CN111601355A - Optimal path selection method in formation maintenance topology of wireless ultraviolet light cooperation unmanned aerial vehicle - Google Patents
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Abstract
The invention provides a method for selecting an optimal path in a formation maintenance topology of a wireless ultraviolet light cooperation unmanned aerial vehicle, which comprises the steps of firstly establishing an inter-aircraft communication path by utilizing an ultraviolet light non-direct-view single scattering model; setting a path weight by using the path loss of the communication link and the residual energy of the node; and finally, obtaining the optimal communication path between any unmanned aerial vehicle nodes in the formation by using the path weight through a Floyd algorithm. The invention adopts the wireless ultraviolet light to cooperate the unmanned aerial vehicle swarm formation flying, has the advantages of all weather, non-direct vision, no radio frequency interference, secret communication and the like, and can provide effective guarantee for the unmanned aerial vehicle swarm to smoothly execute tasks in strong electromagnetic interference environment. The path weight is set according to the path loss of the communication link and the node residual energy, so that the condition that the same path is selected for many times and the energy of the path node is ignored in the communication process can be avoided, the node is dead early, and the life cycle of the network is prolonged.
Description
Technical Field
The invention belongs to the technical field of photoelectric information, and particularly relates to an optimal path selection method in formation maintenance topology of a wireless ultraviolet light cooperation unmanned aerial vehicle.
Background
In recent years, the emerging industries related to unmanned aerial vehicles have been facing a period of high-speed development. Unmanned aerial vehicles play an important role in the civil field and the military field. Because the calculation, detection and operation capabilities of a single unmanned aerial vehicle are limited, the task execution capability of the unmanned aerial vehicle can be fully improved by using the cooperation mode of multiple unmanned aerial vehicles. The 'swarm' formation of the unmanned aerial vehicle is formed by a group of small unmanned aerial vehicles which are in autonomous networking cooperative operation, has the excellent characteristics of low cost, high survivability, good perception capability, strong cooperation capability, functional distribution and the like, and can greatly improve the task completion efficiency.
The unmanned aerial vehicle communication network has the self-organizing characteristic, and an electronic system of the unmanned aerial vehicle communication network is extremely easy to be influenced by electromagnetic pulse, radio frequency interference, a high-intensity radiation field and the like, so that the adoption of an unmanned aerial vehicle cluster internal communication mode with high anti-interference capability is very urgent. Adopt wireless ultraviolet light communication technology in unmanned aerial vehicle bee colony flies, its advantage mainly has following several: the background noise is low; the anti-interference capability is strong; all-weather non-line-of-sight (NLOS) communication; low power consumption is easy to integrate. The wireless ultraviolet light communication technology is applied to communication among unmanned aerial vehicle cellular planes, and the reliable secret communication requirement of the unmanned aerial vehicle in the complex battlefield environment can be met.
The unmanned aerial vehicle formation carries the energy limited in practical application, and when an unmanned aerial vehicle keeps in the formation process, a certain unmanned aerial vehicle transmits messages or issues instructions to other arbitrary unmanned aerial vehicles, the reasonable path weight is set and a path with the minimum communication cost is searched, so that the transmitting power and the total system power of a single node can be effectively reduced, the situation that the same path is selected for many times in the communication process and the energy of the node is ignored is avoided, the energy consumption of the unmanned aerial vehicle node is balanced, and the network life cycle of the unmanned aerial vehicle is prolonged. Therefore, the optimal path selection method in the wireless ultraviolet light cooperation unmanned aerial vehicle formation maintenance topology is provided. .
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 a method for selecting an optimal path in a wireless ultraviolet light cooperation unmanned aerial vehicle formation maintenance topology, which solves the problem of reliability of communication between unmanned aerial vehicle formation machines, balances the energy consumption of unmanned aerial vehicle nodes and prolongs the life cycle of a network.
In order to achieve the purpose, the invention adopts the following technical scheme:
the method for selecting the optimal path in the formation maintenance topology of the wireless ultraviolet light cooperation unmanned aerial vehicle is characterized by comprising the following steps:
s1: establishing an inter-machine communication path by using an ultraviolet light non-direct-view single scattering model;
s2: setting a path weight by using the path loss of a communication link and the residual energy of the node;
s3: and obtaining the optimal communication path between any unmanned aerial vehicle nodes in the formation by using the path weight through a Floyd algorithm.
