CN111600644A - Ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method - Google Patents

Ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method Download PDF

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CN111600644A
CN111600644A CN202010274287.2A CN202010274287A CN111600644A CN 111600644 A CN111600644 A CN 111600644A CN 202010274287 A CN202010274287 A CN 202010274287A CN 111600644 A CN111600644 A CN 111600644A
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unmanned aerial
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赵太飞
曹丹丹
张港
汪月
薛蓉莉
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Xian University of Technology
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    • 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
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    • 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
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    • 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
    • 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
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
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    • 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]
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    • 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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Abstract

The invention provides an ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method, which comprises the following steps: s1: each node in the unmanned aerial vehicle formation reaches a preset aggregation point; s2: each unmanned aerial vehicle node searches for a neighbor node by using a carried wireless ultraviolet MIMO device and establishes a respective neighbor information list; s3: calculating the link weight of each unmanned aerial vehicle node and the neighbor nodes thereof according to the content in the neighbor information list; and S4, generating a distributed formation topology based on the optimal rigid graph. The invention has the advantages that the communication cost is minimum, so that the link of the network is more reliable, the energy consumption of the network is reduced, the purpose of energy saving is realized, and the operation capability of the unmanned aerial vehicle during cluster formation is improved; the information of all unmanned aerial vehicle nodes does not need to be known, and each unmanned aerial vehicle in the formation only needs to know the information of the adjacent unmanned aerial vehicle, so that the unmanned aerial vehicle network is suitable for large-scale unmanned aerial vehicle networks.

Description

Ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method
Technical Field
The invention belongs to the technical field of topology control, and particularly relates to an ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method.
Background
Because the calculation, detection and operation capabilities of a single unmanned aerial vehicle are limited, the advantages of the cluster unmanned aerial vehicles can be fully exerted by using the cooperation mode of multiple unmanned aerial vehicles, and the task execution capability of the unmanned aerial vehicles is improved. The basis of unmanned aerial vehicle formation cooperation is that reliable communication and real-time information sharing are kept among all machines, but under special conditions, especially in the electronic countermeasure process, the unmanned aerial vehicle formation needs to keep a radio silent state so as to reduce exposure risks, and if the unmanned aerial vehicle only uses a radio communication mode, the integrity of a formation communication network is difficult to maintain. The wireless ultraviolet light has the advantages of small background noise, strong anti-interference capability, low power consumption, easy airborne performance and the like, and can meet the requirements of the communication mode.
The task of topology control is to select reasonable logic neighbor nodes from physical neighbor nodes for each node to communicate according to a given rule, so that the transmission power of the nodes is reduced under the condition of global network communication, the life cycle of the network is effectively prolonged, and the topology control is divided into centralized topology control and distributed topology control. The implementation of centralized topology control relies on the acquisition of global information, and thus the network deployability is limited in size. In distributed topology control, each node only needs to autonomously select a logical neighbor node according to information acquired from the physical neighbor node, and typical methods include LMST, CBTC, RNG and the like. The shape of the whole graph cannot be damaged by the movement of any vertex of the topology constructed based on the rigid graph, the method is suitable for the application of unmanned aerial vehicle formation and maintenance, and the optimal rigid graph is the rigid graph with the least number of communication edges and the minimum weighted sum of the side lengths of all the edges.
The stable unmanned aerial vehicle formation communication network can guarantee that the whole formation cluster can execute tasks efficiently, and therefore an information interaction topology needs to be designed for formation, all unmanned aerial vehicles can generate and maintain a given formation shape by using the information interaction topology, and communication cost is minimum. For a large-scale unmanned aerial vehicle network, the communication distance of each unmanned aerial vehicle is limited, and the unmanned aerial vehicle can only communicate with the neighbor nodes of the unmanned aerial vehicle, so that the distributed topology control method based on the optimal rigid graph is provided, the information of all unmanned aerial vehicle nodes does not need to be known, and each unmanned aerial vehicle node only needs to know the information of the adjacent unmanned aerial vehicle.
