CN108282221B - Multi-unmanned aerial vehicle safety communication strategy for reducing unsafe area - Google Patents
Multi-unmanned aerial vehicle safety communication strategy for reducing unsafe area Download PDFInfo
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Abstract
A secure communication strategy for multiple drones that reduces unsafe zones, comprising the steps of: establishing a geometric model according to the flight characteristics and the cluster state of the multiple unmanned aerial vehicles; designing a layering algorithm to layer the unmanned aerial vehicle group, and finding out a group boundary node; reducing the communication range of the boundary node, and finding the optimal communication radius of the boundary node in the process; designing a mobile algorithm to enable the boundary nodes to approach to the group, and further completing effective communication; finally, it is proved by theory that the strategy can reduce the limit value of the proportion of the unsafe area in the case of infinite number of nodes. The invention reduces the range of the unsafe area by reducing the communication range of the boundary nodes of the unmanned aerial vehicle group, has the advantages of simple operation and control, stably reducing the range of the unsafe area and the like, and can ensure that a plurality of unmanned aerial vehicle groups can safely and effectively communicate. The unmanned aerial vehicle cooperative combat has wide application prospect in battlefield environment.
Description
The technical field is as follows:
the invention relates to a method for safety communication of multiple unmanned aerial vehicles, in particular to a novel method for safety communication between unmanned aerial vehicles by unmanned aerial vehicle communication range control and unmanned aerial vehicle flight position control in cooperative flight of multiple unmanned aerial vehicles, and belongs to the technical field of safety communication of multiple unmanned aerial vehicles.
Background art:
the secure communication is not related to specific communication details, but refers to research on relative safety of a drone group by controlling the communication range of the drone and the flight position of the drone. In the process that multiple unmanned aerial vehicles execute tasks, if the communication radius of the unmanned aerial vehicles is larger than the detection radius of the unmanned aerial vehicles, detection blind areas can appear outside the detection range of the unmanned aerial vehicles, in the areas, enemies can easily acquire communication messages of unmanned aerial vehicle groups and cannot be detected by the unmanned aerial vehicle groups, the state is called information leakage, and the areas with the information leakage are defined as unsafe areas. In order to reduce the unsafe area of the unmanned aerial vehicle group in the communication process, the communication range of the boundary unmanned aerial vehicle is adjusted from the cooperative control angle of the unmanned aerial vehicle, so that the communication range of the unmanned aerial vehicle group is reduced, the range of the unsafe area is further reduced, and the group communication is relatively safe.
Unmanned aerial vehicles have originated in the military field, and through decades of development, have entered the rapid development phase at present, and the kind is more and more, and the application field is constantly expanded, and the task type is more and more extensive. In recent years, unmanned aerial vehicles are widely used in multiple fields such as military, civil use, rescue and city management. In the battlefield, the drone is used to perform various search works and surveillance on the battlefield, and is more secure since the drone does not require manual driving. In agriculture, an unmanned aerial vehicle integrated with devices such as a high-definition digital camera, a spectrum analyzer and a thermal infrared sensor flies in a farmland, the planting area of an insurable plot can be accurately measured and calculated, collected data can be used for evaluating the risk condition of crops, and damage can be determined for the damaged farmland. In addition, unmanned aerial vehicle's inspection has still realized the monitoring to crops. When the communication is interrupted, the unmanned aerial vehicle is flexible to operate and can rescue at the fastest speed due to small size. Unmanned aerial vehicles can be used to explore places that human beings can not reach, can deliver article to some places that the topography is complicated. Also have unmanned aerial vehicle's shadow in urban power patrols and examines, unmanned aerial vehicle can follow the electric wire netting and fix a position independently and cruise, and the image is shot in real-time conveying, and the control personnel can watch in step on the computer. The system realizes electronic, informatization and intelligent routing inspection, and improves the working efficiency, the emergency rescue level and the power supply reliability of power line routing inspection. Under emergency such as mountain torrents outbreak, earthquake calamity, unmanned aerial vehicle also can carry out urgent investigation to the potential danger of circuit, such as the problem that the tower footing is subsided, does not receive the road surface situation influence at all. For single unmanned aerial vehicle, many unmanned aerial vehicles can work in coordination, can not lead to the task to terminate because of single unmanned aerial vehicle's damage to accomplish the task more economically and effectively.