Further, the step S2 is specifically as follows:
s201: calculating path loss of two unmanned aerial vehicle node communication links;
based on an ellipsoid coordinate system, an ultraviolet light emitting device and an ultraviolet light receiving device are respectively arranged on two focuses of the ellipsoid coordinate system, and the path loss of the ultraviolet light non-direct-view communication is as follows:
L＝ξrα(1)
wherein r is a communication distance, ξ is a path loss factor, and alpha is a path loss index;
s202: calculating the residual energy of the nodes of the unmanned aerial vehicle;
the residual energy of each unmanned aerial vehicle node after the formation aggregation is completed is as follows:
wherein e is0Is the initial energy of the unmanned plane node, P is the mobile energy consumption, mpIs the payload mass in kg, mvMass of the unmanned aerial vehicle is kg, r is lift-drag ratio, η is energy transfer efficiency of a motor and a propeller, p is power consumption of an electronic device, and the unit is kW, v is diiThe/t is the average speed of the unmanned aerial vehicle in the aggregation process, and the unit is km/h and diiThe distance from an initial position to a fixed position in a formation moves in the unmanned aerial vehicle aggregation process, and t is aggregation time;
s203: setting a path weight;
setting a path weight according to the calculated path loss and the residual energy of each node:
wherein, α1And α2As a weight factor, L is the path loss of the communication link,
for purposes of the communication link path loss average,
is the mean value of the residual energy of the node, erestThe energy is left for the node.
Further, the step S3 is specifically as follows:
s301: initializing Unmanned Aerial Vehicle (UAV)iAnd UAVjWhen two drones can directly communicate with each other, the unmanned aerial vehicle UAV is calculated by using the step S2iAnd UAVjThe path weight between; when the communication between two unmanned aerial vehicles needs to transmit messages through other unmanned aerial vehicle nodes, the path weight is infinite;
s302: UAV (unmanned aerial vehicle)iAnd UAVjInter-joining vertex UAV1Comparison of UAVi，UAV1And UAVjAnd UAViAnd UAVjTaking the path with small weight as the UAViTo UAVjAnd the vertex number is not more than 1;
s303, in unmanned aerial vehicle UAViTo UAVjInter-joining vertex UAV2Obtaining UAVi,...,UAV2And UAV2,...,UAVjWherein, the UAVi,...,UAV2Is a UAViTo UAV2And the number of the intermediate vertex is not more than 1; UAV2,...,UAVjIs a UAV2To UAVjAnd the number of the intermediate vertex is not more than 1; to the UAVi,...,UAV2,...,UAVjComparing the obtained optimal path with the optimal path obtained in step S302, and taking the shorter path as the UAViTo UAVjAnd the intermediate vertex number is not greater than 2;
s304, by analogy, after n times of comparison and correction, the UAV is obtained in the step n-1iTo UAVjThe middle vertex number is not more than n-1, namely the optimal path is any two nodes UAV in the unmanned aerial vehicle formationiTo UAVjThe optimal communication path of (a).
The invention has the beneficial effects that:
1) the invention adopts the wireless ultraviolet light to cooperate the unmanned aerial vehicle swarm formation flying, has the advantages of all weather, non-direct vision, no radio frequency interference, secret communication and the like, and can provide effective guarantee for the unmanned aerial vehicle swarm to smoothly execute tasks in strong electromagnetic interference environment.
2) The invention sets the path weight according to the path loss of the communication link and the node residual energy, can avoid the condition that the energy of the path node is neglected when the same path is selected for many times in the communication process, thereby leading to the premature death of the node and prolonging the life cycle of the network.
Drawings
Fig. 1 is a flowchart of an optimal path selection method in a formation maintenance topology of a wireless ultraviolet light cooperative unmanned aerial vehicle according to the present invention;
FIG. 2 is a diagram of a model of non-direct-view single-scattering communication of ultraviolet light according to the present invention;
FIG. 3 is a diagram of transmit receive elevation angle versus path loss in accordance with the present invention;
fig. 4 is a topological structure diagram of the unmanned aerial vehicle formation flying network of the invention.
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.
