CN112486200A - Multi-unmanned aerial vehicle cooperative countermeasure online re-decision method - Google Patents
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Abstract
The invention provides a multi-unmanned aerial vehicle cooperative confrontation online re-decision method, and relates to the field of unmanned aerial vehicles. The method comprises the following steps: acquiring unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme; carrying out correlation processing on unmanned aerial vehicle air combat data; judging the passive triggering of the re-decision based on the emergency event which occurs when the unmanned aerial vehicle is in air battle, and analyzing the type of the passive triggering of the re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the re-decision triggering comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; carrying out conflict resolution processing on the type of the active trigger of the re-decision and the type of the active trigger of the re-decision to obtain the type of the re-decision of the unmanned aerial vehicle air combat scheme; and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the re-decision type of the unmanned aerial vehicle air combat scheme. The application can enhance the adaptability of the unmanned aerial vehicle air combat scheme during execution.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an online re-decision method for cooperative confrontation of multiple unmanned aerial vehicles.
Background
With the development of science and technology, unmanned aerial vehicles have become one of the important unmanned aerial vehicles in the military field. Unmanned aerial vehicle can independently accomplish multiple tasks, however, unmanned aerial vehicle is continuously propelled in the relevant field application, and single unmanned aerial vehicle has exposed the short slab of flexibility and task completion rate when carrying out the task, therefore, application many unmanned aerial vehicles constitute the cooperative combat system of mutual cooperation, advantage complementation, efficiency multiplication in the air, have become the focus and the target of pursuing of field attention.
The cooperative confrontation of the multiple unmanned aerial vehicles is a complex confrontation process, wherein each unmanned aerial vehicle is responsible for different roles and can execute one or more subtasks, and the tasks which cannot be completed by a single unmanned aerial vehicle can be completed through mutual cooperation and decision among the multiple unmanned aerial vehicles, so that the battle efficiency of the unmanned aerial vehicles is improved. The air combat scheme needs to be deployed before cooperative combat by the multiple unmanned aerial vehicles, so that the unmanned aerial vehicles complete air combat tasks according to the air combat scheme.
However, the inventor of the application finds that in the multi-unmanned-aerial-vehicle cooperative countermeasure environment, the countermeasure situation is changeable instantly, the characteristics of high dynamic, strong real-time and uncertain depth are presented, the overall process time of multi-unmanned-vehicle cooperative countermeasure is long, and detailed prediction on the action of an enemy cannot be made, so that tactical decision, target distribution and other decisions before battle are possibly not suitable for the current environment along with the progress of the countermeasure process, and therefore, a heavy decision needs to be made on an unmanned-aerial-vehicle air combat scheme to solve the defect of poor adaptability of the air combat scheme.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a multi-unmanned aerial vehicle cooperative confrontation online re-decision method, which solves the technical problem of poor adaptability of the prior art.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention provides a multi-unmanned aerial vehicle cooperative countermeasure online re-decision method for solving the technical problem, which is executed by a computer and comprises the following steps:
acquiring unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme;
performing correlation processing on the unmanned aerial vehicle air combat data;
judging the passive triggering of the re-decision based on the emergency event which occurs during the air battle of the unmanned aerial vehicle, and analyzing the type of the passive triggering of the re-decision, wherein the type of the passive triggering of the re-decision comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the active triggering of the re-decision comprises the following steps: tactical re-decision, task re-decision and behavior re-decision;
performing conflict resolution processing on the type of the re-decision passive trigger and the type of the re-decision active trigger to obtain an unmanned aerial vehicle air combat scheme re-decision type;
and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the unmanned aerial vehicle air combat scheme re-decision type.
Preferably, the unmanned aerial vehicle air combat data comprises: enemy flight control data, my flight control data and task action data;
the enemy flight control data includes: the method comprises the following steps of (1) carrying out enemy aircraft speed, enemy aircraft height, enemy aircraft longitude and latitude, enemy aircraft course angle, enemy aircraft roll angle and enemy aircraft pitch angle;
the my party flight control data comprises: the speed, the height, the longitude and latitude, the course angle, the roll angle, the pitch angle and the number of the remaining missiles of the unmanned aerial vehicle of the same party;
the task activity data includes: the number of unmanned aerial vehicles of my party, the number of unmanned aerial vehicles of enemy, the current tactics of my party and the current target distribution list of my party.
Preferably, the performing the association processing on the unmanned aerial vehicle air combat data includes:
preprocessing the unmanned aerial vehicle air combat data based on a data cleaning method;
and performing correlation analysis on the preprocessed unmanned aerial vehicle air combat data based on a correlation algorithm.
Preferably, the determining the passive triggering of the re-decision based on the emergency event occurring during the air battle of the unmanned aerial vehicle and analyzing the type of the passive triggering of the re-decision includes:
for the emergency K, judging the type of the emergency K, wherein the type of the emergency K comprises a first-level emergency, a second-level emergency and a third-level emergency;
if the emergency K is a primary emergency, immediately judging that the decision is triggered passively, wherein the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and continuously judging the passive trigger of the next decision-making;
if the emergency K is a secondary emergency, judging whether the time interval delta t from the moment of the last re-decision passive triggering to the moment of the emergency K is greater than or equal to a first period or not; if yes, immediately judging that the decision is triggered passively to make a decision, wherein the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and continuously judging the passive trigger of the next decision-making; if not, adding the emergency K into a secondary emergency list; when the first period is finished, the method determines that the re-decision is triggered passively, and the type of the re-decision passive trigger is as follows: the decision-making type with the highest priority in the decision-making types corresponding to all the emergency events in the secondary emergency event list; and continuing to judge the passive triggering of the next re-decision;
if the emergency K is a third-level emergency, judging whether the time interval delta t from the moment of the last re-decision passive triggering to the moment of the emergency K is greater than or equal to a first period or not; if yes, immediately judging that the decision is triggered passively to make a decision, wherein the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and continuously judging the passive trigger of the next decision-making; if not, adding the emergency K into a third-level emergency list; when the second period is finished, the passive trigger re-decision is determined, and the type of the re-decision passive trigger is as follows: the decision-making type with the highest priority in the decision-making types corresponding to all the emergency events in the third-level emergency event list; and continuing to judge the passive triggering of the next re-decision;
the priority of the re-decision type is: tactical re-decision > task re-decision > behavioral re-decision.
