CN112911225B - Video monitoring method based on quantum encryption - Google Patents
Video monitoring method based on quantum encryption Download PDFInfo
- Publication number
- CN112911225B CN112911225B CN202110066483.5A CN202110066483A CN112911225B CN 112911225 B CN112911225 B CN 112911225B CN 202110066483 A CN202110066483 A CN 202110066483A CN 112911225 B CN112911225 B CN 112911225B
- Authority
- CN
- China
- Prior art keywords
- unmanned aerial
- aerial vehicle
- task
- area
- alliance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000005540 biological transmission Effects 0.000 claims abstract description 23
- 238000004891 communication Methods 0.000 claims abstract description 10
- 238000012545 processing Methods 0.000 claims abstract description 9
- 230000015572 biosynthetic process Effects 0.000 claims abstract description 7
- 230000008859 change Effects 0.000 claims abstract description 4
- 238000005457 optimization Methods 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 4
- 238000013461 design Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims 3
- 238000005516 engineering process Methods 0.000 abstract description 3
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1433—Vulnerability analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0816—Key establishment, i.e. cryptographic processes or cryptographic protocols whereby a shared secret becomes available to two or more parties, for subsequent use
- H04L9/0852—Quantum cryptography
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/63—Control of cameras or camera modules by using electronic viewfinders
- H04N23/633—Control of cameras or camera modules by using electronic viewfinders for displaying additional information relating to control or operation of the camera
- H04N23/635—Region indicators; Field of view indicators
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/695—Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Computer Security & Cryptography (AREA)
- Multimedia (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Radar, Positioning & Navigation (AREA)
- Theoretical Computer Science (AREA)
- Electromagnetism (AREA)
- Automation & Control Theory (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Aviation & Aerospace Engineering (AREA)
- Closed-Circuit Television Systems (AREA)
Abstract
The invention discloses a video monitoring method based on quantum encryption, which comprises the following steps: s2, based on the current network state, the multiple unmanned aerial vehicles change the formation array type, and the image of the current environment is shot through the holder; s3, sending the shot current image to a central controller or storing the shot current image to a plurality of storage modules of unmanned aerial vehicles; and S4, the central controller controls the display screen to display the current image and controls the unmanned aerial vehicles to attack the suspicious target based on the current image. S22, each unmanned aerial vehicle respectively collects the current transmission state xi (k) of the unmanned aerial vehicle and the central processing unit and the transmission state of the unmanned aerial vehicle at the last moment
Unmanned aerial vehicle in certain area
When, σi|xi(k) If the parameter is the threshold parameter belonging to (0,1), judging that the network delay occurs in the unmanned aerial vehicle shooting of the area, and re-allocating a plurality of unmanned aerial vehicles to shoot the area at the moment kt + 1. The invention mainly aims to provide a video monitoring method based on a quantum communication technology, which solves the problems of security holes and potential safety hazards in the existing video monitoring technology.
Description
Technical Field
The invention relates to a video monitoring system belonging to the field of security and protection, and relates to a video monitoring method based on quantum encryption.
Background
Video surveillance is an important component of security systems. The traditional monitoring system comprises a front-end camera, a transmission cable and a video monitoring platform, wherein the camera can be divided into a network digital camera and an analog camera and can be used for collecting front-end video image signals. The system is a comprehensive system with strong precaution capacity, and video monitoring is widely applied to many occasions due to intuition, accuracy, timeliness and rich information content. But present shooting supervisory equipment all adopts fixed mounting's mode, it adopts and has certain dead angle, and wherein the in-process of shooing, camera at the pivoted in-process of shooing, can have the shooting clearance, thereby cause certain security threat, among the prior art, though monitor a certain region through the combination technique of unmanned aerial vehicle and camera, can effectual solution shoot the dead angle and shoot the problem in clearance, the improvement of certain degree shoots and the security of control, however, do not consider its security problem that can bring for shooting task and monitoring area from network and communication security angle.
Disclosure of Invention
The invention mainly aims to provide a video monitoring method based on quantum encryption, which solves the problems of security holes and potential safety hazards in the existing video monitoring technology.