As shown in fig. 1, assuming that the initial states before the swarm unmanned aerial vehicle nodes are aggregated are equal, after the unmanned aerial vehicles are aggregated and reach the fixed position in the formation, the residual energies of the unmanned aerial vehicle nodes are different. And assisting the inter-drone communication of the swarm unmanned aerial vehicles by using wireless ultraviolet light, and obtaining the path loss of a communication link according to the communication characteristics of the ultraviolet light NLOS. The path weight is set according to the path loss and the residual energy of the nodes, and the optimal communication path between any nodes in the unmanned aerial vehicle formation is selected by adopting the Floyd algorithm, so that the condition that the nodes are dead due to insufficient energy caused by repeated selection of the same node to forward messages in the communication process can be avoided, and the life cycle of the unmanned aerial vehicle network is effectively prolonged.
The invention discloses a method for selecting an optimal path in a formation maintenance topology of a wireless ultraviolet light cooperation unmanned aerial vehicle, which is implemented according to the following steps:
step 1, establishing an inter-machine communication path by using an ultraviolet light non-direct-view single scattering model.
As shown in fig. 2, the ultraviolet light emitting device and the receiving device are respectively disposed on two focal points of an ellipsoid coordinate system based on the ellipsoid coordinate system. Theta1To transmit the elevation angle, theta2For receiving the elevation angle phi1Is the divergence angle of the transmitting end, phi2Is the receiving end field angle.
The path loss of the ultraviolet non-direct-view communication is:
L＝ξrα(1)
where r is the communication distance, ξ is the path loss factor, α is the path loss exponent, the values of α and ξ depend on the sender divergence angle φ1Angle of elevation theta of transmission1And angle of view phi of receiving end2Reception elevation angle theta2When the divergence angle of the transmitting end and the field angle of the receiving end are fixed, different values of α and ξ correspond to different receiving and transmitting elevation angle communication, namely, different path loss values of communication links among all unmanned aerial vehicles.
And 2, setting a path weight value by using the path loss of the communication link and the residual energy of the node.
And 2.1, calculating the path loss of the communication links of the two unmanned aerial vehicle nodes.
From step 1, when phi is1And phi2When fixed, randomly giving a transmitting-receiving end space angle parameter theta between the unmanned aerial vehicles1And theta2The path loss between the two drones can be determined. When phi is shown in the diagram of the relation between the elevation angle and the path loss of the transmitter and the receiver in FIG. 31＝17°，φ2When the angle is 30 degrees, a transmitting and receiving end space angle parameter theta between the unmanned aerial vehicles is randomly given1And theta2And determining the path loss of the communication links of the two unmanned aerial vehicles.
And 2.2, calculating the residual energy of the unmanned aerial vehicle nodes.
The energy of each unmanned aerial vehicle node is equal at the initial position, each unmanned aerial vehicle moves from the initial position to the fixed position in the formation in the aggregation process, the consumed communication energy is approximately equal, and the mobile energy consumption is far greater than that of communication, so that only the mobile energy consumption is considered in the aggregation process. The residual energy of each unmanned aerial vehicle node after the formation aggregation is completed is as follows:
wherein e is0Is the initial energy of each unmanned aerial vehicle node, P is the mobile energy consumption, mpIs the payload mass (kg), mvMass (kg) of the unmanned aerial vehicle, r is lift-drag ratio, η is motorAnd the energy transfer efficiency of the propeller, p is the power consumption (kW) of the electronic device, v ═ diiThe/t is the average speed (km/h) of the unmanned aerial vehicle in the aggregation process, diiThe distance from the initial position to the fixed position in the formation moves in the unmanned aerial vehicle aggregation process, and t is aggregation time.
And 2.3, setting a path weight.
The topological structure of the communication network between the clusters of the formation of the unmanned aerial vehicles is shown in fig. 4, each unmanned aerial vehicle corresponds to a fixed ID number, the numbers 1-9 respectively represent nine unmanned aerial vehicles, the connecting line between the unmanned aerial vehicles represents a communication path, the path between two nodes represents that the two nodes are within the communication range of each other and can be in direct communication, and at least one path between any two unmanned aerial vehicles in the figure is communicated. The path weight value of the link which is directly communicated is set by formula (3), and the path weight value which can not be directly communicated is set to be infinite.
Wherein, α1And α2As a weight factor, L is the path loss of the communication link,
for purposes of the communication link path loss average,
is the mean value of the residual energy of the node, erestThe energy is left for the node.
And 3, obtaining the optimal communication path between any unmanned aerial vehicle nodes in the formation by using the Floyd algorithm through the path weight.
Step 3.1, initialize UAV by step 2iAnd UAVjThe path weights between.
