CN113126651A - Intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles - Google Patents
Intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles Download PDFInfo
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Abstract
The invention provides an intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles, and relates to the field of unmanned aerial vehicle air combat. The intelligent decision device comprises an information acquisition module, an friend-machine information interaction module, a re-decision triggering module and a re-decision execution module, wherein the information acquisition module acquires the unmanned aerial vehicle state data of the current unmanned aerial vehicle; the friend-computer information interaction module acquires unmanned plane state data of a friend-party unmanned plane; the re-decision triggering module judges the triggering of the re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and sends the re-decision triggering type to the re-decision execution module; the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type, generate a control instruction based on the re-decision scheme and send the control instruction to the friend-computer information interaction module, so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle. The method can enhance the adaptability of the unmanned aerial vehicle air combat strategy during execution.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle air combat, in particular to an intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles.
Background
With the development and application of emerging technologies, information countermeasure and intelligent countermeasure have gradually become new operational means and operational forms, and unmanned aerial vehicles are widely applied because they can autonomously complete various tasks. However, with the continuous promotion of the application of the unmanned aerial vehicles in the related fields, a single unmanned aerial vehicle exposes a short board with flexibility and task completion rate when executing tasks, and therefore, the application of multiple unmanned aerial vehicles to form a cooperative combat system with mutual cooperation, complementary advantages and multiplied efficiency in the air becomes a hotspot and a pursuit target concerned in the field.
Many unmanned aerial vehicle are in coordination confrontation is a complicated confrontation process, and wherein, every unmanned aerial vehicle is responsible for different roles, and can execute one or more subtasks, through the mutual cooperation and the decision-making between many unmanned aerial vehicles, carries out the task according to predetermined unmanned aerial vehicle air combat strategy, accomplishes the task that single unmanned aerial vehicle can't accomplish, and then promotes unmanned aerial vehicle efficiency of fighting.
However, the inventor of the present application finds that in the multi-unmanned-aerial-vehicle cooperative countermeasure environment, the countermeasure situation is instantly changeable, and the characteristics of high dynamics, high real-time performance and high uncertainty are presented, and the overall process time of multi-unmanned-vehicle cooperative countermeasure is long, and detailed prediction cannot be made on the action of an enemy, so that tactical decision, target allocation and other decisions before battle are likely to be carried out along with the progress in the countermeasure process and are no longer suitable for the current environment, and for this reason, a decision maker needs to carry out re-decision on the multi-unmanned-aerial-vehicle battle strategy according to a complex and dynamically-changing battlefield environment. The adaptability of the existing unmanned aerial vehicle air combat strategy is poor.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles, and solves the problem that the existing unmanned aerial vehicle air combat strategy is poor in adaptability.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention provides an intelligent decision-making device for multi-unmanned aerial vehicle cooperative confrontation, which solves the technical problem and comprises: the system comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module;
the information acquisition module is configured to acquire unmanned aerial vehicle state data of the current unmanned aerial vehicle and send the unmanned aerial vehicle state data to the friend-computer information interaction module;
the friend-machine information interaction module is configured to acquire unmanned aerial vehicle state data of a friend unmanned aerial vehicle and send the unmanned aerial vehicle state data of the current unmanned aerial vehicle and the unmanned aerial vehicle state data of the friend unmanned aerial vehicle to the re-decision triggering module;
the re-decision triggering module is configured to judge the triggering of a re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and send the re-decision triggering type to the re-decision execution module;
the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type; and generating a control instruction based on the re-decision scheme and sending the control instruction to the friend-computer information interaction module so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle.
Preferably, the information acquisition module is further configured to acquire unmanned aerial vehicle state data in a sensor inside the unmanned aerial vehicle and send the unmanned aerial vehicle state data to the friend-computer information interaction module.
Preferably, unmanned aerial vehicle state data of current unmanned aerial vehicle and unmanned aerial vehicle state data of friend's unmanned aerial vehicle all include: unmanned aerial vehicle abscissa, unmanned aerial vehicle ordinate, unmanned aerial vehicle flying height, unmanned aerial vehicle flying speed, unmanned aerial vehicle roll angle, unmanned aerial vehicle course angle, unmanned aerial vehicle pitch angle, unmanned aerial vehicle surplus bullet quantity and unmanned aerial vehicle type.