It is noted that this section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
Disclosure of Invention
The invention aims to provide an optimal rigid topology generation method for ultraviolet-assisted unmanned aerial vehicle formation, so that the complexity of the topology is reduced while the formation of unmanned aerial vehicles is kept, the constructed network is a topological graph with the minimum link weight value, the energy consumption of the network is reduced, and the aim of saving energy is fulfilled.
In order to achieve the purpose, the invention adopts the following technical scheme:
the ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method is characterized by comprising the following steps:
s1: each node in the unmanned aerial vehicle formation reaches a preset aggregation point;
s2: each unmanned aerial vehicle node searches for a neighbor node by using a carried wireless ultraviolet MIMO device and establishes a respective neighbor information list;
s3: calculating the link weight of each unmanned aerial vehicle node and the neighbor nodes thereof according to the content in the neighbor information list;
and S4, forming a local optimal rigid topology by each unmanned aerial vehicle node and the neighbor nodes according to the link weight in the step S3, generating an optimal rigid subgraph, deleting edges which do not belong to the optimal rigid graph to obtain a global optimal rigid formation graph, and generating a distributed formation topology based on the global optimal rigid formation graph.
Further, in the step S1, the top and the bottom of each drone in the formation of drones are loaded with a hemispherical LED array.
Further, the step S2 is specifically as follows:
s201: each unmanned aerial vehicle node uses a carried wireless ultraviolet MIMO device to search a neighbor node of the unmanned aerial vehicle node in a weft scanning and warp scanning alternating mode, and then sends an information frame to the neighbor node;
s202: after receiving the sending information frame, the neighbor node sends a response information frame to the node sending the information frame in the same weft scanning and warp scanning modes;
s203: when the node sending the information frame receives the response information frame, a neighbor information list of the node is established according to the content in the response information frame;
further, the sending information frame includes the ID number of the node itself, the information type identification code, and the LED longitude and latitude code.
Further, the response information frame comprises the ID number, the information type identification code and the direction code of the node sending the response information frame, and the ID number, the direction code, the residual energy and the position coordinate of the node sending the response information frame.
Further, the neighbor information list includes ID numbers of neighbor nodes, remaining energy of neighbor nodes, directional coordinates of neighbor nodes with respect to themselves, positions of neighbor nodes, and weights of links.
Further, the step S3 is specifically as follows:
in the formation of unmanned aerial vehicles, the link weight functions of two nodes i and j with neighbor relation are as follows:
Figure BDA0002444227110000031
wherein, L is the path loss of the communication between the two nodes; etiAnd ErjAnd represents the energy consumption of data transmission and reception between two nodes through ultraviolet light; e.g. of the typei、ejThe residual energy of the node after the aggregation is completed.
The invention has the beneficial effects that:
(1) the invention has the advantages of minimum communication cost, more reliable network link, reduced energy consumption of the network, energy saving and improved operation capability of unmanned aerial vehicle cluster formation.
(2) The invention does not need to know the information of all unmanned aerial vehicle nodes, and each unmanned aerial vehicle in the formation only needs to know the information of the adjacent unmanned aerial vehicle, thereby being suitable for large-scale unmanned aerial vehicle networks.
Drawings
FIG. 1 is a distributed flow chart based on an optimal stiffness diagram according to the present invention;
fig. 2 is a schematic diagram of the basic structure of the unmanned aerial vehicle in the invention;
FIG. 3 is a diagram of a hemispherical ultraviolet LED communication node structure carried by an unmanned aerial vehicle according to the invention;
FIG. 4 is a frame diagram of the sending and responding information of the unmanned aerial vehicle in the neighbor searching stage;
FIG. 5 is a table of neighbor information for each UAV node in the present invention;
FIG. 6 is a graph of variability involved in the present invention;
FIG. 7 is a rigidity diagram related to the present invention;
fig. 8 is a diagram of the minimum rigidity involved in the present invention.
The reference numbers are as follows:
1-hemisphere, 2-ultraviolet LED, 3-omnidirectional receiver.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features or characteristics may be combined in any suitable manner in one or more embodiments.