The application provides a video monitoring method based on quantum encryption, which is characterized by comprising the following steps:
s1, monitoring the network states of the unmanned aerial vehicles and the central controller;
s2, based on the current network state, the multiple unmanned aerial vehicles change the formation array type, and the image of the current environment is shot through the holder;
s3, sending the shot current image to a central controller or storing the shot current image to a plurality of storage modules of unmanned aerial vehicles;
s4, the central controller controls the display screen to display the current image and controls a plurality of unmanned aerial vehicles to attack the suspicious target based on the current image
Wherein, step S2, based on current network state, a plurality of unmanned aerial vehicles transform formation array type to shoot the image of current environment through the cloud platform and specifically include:
s21, each unmanned aerial vehicle respectively collects the current transmission state xi (k) of the unmanned aerial vehicle and the central processing unit and the transmission state of the unmanned aerial vehicle at the last moment
In that
When, σi|xi(k) | is a threshold parameter belonging to (0, 1); judging that the unmanned aerial vehicles in each area have no network problem, and shooting the environment of each area by the unmanned aerial vehicles in each area in real time;
s22, each unmanned aerial vehicle respectively collects the current transmission state xi (k) of the unmanned aerial vehicle and the central processing unit and the transmission state of the unmanned aerial vehicle at the last moment
Unmanned aerial vehicle in certain area
When, σi|xi(k) If the parameter is the threshold parameter belonging to (0,1), judging that the unmanned aerial vehicle in the area shoots the area with network delay, setting the unmanned aerial vehicle in the area as a alliance leader, and re-allocating a plurality of unmanned aerial vehicles to shoot the area by the alliance leader at the moment of kt + 1; the long plane of alliance communicates through quantum communication mode with many unmanned aerial vehicles, and wherein, trigger time kt +1 is:
kt+1＝infk{(k＞kt|[x(k)-x(kt)]TW[x(k)-x(kt)]＞σxT(kt)Wx(kt))}；
wherein, x (kt) is the latest transmission state of the alliance long machine at the triggering moment kt, and x (k) is the state of the alliance long machine at the current sampling moment; σ is a threshold parameter belonging to (0, 1);
and S23, when the unmanned aerial vehicle in the current area is not reconnected with the central controller at the preset moment, judging that the network is interrupted, subdividing the whole video monitoring area, and redistributing the shooting task of the unmanned aerial vehicle.
Preferably, the redeploying, by the leader of the alliance, the plurality of drones to shoot the area at the time kt +1 comprises: step 22.1: the alliance leader searches the task area i, when the first unmanned aerial vehicle in the task area i finds the target, the position information and the resource information of the target are obtained, and the first unmanned aerial vehicle becomes the alliance leader again; the long machine sends the position information and the resource information of the target to other unmanned aerial vehicles in the task area;
step 22.2, the idle unmanned aerial vehicle executing the search task returns the earliest arrival time and the total flight range to the long aircraft;
step 22.3, the long machine builds the alliance according to the returned information and sends the time of arrival of the alliance in the field to the alliance members; the long alliance machine obtains a task clustering optimization function based on a plurality of search subtasks and all unmanned aerial vehicles executing the tasks;
step 22.4, dividing the detection subtasks into a set number of subtask groups based on the task grouping optimization function;
and step 22.5, planning the unmanned plane flight path corresponding to each subtask group based on the acquired unmanned plane parameters, and distributing each subtask group to the corresponding unmanned plane.
Preferably, step 22.4, based on the task clustering optimization function, the dividing the detection subtasks into a set number of subtask clusters includes: the task clustering optimization function is: j. the design is a squareA＝ω1λ+ω2Eta, omega 1 and omega 2 are respectively the weight of the task group distribution index and the task total flight range index.
Preferably, the task group assignment index is:
wherein A isiRepresents the ith sub-task group in the set number of sub-task groups, S represents the number of sub-task groups,
represents AiT represents a search subtask,
representing search subtasks T and AiCluster center of
The euclidean distance of (c).