Preferably, the triggering of the re-decision comprises: a re-decision active trigger and a re-decision passive trigger;
the re-decision trigger types include: tactical decision making and target assignment.
Preferably, the re-decision triggering module is further configured to:
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;
obtaining the type of the re-decision active trigger;
performing conflict resolution on the type of the re-decision passive trigger and the type of the re-decision active trigger based on a preset re-decision type priority to obtain a re-decision trigger type; the preset re-decision type priority is as follows: tactical decision > target assignment.
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 again, wherein the decision-making triggering type is a decision-making type corresponding to the emergency K, and continuously judging the passive triggering 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 re-decision triggering type 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 again, wherein the decision-making triggering type is a decision-making type corresponding to the emergency K, and continuously judging the passive triggering of the next decision-making; if not, adding the emergency K into a third-level emergency list; when the second period is finished, the method determines that the re-decision is triggered passively, and the re-decision triggering type 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.
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 type of active trigger for obtaining the re-decision includes:
inputting all unmanned aerial vehicle state data into a pre-constructed fully-connected neural network to obtain a re-decision active triggering result; the re-decision active triggering result comprises: no active re-decision, tactical decision and target assignment are performed.
The invention provides an intelligent decision-making system for multi-unmanned aerial vehicle cooperative confrontation, which solves the technical problem, and comprises a plurality of unmanned aerial vehicles, wherein each unmanned aerial vehicle comprises an intelligent decision-making device for multi-unmanned aerial vehicle cooperative confrontation; the unmanned planes comprise a long plane and a plurality of wing planes;
each wing plane sends respective unmanned aerial vehicle state data to the long plane based on an intelligent decision device for cooperative confrontation of multiple unmanned aerial vehicles;
the intelligent decision device of the long plane based on the cooperative confrontation of the multiple unmanned planes generates a re-decision scheme and a control instruction, and sends the control instruction to each wing plane.
(III) advantageous effects
The invention provides an intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles. Compared with the prior art, the method has the following beneficial effects:
the intelligent decision device provided by the invention comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module. The information acquisition module acquires unmanned aerial vehicle state data of the current unmanned aerial vehicle; the friend-computer information interaction module acquires unmanned plane state data of a friend-party unmanned plane; the re-decision triggering module judges the triggering of the re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and sends the re-decision triggering type to the re-decision execution module; the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type, generate a control instruction based on the re-decision scheme and send the control instruction to the friend-computer information interaction module, so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle. Due to the dynamics and uncertainty existing in the cooperative countermeasure process of multiple unmanned aerial vehicles and the complexity of cooperative control, the existing unmanned aerial vehicle air combat strategy cannot adapt to a complex countermeasure environment. According to the unmanned aerial vehicle air combat strategy adjustment method and device, the unmanned aerial vehicle state data are obtained and corresponding re-decision is carried out, so that the unmanned aerial vehicle air combat strategy is rapidly adjusted according to the situation change in the countermeasure, and the adaptability of the unmanned aerial vehicle air combat strategy in execution can be enhanced.
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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 a general schematic diagram of an intelligent decision device for cooperative confrontation of multiple drones according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a fully-connected neural network in an intelligent decision device for cooperative confrontation of multiple drones 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 existing unmanned aerial vehicle air combat strategy by providing the intelligent decision-making device and system for cooperative confrontation of multiple unmanned aerial vehicles, and improves the adaptability of the multiple unmanned aerial vehicles during task execution.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the intelligent decision device provided by the embodiment of the invention comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module. The information acquisition module acquires unmanned aerial vehicle state data of the current unmanned aerial vehicle; the friend-computer information interaction module acquires unmanned plane state data of a friend-party unmanned plane; the re-decision triggering module judges the triggering of the re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and sends the re-decision triggering type to the re-decision execution module; the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type, generate a control instruction based on the re-decision scheme and send the control instruction to the friend-computer information interaction module, so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle. Due to the dynamics and uncertainty existing in the cooperative countermeasure process of multiple unmanned aerial vehicles and the complexity of cooperative control, the existing unmanned aerial vehicle air combat strategy cannot adapt to a complex countermeasure environment. According to the unmanned aerial vehicle air combat strategy adjustment method and device, the unmanned aerial vehicle state data are obtained and corresponding re-decision is carried out, so that the unmanned aerial vehicle air combat strategy is rapidly adjusted according to the situation change in the countermeasure, and the adaptability of the unmanned aerial vehicle air combat strategy in execution can be enhanced.