The invention discloses an ultraviolet light assisted unmanned aerial vehicle optimal rigid topology generation method, which is implemented according to the following steps:
step 1, each node in the unmanned aerial vehicle formation reaches a preset aggregation point;
the ground control station sends the aggregation position specified in advance to each unmanned aerial vehicle in the formation, as shown in fig. 2, the unmanned aerial vehicle module comprises a GPS module, a controller, an ultraviolet light device, a radio transceiver module and a memory, wherein the GPS module, the ultraviolet light device, the radio transceiver module and the memory are connected with the controller and used for receiving instructions sent by the controller. The GPS module is used for precisely positioning the unmanned aerial vehicle; the wireless transceiver module is used for receiving the instruction of the control platform in the aggregation process, so that the unmanned aerial vehicle can quickly reach the aggregation position; the ultraviolet light device is used for assisting the unmanned aerial vehicle node to discover neighbor nodes in a communication range; the memory is used for storing the information that the unmanned aerial vehicle node received other nodes.
Step 2, each unmanned aerial vehicle node searches for own neighbor nodes by using the carried wireless ultraviolet MIMO device and establishes respective neighbor information lists;
after unmanned aerial vehicle reachd own aggregation position, the radio transceiver sends the information that finishes of aggregating and gives ground control platform, and ground control platform returns a start message after receiving this information and gives unmanned aerial vehicle's controller, and afterwards, the wireless ultraviolet ray MIMO device that unmanned aerial vehicle carried on begins to look for self neighbor node. Since drones are formed in a three-dimensional space, in order for a drone to discover all neighboring drone nodes within communication range, the light beams emitted by the wireless ultraviolet MIMO device must cover the three-dimensional space around the nodes. The spherical node has the best coverage performance, so that omnidirectional transmission can be realized by arranging a plurality of LEDs on the surface of the spherical node on the basis of a spherical structure. In order to simplify the design, the spherical structure can be changed into a semispherical structure, and three-dimensional coverage can be completed by using the two pairs.
Fig. 3 is a view of a hemispherical LED node structure according to the present invention, the surface of which is divided into M latitudinal directions and N longitudinal directions. The node structure comprises a hemisphere 1, wherein a plurality of ultraviolet light LEDs 2 are uniformly arranged on the surface of the hemisphere 1 in the longitudinal and latitudinal directions, the divergence angle is 15 degrees, each ultraviolet light LED2 is connected with a main control chip through a driving circuit, and an omnidirectional receiver 3 connected with the main control chip is arranged at the top of the hemisphere 1. And assigning an ID number with a unique identifier to the node structure, and coding each ultraviolet LED2 position according to the warp direction and the weft direction respectively to obtain the warp direction code and the weft direction code of the ultraviolet LED2 position.
The specific process is as follows:
and 2.1, after receiving the instruction of the controller, the unmanned aerial vehicle sequentially starts the carried wireless ultraviolet MIMO device to search the neighbor nodes of the unmanned aerial vehicle. If all the LEDs send information simultaneously, neighbor nodes in a communication range can receive the information certainly, but the energy carried by the unmanned aerial vehicle in the air is limited, and the mode is overlarge in power consumption, low in efficiency and not applicable any more. Therefore, the neighbor discovery needs to be sent in a scanning mode, and if the mode of scanning by the LEDs one by one is adopted, the scanning period is too large, and the real-time property of neighbor discovery is not high. The weft scanning and warp scanning can be alternatively adopted, so that the scanning period can be greatly reduced, and the complexity of a control circuit can also be reduced. The transmitted information frame, as shown in fig. 4, includes the ID number of the node itself, and an information type identifier F, LED warp/weft encoding D for identifying whether the information is transmitted information or response information.
And 2.2, receiving information by the unmanned aerial vehicle node through the omnidirectional receiver at the top. And after the neighbor nodes in the node communication range receive the longitude and latitude codes of the sending node, the initiating node is taken as a destination node, and response information is sent in the same longitude and latitude scanning mode. The response information frame includes, as shown in fig. 3, the ID number of the transmitting node, the information type identification code, the direction code and its own ID number, the direction code of the transmission information, and the remaining energy at that time. When the sending node receives the response message, a neighbor information list of the sending node is established according to the content in the message. The neighbor information list of the node is shown in fig. 4, and includes the ID number of the neighbor node, the current residual energy E of the neighbor node, the directional coordinate L of the neighbor node relative to itself, and the weight W of each link, the directional coordinate L in the list is composed of warp coding and weft coding, the position of the neighbor node can be determined, and the residual energy E is used for calculating the weight of the back link.
Step 3, calculating the link weight of each unmanned aerial vehicle node and the neighbor node according to the neighbor information list established in the step 2;
in the step 2, each unmanned aerial vehicle node establishes a neighbor information list thereof, and the neighbor information list can be used for calculating the weight of the communication link. In addition to considering the energy consumed in transmitting and receiving information and the initial energy of the node, the reliability of the link quality should be considered when determining the link. The link weight function of any two unmanned aerial vehicle nodes i and j with neighbor relation in the network is as follows:
Figure BDA0002444227110000061
the method comprises the following steps:
l is the path loss of two nodes of the drone, the path loss is directly affected by the transceiver end and the communication distance in the uv communication system, and the increase of the communication distance and the increase of the elevation angle of transmission and reception both result in the increase of the path loss, which can be represented by L- ξ rαThe calculation result is that ξ is a path loss factor, α is a path loss index, r is a distance between two nodes, the values of α and ξ depend on a transmitting end divergence angle, a transmitting elevation angle, a receiving end angle of view and a receiving elevation angle, and when the transmitting end divergence angle and the receiving end angle of view are fixed, different values of α and ξ are obtained when the transmitting end divergence angle and the receiving end angle of view are used for communication at different transmitting and receiving elevation angles.
EtiAnd ErjThe energy consumption of data transmission and reception between two nodes through ultraviolet light is shown, and when the unmanned aerial vehicle carries out wireless ultraviolet light communication transmission, the emission pulse energy E is giventIn time, the energy consumed by the transmitting end to compensate the energy attenuation of the atmospheric channel to the ultraviolet light transmission signal is:
Figure BDA0002444227110000071
wherein, ηtEfficiency of electro-optical energy conversion at the emitting end, ETThe energy consumed for transmitting unit bit data for the transmitting end. In order to enable the received signal to reach an acceptable signal-to-noise ratio, when the unmanned aerial vehicle sends kbit data to a receiving end with a distance r, the energy consumed by the node is as follows: eti(k)＝k(ET+EL) And the energy consumed by the unmanned aerial vehicle node receiving kbit data at the receiving end is as follows: eRx(k)＝kER，ERThe energy consumed for receiving a unit bit of data.
ei、ejThe residual energy of the node after the aggregation is completed.
And (4) recording the calculated link weight value in a position corresponding to the neighbor information list by each unmanned aerial vehicle node, so that the neighbor information list of each node records the basic information of the node and all neighbor nodes, and the node is used for constructing the optimal rigid topology in the step 4.
And 4, generating a distributed formation topology based on the optimal rigid graph.
If the length of each side is kept constant, a graph is not deformed or is a rigid graph, for example, a figure 6 is a variability graph, a figure 7 is a rigid graph, the shape of the whole graph cannot be damaged by the movement of any vertex in the rigid graph, a figure 8 is a minimum rigid graph and consists of the fewest sides, and the graph corresponding to the optimal rigid graph is the minimum rigid graph and the weighted sum of the side lengths of each side is minimum.
Fig. 6 to 8 are flows of an optimal rigid graph distributed generation method, where for a given unmanned aerial vehicle formation network, each node generates an optimal rigid subgraph with its own neighbor node first, and finally, an edge not belonging to the optimal rigid graph is deleted to obtain an optimal formation rigid graph. The specific generation method comprises the following steps:
step 4.1, after receiving the response message, the node establishes a neighbor information list of the node, and calculates communication links of the node and all neighbor nodes, namely weights corresponding to all links in the neighbor information list according to a weight formula;
4.2, arranging the lists in an ascending order according to the link weight;
4.3, establishing a rigid matrix of the subgraph according to the sequence;
the rigid map is typically constructed from a rigid matrix, first, arranging the vertex coordinates in the following order,
Figure BDA0002444227110000081
then, a matrix is established, whichThe rows and columns correspond to the coordinates of the edges and vertices, respectively.