Preferably, the mission total flight range index is:
L(Projecti) MaxL (V) representing the flight required for the unmanned aerial vehicle Vi to execute the mission Allocation plani) Indicating unmanned aerial vehicle ViOf (d), apparently L (Project)i)≤MaxL(Vi)，i＝1,2…Nv；SpeediSetting the value as a constant for the flight speed of the unmanned aerial vehicle Vi in the task execution process; t (Project)i) And allocating the time required by protection for the unmanned aerial vehicle Vi to execute the task.
Preferably, the step S23 includes: the whole video monitoring area is subjected to grid division, each grid (i, j) is assigned with a variable W (i, j) to represent the attention degree of the grid, and the attention degree of each grid in the space can be described as follows:
Preferably, if the region is not detected, the attention degree of the region is increased by a proper amount, and the searching of the key region and the unsearched region can be guided with higher probability; the increase in its focus can be described as: p (i, j, t +1) ═ P (i, j, t) + W · W (i, j); wherein w is a non-negative constant;
preferably, the reward function of the video surveillance area search coverage is defined as: SF ∑ I ∑ J ∑ TFg (I, J, t) · P (I, J, t).
In addition, when the task is executed, each unmanned aerial vehicle respectively acquires the current transmission states xi (k) and xi (k) of the unmanned aerial vehicle and the central processing unitTransmission state of last moment
Unmanned aerial vehicle in certain area
When the unmanned aerial vehicle is used for shooting, network delay is judged to occur in the unmanned aerial vehicle shooting in the area, the fact that interference possibly occurs in the unmanned aerial vehicle executing task at the moment is explained, the important area needs to be monitored, the unmanned aerial vehicle is reconfigured in the important area, important monitoring is carried out, then an intruder possibly occurring in the area can be found, after communication is interrupted, the unmanned aerial vehicle loses control of the controller, the unmanned aerial vehicle reconstructs an unmanned aerial vehicle cluster, the shooting task in the whole monitoring area is redistributed, the monitoring force can be further improved, and then the intruder or the potential safety hazard in the area can be eliminated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a flow chart of a video monitoring method based on quantum encryption according to the present invention;
FIG. 2 is a flow chart of network delay unmanned aerial vehicle fleet deployment according to the present invention;
FIG. 3 is a control diagram of the drone swarm of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that all the directional indicators (such as up, down, left, right, front, and rear … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indicator is changed accordingly.
In addition, the descriptions related to "first", "second", etc. in the present invention are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
Referring to fig. 1 to 3, in the preferred embodiment, a video monitoring method based on quantum encryption includes the following steps:
s1, monitoring the network states of the unmanned aerial vehicles and the central controller;
s2, based on the current network state, the multiple unmanned aerial vehicles change the formation array type, and the image of the current environment is shot through the holder;
s3, sending the shot current image to a central controller or storing the shot current image to a plurality of storage modules of unmanned aerial vehicles;
s4, the central controller controls the display screen to display the current image and controls a plurality of unmanned aerial vehicles to attack the suspicious target based on the current image
Wherein, step S2, based on current network state, a plurality of unmanned aerial vehicles transform formation array type to shoot the image of current environment through the cloud platform and specifically include:
s21, each unmanned aerial vehicle respectively collects the current transmission state xi (k) of the unmanned aerial vehicle and the central processing unit and the transmission state of the unmanned aerial vehicle at the last moment
In that
When, σi|xi(k) | is a threshold parameter belonging to (0, 1); judging that the unmanned aerial vehicles in each area have no network problem, and shooting the environment of each area by the unmanned aerial vehicles in each area in real time;
s22, each unmanned aerial vehicle respectively collects the current transmission state xi (k) of the unmanned aerial vehicle and the central processing unit and the transmission state of the unmanned aerial vehicle at the last moment
Unmanned aerial vehicle in certain area
When, σi|xi(k) If the parameter is the threshold parameter belonging to (0,1), judging that the unmanned aerial vehicle in the area shoots the area with network delay, setting the unmanned aerial vehicle in the area as a alliance leader, and re-allocating a plurality of unmanned aerial vehicles to shoot the area by the alliance leader at the moment of kt + 1; the long plane of alliance communicates through quantum communication mode with many unmanned aerial vehicles, and wherein, trigger time kt +1 is:
kt+1＝infk{(k＞kt|[x(k)-x(kt)]TW[x(k)-x(kt)]＞σxT(kt)Wx(kt))}；
wherein, x (kt) is the latest transmission state of the alliance long machine at the triggering moment kt, and x (k) is the state of the alliance long machine at the current sampling moment; σ is a threshold parameter belonging to (0, 1);
and S23, when the unmanned aerial vehicle in the current area is not reconnected with the central controller at the preset moment, judging that the network is interrupted, subdividing the whole video monitoring area, and redistributing the shooting task of the unmanned aerial vehicle.