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 an intelligent decision-making device for cooperative confrontation of multiple unmanned aerial vehicles, which comprises the following components in part by weight as shown in figure 1: the system comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module.
The information acquisition module is configured to acquire unmanned aerial vehicle state data of the current unmanned aerial vehicle and send the unmanned aerial vehicle state data to the friend-computer information interaction module.
The friend-machine information interaction module is configured to acquire unmanned aerial vehicle state data of the friend unmanned aerial vehicle and send the unmanned aerial vehicle state data of the current unmanned aerial vehicle and the unmanned aerial vehicle state data of the friend unmanned aerial vehicle to the re-decision triggering module.
The re-decision triggering module is configured to determine a re-decision trigger and a re-decision trigger type based on all the drone status data, and send the re-decision trigger type to the re-decision execution module.
The re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type; and generating a control instruction based on the re-decision scheme and sending the control instruction to the friend-computer information interaction module so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle.
The intelligent decision device provided by the embodiment of the invention comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module. The information acquisition module acquires unmanned aerial vehicle state data of the current unmanned aerial vehicle; the friend-computer information interaction module acquires unmanned plane state data of a friend-party unmanned plane; the re-decision triggering module judges the triggering of the re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and sends the re-decision triggering type to the re-decision execution module; the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type, generate a control instruction based on the re-decision scheme and send the control instruction to the friend-computer information interaction module, so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle. According to the unmanned aerial vehicle air combat system and the method, the unmanned aerial vehicle state data are obtained and corresponding re-decision is carried out, so that the unmanned aerial vehicle air combat scheme is suitable for the current situation, and the adaptability of the unmanned aerial vehicle air combat scheme during execution can be enhanced.
In some embodiments, the information acquisition module is specifically connected with the sensor inside the unmanned aerial vehicle, can acquire data in the sensor inside the unmanned aerial vehicle, such as unmanned aerial vehicle state data, and sends unmanned aerial vehicle state data to the friend-computer information interaction module.
In some embodiments, the drone status data for the current drone and the drone status data for the friend drone each include: unmanned aerial vehicle abscissa, unmanned aerial vehicle ordinate, unmanned aerial vehicle flying height, unmanned aerial vehicle flying speed, unmanned aerial vehicle roll angle, unmanned aerial vehicle course angle, unmanned aerial vehicle pitch angle, unmanned aerial vehicle surplus bullet quantity and unmanned aerial vehicle type.
In some embodiments, the triggering of the re-decision comprises: a re-decision active trigger and a re-decision passive trigger.
Wherein the re-decision trigger types include: tactical decision making and target assignment.
Tactical decision-making refers to the process of organizing, commanding, controlling and cooperatively flying in air battles by a plurality of unmanned aerial vehicles. Including direct attack, flank detour, horizontal combing, vertical combing, etc.
Target Assignment (WTA) issues refer to assigning a limited number of interceptors to an incoming missile to minimize the probability of the missile destroying a protected asset or assigning a priority missile to an incoming target to maximize the probability of catalyzing the target.
It should be noted that the re-decision triggering module performs re-decision active triggering judgment and re-decision passive triggering judgment respectively.
Wherein, the result of the decision making initiative triggering judgment comprises: and carrying out active re-decision and not carrying out active re-decision. Two types are included when active re-decision is made: tactical decision making and target assignment.
In some embodiments, the re-decision triggering module is further configured to:
s31, 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.
And S32, acquiring the type of the active trigger of the re-decision.
S33, carrying out conflict resolution on the type of the re-decision passive trigger and the type of the re-decision active trigger based on the preset re-decision type priority to obtain a re-decision trigger type; the preset priority of the re-decision type is as follows: tactical decision > target assignment.