Preferably, the primary emergency event includes: the method comprises the following steps that a failure event of the unmanned aerial vehicle of the my party, a number change event of the unmanned aerial vehicles of the enemy party, a radar locking event of the unmanned aerial vehicle of the my party by the enemy party, a re-decision command event issued by a command center, a new task event issued by the command center and a task completion event are issued by the command center;
the secondary emergency event comprises: the method comprises the following steps that an event that the speed of the unmanned aerial vehicle of the owner is lower than a threshold value, an event that the height of the unmanned aerial vehicle of the owner is lower than the threshold value and an event that the residual energy of the unmanned aerial vehicle of the owner is lower than the threshold value are taken;
the tertiary emergency events include: the method comprises the following steps of an event that the communication of the unmanned aerial vehicle of the my party is interrupted, an event that the surplus of the unmanned aerial vehicle of the my party is lower than a threshold value, an event that the position of the unmanned aerial vehicle of the my party exceeds a communication range and a weather environment change event.
Preferably, the determining the active triggering of the re-decision based on the correlated unmanned aerial vehicle air combat data and analyzing the type of the active triggering of the re-decision include:
starting timing from the moment of the last re-decision passive triggering, judging whether the timing time delta t is greater than or equal to a first period, and if not, waiting;
if yes, then:
calculating global similarity based on the correlated unmanned aerial vehicle air combat data and a preset case library; judging whether the global similarity exceeds a preset global similarity threshold, and if so, judging that case reasoning re-decision is actively triggered;
carrying out rule reasoning on the associated unmanned aerial vehicle air combat data, judging whether a preset rule reasoning condition is met or not, and if so, judging that rule reasoning is actively triggered to make a decision again;
performing conflict resolution on the type of the case reasoning re-decision active trigger and the type of the rule reasoning re-decision active trigger to obtain the type of the re-decision active trigger, and judging the type of the re-decision active trigger as the active trigger of the re-decision; and continuing to judge the active trigger of the next re-decision after waiting for the time of the first period.
Preferably, the performing conflict resolution on the type of the case inference re-decision active trigger and the type of the rule inference re-decision active trigger to obtain the type of the re-decision active trigger includes:
when the case reasoning re-decision and the rule reasoning re-decision are triggered independently, the case reasoning re-decision and the rule reasoning re-decision are judged to trigger the re-decision of the corresponding type actively;
when the case reasoning re-decision and the rule reasoning re-decision are all triggered, comparing the sizes of the case reasoning score and the rule reasoning score, and judging that the type corresponding to the re-decision with the higher active triggering score is determined;
the case inference score refers to: the product of the global similarity and a weight coefficient of a type corresponding to the case-based reasoning decision-making; the rule inference score indicates: the rule reasoning re-decision is used for determining the weight coefficient of the corresponding type;
the weight coefficients are: tactical re-decision is a, mission re-decision is b, behavior re-decision is c, and a > b > c.
Preferably, the calculating the global similarity based on the correlated unmanned aerial vehicle air combat data and a preset case library includes:
extracting characteristic attributes of the associated unmanned aerial vehicle air combat data;
searching a preset case base, and confirming each case in the case base;
comparing the extracted characteristic attributes with each case, and calculating attribute similarity;
calculating a global similarity based on the attribute similarities.
Preferably, performing conflict resolution processing on the type of the re-decision passive trigger and the type of the re-decision active trigger includes:
if the type of the re-decision passive trigger is the same as that of the re-decision active trigger, judging to execute a corresponding re-decision type;
if the type of the re-decision passive trigger is different from that of the re-decision active trigger, executing the following steps based on a preset priority: a high-priority re-decision type in the re-decision passive triggering type and the re-decision active triggering type; the preset priority is as follows: tactical re-decision > task re-decision > behavioral re-decision.
Preferably, the performing of the re-decision processing on the unmanned aerial vehicle air combat scheme based on the unmanned aerial vehicle air combat scheme re-decision type includes:
selecting a re-decision method based on a preset method library, and performing re-decision processing of corresponding types on the unmanned aerial vehicle air combat schemes to obtain a plurality of re-decided unmanned aerial vehicle air combat schemes;
and extracting a re-decision scheme selection method based on a preset method library, selecting a re-decided unmanned aerial vehicle air combat scheme, and executing the scheme.
(III) advantageous effects
The invention provides a multi-unmanned aerial vehicle cooperative confrontation online re-decision method. Compared with the prior art, the method has the following beneficial effects:
the unmanned aerial vehicle air combat data is obtained when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme; carrying out correlation processing on unmanned aerial vehicle air combat data; judging the passive triggering of the re-decision based on the emergency event which occurs when the unmanned aerial vehicle is in air battle, and analyzing the type of the passive triggering of the re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the re-decision triggering comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; carrying out conflict resolution processing on the type of the active trigger of the re-decision and the type of the active trigger of the re-decision to obtain the type of the re-decision of the unmanned aerial vehicle air combat scheme; and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the re-decision type of the unmanned aerial vehicle air combat scheme. The invention triggers and judges the re-decision from an active layer and a passive layer and carries out conflict resolution on the two re-decision types, thereby executing the re-decision on the unmanned aerial vehicle air combat scheme, enhancing the adaptability of the unmanned aerial vehicle air combat scheme during execution, and enabling the re-decision to change situation, change from bad to excellent and effectively enhance the situation advantage of the same party in the countermeasure process.
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 drawings without creative efforts.
Fig. 1 is an overall flowchart of a cooperative countermeasure online re-decision method for multiple drones according to an embodiment of the present invention;
fig. 2 is a flowchart of a multi-drone cooperative countermeasure online re-decision method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but 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.