The invention is realized by the unmanned aerial vehicle and the unmanned aerial vehicleThe unmanned aerial vehicle is communicated in a quantum communication mode, so that the communication safety is ensured, and in addition, when a task is executed, each unmanned aerial vehicle respectively acquires the current transmission state xi (k) of the unmanned aerial vehicle and the central processing unit and the transmission state of the unmanned aerial vehicle at the last moment
Unmanned aerial vehicle in certain area
When the unmanned aerial vehicle is used for shooting, network delay is judged to occur in the unmanned aerial vehicle shooting in the area, the fact that interference possibly occurs in the unmanned aerial vehicle executing task at the moment is explained, the important area needs to be monitored, the unmanned aerial vehicle is reconfigured in the important area, important monitoring is carried out, then an intruder possibly occurring in the area can be found, after communication is interrupted, the unmanned aerial vehicle loses control of the controller, the unmanned aerial vehicle reconstructs an unmanned aerial vehicle cluster, the shooting task in the whole monitoring area is redistributed, the monitoring force can be further improved, and then the intruder or the potential safety hazard in the area can be eliminated.
The alliance leader relocates a plurality of unmanned aerial vehicles to shoot the area at kt +1 moment, and the method comprises the following steps: step 22.1: the alliance leader searches the task area i, when the first unmanned aerial vehicle in the task area i finds the target, the position information and the resource information of the target are obtained, and the first unmanned aerial vehicle becomes the alliance leader again; the long machine sends the position information and the resource information of the target to other unmanned aerial vehicles in the task area;
step 22.2, the idle unmanned aerial vehicle executing the search task returns the earliest arrival time and the total flight range to the long aircraft;
step 22.3, the long machine builds the alliance according to the returned information and sends the time of arrival of the alliance in the field to the alliance members; the long alliance machine obtains a task clustering optimization function based on a plurality of search subtasks and all unmanned aerial vehicles executing the tasks;
step 22.4, dividing the detection subtasks into a set number of subtask groups based on the task grouping optimization function;
and step 22.5, planning the unmanned plane flight path corresponding to each subtask group based on the acquired unmanned plane parameters, and distributing each subtask group to the corresponding unmanned plane.
The expression of the mathematical model added with the wind field influence factor is as follows:
wherein (x, y) is the coordinate position of the unmanned aerial vehicle on a two-dimensional plane, theta is a course angle, v and R are the flight speed and the minimum turning radius of the unmanned aerial vehicle respectively, u is control input, and (x, y, theta) belongs to R2X S represents the state of the drone, vw＝[vwx，vwy]Is the wind velocity vector, vwxAnd vwyThe velocity components of the wind in the x-axis and y-axis, respectively.
Step 22.4, based on the task clustering optimization function, dividing the detection subtasks into a set number of subtask groups, including: the task clustering optimization function is: j. the design is a squareA＝ω1λ+ω2Eta, omega 1 and omega 2 are respectively the weight of the task group distribution index and the task total flight range index.
Task group assignment index:
wherein A isiRepresents the ith sub-task group in the set number of sub-task groups, S represents the number of sub-task groups,
represents AiT represents a search subtask,
representing search subtasks T and AiCluster center of
The euclidean distance of (c). And (3) total flight range index of the mission:
L(Projecti) MaxL (V) representing the flight required for the unmanned aerial vehicle Vi to execute the mission Allocation plani) Indicating unmanned aerial vehicle ViOf (d), apparently L (Project)i)≤MaxL(Vi)，i＝1,2…Nv；SpeediSetting the value as a constant for the flight speed of the unmanned aerial vehicle Vi in the task execution process; t (Project)i) And allocating the time required by protection for the unmanned aerial vehicle Vi to execute the task.