Step 3.2, in UAVi，UAVjInter-joining vertex UAV1Comparison (UAV)i，UAV1，UAVj) And (UAV)i，UAVj) Taking the path with small weight as the UAViTo UAVjAnd the vertex number is not greater than 1.
Step 3.3, in UAViTo UAVjInter-joining vertex UAV2Obtaining (UAV)i,...,UAV2) And (UAV)2,...,UAVj). Wherein (UAV)i,...,UAV2) Is a UAViTo UAV2And the number of the intermediate vertex is not more than 1; (UAV)2,...,UAVj) Is a UAV2To UAVjAnd the median vertex number is not greater than 1, which have been found in step 3.2. General (UAV)i,...,UAV2,...,UAVj) Comparing with the optimal path obtained in the step 3.2, and taking the shorter path as the UAViTo UAVjAnd the intermediate vertex number is not more than 2
3.4, repeating the above steps, comparing and correcting for n times, and obtaining the UAV in the (n-1) th stepiTo UAVjAnd the middle vertex number is not more than n-1, namely the optimal path is any two-node UAV in the unmanned aerial vehicle formationiTo UAVjThe optimal communication path of (a).
Example (b):
step 1, each unmanned aerial vehicle is provided with an ultraviolet light transmitting and receiving device, the ultraviolet light transmitting device transmits ultraviolet light with the wavelength of 260nm and the luminous power of 0.6 mw.
By the formula of path weight
And fig. 4 shows a topology structure diagram of the unmanned aerial vehicle formation flying network, and the path weight matrix of the unmanned aerial vehicle network topology obtained by calculation is:
A＝[0 0.9950 1.2566 1.0788 inf inf inf inf inf；0.9950 0 1.2314 infinf 0.9912 1.8027 inf inf；1.2566 1.2314 0 1.0314 0.9192 0.9811 inf inf inf；1.0788 inf 1.0314 0 1.0148 inf inf inf inf；inf inf 0.9192 1.0148 0 inf infinf 1.0377；inf 0.9912 0.9811 inf inf 0 inf 0.8563 1.0583；inf 1.8027 inf infinf inf 0 0.8353 inf；inf inf inf inf inf 0.8563 0.83530 0.9744；inf inf infinf 1.0377 1.0583 inf 0.9744 0]；
and 3, simulating according to a Floyd algorithm, inputting node IDs of any two unmanned aerial vehicles as a starting point and an end point, and outputting the node IDs of the obtained optimal communication path, namely the optimal communication path selected when any two nodes in the unmanned aerial vehicle formation communicate.
(1) Inputting a starting point: 1; inputting an end point: 9;
optimal communication path: 1-2-6-9
(2) Inputting a starting point: 3; inputting an end point: 7;
optimal communication path: 3-6-8-7
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 (3)
1. The method for selecting the optimal path in the formation maintenance topology of the wireless ultraviolet light cooperation unmanned aerial vehicle is characterized by comprising the following steps:
s1: establishing an inter-machine communication path by using an ultraviolet light non-direct-view single scattering model;
s2: setting a path weight by using the path loss of a communication link and the residual energy of the node;
s3: and obtaining the optimal communication path between any unmanned aerial vehicle nodes in the formation by using the path weight through a Floyd algorithm.
2. The method for selecting the optimal path in the formation maintenance topology of the wireless ultraviolet light cooperative unmanned aerial vehicles according to claim 1, wherein the step S2 is as follows:
s201: calculating path loss of two unmanned aerial vehicle node communication links;
based on an ellipsoid coordinate system, an ultraviolet light emitting device and an ultraviolet light receiving device are respectively arranged on two focuses of the ellipsoid coordinate system, and the path loss of the ultraviolet light non-direct-view communication is as follows:
L＝ξrα(1)
wherein r is a communication distance, ξ is a path loss factor, and alpha is a path loss index;
s202: calculating the residual energy of the nodes of the unmanned aerial vehicle;
the residual energy of each unmanned aerial vehicle node after the formation aggregation is completed is as follows:
wherein e is0Is the initial energy of the unmanned plane node, P is the mobile energy consumption, mpIs the payload mass in kg, mvMass of the unmanned aerial vehicle is kg, r is lift-drag ratio, η is energy transfer efficiency of a motor and a propeller, p is power consumption of an electronic device, and the unit is kW, v is diiThe/t is the average speed of the unmanned aerial vehicle in the aggregation process, and the unit is km/h and diiThe distance from an initial position to a fixed position in a formation moves in the unmanned aerial vehicle aggregation process, and t is aggregation time;
s203: setting a path weight;
setting a path weight according to the calculated path loss and the residual energy of each node:
wherein, α1And α2As a weight coefficient, α1+α2L is the path loss of the communication link, 1,
for purposes of the communication link path loss average,
is the mean value of the residual energy of the node, erestThe energy is left for the node.