The embodiment of the application solves the problem of poor adaptability of the prior art and improves the adaptability of the air combat scheme by providing the online re-decision method for the cooperative confrontation of the multiple unmanned aerial vehicles.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the method and the device for controlling the unmanned aerial vehicle air combat system acquire unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme; carrying out correlation processing on unmanned aerial vehicle air combat data; judging the passive triggering of the re-decision based on the emergency event which occurs when the unmanned aerial vehicle is in air battle, and analyzing the type of the passive triggering of the re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the re-decision triggering comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; carrying out conflict resolution processing on the type of the active trigger of the re-decision and the type of the active trigger of the re-decision to obtain the type of the re-decision of the unmanned aerial vehicle air combat scheme; and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the re-decision type of the unmanned aerial vehicle air combat scheme. The embodiment of the invention triggers and judges the re-decision from an active layer and a passive layer and carries out conflict resolution on the two re-decision types, thereby executing the re-decision on the unmanned aerial vehicle air combat scheme, enhancing the adaptability of the unmanned aerial vehicle air combat scheme during execution, and enabling the re-decision to change situation, change from bad to excellent and effectively enhance the situation advantage of our situation in the countermeasure process.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
The embodiment of the invention provides a multi-unmanned aerial vehicle cooperative confrontation online re-decision method, which is executed by a computer. As shown in fig. 1, which is an overall flowchart of an embodiment of the present invention, fig. 2 is a flowchart of a flow framework of an embodiment of the present invention, and the method includes the following steps:
s1, acquiring unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme;
s2, performing correlation processing on the unmanned aerial vehicle air combat data;
s3, judging the passive triggering of the re-decision based on the emergency happening during the unmanned aerial vehicle air battle, and analyzing the type of the passive triggering of the re-decision, wherein the type of the passive triggering of the re-decision comprises: tactical re-decision, task re-decision and behavior re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the active triggering of the re-decision comprises the following steps: tactical re-decision, task re-decision and behavior re-decision;
s4, carrying out conflict resolution processing on the type of the re-decision passive trigger and the type of the re-decision active trigger to obtain the air combat scheme re-decision type of the unmanned aerial vehicle;
and S5, carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the unmanned aerial vehicle air combat scheme re-decision type.
The method and the device for controlling the unmanned aerial vehicle air combat system acquire unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme; carrying out correlation processing on unmanned aerial vehicle air combat data; judging the passive triggering of the re-decision based on the emergency event which occurs when the unmanned aerial vehicle is in air battle, and analyzing the type of the passive triggering of the re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the re-decision triggering comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; carrying out conflict resolution processing on the type of the active trigger of the re-decision and the type of the active trigger of the re-decision to obtain the type of the re-decision of the unmanned aerial vehicle air combat scheme; and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the re-decision type of the unmanned aerial vehicle air combat scheme. The embodiment of the invention triggers and judges the re-decision from an active layer and a passive layer and carries out conflict resolution on the two re-decision types, thereby executing the re-decision on the unmanned aerial vehicle air combat scheme, enhancing the adaptability of the unmanned aerial vehicle air combat scheme during execution, and enabling the re-decision to change situation, change from bad to excellent and effectively enhance the situation advantage of our situation in the countermeasure process.
The following is a detailed analysis of each step.
In step S1, unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute the unmanned aerial vehicle air combat plan is acquired.
Specifically, unmanned aerial vehicle air combat data includes: enemy flight control data, my flight control data, and task action data.
Wherein, through fire control radar acquisition enemy flight control data, include: the device comprises a enemy plane speed, an enemy plane height, an enemy plane longitude and latitude, an enemy plane course angle, an enemy plane roll angle and an enemy plane pitch angle.
Acquire our side through unmanned aerial vehicle self sensor and fly to control data, include: the speed, the height, the longitude and latitude, the course angle, the roll angle, the pitch angle and the number of the remaining missiles of the unmanned aerial vehicle of the same party.
Acquiring task action data through a battle command center, wherein the task action data comprises the following steps: the number of unmanned aerial vehicles of my party, the number of unmanned aerial vehicles of enemy, the current tactics of my party and the current target distribution list of my party.
In step S2, the unmanned aerial vehicle air combat data is subjected to correlation processing. The method specifically comprises the following steps:
preprocessing the unmanned aerial vehicle air combat data based on a data cleaning method;
and performing correlation analysis on the preprocessed unmanned aerial vehicle air combat data based on a correlation algorithm.
In the embodiment of the present invention, the data cleansing method and the associated algorithm are all the prior art, and are not described herein.
In step S3, determining a passive trigger for a re-decision based on an emergency occurring during an air battle of the unmanned aerial vehicle, and analyzing the type of the passive trigger for the re-decision; and judging the active triggering of the re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision.
Wherein the types of the re-decision trigger include: tactical re-decisions, mission re-decisions, and behavior re-decisions.
Tactical re-decision means: in the cooperative countermeasure process of multiple unmanned aerial vehicles, when the multiple unmanned aerial vehicles of the same party encounter the conditions of being serious and threatening the safety of the multiple unmanned aerial vehicles, tactical re-decision can be made, for example: the unmanned aerial vehicle of our party is damaged, and the command center forces factors such as a heavy decision and the like. The tactical re-decision is the top layer of the hierarchical re-decision, and determines the macro re-decision of the multiple drones, for example: flank roundabout cooperative tactics, bidirectional roundabout cooperative tactics, vertical unwrap cooperative tactics, horizontal unwrap cooperative tactics, combined unwrap cooperative tactics, and the like.
Task re-decision means: in the cooperative countermeasure process of multiple unmanned aerial vehicles, when the situation change of an enemy exceeds a threshold value, tasks are increased or reduced by one party, and the like, the safety of the multiple unmanned aerial vehicles of the one party is not threatened, so that tactical re-decision is not needed, and at the moment, the task re-decision of a mesoscopic level can be carried out. The task re-decision is positioned in the middle layer of the layered re-decision, provides decisions such as task re-allocation and target re-allocation for the multiple unmanned aerial vehicles, and belongs to the mesoscopic layered re-decision.
Behavior re-decision means: in the process of multi-unmanned aerial vehicle confrontation, on one hand, the confrontation process is a process from far to near, when the long-distance confrontation fails to determine the victory or defeat, the battle generally shifts to a close combat, and the triggered re-decision is a behavior re-decision. On the other hand, the behavior change of the enemy in the next step is predicted according to the factors such as the speed, the angle and the height of the enemy unmanned aerial vehicle in the countermeasure process, and when the triggering threshold value of the re-decision is reached, the behavior re-decision is carried out. The behavior re-decision is positioned at the lowest layer in the hierarchical re-decision, and is mainly used for providing instantaneous maneuver re-decision for a single unmanned aerial vehicle, such as: keeping the original flight; the maximum acceleration is directly flown; maximum overload left turn; maximum overload right turn; climbing under maximum overload; maximum overload dive; the specific measures such as maximum deceleration flight and the like belong to the decision-making at the microscopic level.
