmission radius, and the unmanned aerial vehicle entersAnd is adapted to the space transmission requirements. The ultraviolet spherical LED arrays are shown in fig. 2, and each spherical LED array consists of 18 single LEDs and is respectively positioned at the intersection of warp and weft;
step 2: partitioning of virtual grids
The maximum communication radius under the ultraviolet light non-direct view A type communication mode can be obtained by OOK modulation, the ultraviolet light non-direct view A type communication mode is shown in figure 3, whereinAnd->Respectively transmit and receive elevation angle, theta T Is the divergence angle, theta R To receive the angle of view, T x And R is x Representing the transmitting end and the receiving end, respectively. The communication radius at this time can be expressed as:
where α is the path loss index, ζ is the path loss factor, when receiving and transmitting elevation angleAnd->All take 90 degrees and the divergence angle theta T And a receiving field angle theta R Respectively taking 17 degrees, 30 degrees, alpha=1.23 degrees, xi=1.6×10 degrees 9 Eta is the quantum efficiency of the optical filter and the photoelectric detector, R b Information modulation rate, c is light speed, h is Planck constant, lambda is wireless ultraviolet wavelength, P t To transmit optical power, P e Is the system error rate. Because links between clusters are common links, and communication links from any virtual cluster head to the unmanned aerial vehicle base station are backbone links. Because the common link bandwidth is limited, serial communication is realized in the cluster in a TDMA mode, and the communication link from the cluster head to the unmanned aerial vehicle base station is a backbone link and is communicatedThe capacity is large to meet the parallel communication. The optimal virtual grid number can be obtained as follows:
wherein f c And B is the backbone link communication bandwidth for the carrier frequency.
Dividing m virtual grids, selecting the closest plane with the mass center of each grid as a virtual cluster head, loading the state information of each plane to an ultraviolet spherical LED array by adopting an OOK modulation mode, sending the ultraviolet spherical LED array to the virtual cluster head, collecting and fusing the plane information in the virtual grids by the virtual cluster head, and sending the plane information to an unmanned plane base station, and finishing first data transmission. Fig. 4 is a plan view of virtual grid division, where the projection coordinates of the initial position of the base station of the unmanned aerial vehicle on the xoy plane are (50, 50).
Step 3: inter-cluster information forwarding for virtual cluster heads
The virtual cluster head collects and fuses the state information of the plane in the virtual grid and sends the fused information to the unmanned aerial vehicle base station, if the distance d between the virtual cluster head and the unmanned aerial vehicle base station is smaller than or equal to the maximum communication radius r ook 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 r ook And transmitting the fusion information to the unmanned aerial vehicle base station through the rest virtual cluster heads and the multi-hop inter-cluster forwarding function, and after the unmanned aerial vehicle base station serving as a central processing module grasps the global unmanned aerial vehicle state information, sending a central control instruction to guide all the auxiliary machines to adjust the state distribution.
Step 4: introducing LEACH clustering management mechanism
Aiming at a new wing distribution state, a clustering topology management mechanism of LEACH is introduced, and the maximum iteration round number is set as R max As a network lifetime, the global network is managed in a round-robin operation mode, in each round, each wing machine randomly generates a random number, and compared with a threshold election threshold T (n), if the random number is smaller than the election threshold, the cluster head of the round is elected, and the method specifically comprises the following steps:
wherein p is the percentage of the cluster head plane in all the planes, R represents the current number of wheels,and G represents the number of the wing machines which select the cluster head in the round of circulation, and G is the set of the wing machines which do not select the cluster head in the round of circulation.
Step 5: cluster first-choice lifting phase threshold optimization
Because formula (3) is a hard threshold election threshold, and the states (positions, node degrees, power, energy and the like) of unmanned aerial vehicles in the network are dynamically changed at any time, the first-choice stage of the unmanned aerial vehicle network cluster is improved by adopting a soft threshold election threshold, and three types of unmanned aerial vehicles are respectively a reconnaissance unmanned aerial vehicle, a defending unmanned aerial vehicle and an attack unmanned aerial vehicle, and the first-class soft threshold election threshold can be obtained by optimizing formula (3):
where k=1, 2,3,n 1 、n 2 、n 3 respectively the number T of three unmanned aerial vehicles with the current wheel not disabled k (n)' is a first-level soft threshold election threshold of the kth class unmanned aerial vehicle; considering factors such as distance from a plane in the R-th wheel to a base station of the unmanned aerial vehicle, residual energy, node degree, residual electric quantity and the like, further optimizing the formula (4) to obtain a secondary soft threshold election threshold as follows:
wherein,the two-level soft threshold election threshold for three task type unmanned aerial vehicles can be obtained through the formula (5): t (T) k (n) ". Wherein w is 1 、w 2 、w 3 、w 4 Distance weight factor, energy weight factor, node degree weight factor and electric quantity weight factor, dist respectively i 、E i 、D i Power i The distance from the plane i to the base station of the unmanned plane in the R wheel, the residual energy of the plane i, the node degree of the plane i and the residual electric quantity of the plane i are respectively the k-th unmanned plane. />And +.>The average distance from the non-failed plane to the unmanned plane base station, the average residual energy of the non-failed plane, the average node degree of the non-failed plane and the average residual power of the non-failed plane of the class k unmanned plane at the R-th wheel are respectively. The soft threshold is adopted to simulate special cases so as to verify the effectiveness of an optimization scheme, namely three unmanned aerial vehicles based on task allocation are simplified into one unmanned aerial vehicle: the reconnaissance unmanned aerial vehicle can verify the simulation result from the two aspects of energy consumption and death node number of the network as shown in fig. 5. Simulation results show that the BEAD-LEACH of the soft threshold optimization scheme can effectively balance network energy consumption and prolong the life cycle of the network through optimizing the first lifting stage of the cluster.