In the research of multi-drone secure communications, aiming at a security group communication problem, i.e., if a drone group signal is weak, a method of increasing a signal-to-noise ratio is to increase a drone signal strength, which may lead to a problem of group information exposure, the massachusetts proposed a multi-drone control method based on space secure communications, in which communication power set from a central node to a boundary node is gradually reduced, thereby causing a change in a communication range of drones, and finally ensuring communication security, but distributed control of power of each drone is required, and power difference of drones causes survival time of drones to be unequal, thereby causing a problem of fast reduction of members of a drone group, a trainee of the virginia university, finds that a drone can provide instant communication by comparing a ground base station with a drone as an aerial base station, finds that a drone can effectively establish a line-of-sight-sig (L oS) communication link at high altitude, thereby reducing signal blocking and layer-to-layer interference, thereby maximizing a mobile-to-unmanned-control-communication-link-based on-a framework of-which unmanned-flight control communications can be effectively established by-a unmanned-flight-control-communication-link-finding, thereby maximizing a collaborative-a problem of-a collaborative-search-for-a unmanned-flight-control-flight-communication-control-communication-of-for-of-a unmanned-communication-of-a communication-for-of-a communication-of-a communication-of-a communication-of-a-
The invention content is as follows:
based on the problems, the invention aims at the problem of safe communication when the unmanned aerial vehicle group flies, integrates cooperative control and safe communication of multiple unmanned aerial vehicles, and from the perspective of communication safety of the multiple unmanned aerial vehicles, the communication radius of the boundary nodes of the multiple unmanned aerial vehicles is reduced by cooperatively controlling the flying positions of the multiple unmanned aerial vehicles, so that the purpose of safe communication is finally achieved. The main scheme of the invention is as follows:
a secure communication strategy for multiple drones that reduces unsafe zones, comprising the steps of:
step 1: designing a layering algorithm to layer the groups and find boundary nodes;
step 2: finding boundary nodes with the outermost layer nodes as groups, and reducing the communication radius of the boundary nodes so as to find the optimal communication radius R;
and step 3: and designing a mobile algorithm to move the boundary nodes to approach the center of the group, so that the boundary nodes and the group nodes are effectively communicated.
The step 1 further comprises:
step 1.1: determining the adjacency relation among the nodes of the multiple unmanned aerial vehicles according to the geometric models of the multiple unmanned aerial vehicles, and solving an adjacency matrix a among the multiple unmanned aerial vehiclesij；
Step 1.2: two points with the maximum European distance in the unmanned aerial vehicle group are calculated, and a formula is utilized
Taking the midpoint of the two points as a group center c; piAnd PjRespectively representing the coordinates of the node i and the node j;
step 1.3: initializing and storing a node matrix level and a variable k of the unmanned aerial vehicle group layer;
step 1.4, adding the c as the first layer in the group into a matrix level (k);
step 1.5, judging whether all unmanned aerial vehicle nodes are traversed, if so, ending the circulation; if not, continuing to execute the step 6;
step 1.6 byijFinding out level (k) adjacent nodes (excluding traversed nodes), and adding the adjacent nodes into the temporary matrix q;
step 1.7: adding 1 to the number k of layers;
step 1.8: adding the temporary matrix q into the level (k), and executing the step 1.5.
A critical value exists in the communication radius in the step 2, in this case, the unsafe area of the unmanned aerial vehicle group is the smallest, and the critical value of the boundary point communication radius is defined as the optimal communication radius of the boundary point; the definition is as follows:
R＝{0＜r＜rB:cA∩cB＝cA,dr＝rB-rA,A∈No,B∈Ni}
wherein c isARepresenting a boundary circle, cBRepresents and cAIntersecting inner circle, drIs the distance between the two circle centers, rBIs the inner layer circle radius, rAIs the radius of a boundary circle, NoAs a set of boundary circles, NiIs a set of inner circle;
the step 3 further comprises:
step 3.1: initializing the number n of boundary nodes, a loop variable i and a moving step length;
step 3.2: the ith boundary node moves to the center c of the group with the distance of step;
step 3.3, calculating the distance between the boundary node i and the rest nodes of the group, and finding out the shortest distance s;
step 3.4, judging whether s is smaller than the optimal communication radius R, if so, executing step 3.5, otherwise, returning to execute step 3.2;
step 3.5, i is i + 1;
step 3.6, judging whether i is smaller than n; if yes, returning to execute the step 3.2; if not, the algorithm ends.
The invention has the beneficial effects that:
research on safety communication and coordinated control is more unilateral, however, most unmanned aerial vehicles need to consider the two aspects in combination in a battlefield environment. Therefore, the invention can be used for carrying out optimal position selection aiming at the cooperative control of multiple unmanned aerial vehicles, and mutual communication is kept so as to transfer information in real time. In communication, the communication range of the boundary node is controlled to ensure the group communication to be safe in consideration of the safety of information, so that the multiple unmanned aerial vehicles can be ensured to carry out safe communication.
Description of the drawings:
FIG. 1 is a flowchart illustrating specific steps of solving a boundary node matrix according to the present invention;
FIG. 2 is a flow chart of the steps involved in designing a motion algorithm according to the present invention.
The specific implementation mode is as follows:
the following detailed description of the present invention is provided in conjunction with the accompanying drawings, and the detailed description is not intended to limit the scope of the present invention.
A safety communication strategy of multiple unmanned aerial vehicles for reducing unsafe areas mainly comprises the following steps of: solving a boundary node matrix edge;
1.1 initialize the drone group N, the drone communication radius r, the marker matrix mark.
1.2, according to the adjacency relation among the unmanned aerial vehicles, the adjacency matrix a _ ij of the multiple unmanned aerial vehicles is obtained. According to the formula | | qj-qiAnd d, calculating the distance between the node i and the node j, wherein q represents the position of the unmanned aerial vehicle, and N represents the set of the unmanned aerial vehicle group. If d < r, node i and node j can communicate, a _ ij ≠ 0, and vice versa. Wherein r is the communication radius of the drone.
1.3 find out the two points with the maximum distance in the group, and use the formula
The group center point c is obtained. PiAnd PjRespectively representing the coordinates of the node i and the node j;
1.4 initialize the UAV layer matrix and set the group center point c as the first layer node.
1.5 taking the node of the k layer as an input, searching the adjacent node of the k layer of the unmanned aerial vehicle by using a _ ij, if the searched node is marked in the mark matrix mark, the node is already searched, and continuously searching other adjacent nodes. If the node is not marked, adding the node into the matrix of the (k + 1) th layer.
1.6 step 1.5 is executed until the number of nodes of the unmanned plane layer matrix is equal to the number of nodes N of the unmanned plane.
1.7 finding out the last layer in the layer matrix, namely the boundary node.
And a second stage: determining optimal communication radius of boundary node
In the process of reducing the communication radius of the boundary node, a critical value exists in the communication radius of the boundary node, in this case, the unsafe area of the unmanned aerial vehicle group is the minimum, and the critical value of the communication radius of the boundary point is defined as the optimal communication radius of the boundary point. The definition is as follows:
R＝{0＜r＜rB:cA∩cB＝cA,dr＝rB-rA,A∈No,B∈Ni}
wherein c isARepresenting a boundary circle, cBRepresents and cAIntersecting inner circle, drIs the distance between the two circle centers, rBIs the inner layer circle radius, rAIs the radius of a boundary circle, NoAs a set of boundary circles, NiIs a set of inner circles.