It should be noted that, in the embodiment of the present invention, according to the severity and the emergency degree of the emergency event affecting the cooperative countermeasure of the multiple drones, three emergency events may be set in advance by using methods such as expert evaluation, and are respectively recorded as: primary emergency, secondary emergency, and tertiary emergency. Wherein, the urgency of the first level emergency is the highest and needs to be executed preferentially, the urgency of the second level emergency is the second level emergency, and the urgency of the third level emergency is the weakest. Meanwhile, in order to avoid excessive repeated re-decision, the first period is preset as TminAnd the second period is T.
Specifically, the method for judging the re-decision passive triggering comprises the following steps:
when the cooperative confrontation of the multiple unmanned aerial vehicles is started, whether an emergency happens is always detected.
And judging the type of the emergency K, including a first-level emergency, a second-level emergency and a third-level emergency.
And if the emergency K is a primary emergency, immediately judging that the decision is a passive triggering decision, namely judging that the decision is a passive triggering decision when the emergency K occurs. And the type of the re-decision passive trigger is the re-decision type corresponding to the emergency K, and the next passive trigger of the re-decision is continuously judged.
If the emergency K is a secondary emergency, judging whether the time interval delta T from the moment of the last re-decision passive triggering to the moment of the emergency K is more than or equal to a first period Tmin(ii) a If yes, the method immediately judges that the decision is triggered again passively, the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and the next time of the decision-making passive trigger is continuously judged. And if not, adding the emergency K into the secondary emergency list. When the first period is finished, the method determines that the re-decision is passively triggered, namely the emergency K passes through the first period T after the occurrence of the emergency KminAfter corresponding time, determining to be passively triggered to make a re-decision; the type of the re-decision passive trigger is as follows: the decision-making type with the highest priority in the decision-making types corresponding to all the emergency events in the secondary emergency event list; and continuing to judge the passive triggering of the next re-decision.
In the embodiment of the present invention, the priority of the re-decision type is: tactical re-decision > task re-decision > behavioral re-decision.
Specifically, the re-decision types corresponding to all the emergency events in the secondary emergency event list are summarized, and the re-decision type with the highest triggering priority is determined.
If the emergency K is a third-level emergency, judging whether the time interval delta T from the moment of the last re-decision passive triggering to the moment of the emergency K is greater than or equal to a first period Tmin(ii) a If yes, the method immediately judges that the decision is triggered again passively, the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and the next time of the decision-making passive trigger is continuously judged. If not, adding the emergency K into a third-level emergency list; when the second period T is finished, determining that the re-decision is triggered passively, namely determining that the re-decision is triggered passively after the time corresponding to the second period T passes after the emergency K occurs; whereinThe type of the re-decision passive trigger is: the decision-making type with the highest priority in the decision-making types corresponding to all the emergency events in the third-level emergency event list; and continuing to judge the passive triggering of the next re-decision.
In the embodiment of the present invention, the first period T may be setminFor 5s, and a second period T of 8 s.
Primary emergencies include: the method comprises the following steps that a failure event of the unmanned aerial vehicle of the my party, a radar locking event of the unmanned aerial vehicle of the my party, a number change event of the unmanned aerial vehicles of the enemies, a re-decision command event issued by a command center, a new task event issued by the command center and a task completion event are issued by the command center.
Wherein, my unmanned aerial vehicle failure event means: in the countermeasure process, when the unmanned aerial vehicle of our party has the condition such as damage, mechanical failure, trigger tactics and decide again.
The event that my unmanned aerial vehicle is locked by enemy radar means that: in the countermeasure process, when my unmanned aerial vehicle is locked by an enemy radar, behavior re-decision is triggered.
The enemy unmanned aerial vehicle number change event is as follows: when the enemy increases or decreases the unmanned aerial vehicles, the mission planning and the target distribution of the enemy are influenced, and tactical re-decision is triggered.
The command center issues a re-decision command event: in the countermeasure process, when the command center issues a re-decision command, a tactical re-decision is triggered.
The command center issues a new task event finger: when a new task is issued, the current task planning arrangement is changed, the new task needs to be reasonably distributed, and task re-decision is triggered.
The task completion event means: the completion of each task can fluctuate the overall task progress of our parties. Therefore, after a task is completed, task arrangement needs to be performed again, and task re-decision is triggered.
Secondary emergencies include: the method comprises the following steps of an event that the speed of the unmanned aerial vehicle of the my party is lower than a threshold value, an event that the height of the unmanned aerial vehicle of the my party is lower than a threshold value and an event that the remaining energy of the unmanned aerial vehicle of the my party is lower than a threshold value.
Wherein, the event that the speed of the unmanned aerial vehicle of our party is lower than the threshold means: in the countermeasure process, when the speed of the unmanned aerial vehicle of the party is too low, behavior re-decision is triggered.
Event that the height of unmanned aerial vehicle of my party is lower than the threshold means: in the countermeasure process, when the flying height of the unmanned aerial vehicle at the party is too low, action re-decision is triggered.
Event that the remaining energy of unmanned aerial vehicle of my party is lower than the threshold value means: in the countermeasure process, the platform of our party has insufficient residual energy, which causes the conditions of unstable signal and position judgment and triggers task re-decision.
Three levels of emergency events include: the method comprises the following steps of an event that the communication of the unmanned aerial vehicle of the my party is interrupted, an event that the surplus of the unmanned aerial vehicle of the my party is lower than a threshold value, an event that the position of the unmanned aerial vehicle of the my party exceeds a communication range and a weather environment change event.
Wherein, my party unmanned aerial vehicle communication interruption event indicates: in the process of confrontation, when the enemy platform causes a communication terminal to the platform of the enemy through radar interference and other modes, the task is triggered to make a decision again.
The event that the surplus bullet of the unmanned aerial vehicle of the my party is lower than the threshold value means that: in the countermeasure process, when the platform of the client has the conditions of insufficient residual elasticity and the like, the task re-decision is triggered at the moment.
The event that the position of the unmanned aerial vehicle of the party exceeds the communication range means that: in the countermeasure process, the flight position of the platform at one part exceeds the communication range between friend machines, so that poor or interrupted communication is caused, and action decision is triggered.
Weather environment change events refer to: in the countermeasure process, when the weather environment changes, information interaction and other conditions of the platform of the party are influenced, and behavior re-decision is triggered.