After the communication is interrupted, the unmanned aerial vehicle carries out the task allocation again, carries out omnidirectional search to whole monitoring area to carry out the grid division with whole video region, make every grid can both be shot and control by unmanned aerial vehicle, thereby improved the coverage of shooing, and grid division mode wherein does: the step S23 includes: the whole video monitoring area is subjected to grid division, each grid (i, j) is assigned with a variable W (i, j) to represent the attention degree of the grid, and the attention degree of each grid in the space can be described as follows:
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (6)
1. A video monitoring method based on quantum encryption is characterized by comprising the following steps:
s1, monitoring the network states of the unmanned aerial vehicles and the central controller;
s2, based on the current network state, the multiple unmanned aerial vehicles change the formation array type, and the image of the current environment is shot through the holder;
s3, sending the shot current image to a central controller or storing the shot current image to a plurality of storage modules of unmanned aerial vehicles;
s4, the central controller controls the display screen to display the current image and controls the unmanned aerial vehicles to attack the suspicious target based on the current image;
wherein, step S2, based on current network state, a plurality of unmanned aerial vehicles transform formation array type to shoot the image of current environment through the cloud platform and specifically include:
s21, each unmanned aerial vehicle respectively collects the current transmission state x between the unmanned aerial vehicle and the central processing uniti(k) And the transmission state at the previous moment
In that
When, σi|xi(k) | is a threshold parameter belonging to (0, 1); judging that the unmanned aerial vehicles in each area have no network problem, and shooting the environment of each area by the unmanned aerial vehicles in each area in real time;
s22, each unmanned aerial vehicle respectively collects the current transmission state x between the unmanned aerial vehicle and the central processing uniti(k) And the transmission state at the previous moment
Unmanned aerial vehicle in certain area
When, σi|xi(k) If the parameter is the threshold parameter belonging to (0,1), judging that the unmanned aerial vehicle in the area shoots the area with network delay, setting the unmanned aerial vehicle in the area as a alliance leader, and re-allocating a plurality of unmanned aerial vehicles to shoot the area by the alliance leader at the moment kt + 1; the long plane of the alliance communicates with a plurality of unmanned aerial vehicles in a quantum communication mode, wherein the triggering time kt+1Comprises the following steps:
kt+1＝infk{(k＞kt|[x(k)-x(kt)]TW[x(k)-x(kt)]＞σxT(kt)Wx(kt))}；
wherein, x (k)t) The latest transmission state of the long alliance machine at the triggering moment kt is shown, and x (k) is the state of the long alliance machine at the current sampling moment; σ is a threshold parameter belonging to (0, 1); infk denotes the infimum bound, i.e. the smallest upper bound of the set; w is an event trigger matrix; w2]For triggering a time ktThe latest transmission state x (k) oft) Multiplying a matrix of difference values of the state x (k) of the long alliance machine at the current sampling moment by an event trigger matrix; x () is the trigger time ktThe latest transmission state x (k) oft)；
And S23, when the unmanned aerial vehicle in the current area is not reconnected with the central controller at the preset moment, judging that the network is interrupted, subdividing the whole video monitoring area, and redistributing the shooting task of the unmanned aerial vehicle.
2. The quantum encryption-based video surveillance method of claim 1, wherein the alliance leader relocates a plurality of drones to shoot the area at kt +1 comprises: step 22.1: the alliance leader searches the task area i, when the first unmanned aerial vehicle in the task area i finds the target, the position information and the resource information of the target are obtained, and the first unmanned aerial vehicle becomes the alliance leader again; the long machine sends the position information and the resource information of the target to other unmanned aerial vehicles in the task area;
step 22.2, the idle unmanned aerial vehicle executing the search task returns the earliest arrival time and the total flight range to the long aircraft;
step 22.3, the long machine builds the alliance according to the returned information and sends the time of arrival of the alliance in the field to the alliance members; the long alliance machine obtains a task clustering optimization function based on a plurality of search subtasks and all unmanned aerial vehicles executing the tasks;
step 22.4, dividing the detection subtasks into a set number of subtask groups based on the task grouping optimization function;
and step 22.5, planning the unmanned plane flight path corresponding to each subtask group based on the acquired unmanned plane parameters, and distributing each subtask group to the corresponding unmanned plane.