In some embodiments, step S31 specifically includes:
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 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 again, wherein the decision-making triggering type is a decision-making type corresponding to the emergency K, and continuously judging the passive triggering 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 re-decision triggering type 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 again, wherein the decision-making triggering type is a decision-making type corresponding to the emergency K, and continuously judging the passive triggering of the next decision-making; if not, adding the emergency K into a third-level emergency list; when the second period is finished, the method determines that the re-decision is triggered passively, and the re-decision triggering type 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.
In the embodiment of the present invention, the first period T may be setminFor 5s, and a second period T of 8 s.
In some embodiments, wherein the my drone failure event refers to: in the countermeasure process, when the unmanned aerial vehicle of our party has the condition such as damage, mechanical failure, trigger tactics decision-making.
The event that my unmanned aerial vehicle is locked by enemy radar means that: during the countermeasure, when my drone is locked by an enemy radar, target assignment 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 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 decision is triggered.
The command center issues a new task event finger: when a new task is issued, the current task plan arrangement is changed, the new task needs to be reasonably distributed, and target distribution 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, the task arrangement needs to be performed again to trigger target allocation.
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, tactical decision is triggered.
Event that the height of unmanned aerial vehicle of my party is lower than the threshold means: in the process of confrontation, when the flying height of the unmanned aerial vehicle of the party is too low, tactical 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 unmanned aerial vehicle at the party has insufficient residual energy, and the situations such as signals, unstable position judgment and the like are caused, so that tactical decision is triggered.
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 countermeasure process, when the enemy unmanned aerial vehicle passes through modes such as radar interference to my unmanned aerial vehicle, cause communication terminal, trigger the target distribution this moment.
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 unmanned aerial vehicle of our party has the situation of insufficient residual elasticity and the like, target distribution 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 unmanned aerial vehicle at one part exceeds the communication range between the unmanned aerial vehicles at the other part, so that poor or interrupted communication is caused, and target distribution is triggered.
Weather environment change events refer to: when the confrontation process is met, the change of the meteorological environment influences the information interaction and other conditions of the unmanned aerial vehicle of the party, and tactical decision is triggered.
In some embodiments, step S31 specifically includes:
and inputting all unmanned aerial vehicle state data into a pre-constructed fully-connected neural network to obtain a re-decision active triggering result.
As shown in fig. 2, which is a schematic diagram of a fully-connected neural network, the fully-connected neural network may be a neural network trained in advance through an Actor-Critic algorithm in reinforcement learning. The specific parameters of the fully-connected neural network are shown in table 1.
TABLE 1 fully-connected neural network specific parameters
The re-decision active triggering result comprises: no active re-decision, tactical decision and target assignment are performed.
The embodiment of the invention also provides an intelligent decision-making system for cooperative confrontation of multiple unmanned aerial vehicles, which comprises a plurality of unmanned aerial vehicles, wherein each unmanned aerial vehicle comprises the intelligent decision-making device for cooperative confrontation of multiple unmanned aerial vehicles, and the unmanned aerial vehicles comprise a long plane and a plurality of wing planes.
It should be noted that the slot plane may be any one of unmanned planes set by the unmanned planes in the task execution, and when the slot plane is damaged, another wing plane may be selected as a new slot plane and the task is continuously executed.
And each wing plane sends respective unmanned aerial vehicle state data to the long plane based on the intelligent decision device for the cooperative confrontation of the multiple unmanned aerial vehicles.
The intelligent decision device of the co-countermeasure of the long plane based on the multiple unmanned planes generates a re-decision scheme and a control instruction, and sends the control instruction to each wing plane to execute the re-decision scheme.
In summary, compared with the prior art, the method has the following beneficial effects:
the intelligent decision device provided by the invention comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module. The information acquisition module acquires unmanned aerial vehicle state data of the current unmanned aerial vehicle; the friend-computer information interaction module acquires unmanned plane state data of a friend-party unmanned plane; the re-decision triggering module judges the triggering of the re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and sends the re-decision triggering type to the re-decision execution module; the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type, generate a control instruction based on the re-decision scheme and send the control instruction to the friend-computer information interaction module, so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle. Due to the dynamics and uncertainty existing in the cooperative countermeasure process of multiple unmanned aerial vehicles and the complexity of cooperative control, the existing unmanned aerial vehicle air combat strategy cannot adapt to a complex countermeasure environment. According to the unmanned aerial vehicle air combat strategy adjustment method and device, the unmanned aerial vehicle state data are obtained and corresponding re-decision is carried out, so that the unmanned aerial vehicle air combat strategy is rapidly adjusted according to the situation change in the countermeasure, and the adaptability of the unmanned aerial vehicle air combat strategy in execution can be enhanced.