Judging the initiative trigger of the decision-making again based on the unmanned aerial vehicle air combat data after the association, including:
s301, starting timing from the moment of the last re-decision passive triggering, judging whether the timing time delta t is greater than or equal to a first period, and if not, waiting.
If yes, then:
s302, calculating global similarity based on the unmanned aerial vehicle air combat data after correlation and a preset case base.
In the embodiment of the invention, the cases in the case base can be obtained through the historical combat experiences of multiple unmanned aerial vehicles of one party, can also be obtained through the historical combat experiences of other unmanned aerial vehicles or manned machines, and the case base can be updated according to the condition of the re-decision after the re-decision is finished each time.
In the embodiment of the present invention, a case library is exemplarily given as shown in table 1.
TABLE 1 Re-decision trigger case base
| Case | RS1 | RS2 | DH | RPX | RPY | GS | RV | Type of re-decision |
| 1 | 2 | 2 | 0 | Tactical re-decision | ||||
| 2 | 2 | 1 | 0 | 0 | Tactical re-decision | |||
| 3 | 1 | 2 | 0 | 0 | Tactical re-decision | |||
| 4 | 0 | 0 | Tactical re-decision | |||||
| 5 | 0 | 1 | -2 | 0 | Tactical re-decision | |||
| 6 | 1 | 1 | 1 | 2 | 1 | Task re-decision | ||
| 7 | 1 | 1 | 0 | 1 | 1 | Task re-decision | ||
| 8 | 1 | 1 | 2 | 0 | 0 | Task re-decision | ||
| 9 | 2 | 0 | 1 | 1 | 0 | Task re-decision | ||
| 10 | 0 | 2 | 1 | 1 | Task re-decision | |||
| 11 | 1 | 1 | 1 | -0 | -0 | 1 | 1 | Behavioral re-decision |
| 12 | 1 | 1 | 2 | 1 | 1 | Behavioral re-decision | ||
| 13 | 1 | 1 | 0 | 2 | 1 | 0 | Behavioral re-decision | |
| 14 | 1 | 0 | 2 | 1 | 1 | 1 | Behavioral re-decision |
Wherein: in the table, "-0" indicates "non-0 value", and indicates attribute values of 1 and 2; "-2" represents a "non-2 value", representing attribute values of 0 and 1; in the table, white represents "0", "1" and "2".
The re-decision feature attribute notation is shown in table 2.
Table 2 re-decision characteristic attribute correspondence symbol table
| Serial number | Re-decision feature attributes | Symbol |
| 1 | Relative situation variable of long plane and enemy plane | RS1 |
| 2 | Relative situation variable of wing plane and enemy plane | RS2 |
| 3 | Flight altitude difference variable of enemy plane and formation of our party | DH |
| 4 | Horizontal position variable of enemy against my formation | RPX |
| 5 | Vertical position variable of enemy relative to my formation | RPY |
| 6 | Selected state of enemy attack target | GS |
| 7 | Relative speed difference variable of both friend and foe | RV |
The re-decision feature attribute values are shown in table 3.
TABLE 3 Re-decision feature Attribute dereferencing
The global similarity calculation method comprises the following steps:
and S3021, extracting characteristic attributes of the unmanned aerial vehicle air combat data after correlation.
Specifically, the types of attributes are of two types: one is to determine the symbolic attributes, the relative situation of a grand plane or a wing plane and a enemy plane, the selected state of an enemy attack target, the flight altitude difference of the enemy plane and a formation of the enemy plane, the horizontal position and the vertical position of the enemy plane relative to the formation of a formation of. The second is determining number attributes, and the difference between the determining number attributes can be reflected by the distance between points.
S3022, searching the preset case base, and confirming each case in the case base.
And S3023, comparing the extracted characteristic attributes with each case, and calculating attribute similarity. The attribute similarity calculation method is as follows:
determining the symbol attribute:
Determining a number attribute:
And S3024, calculating the global similarity based on the attribute similarity.
When the global similarity is calculated, the calculation can be performed only according to the common attributes, and therefore, the normalization process needs to be performed again on the weight of each common attribute, and the calculation method is as follows:
in the above formula, the global similarity is represented by Ssim(Q, C) represents, wherein Q represents the characteristic attribute set of the problem case, C represents the characteristic attribute set of the source case, m is the number of characteristic attributes in the intersection of Q and C, and omegaiWeight, W, representing the ith characteristic attribute in the intersection of Q and CQ∩CRepresenting the sum of the weights of all feature attributes in the intersection of Q and C.
And judging whether the global similarity exceeds a preset global similarity threshold, and if so, judging that case reasoning re-decision is actively triggered.
And when the global similarity exceeds a preset global similarity threshold, judging that case reasoning re-decision is actively triggered. And extracting the case with the maximum attribute similarity, and taking the type corresponding to the case as the re-decision type of the case reasoning re-decision.
In the embodiment of the present invention, the threshold is set to 0.8.
And S303, carrying out rule reasoning on the associated unmanned aerial vehicle air combat data, judging whether a preset rule reasoning condition is met, and if so, judging that the rule reasoning decision is actively triggered.
Specifically, the rule reasoning means that advantages such as situation advantages and capability advantages are calculated according to collected unmanned aerial vehicle air combat data, and when certain conditions are met, a re-decision is triggered.
The rule reasoning in the embodiment of the invention is mainly judged from three aspects of target miss of the missile, decision miss and failure, situation crisis of our party and the like. The preset rule reasoning conditions comprise:
missile miss target: when the missile of one party does not hit the target of the enemy, the number of the missiles is reduced, the missiles are in unfavorable positions, and tactical re-decision should be made in time. When the enemy missile does not hit the enemy missile, the enemy missile should quickly adopt attack situation, increase the situation advantage of the enemy missile, and make tactical re-decision.
Decision errors and failures: too large a prediction error will lead to a decision miss and a rapid change in the battlefield situation dominance will lead to a decision failure. Both errors and failures are reflected in significant deviations of the actual battlefield situation advantage from the predicted outcome of the last decision. At time t, triggering task re-decision if one of the following conditions is met:
wherein: x (t),
Eta (t) is the longitude and latitude of the position of the local machine at the time t, the longitude and latitude of the position of the enemy machine and the situation dominance value respectively;
for X (t) and X (t) in the last decision,
A predicted value of η (t); Δ Xmax、ΔXTmaxAnd Δ ηmaxIs a threshold value.