Step 6: stable data transfer phase
The first stage of the LEACH clustering mechanism is a cluster first-choice lifting stage, after the cluster first-choice lifting stage is finished, the selected cluster head broadcasts identity information to the whole network, other auxiliary machines select a slave machine closest to the slave machine as the cluster head through a communication cost minimum principle, and send a request-to-cluster message, after the clustering stage is finished, the cluster head distributes communication time slots for each member in the cluster, then collects and fuses member state information 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.
Step 7: control instruction guided drone state update
Fig. 6 is a schematic diagram of control instruction guiding unmanned aerial vehicle state updating, where an unmanned aerial vehicle base station 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 state, send a central control instruction to each wing aircraft via the cluster head, and trigger a wing aircraft motion system to start as a feedback signal, and move to a corresponding position according to track planning of the control instruction, where an onboard anti-collision sensing device provides a guarantee for anti-collision during updating of the wing aircraft position. When the updated position state is matched with the feedback signal guiding position, the motion system is closed and enters a sleep state, and the feedback signal is triggered at the next moment. The central control instruction is used as feedback information to trigger the plane movement system to guide the unmanned plane to move as required to change the current state, and the dynamic network is converted into a relatively static network, so that the limit of LEACH for the static network is broken. At this time, the number of rounds R is increased by 1, and the number of rounds R and the preset lifetime R are judged max The relation between R and R is smaller than or equal to R max Turning to step 4; if R is greater than or equal to R max And (5) ending the dynamic clustering method and jumping out of the circulation.
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 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 principles and spirit of the invention, but such changes and modifications fall within the scope of the invention.
Claims (4)
1. The method for the secret dynamic clustering of the wireless ultraviolet light cooperative unmanned aerial vehicle is characterized by comprising the following steps of:
step 1: initializing distribution of unmanned aerial vehicles;
step 2: constructing an optimal virtual grid number through the relation between carrier waves and bandwidth, primarily managing the unmanned aerial vehicle in an initial state, selecting a virtual cluster head through the principle that the distance from the virtual centroid is minimum, and carrying out primary data transmission, wherein the method comprises the following specific steps:
the maximum communication radius under the ultraviolet light non-direct view A type communication mode is obtained by OOK modulation, and the communication radius is expressed as:
where α is the path loss index, ζ is the path loss factor, η is the quantum efficiency of the filter and photodetector, R b Information modulation rate, c is light speed, h is Planck constant, lambda is wireless ultraviolet wavelength, P t To transmit optical power, P e The error rate of the system;
the links between clusters are common links, serial communication is realized in the clusters in a TDMA mode, the communication link from the cluster head to the unmanned aerial vehicle base station is a backbone link, the communication capacity meets the parallel communication, and the optimal virtual grid number is obtained as follows:
wherein f c The carrier frequency is used, and B is backbone link communication bandwidth;
dividing m virtual grids, selecting the plane closest to the center of mass of each grid as a virtual cluster head, loading self state information to an ultraviolet spherical LED array by each plane in an OOK modulation mode, sending the ultraviolet spherical LED array to the virtual cluster head, collecting and fusing plane information in the virtual grids by the virtual cluster head, and sending the plane information to an unmanned plane base station, and finishing first data transmission;
step 3: the method comprises the steps of sending the information of the plane in each grid to an unmanned aerial vehicle base station through a virtual cluster head, and making a feedback control instruction by the unmanned aerial vehicle base station according to state information to guide the whole-network plane to make position update, wherein the specific method comprises the following steps:
the virtual cluster head collects and fuses the state information of the plane in the virtual grid, and sends the fused information to the unmanned aerial vehicle base station, if virtualThe distance d from the pseudo-cluster head to the unmanned aerial vehicle base station is smaller than or equal to the maximum communication radius r ook The one-hop neighbor node serving as the unmanned aerial vehicle base station sends the fusion information to the unmanned aerial vehicle base station, if d is larger than r ook The fusion information is sent to the unmanned aerial vehicle base station through the rest virtual cluster heads and the multi-hop inter-cluster forwarding function, and after the unmanned aerial vehicle base station serving as a central processing module grasps the global unmanned aerial vehicle state information, a central control instruction is sent to guide all the plane computers to adjust the state distribution;
step 4: aiming at a new wing distribution state, a clustering topology management mechanism of LEACH is introduced, and the maximum iteration round number is set as R max As a network lifetime, the global network is managed in a round-robin working mode, in each round, each wing machine randomly generates a random number, and compared with a threshold election threshold T (n), if the random number is smaller than the threshold election threshold, the current round cluster head is selected, which comprises the following steps:
wherein p is the percentage of the cluster head plane in all the planes, R represents the current number of wheels,the number of the wing machines selected from the cluster head in the round of circulation is represented, and G is a set of the wing machines not selected from the cluster head in the round of circulation;
step 5: the cluster first-choice stage threshold optimization method comprises the following specific steps:
because the formula (3) in the step 4 is a hard threshold election threshold, and the position, node degree, power and energy of the unmanned aerial vehicle in the network are dynamically changed at any time, the soft threshold election threshold is adopted to improve the first election stage of the unmanned aerial vehicle network cluster, and three types of unmanned aerial vehicles are respectively a reconnaissance unmanned aerial vehicle, a defending unmanned aerial vehicle and an attack unmanned aerial vehicle, and the first-level soft threshold election threshold is obtained through the optimization formula (3):
where k=1, 2,3,n 1 、n 2 、n 3 respectively the number T of three unmanned aerial vehicles with the current wheel not disabled k (n)' is a first-level soft threshold election threshold of the kth class unmanned aerial vehicle; considering the factors of the distance from the plane to the unmanned plane base station in the R-th wheel, the residual energy, the node degree and the residual electric quantity, further optimizing the formula (4) to obtain a secondary soft threshold election threshold as follows:
wherein,obtaining a second-level soft threshold election threshold for three task type unmanned aerial vehicles through a formula (5): t (T) k (n) ", wherein w 1 、w 2 、w 3 、w 4 Distance weight factor, energy weight factor, node degree weight factor and electric quantity weight factor, dist respectively i 、E i 、D i Power i The distance from the plane i to the base station of the unmanned plane in the R wheel, the residual energy of the plane i, the node degree of the plane i and the residual electric quantity of the plane i are respectively the k-th unmanned plane>And +.>The average distance from the non-failed plane to the unmanned plane base station of the R wheel of the k-type unmanned plane, the average residual energy of the non-failed plane, the average node degree of the non-failed plane and the average residual electric quantity of the non-failed plane are respectively;
step 6: a stable data transmission phase;
step 7: the control instructions direct the unmanned aerial vehicle status update.
2. The method for the stealth dynamic clustering of the wireless ultraviolet light cooperative unmanned aerial vehicle according to claim 1, wherein the specific practice of the step 1 is as follows:
the unmanned aerial vehicles are preliminarily distributed in a given area according to the requirement of executing tasks, unmanned aerial vehicles with different functions are deployed in corresponding numbers in the given area according to certain requirements, are randomly distributed in a given space, and are detected, defended and attacked, wherein the initial numbers of the three unmanned aerial vehicles are N respectively 1 、N 2 N 3 And carrying the same energy E 0 =300J, each unmanned aerial vehicle is arranged in 20 frames, i.e. N 1 ＝N 2 ＝N 3 The number of the samples is =20, the unmanned aerial vehicle is randomly scattered and distributed in 100 multiplied by 100m in the initial period 3 The unmanned aerial vehicle base station as a central processing module initially hovers at coordinates (50,50,50) and then adjusts position in real time as the network topology changes.
3. The method for the stealth and dynamic clustering of the wireless ultraviolet light cooperative unmanned aerial vehicle according to claim 1, wherein the specific practice of the step 6 is as follows:
the first stage of the LEACH clustering mechanism is a cluster first-choice lifting stage, after the cluster first-choice lifting stage is finished, the selected cluster head broadcasts identity information to the whole network, other auxiliary machines select a slave machine closest to the selected auxiliary machine as the cluster head through a communication cost minimum principle, and send a request-to-enter cluster message, after the clustering stage is finished, the cluster head distributes communication time slots for each member in the cluster, then collects and fuses member state information in the cluster, a one-hop transmission mode or a multi-hop transmission mode is adopted in the cluster, and the cluster head transmits fused information to an unmanned aerial vehicle base station through a parallel transmission mode.
4. The method for the stealth and dynamic clustering of the wireless ultraviolet light cooperative unmanned aerial vehicle according to claim 1, wherein the specific practice of the step 7 is as follows:
the unmanned aerial vehicle base station receives the fusion data of each cluster head, obtains the state information of the global unmanned aerial vehicle, makes judgment on the global, sends a central control instruction to each auxiliary plane again through the cluster head, and uses the central control instruction as a feedback signal to trigger the auxiliary plane motion system to start, and moves to the corresponding position according to the track planning of the control instruction, so that an onboard anti-collision sensing device provides a guarantee for anti-collision during the updating of the auxiliary plane position; when the updated position state is matched with the feedback signal guiding position, the motion system is closed and enters a sleep state, the feedback signal is triggered at the next moment, the number of rounds R is increased by 1, and the number of rounds R and the preset lifetime R are judged max The relation between R and R is smaller than or equal to R max Turning to step 4; if R is greater than or equal to R max And (5) ending the dynamic clustering method and jumping out of the circulation.
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