3. The video monitoring method based on quantum cryptography according to claim 2, wherein the step 22.4 of dividing the detection subtasks into a set number of subtask groups based on a task grouping optimization function comprises: the task clustering optimization function is: j. the design is a squareA＝ω1λ+ω2Eta, omega 1 and omega 2 are respectively the weight of the distribution index of the task group and the total flight distance index of the task; lambda is a task group distribution index; eta is the total flight path index of the mission;
task group assignment index:
wherein Ai represents the ith sub-task group in the set number of sub-task groups, S represents the number of the sub-task groups,
represents the cluster center of Ai, T represents the search subtask,
representing search subtasks T and AiClustering center
The Euclidean distance of (c);
and (3) total flight range index of the mission:
L(Projecti) MaxL (V) representing the flight required for the unmanned aerial vehicle Vi to execute the mission Allocation plani) Indicating unmanned aerial vehicle ViOf (d), apparently L (Project)i)≤MaxL(Vi) Nv,. 1, 2.. n; speedi is the flight speed of the unmanned aerial vehicle Vi in the task execution process, and the value is set as a constant; t (Project)i) And allocating the time required by protection for the unmanned aerial vehicle Vi to execute the task.
4. The video monitoring method based on quantum encryption according to claim 1, wherein the step S23 includes: the whole video monitoring area is subjected to grid division, each grid (i, j) is assigned with a variable W (i, j) to represent the attention degree of the grid, and the attention degree of each grid in the space can be described as follows:
5. The method for monitoring video based on quantum cryptography according to claim 4, wherein if a region is not detected, the attention of the region is increased by a proper amount, and the search for the key region and the unsearched region can be conducted with higher probability; the increase in its focus can be described as: p (i, j, t +1) ═ P (i, j, t) + W · W (i, j); wherein w is a non-negative constant; p (i, j, t) is the grid (i, j) probability at time t.
6. The quantum encryption-based video surveillance method according to claim 5, wherein the reward function of the video surveillance area search coverage is defined as: SF ∑ I ∑ J ∑ t (projei) Fg (I, J, t) · P (I, J, t); t (project i) time required for the drone Vi to perform task allocation and protection.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110066483.5A CN112911225B (en) | 2021-01-19 | 2021-01-19 | Video monitoring method based on quantum encryption |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110066483.5A CN112911225B (en) | 2021-01-19 | 2021-01-19 | Video monitoring method based on quantum encryption |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112911225A CN112911225A (en) | 2021-06-04 |
| CN112911225B true CN112911225B (en) | 2022-01-28 |
Family
ID=76115089
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110066483.5A Active CN112911225B (en) | 2021-01-19 | 2021-01-19 | Video monitoring method based on quantum encryption |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112911225B (en) |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1639479B1 (en) * | 2003-06-30 | 2008-09-03 | Raytheon Company | Efficient memory controller |
| CN103777640B (en) * | 2014-01-15 | 2016-05-04 | 北京航空航天大学 | A kind of distributed control unmanned aerial vehicle group is concentrated sub-clustering formation method |
| CN103995539B (en) * | 2014-05-15 | 2016-04-20 | 北京航空航天大学 | A kind of unmanned plane autonomous formation evaluation index and MPC formation control method |
| US10147860B2 (en) * | 2015-04-19 | 2018-12-04 | Reebeez, Inc. | Lightweight thermionic microengines for aerial vehicles |
| CN105278542A (en) * | 2015-09-23 | 2016-01-27 | 沈阳航空航天大学 | Counter-attack countermeasure optimal strategy method for multi-unmanned plane cooperative strike task |
| CN105223964B (en) * | 2015-09-28 | 2018-03-09 | 沈阳航空航天大学 | A kind of control system for UAV Formation Flight |
| US10764114B2 (en) * | 2016-03-10 | 2020-09-01 | Cisco Technology, Inc. | Techniques for wireless access and wireline network integration |