The situation of our party is critical: when the local computer enters a state with a very unfavorable situation, the last decision result can not be adopted at the moment, and a new decision should be triggered to change the unfavorable situation in time. That is, at time t, a behavior re-decision is triggered if the following conditions are met.
η(t)＜ηmin
Wherein: eta (t) is a situation dominance function of the enemy of the party; etaminIs the threshold of the situational merit function.
S304, conflict resolution is carried out on the active trigger case reasoning re-decision and the rule reasoning re-decision, the type of the re-decision active trigger is obtained, and the re-decision active trigger is judged.
Specifically, when the case reasoning re-decision and the rule reasoning re-decision are triggered independently, the case reasoning re-decision and the rule reasoning re-decision are judged to trigger the re-decision of the corresponding type actively.
When only the case reasoning re-decision is triggered, the case reasoning re-decision type is judged to be actively triggered; and when only triggering the rule inference re-decision, judging as the re-decision type for actively triggering the rule inference re-decision.
And when the case reasoning re-decision and the rule reasoning re-decision are all triggered, comparing the sizes of the case reasoning score and the rule reasoning score, and judging the type corresponding to the re-decision with the higher active triggering score.
Specifically, when the case reasoning score is greater than the rule reasoning score, the type of triggering the case reasoning re-decision is determined; and when the rule reasoning score is larger than the case reasoning score, judging the type of triggering the rule reasoning re-decision.
In the embodiment of the invention, case reasoning score indicates that: and the product of the global similarity and the weight coefficient of the type corresponding to the case reasoning decision-making.
Specifically, weighting coefficients are given to three types of re-decisions in advance: tactical re-decision is a, mission re-decision is b, behavior re-decision is c, and a > b > c. For example, it may be: tactical re-decision is 3, task re-decision is 2, and behavior re-decision is 1.
Rule inference score indicates: and the rule reasoning re-decision is used for re-deciding the weight coefficient of the corresponding type.
In step S4, performing conflict resolution processing on the type of the re-decision passive trigger and the type of the re-decision active trigger to obtain an unmanned aerial vehicle air combat scheme re-decision type.
Specifically, if the type of the re-decision passive trigger is the same as the type of the re-decision active trigger, determining to execute a corresponding re-decision type; if the type of the re-decision passive trigger is different from that of the re-decision active trigger, executing the following steps based on a preset priority: the type of the re-decision passive trigger and the type of the re-decision active trigger have a higher priority.
The preset priority is as follows: tactical re-decision > task re-decision > behavioral re-decision.
In step S5, the unmanned aerial vehicle air combat scheme is subjected to a re-decision process based on the unmanned aerial vehicle air combat scheme re-decision type. The method comprises the following steps:
and selecting a re-decision method based on a preset method library, and performing re-decision processing of corresponding types on the unmanned aerial vehicle air combat schemes to obtain a plurality of re-decided unmanned aerial vehicle air combat schemes.
The tactical re-decision method comprises the following steps: petri net, fuzzy Petri, dynamic Bayesian network, case reasoning and rule reasoning method. The task re-decision method comprises the following steps: contract net, particle swarm algorithm, genetic algorithm and reinforcement learning. The behavior re-decision method comprises the following steps: genetic algorithm, deep learning method and reinforcement learning method.
And extracting a re-decision scheme selection method based on a preset method library, selecting a re-decided unmanned aerial vehicle air combat scheme, and executing the scheme.
Specifically, the method for selecting the re-decision scheme is a selection method, and the specific selection method may adopt the prior art, which is not limited in this embodiment.
The embodiment of the invention can accurately change the key opportunity of the current decision according to the complex and dynamically changed battlefield environment, and accurately trigger, so that the re-decision becomes a great measure for changing situation, changing from inferior to superior and effectively enhancing the situation advantage of our situation in the countermeasure process.
In summary, compared with the prior art, the method has the following beneficial effects:
the method and the device for controlling the unmanned aerial vehicle air combat system acquire unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme; carrying out correlation processing on unmanned aerial vehicle air combat data; judging the passive triggering of the re-decision based on the emergency event which occurs when the unmanned aerial vehicle is in air battle, and analyzing the type of the passive triggering of the re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the re-decision triggering comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; carrying out conflict resolution processing on the type of the active trigger of the re-decision and the type of the active trigger of the re-decision to obtain the type of the re-decision of the unmanned aerial vehicle air combat scheme; and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the re-decision type of the unmanned aerial vehicle air combat scheme. The embodiment of the invention triggers and judges the re-decision from an active layer and a passive layer and carries out conflict resolution on the two re-decision types, thereby executing the re-decision on the unmanned aerial vehicle air combat scheme, enhancing the adaptability of the unmanned aerial vehicle air combat scheme during execution, and enabling the re-decision to change situation, change from bad to excellent and effectively enhance the situation advantage of our situation in the countermeasure process.
It should be noted that, through the above description of the embodiments, it is clear to those skilled in the art that the embodiments may be implemented by software plus a necessary general-purpose hardware drone. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments. In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A multi-unmanned aerial vehicle cooperative confrontation online re-decision method, which is executed by a computer, is characterized by comprising the following steps:
acquiring unmanned aerial vehicle air combat data when a plurality of unmanned aerial vehicles cooperatively execute an unmanned aerial vehicle air combat scheme;
performing correlation processing on the unmanned aerial vehicle air combat data;
judging the passive triggering of the re-decision based on the emergency event which occurs during the air battle of the unmanned aerial vehicle, and analyzing the type of the passive triggering of the re-decision, wherein the type of the passive triggering of the re-decision comprises the following steps: tactical re-decision, task re-decision and behavior re-decision; judging active triggering of a re-decision based on the correlated unmanned aerial vehicle air combat data, and analyzing the type of the active triggering of the re-decision, wherein the type of the active triggering of the re-decision comprises the following steps: tactical re-decision, task re-decision and behavior re-decision;
performing conflict resolution processing on the type of the re-decision passive trigger and the type of the re-decision active trigger to obtain an unmanned aerial vehicle air combat scheme re-decision type;
and carrying out re-decision processing on the unmanned aerial vehicle air combat scheme based on the unmanned aerial vehicle air combat scheme re-decision type.