3. The method for selecting the optimal path in the formation maintenance topology of the wireless ultraviolet light cooperative unmanned aerial vehicles according to claim 1, wherein the step S3 is as follows:
s301: initializing Unmanned Aerial Vehicle (UAV)iAnd UAVjWhen two drones can directly communicate with each other, the unmanned aerial vehicle UAV is calculated by using the step S2iAnd UAVjThe path weight between; when the communication between two unmanned aerial vehicles needs to transmit messages through other unmanned aerial vehicle nodes, the path weight is infinite;
s302: UAV (unmanned aerial vehicle)iAnd UAVjInter-joining vertex UAV1Comparison of UAVi，UAV1And UAVjAnd UAViAnd UAVjTaking the path with small weight as the UAViTo UAVjAnd the vertex number is not more than 1;
s303, in unmanned aerial vehicle UAViTo UAVjInter-joining vertex UAV2Obtaining UAVi,...,UAV2And UAV2,...,UAVjWherein, the UAVi,...,UAV2Is a UAViTo UAV2And the number of the intermediate vertex is not more than 1; UAV2,...,UAVjIs a UAV2To UAVjAnd the number of the intermediate vertex is not more than 1; to the UAVi,...,UAV2,...,UAVjComparing the obtained optimal path with the optimal path obtained in step S302, and taking the shorter path as the UAViTo UAVjAnd the intermediate vertex number is not greater than 2;
s304, by analogy, after n times of comparison and correction, the UAV is obtained in the step n-1iTo UAVjThe middle vertex number is not more than n-1, namely the optimal path is any two nodes UAV in the unmanned aerial vehicle formationiTo UAVjThe optimal communication path of (a).
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|---|---|---|---|---|
| CN114302265A (en) * | 2021-11-26 | 2022-04-08 | 军事科学院***工程研究院网络信息研究所 | Coordinate-addressing all-optical networking method for unmanned aerial vehicle |
| CN114531201A (en) * | 2021-12-27 | 2022-05-24 | 西安理工大学 | Method for simplifying path loss model of non-direct-view ultraviolet communication single scattering |
| CN114553290A (en) * | 2022-01-07 | 2022-05-27 | 西安理工大学 | Wireless ultraviolet light communication tracking and maintaining method based on MIMO structure |
| CN116261150A (en) * | 2023-03-03 | 2023-06-13 | 深圳市云联友科科技有限公司 | Wireless network bridge data transmission interference resistance method, device, equipment and medium |
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101494590A (en) * | 2008-01-23 | 2009-07-29 | 中兴通讯股份有限公司 | Optimum path selection method of communication network based on load balance |
| US20140103158A1 (en) * | 2012-10-12 | 2014-04-17 | Benjamin Lawrence Berry | AirShip Endurance VTOL UAV and Solar Turbine Clean Tech Propulsion |
| US20150103671A1 (en) * | 2013-10-11 | 2015-04-16 | Telefonaktiebolaget L M Ericsson (Publ) | High Performance LFA Path Algorithms |
| CN105764114A (en) * | 2016-04-19 | 2016-07-13 | 浙江理工大学 | Underwater wireless sensor network topology control method based on balanced energy consumption |
| CN106525047A (en) * | 2016-10-28 | 2017-03-22 | 重庆交通大学 | Unmanned aerial vehicle path planning method based on floyd algorithm |
| CN108541039A (en) * | 2018-04-24 | 2018-09-14 | 苏州市职业大学 | A kind of power consumption wireless sensor network static node-routing method |
| CN108924788A (en) * | 2018-06-21 | 2018-11-30 | 西安理工大学 | Energy consumption balance method in wireless ultraviolet light cooperation unmanned plane formation network |
| WO2019077006A1 (en) * | 2017-10-18 | 2019-04-25 | Uvue Ltd | System and method for determining optimal paths for drones |