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 (9)
1. An intelligent decision-making device for cooperative confrontation of multiple unmanned aerial vehicles, the device comprising: the system comprises an information acquisition module, an friend-computer information interaction module, a re-decision triggering module and a re-decision execution module;
the information acquisition module is configured to acquire unmanned aerial vehicle state data of the current unmanned aerial vehicle and send the unmanned aerial vehicle state data to the friend-computer information interaction module;
the friend-machine information interaction module is configured to acquire unmanned aerial vehicle state data of a friend unmanned aerial vehicle and send the unmanned aerial vehicle state data of the current unmanned aerial vehicle and the unmanned aerial vehicle state data of the friend unmanned aerial vehicle to the re-decision triggering module;
the re-decision triggering module is configured to judge the triggering of a re-decision and the re-decision triggering type based on all the unmanned aerial vehicle state data, and send the re-decision triggering type to the re-decision execution module;
the re-decision execution module is configured to obtain a re-decision scheme corresponding to the re-decision type; and generating a control instruction based on the re-decision scheme and sending the control instruction to the friend-computer information interaction module so that the friend-computer information interaction module sends the control instruction to the friend unmanned aerial vehicle.
2. The decision-making device of claim 1, wherein the information collection module is further configured to obtain drone status data in sensors inside the drone and send to the friend-machine information interaction module.
3. The decision-making device of claim 1, wherein the drone status data for the current drone and the drone status data for the friend drone each include: unmanned aerial vehicle abscissa, unmanned aerial vehicle ordinate, unmanned aerial vehicle flying height, unmanned aerial vehicle flying speed, unmanned aerial vehicle roll angle, unmanned aerial vehicle course angle, unmanned aerial vehicle pitch angle, unmanned aerial vehicle surplus bullet quantity and unmanned aerial vehicle type.
4. The decision-making apparatus of claim 1, wherein the triggering of the re-decision comprises: a re-decision active trigger and a re-decision passive trigger;
the re-decision trigger types include: tactical decision making and target assignment.
5. The decision device of claim 4, wherein the re-decision triggering module is further configured to:
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;
obtaining the type of the re-decision active trigger;
performing conflict resolution on the type of the re-decision passive trigger and the type of the re-decision active trigger based on a preset re-decision type priority to obtain a re-decision trigger type; the preset re-decision type priority is as follows: tactical decision > target assignment.
6. The decision-making device according to claim 5, wherein the determining a passive trigger for a re-decision based on an emergency event occurring during an air war of the drone and analyzing the type of the passive trigger for the 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 again, wherein the decision-making triggering type is a decision-making type corresponding to the emergency K, and continuously judging the passive triggering 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 re-decision triggering type 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 again, wherein the decision-making triggering type is a decision-making type corresponding to the emergency K, and continuously judging the passive triggering of the next decision-making; if not, adding the emergency K into a third-level emergency list; when the second period is finished, the method determines that the re-decision is triggered passively, and the re-decision triggering type 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.
7. The decision-making device according to claim 6, 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.
8. The decision-making apparatus according to claim 5, wherein the obtaining of the type of the re-decision active trigger comprises:
inputting all unmanned aerial vehicle state data into a pre-constructed fully-connected neural network to obtain a re-decision active triggering result; the re-decision active triggering result comprises: no active re-decision, tactical decision and target assignment are performed.
9. An intelligent decision making system for cooperative multi-drone confrontation, the system comprising a plurality of drones, each drone comprising an intelligent decision making device for cooperative multi-drone confrontation according to any one of claims 1 to 9; the unmanned planes comprise a long plane and a plurality of wing planes;
each wing plane sends respective unmanned aerial vehicle state data to the long plane based on an intelligent decision device for cooperative confrontation of multiple unmanned aerial vehicles;
the intelligent decision device of the long plane based on the cooperative confrontation of the multiple unmanned planes generates a re-decision scheme and a control instruction, and sends the control instruction to each wing plane.
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