2. The re-decision method of claim 1, wherein the drone air combat data comprises: enemy flight control data, my flight control data and task action data;
the enemy flight control data includes: the method comprises the following steps of (1) carrying out enemy aircraft speed, enemy aircraft height, enemy aircraft longitude and latitude, enemy aircraft course angle, enemy aircraft roll angle and enemy aircraft pitch angle;
the my party flight control data comprises: the speed, the height, the longitude and latitude, the course angle, the roll angle, the pitch angle and the number of the remaining missiles of the unmanned aerial vehicle of the same party;
the task activity data includes: the number of unmanned aerial vehicles of my party, the number of unmanned aerial vehicles of enemy, the current tactics of my party and the current target distribution list of my party.
3. The re-decision method of claim 1, wherein the correlating the drone air combat data comprises:
preprocessing the unmanned aerial vehicle air combat data based on a data cleaning method;
and performing correlation analysis on the preprocessed unmanned aerial vehicle air combat data based on a correlation algorithm.
4. The re-decision method of claim 1, wherein the determining a passive trigger for re-decision based on an emergency event occurring during an air war of the drone and analyzing the type of passive trigger for re-decision comprises:
for the emergency K, judging the type of the emergency K, wherein the type of the emergency K comprises a first-level emergency, a second-level emergency and a third-level emergency;
if the emergency K is a primary emergency, immediately judging that the decision is triggered passively, wherein the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and continuously judging the passive trigger of the next decision-making;
if the emergency K is a secondary emergency, judging whether the time interval delta t from the moment of the last re-decision passive triggering to the moment of the emergency K is greater than or equal to a first period or not; if yes, immediately judging that the decision is triggered passively to make a decision, wherein the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and continuously judging the passive trigger of the next decision-making; if not, adding the emergency K into a secondary emergency list; when the first period is finished, the method determines that the re-decision is triggered passively, and the type of the re-decision passive trigger is as follows: the decision-making type with the highest priority in the decision-making types corresponding to all the emergency events in the secondary emergency event list; and continuing to judge the passive triggering of the next re-decision;
if the emergency K is a third-level emergency, judging whether the time interval delta t from the moment of the last re-decision passive triggering to the moment of the emergency K is greater than or equal to a first period or not; if yes, immediately judging that the decision is triggered passively to make a decision, wherein the type of the decision-making passive trigger is the decision-making type corresponding to the emergency K, and continuously judging the passive trigger of the next decision-making; if not, adding the emergency K into a third-level emergency list; when the second period is finished, the passive trigger re-decision is determined, and the type of the re-decision passive trigger is as follows: the decision-making type with the highest priority in the decision-making types corresponding to all the emergency events in the third-level emergency event list; and continuing to judge the passive triggering of the next re-decision;
the priority of the re-decision type is: tactical re-decision > task re-decision > behavioral re-decision.
5. The re-decision method of claim 4, wherein the primary emergency event comprises: the method comprises the following steps that a failure event of the unmanned aerial vehicle of the my party, a number change event of the unmanned aerial vehicles of the enemy party, a radar locking event of the unmanned aerial vehicle of the my party by the enemy party, a re-decision command event issued by a command center, a new task event issued by the command center and a task completion event are issued by the command center;
the secondary emergency event comprises: the method comprises the following steps that an event that the speed of the unmanned aerial vehicle of the owner is lower than a threshold value, an event that the height of the unmanned aerial vehicle of the owner is lower than the threshold value and an event that the residual energy of the unmanned aerial vehicle of the owner is lower than the threshold value are taken;
the tertiary emergency events include: the method comprises the following steps of an event that the communication of the unmanned aerial vehicle of the my party is interrupted, an event that the surplus of the unmanned aerial vehicle of the my party is lower than a threshold value, an event that the position of the unmanned aerial vehicle of the my party exceeds a communication range and a weather environment change event.
6. The re-decision method of claim 4, wherein the determining the active trigger of the re-decision based on the correlated drone air combat data and analyzing the type of the active trigger of the re-decision comprises:
starting timing from the moment of the last re-decision passive triggering, judging whether the timing time delta t is greater than or equal to a first period, and if not, waiting;
if yes, then:
calculating global similarity based on the correlated unmanned aerial vehicle air combat data and a preset case library; judging whether the global similarity exceeds a preset global similarity threshold, and if so, judging that case reasoning re-decision is actively triggered;
carrying out rule reasoning on the associated unmanned aerial vehicle air combat data, judging whether a preset rule reasoning condition is met or not, and if so, judging that rule reasoning is actively triggered to make a decision again;
and carrying out conflict resolution on the type of the case reasoning and re-decision active trigger and the type of the rule reasoning and re-decision active trigger to obtain the type of the re-decision active trigger, and judging the type of the re-decision active trigger as the active trigger of the re-decision.
7. The re-decision method of claim 6, wherein the performing conflict resolution on the type of the case-inference re-decision active trigger and the type of the rule-inference re-decision active trigger to obtain the type of the re-decision active trigger comprises:
when the case reasoning re-decision and the rule reasoning re-decision are triggered independently, the case reasoning re-decision and the rule reasoning re-decision are judged to trigger the re-decision of the corresponding type actively;
when the case reasoning re-decision and the rule reasoning re-decision are all triggered, comparing the sizes of the case reasoning score and the rule reasoning score, and judging that the type corresponding to the re-decision with the higher active triggering score is determined;
the case inference score refers to: the product of the global similarity and a weight coefficient of a type corresponding to the case-based reasoning decision-making; the rule inference score indicates: the rule reasoning re-decision is used for determining the weight coefficient of the corresponding type;
the weight coefficients are: tactical re-decision is a, mission re-decision is b, behavior re-decision is c, and a > b > c.
8. The re-decision method of claim 6, wherein the calculating global similarity based on the correlated unmanned aerial vehicle air combat data and a preset case base comprises:
extracting characteristic attributes of the associated unmanned aerial vehicle air combat data;
searching a preset case base, and confirming each case in the case base;
comparing the extracted characteristic attributes with each case, and calculating attribute similarity;
calculating a global similarity based on the attribute similarities.