4.4, establishing an optimal rigid subgraph of the node and the neighbor nodes thereof, wherein the construction method of the optimal rigid subgraph comprises the following steps:
① initialize the matrix MiA first row of the rigid matrix;
② adding the second row of the stiffness matrix to matrix MiGenerating a new matrix in the middle and first rows, and calculating the rank of the matrix;
and thirdly, judging whether the rank of the new matrix is a full rank, if so, adding a second row, and if not, deleting the row from the new matrix. Then adding the next row of the stiffness matrix into the new matrix until 3n-6 linearly independent row vectors are found;
and fourthly, forming a graph by using edges corresponding to the 3n-6 row vectors.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

Claims (7)

1. An ultraviolet light assisted unmanned aerial vehicle formation optimal rigid topology generation method is characterized by comprising the following steps:
s1: each node in the unmanned aerial vehicle formation reaches a preset aggregation point;
s2: each unmanned aerial vehicle node searches for a neighbor node by using a carried wireless ultraviolet MIMO device and establishes a respective neighbor information list;
s3: calculating the link weight of each unmanned aerial vehicle node and the neighbor nodes thereof according to the content in the neighbor information list;
and S4, forming a local optimal rigid topology by each unmanned aerial vehicle node and the neighbor nodes according to the link weight in the step S3, generating an optimal rigid subgraph, deleting edges which do not belong to the optimal rigid graph to obtain a global optimal rigid formation graph, and generating distributed formation based on the global optimal rigid formation graph.
2. The method for generating the optimal rigid topology for ultraviolet light assisted unmanned aerial vehicle formation according to claim 1, wherein the method comprises the following steps: step S1 is to load a hemispherical LED array on the top and bottom of each drone in the formation of drones.
3. The method for generating the optimal rigid topology for ultraviolet light assisted unmanned aerial vehicle formation according to claim 1, wherein the step S2 is as follows:
s201: each unmanned aerial vehicle node uses a carried wireless ultraviolet MIMO device to search a neighbor node of the unmanned aerial vehicle node in a weft scanning and warp scanning alternating mode, and then sends an information frame to the neighbor node;
s202: after receiving the sending information frame, the neighbor node sends a response information frame to the node sending the information frame in the same weft scanning and warp scanning modes;
s203: when the node sending the information frame receives the response information frame, a neighbor information list of the node is established according to the content in the response information frame.
4. The method for generating the optimal rigid topology for ultraviolet light assisted unmanned aerial vehicle formation according to claim 3, wherein the method comprises the following steps: the sending information frame comprises the ID number of the node, an information type identification code and an LED longitude and latitude code.
5. The method for generating the optimal rigid topology for ultraviolet light assisted unmanned aerial vehicle formation according to claim 3, wherein the method comprises the following steps: the response information frame comprises the ID number, the information type identification code and the direction code of the node sending the information frame, and the ID number, the direction code, the residual energy and the position coordinate of the node sending the response information frame.
6. The method for generating the optimal rigid topology for ultraviolet light assisted unmanned aerial vehicle formation according to claim 3, wherein the method comprises the following steps: the neighbor information list comprises the ID number of the neighbor node, the residual energy of the neighbor node, the direction coordinate of the neighbor node relative to the neighbor node, the position of the neighbor node and the weight of each link.
7. The method for generating the optimal rigid topology for ultraviolet light assisted unmanned aerial vehicle formation according to claim 1, wherein the step S3 is as follows:
in the formation of unmanned aerial vehicles, the link weight functions of two nodes i and j with neighbor relation are as follows:
Figure FDA0002444227100000021
wherein, L is the path loss of the communication between the two nodes; etiAnd ErjAnd represents the energy consumption of data transmission and reception between two nodes through ultraviolet light; e.g. of the typei、ejThe residual energy of the node after the aggregation is completed.
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