And a third stage: designing a movement algorithm
3.1 initializing the number n of boundary nodes and moving step size step.
3.2 the ith boundary node moves to the cluster center c by step.
3.3 calculating the distance between the boundary node i and the rest nodes of the group, and finding out the shortest distance s.
3.4 judge if s is smaller than the optimum communication radius R. If yes, proving that the node i can communicate with other nodes in the group, executing 3.5, if not, the moving distance of the boundary node is not enough to effectively communicate with other nodes in the group, continuing to move the boundary node to the center of the group, and returning to execute 3.2.
3.5 judging whether i is less than n, if yes, then some nodes in the boundary nodes do not establish communication link with the group, and returning to execute step 2. If not, all the boundary nodes are moved completely, effective communication with the group can be realized, and the algorithm is ended.
The detailed description is presented to facilitate a person skilled in the art to make and use the invention and is not intended to limit the scope of the invention. After reading the present disclosure, appropriate modifications can be made by those skilled in the art. The protection of the present invention is subject to the content of the claims. Various modifications, alterations, substitutions and the like can be made to the present invention without departing from the spirit and scope of the claims.
Claims (1)
1. A safe communication method of multiple unmanned aerial vehicles for reducing unsafe areas is characterized by comprising the following steps:
step 1: designing a layering algorithm to layer the groups and find boundary nodes;
step 2: finding boundary nodes with the outermost layer nodes as groups, and reducing the communication radius of the boundary nodes so as to find the optimal communication radius R;
and step 3: designing a mobile algorithm to move the boundary nodes to approach the center of the group, and further enabling the boundary nodes to effectively communicate with the group nodes;
the step 1 specifically comprises:
step 1.1: determining the adjacency relation among the nodes of the multiple unmanned aerial vehicles according to the geometric models of the multiple unmanned aerial vehicles, and solving an adjacency matrix a among the multiple unmanned aerial vehiclesij；
Step 1.2: two points with the maximum European distance in the unmanned aerial vehicle group are calculated, and a formula is utilized
Taking the midpoint of the two points as a group center c; piAnd PjRespectively representing the coordinates of the node i and the node j;
step 1.3: initializing and storing a node matrix level and a variable k of the unmanned aerial vehicle group layer;
step 1.4, adding the c as the first layer in the group into a matrix level (k);
step 1.5, judging whether all unmanned aerial vehicle nodes are traversed, if so, ending the circulation; if not, continuing to execute the step 6;
step 1.6 byijFinding out level (k) adjacent nodes, excluding traversed nodes, and adding the nodes into the temporary matrix q;
step 1.7: adding 1 to the number k of layers;
step 1.8: adding the temporary matrix q into level (k), and executing the step 1.5;
step 2, a critical value exists in the communication radius, in this case, the unsafe area of the unmanned aerial vehicle group is the minimum, and the critical value of the boundary point communication radius is defined as the optimal communication radius of the boundary point; the definition is as follows:
R＝{0＜r＜rB:cA∩cB＝cA,dr＝rB-rA,A∈No,B∈Ni}
wherein c isARepresenting a boundary circle, cBRepresents and cAIntersecting inner circle, drIs the distance between the two circle centers, rBIs the inner layer circle radius, rAIs the radius of a boundary circle, NoAs a set of boundary circles, NiIs a set of inner circle;
the step 3 specifically comprises the following steps:
step 3.1: initializing the number n of boundary nodes, a loop variable i and a moving step length;
step 3.2: the ith boundary node moves to the center c of the group with the distance of step;
step 3.3, calculating the distance between the boundary node i and the rest nodes of the group, and finding out the shortest distance s;
step 3.4, judging whether s is smaller than the optimal communication radius R, if so, executing step 3.5, otherwise, returning to execute step 3.2;
step 3.5, i is i + 1;
step 3.6, judging whether i is smaller than n; if yes, returning to execute the step 3.2; if not, the algorithm ends.
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