9. The re-decision method according to claim 1, wherein performing conflict resolution processing on the type of the re-decision passive trigger and the type of the re-decision active trigger comprises:
if the type of the re-decision passive trigger is the same as that of the re-decision active trigger, judging to execute a corresponding re-decision type;
if the type of the re-decision passive trigger is different from that of the re-decision active trigger, executing the following steps based on a preset priority: a high-priority re-decision type in the re-decision passive triggering type and the re-decision active triggering type; the preset priority is as follows: tactical re-decision > task re-decision > behavioral re-decision.
10. The re-decision method of claim 6, wherein the re-decision processing of the drone air battle scheme based on the drone air battle scheme re-decision type comprises:
selecting a re-decision method based on a preset method library, and performing re-decision processing of corresponding types on the unmanned aerial vehicle air combat schemes to obtain a plurality of re-decided unmanned aerial vehicle air combat schemes;
and extracting a re-decision scheme selection method based on a preset method library, selecting a re-decided unmanned aerial vehicle air combat scheme, and executing the scheme.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112990452A (en) * | 2021-05-06 | 2021-06-18 | 中国科学院自动化研究所 | Man-machine confrontation knowledge driving type decision-making method and device and electronic equipment |
| CN115268496A (en) * | 2022-08-03 | 2022-11-01 | 中国航空工业集团公司沈阳飞机设计研究所 | Unmanned aerial vehicle aerial countermeasure aircraft controller and design method thereof |
| CN115268481A (en) * | 2022-07-06 | 2022-11-01 | 中国航空工业集团公司沈阳飞机设计研究所 | Unmanned aerial vehicle countermeasure strategy decision method and system |
| CN117371655A (en) * | 2023-10-12 | 2024-01-09 | 中山大学 | Unmanned plane collaborative decision evaluation method, system, equipment and medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2000030423A2 (en) * | 1998-09-17 | 2000-06-02 | 21St Century Systems, Inc. | Method and system for intelligent agent decision making for tactical aerial warfare |
| CN104298242A (en) * | 2014-04-10 | 2015-01-21 | 中国人民解放军海军航空工程学院 | Multiple unmanned aerial vehicle cooperation method and system based on workflow |
| CN105122249A (en) * | 2012-12-31 | 2015-12-02 | 加里·斯蒂芬·舒斯特 | Decision making using algorithmic or programmatic analysis |
| CN107390706A (en) * | 2017-07-26 | 2017-11-24 | 北京航空航天大学 | A kind of unmanned plane short range combat decision-making technique based on the motor-driven algorithm of preview |
| CN108319286A (en) * | 2018-03-12 | 2018-07-24 | 西北工业大学 | A kind of unmanned plane Air Combat Maneuvering Decision Method based on intensified learning |
| CN108427286A (en) * | 2018-04-12 | 2018-08-21 | 合肥工业大学 | For the training method of unmanned plane depth decision under strong Antagonistic Environment and training network |
| CN108680063A (en) * | 2018-05-23 | 2018-10-19 | 南京航空航天大学 | A kind of decision-making technique for the dynamic confrontation of extensive unmanned plane cluster |
| CN109933053A (en) * | 2017-12-15 | 2019-06-25 | 海鹰航空通用装备有限责任公司 | A kind of unmanned aerial vehicle (UAV) control method and unmanned plane based on maneuver chain |
| CN110694256A (en) * | 2019-09-18 | 2020-01-17 | 徐磊 | Novel emergency computer war game deduction system and method |
-
2020
- 2020-10-15 CN CN202011101859.3A patent/CN112486200B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2000030423A2 (en) * | 1998-09-17 | 2000-06-02 | 21St Century Systems, Inc. | Method and system for intelligent agent decision making for tactical aerial warfare |
| CN105122249A (en) * | 2012-12-31 | 2015-12-02 | 加里·斯蒂芬·舒斯特 | Decision making using algorithmic or programmatic analysis |
| CN104298242A (en) * | 2014-04-10 | 2015-01-21 | 中国人民解放军海军航空工程学院 | Multiple unmanned aerial vehicle cooperation method and system based on workflow |
| CN107390706A (en) * | 2017-07-26 | 2017-11-24 | 北京航空航天大学 | A kind of unmanned plane short range combat decision-making technique based on the motor-driven algorithm of preview |
| CN109933053A (en) * | 2017-12-15 | 2019-06-25 | 海鹰航空通用装备有限责任公司 | A kind of unmanned aerial vehicle (UAV) control method and unmanned plane based on maneuver chain |
| CN108319286A (en) * | 2018-03-12 | 2018-07-24 | 西北工业大学 | A kind of unmanned plane Air Combat Maneuvering Decision Method based on intensified learning |
| CN108427286A (en) * | 2018-04-12 | 2018-08-21 | 合肥工业大学 | For the training method of unmanned plane depth decision under strong Antagonistic Environment and training network |
| CN108680063A (en) * | 2018-05-23 | 2018-10-19 | 南京航空航天大学 | A kind of decision-making technique for the dynamic confrontation of extensive unmanned plane cluster |
| CN110694256A (en) * | 2019-09-18 | 2020-01-17 | 徐磊 | Novel emergency computer war game deduction system and method |
Non-Patent Citations (2)
| Title |
|---|
| XIAOXUAN HU ET AL.: "Hierarchical method of task assignment for multiple cooperating UAV teams", 《JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS》, vol. 26, no. 5, 30 November 2015 (2015-11-30), pages 1000 - 1009 * |
| 顾东杰等: "智能舰艇编队指挥控制系统体系结构设计", 《指挥控制与仿真》, vol. 31, no. 2, 30 April 2009 (2009-04-30), pages 92 - 95 * |
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| CN112990452A (en) * | 2021-05-06 | 2021-06-18 | 中国科学院自动化研究所 | Man-machine confrontation knowledge driving type decision-making method and device and electronic equipment |
| CN112990452B (en) * | 2021-05-06 | 2021-08-31 | 中国科学院自动化研究所 | Man-machine confrontation knowledge driving type decision-making method and device and electronic equipment |
| CN115268481A (en) * | 2022-07-06 | 2022-11-01 | 中国航空工业集团公司沈阳飞机设计研究所 | Unmanned aerial vehicle countermeasure strategy decision method and system |
| CN115268496A (en) * | 2022-08-03 | 2022-11-01 | 中国航空工业集团公司沈阳飞机设计研究所 | Unmanned aerial vehicle aerial countermeasure aircraft controller and design method thereof |
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