| CN110456813A (en) * | 2019-04-16 | 2019-11-15 | 西安理工大学 | The unmanned plane of wireless ultraviolet light guidance is formed into columns the method that optimal sub-clustering formation is kept |
-
2020
- 2020-04-09 CN CN202010274949.6A patent/CN111601355B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101494590A (en) * | 2008-01-23 | 2009-07-29 | 中兴通讯股份有限公司 | Optimum path selection method of communication network based on load balance |
| US20140103158A1 (en) * | 2012-10-12 | 2014-04-17 | Benjamin Lawrence Berry | AirShip Endurance VTOL UAV and Solar Turbine Clean Tech Propulsion |
| US20150103671A1 (en) * | 2013-10-11 | 2015-04-16 | Telefonaktiebolaget L M Ericsson (Publ) | High Performance LFA Path Algorithms |
| CN105764114A (en) * | 2016-04-19 | 2016-07-13 | 浙江理工大学 | Underwater wireless sensor network topology control method based on balanced energy consumption |
| CN106525047A (en) * | 2016-10-28 | 2017-03-22 | 重庆交通大学 | Unmanned aerial vehicle path planning method based on floyd algorithm |
| WO2019077006A1 (en) * | 2017-10-18 | 2019-04-25 | Uvue Ltd | System and method for determining optimal paths for drones |
| CN108541039A (en) * | 2018-04-24 | 2018-09-14 | 苏州市职业大学 | A kind of power consumption wireless sensor network static node-routing method |
| CN108924788A (en) * | 2018-06-21 | 2018-11-30 | 西安理工大学 | Energy consumption balance method in wireless ultraviolet light cooperation unmanned plane formation network |
| CN110456813A (en) * | 2019-04-16 | 2019-11-15 | 西安理工大学 | The unmanned plane of wireless ultraviolet light guidance is formed into columns the method that optimal sub-clustering formation is kept |
Non-Patent Citations (7)
| Title |
|---|
| SHITAL JOSHI: "Energy efficient routing considering link robustness in wireless sensor networks", 《IEEE》 * |
| 王立春;罗守品;吴继浩;: "改进A~*算法在AGV小车路径规划中的应用", no. 02 * |
| 秦相林;张盈盈;: "基于剩余能量和节点度的多跳分簇算法的研究", 信息技术, no. 02 * |
| 罗小元;王慧彬;王金然;关新平;: "基于最优刚性图的链路质量与能量的拓扑控制算法", no. 11 * |
| 赵太飞;冷昱欣;王玉;: "紫外光NLOS通信的机群间通路快速恢复算法", no. 05, pages 1 - 2 * |
| 郑繁繁;张立冬;赵浦媛;吕欣;郝明;: "启发式无人机蜂群自组网协议及仿真", 指挥与控制学报, no. 01 * |
| 金冬成: "无线Mesh网络路径选择协议和信道分配方案的研究与改进", 《中国博士学位论文全文数据库》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114302265A (en) * | 2021-11-26 | 2022-04-08 | 军事科学院***工程研究院网络信息研究所 | Coordinate-addressing all-optical networking method for unmanned aerial vehicle |
| CN114302265B (en) * | 2021-11-26 | 2024-06-04 | 军事科学院***工程研究院网络信息研究所 | Coordinate addressing unmanned aerial vehicle all-optical networking method |
| CN114531201A (en) * | 2021-12-27 | 2022-05-24 | 西安理工大学 | Method for simplifying path loss model of non-direct-view ultraviolet communication single scattering |
| CN114553290A (en) * | 2022-01-07 | 2022-05-27 | 西安理工大学 | Wireless ultraviolet light communication tracking and maintaining method based on MIMO structure |
| CN116261150A (en) * | 2023-03-03 | 2023-06-13 | 深圳市云联友科科技有限公司 | Wireless network bridge data transmission interference resistance method, device, equipment and medium |
| CN116261150B (en) * | 2023-03-03 | 2023-09-15 | 深圳市云联友科科技有限公司 | Wireless network bridge data transmission interference resistance method, device, equipment and medium |
| CN117240359A (en) * | 2023-11-10 | 2023-12-15 | 西安现代控制技术研究所 | Ultraviolet light-based unmanned aerial vehicle cluster photoelectric hybrid networking method |
| CN117240359B (en) * | 2023-11-10 | 2024-03-15 | 西安现代控制技术研究所 | Ultraviolet light-based unmanned aerial vehicle cluster photoelectric hybrid networking method |
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