| CN107017942A (en) * | 2017-05-22 | 2017-08-04 | 苏州席正通信科技有限公司 | A kind of fiber network monitoring and management system |
| EP3506665B1 (en) * | 2017-12-28 | 2020-10-21 | Tata Consultancy Services Limited | An aerial communication framework for providing communication services to users trapped in emergency |
| CN108521670B (en) * | 2018-03-14 | 2020-10-23 | 中国人民解放军国防科技大学 | UWB communication and positioning based method for multi-machine-oriented close formation flight and integrated system |
| CN109084774B (en) * | 2018-08-07 | 2022-07-26 | 西安电子科技大学 | Unmanned aerial vehicle cluster positioning method based on channel state information |
| CN109917805A (en) * | 2019-01-21 | 2019-06-21 | 西北工业大学 | A kind of lower multiple no-manned plane task assignment conflict resolution method of communication delay constraint |
| CN110018691B (en) * | 2019-04-19 | 2022-04-15 | 天津大学 | Flight state estimation system and method for small multi-rotor unmanned aerial vehicle |
| CN111192481B (en) * | 2019-12-17 | 2021-02-23 | 中国民用航空总局第二研究所 | Method for determining boundary of unmanned aerial vehicle control area of approach and departure procedure based on collision risk |
| CN111142555B (en) * | 2019-12-17 | 2020-12-22 | 中国民用航空总局第二研究所 | Airport unmanned aerial vehicle control area planning method based on collision risk |
-
2021
- 2021-01-19 CN CN202110066483.5A patent/CN112911225B/en active Active
Non-Patent Citations (2)
| Title |
|---|
| "基于最优停止理论的多无人机数据传输能耗优化";柔莹莹;《中国优秀硕士学位论文全文数据库》;20180515;全文 * |
| 多无人机协同任务分群方案研究;王毅，谢瑞煜，杨利斌，赵建军;《舰船电子工程》;20181020;第38卷(第10期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112911225A (en) | 2021-06-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109144097B (en) | Obstacle or ground recognition and flight control method, device, equipment and medium | |
| EP3509025A1 (en) | Automated multi-domain operational services | |
| CN114840022A (en) | MAS-based multi-unmanned system supervision control method | |
| CN111601361A (en) | Method and device for detecting key nodes of Ad hoc network in real time | |
| CN109118064B (en) | Optimal resource allocation method for probe task planning | |
| CN115187005B (en) | Scheduling method, device, equipment and storage medium | |
| US20180348358A1 (en) | Measuring an area of interest based on a sensor task | |
| CN112001309A (en) | Target searching method, device and equipment based on unmanned aerial vehicle cluster and storage medium | |
| CN115840463A (en) | Data processing method and device for unmanned aerial vehicle cluster cooperative reconnaissance | |
| CN114020028A (en) | Task allocation method based on multiple unmanned aerial vehicles | |
| CN112911225B (en) | Video monitoring method based on quantum encryption | |
| CN113821317B (en) | Side cloud cooperative microservice scheduling method, device and equipment | |
| CN109062677B (en) | Unmanned aerial vehicle system calculation migration method | |
| CN114244588B (en) | Big data analysis interception method and information interception system applying artificial intelligence analysis | |
| CN113253292B (en) | Unmanned aerial vehicle early warning processing method and system based on artificial intelligence technology | |
| CN113126651B (en) | Intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles | |
| US10873471B1 (en) | Measuring an area of interest based on a sensor task | |
| US20210334649A1 (en) | Apparatus and method for distributed reinforcement learning | |
| Taherizadeh et al. | Real-time data-intensive telematics functionalities at the extreme edge of the network: experience with the PrEstoCloud project | |
| Hu et al. | Research on evolution method of aircraft swarms space configuration based on event-driven | |
| CN115640106B (en) | Man-machine function distribution method and system for multi-unmanned aerial vehicle command control | |
| Rakushev et al. | The Technique of the Information and Telecommunication System" Terminal" Use for UAVs Acquired Data | |
| CN114077476B (en) | Multi-platform elastic avionics system cloud system and method | |
| CN114237284B (en) | Unmanned aerial vehicle multitasking planning method based on improved mayday algorithm | |
| CN117152650B (en) | Video content analysis method and video event information network for massive videos |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |