CN117436223A - Construction method of intelligent cluster system combat effectiveness evaluation index system - Google Patents

Abstract

The invention discloses a construction method of an intelligent cluster system combat effectiveness evaluation index system, which comprises the following steps: analyzing an intelligent cluster, providing an evaluation requirement, defining an evaluation purpose, and constructing a combat effectiveness index system according to the evaluation requirement and the evaluation purpose; step two, constructing a simulation test platform on the basis, collecting simulation test data, researching a combat effectiveness evaluation method, processing and analyzing the simulation test data to complete intelligent cluster combat effectiveness evaluation, and analyzing an evaluation result; according to the construction method of the intelligent cluster system combat effectiveness evaluation index system, combat effectiveness influencing factors are extracted according to the combat process and the sequence of events in the combat process, the combat effectiveness influencing factors are extracted according to the combat characteristics of the intelligent cluster system, the principle that the factors are decomposed from top to bottom step by step from top to subsystem is followed, indexes are refined and quantized to the extent that engineering can be achieved, and finally comprehensive standards for assessing combat effectiveness are established.

Description

Construction method of intelligent cluster system combat effectiveness evaluation index system

Technical Field

The invention relates to a construction method of an intelligent cluster system combat effectiveness evaluation index system, and belongs to the technical field of intelligent cluster system combat effectiveness evaluation.

Background

Intelligent questions generally refer to a single entity that is capable of self-sensing changes in the surrounding environment and making strain adjustments accordingly in some unique environment. The intelligent cluster system is a multi-agent system composed of a large number of single agent entities, the sense of concept of the intelligent cluster system is derived from the behaviors of the community in the biology world, such as the bee colony, the wolf colony and the fish colony in the real world, and a plurality of modern high and new technologies are fused on the basis of the sense of concept of the intelligent cluster system, so that the intelligent cluster system is a typical representative of the intelligence. The system can make up the short boards of the functions of the single intelligent agent, converts the quantity advantage into the action advantage, and individuals in the system can cooperate with each other to jointly complete the set aim without being limited by the damage or disablement of the single intelligent agent. Therefore, in the process of mutual cooperation of multiple agents, tasks exceeding the capability limit of a single agent can be completed through mutual cooperation, the effect of 1+1 & gt2 is exerted, and few intelligent cluster systems in the prior art are applied to the fight of weaponry. The invention applies the intelligent cluster system to the weapon equipment operation, the researched content has universality, the object of the intelligent cluster system is not limited, the common problems of the intelligent cluster system in the weapon equipment operation are only researched, the common problems comprise system characteristics, the fight process, the fight efficiency index system, the index test quantization method and the like, references are provided for different types of intelligent cluster systems, for example, the intelligent cluster system formed by various kinds of ammunition, intelligent monomers such as unmanned aerial vehicles and the like can also be provided, and a new idea is provided for the application of the intelligent cluster system in the weapon equipment operation.

Disclosure of Invention

In order to solve the problems, the invention provides a construction method of an intelligent cluster system combat effectiveness evaluation index system, which establishes a comprehensive standard for assessing combat effectiveness.

The invention discloses a construction method of an intelligent cluster system combat effectiveness evaluation index system, which comprises the following steps:

analyzing an intelligent cluster, providing an evaluation requirement, defining an evaluation purpose, and constructing a combat effectiveness index system according to the evaluation requirement and the evaluation purpose;

step two, constructing a simulation test platform on the basis, collecting simulation test data, researching a combat effectiveness evaluation method, processing and analyzing the simulation test data to complete intelligent cluster combat effectiveness evaluation, and analyzing an evaluation result.

Further, the specific operation method of the first step is as follows:

the first step, analysis of the intelligent cluster combat process and combat effectiveness influence factors,

A. the intelligent cluster fight process comprises four stages of pre-shooting task planning, cooperative formation flying, cooperative perception decision making and dynamic cooperative attack;

(1) In the pre-shooting task planning stage, a collaborative task planning technology is applied to complete initial task allocation and corresponding path planning; specifically, the intelligent cluster analyzes and judges the distance between each monomer and the target according to the current battlefield situation, oil consumption required by reaching the target, threat degree of the target and target value are analyzed, and the like, and the battlefield information is synthesized to make a task planning algorithm on the basis of the principle that the task planning benefit value reaches the optimum, and task allocation is carried out on the monomers in the cluster system according to the made algorithm, so that a pre-shooting task planning scheme is finally obtained;

(2) In the cooperative formation flight stage, the cluster system realizes patrol flight by forming flight and approaching to a target area; specifically, when the monomers in the cluster fly in formation, a plurality of formations are generally formed according to the number of the monomers, one of the monomers is selected in each formation to bear the function of the long machine, the other monomers are equivalent to the roles of the plane, and the plane cooperatively forms the flight under the driving of the long machine;

(3) In the collaborative awareness decision stage, the cluster system carries out intelligent collaborative situation awareness on the target area, determines a hit target, carries out intelligent online planning and decision technology, and distributes attack, seal control and continuous reconnaissance monomers; specifically, firstly, after a cluster system flies against a battle area through intelligent collaborative situation awareness, the cluster system carries out intelligent autonomous detection and identification on a ground suspicious target in a target space based on an area situation awareness technology of a battlefield information distributed awareness and tracking method; then, according to situation awareness information, the intelligent cluster needs to establish a task planning scheme according to the principle that the current situation still reaches the optimal value of the task planning benefit, and meanwhile, when the cluster system encounters emergency situations, such as the situation that a monomer in the cluster is damaged, the situation that the number of enemy targets is increased, and the like, task decision deployment is timely adjusted, and the task planning scheme is updated;

(4) In the dynamic collaborative attack stage, the clusters update the single flight path according to the changed task state, and autonomous dynamic collaborative attack is carried out to form a combat closed loop; specifically, after a task planning scheme is formulated, the cluster system deploys cooperative attack according to the distributed hit targets and the planning paths;

B. analysis of the factors affecting the effectiveness of the combat,

(1) Analyzing the pre-shooting task planning, wherein the evaluation of the quality of the pre-shooting task planning actually requires the evaluation of the quality of a pre-shooting task planning algorithm, and the key parameter reflecting the quality of the task allocation algorithm is a task planning benefit value; the larger the task planning benefit value is, the better the pre-shooting task allocation scheme is; however, only the task benefit value result can only indicate the quality of the task planning result of different times under the same task planning algorithm, and the quality of the pre-shooting task planning algorithm cannot be indicated, so that a reliable reference standard is needed to verify the quality of the pre-shooting task planning; therefore, 100 offline task planning tests are carried out, and based on the offline task planning tests, the ratio of the pre-shooting task planning benefit value to the offline task planning benefit value is calculated, and the larger the ratio of the pre-shooting task planning benefit value to the offline task planning benefit value is, the better the pre-shooting task planning effect is; in addition, the time for completing task planning shows the timeliness of task planning, and the shorter the task planning time is, the higher the timeliness for completing task planning is, which is an important parameter for reflecting the task planning effect;

(2) The analysis of the cooperative formation flying is that the cooperative formation flying capability runs through the whole process of the combat operation, is a necessary condition for the cluster system to complete the combat task, and is an important factor influencing the cluster combat effect; in the flight process, the most ideal flight environment is that battlefield information is not changed, and long aircraft does not need to give any maneuvering command in the flight process, so that the current technical level is that the cluster formation flight capability can completely meet the combat requirement; however, in actual flight, battlefield information is always changed, the long aircraft needs to adjust the flight altitude and the flight route in time according to the current battlefield situation, a maneuvering command for pulling up or lowering is issued to the bureau aircraft, the degree of the bureau aircraft responding to the maneuvering command is an important capability index of the cluster cooperative formation flying capability, and the time of the bureau aircraft responding to the maneuvering command reflects the degree of the bureau aircraft responding to the maneuvering command in response to the maneuvering command; on the other hand, when the intensive fire interception condition of the enemy is met in the formation flight process, whether the cluster is burst-proof is successful or not can directly influence the subsequent combat action, and index parameters influencing the burst-proof capability mainly comprise average maximum and minimum flight speeds, air time and the like which can be achieved by the cluster;

(3) The method comprises the steps of analyzing collaborative perception decisions, wherein main influencing factors of intelligent collaborative situation perception capability are target detection probability, target recognition probability and target positioning error, wherein the target detection rate is the capability of a cluster situation perception to obtain a ground target, the target recognition rate is the capability of a cluster not recognizing an enemy target from among the perceived targets, and the positioning error refers to a capability index of a cluster system for accurately positioning the enemy target after the identification; the important index of the intelligent decision capability is still a task planning benefit value, and particularly, the task planning benefit value after a plurality of monomers in the cluster system are damaged or the number of enemy targets is detected to be increased is mainly inspected, so that the aim of inspecting whether the cluster system can timely formulate an optimal strategy of task planning according to the current situation is achieved;

(4) The analysis of dynamic collaborative attack has the advantages that although any monomer in the cluster cannot finish the damage to the target, the target can be damaged when all monomers in the formation exert force together, so that the key of whether the cluster can kill the target efficiently is whether the monomers in the cluster exert force together, namely, whether the collaborative action and the collaborative attack can be unfolded, and therefore, the collaborative action capacity and the collaborative attack capacity are important factors influencing the final attack effect; the quality of the cooperative mobility is thinned to be the consistency of time when the clusters reach the target effective attack range according to the actual combat process, and the consistency of the detonation time of the same formation attack target is achieved after the clusters reach the effective attack range; on the premise of the same monomer performance, the smaller the time difference in reaching the effective attack range is, the smaller the detonation time difference is, and the better the synergistic attack effect is; the most direct method for representing the cooperative striking effect is to count the hit condition of the enemy target, and the higher the hit ratio of the target is, the better the cooperative striking effect is, so that the hit probability is an important index for checking the cooperative striking effect;

Second, constructing an intelligent cluster combat effectiveness evaluation index system,

and finally forming an intelligent cluster collaborative combat effectiveness evaluation index system through the decomposition of pre-shooting collaborative task planning capability, collaborative formation flying capability, intelligent collaborative situation perception decision-making capability and autonomous dynamic collaborative attack capability.

Still further, the pre-shooting cooperative task planning capability is decomposed into a ratio of a pre-shooting cooperative task planning benefit value to an off-line cooperative task planning benefit value and pre-shooting cooperative task planning time, and the ratio of the pre-shooting cooperative task planning benefit value to the off-line cooperative task planning benefit value and the pre-shooting cooperative task planning time are respectively represented, wherein the off-line cooperative task planning means that the hitting task is completely and randomly distributed by a cluster under the condition that factors such as distance, oil consumption, target threat degree, target value and the like are considered; the pre-shooting collaborative task planning refers to the allocation of hitting tasks to the clusters according to a certain task planning algorithm; the ratio of the pre-shooting cooperative task planning benefit value to the off-line cooperative task planning benefit value reflects the advantages and disadvantages of the pre-shooting cooperative task planning effect, and the bigger the result is, the better the effect of the pre-shooting task planning algorithm is; the time for planning the pre-shooting cooperative task refers to the time for distributing the single hit targets and binding the distributed information before the cluster is launched, and the shorter the time is, the higher the timeliness of the pre-shooting task planning is, and the time is used for collecting records in simulation deduction.

Still further, the coordinated formation flying ability is decomposed into timeliness of a cluster response command and accuracy of a response position after battlefield information is changed, and the maximum adjustment time, steady state error and maximum/small average flying speed are used as attribute indexes of the coordinated formation flying ability, wherein the maximum adjustment time refers to a time difference between the moment when the last monomer in the cluster reaches and is stabilized within a range of +/-5% of an expected height (or other stability standards) and the moment when the cluster sends out a height maneuvering instruction, and the smaller the difference, the shorter the adjustment time is, and the more flexible the cluster maneuvering is; the steady-state error is the average level of the ratio of the actual maneuvering height of the cluster to the maneuvering instruction value of the height, and the smaller the steady-state error is, the better the flight stability of the cluster is; meanwhile, the flight speed of the clusters is required to be continuously adjusted according to battlefield environments, the relative positions in the clusters are changed, enemy firepower is avoided, meanwhile, the cluster system architecture is kept relatively stable, the quantification method is to record the maximum/small flight speed of each monomer in the clusters in each simulation deduction process respectively, and then the average value is calculated to represent the average level of the maneuvering speed of the clusters.

Still further, the intelligent collaborative situation awareness decision-making capability is decomposed into target detection probability, target recognition probability and target positioning accuracy; the intelligent decision-making ability is quantized into a task planning benefit value index after a plurality of monomers are damaged or the target number of enemy is detected to be increased; the target detection rate, the target recognition rate, the ratio of the task planning benefit value after the damage of a part of bullets and the offline task planning benefit value after the damage of a part of bullets, and the ratio of the task planning benefit value after the increase of the enemy targets and the offline task planning benefit value after the increase of the enemy targets are used as attribute indexes of intelligent collaborative situation perception decision-making capability, wherein the target detection rate refers to an objective limit value determined by the percentage of the detected number of targets to the total number of targets, the performance of equipment and the like, and the approximate value of the target detection rate can be obtained through experience statistics of mass use of equipment or statistics deduced through mass simulation in actual application; the target recognition rate refers to the percentage of the number of recognition targets to the total number of targets; the acquisition method in actual application is the same as the target detection rate acquisition method; the ratio of the task planning benefit value after the damage of the partial bullet to the off-line task planning benefit value after the damage of the partial bullet is characterized by the on-line intelligent decision-making capability of the cluster after the damage of the individual in the cluster, and the larger the ratio is, the better the on-line decision-making capability is; the ratio of the task planning benefit value after the enemy target is increased to the offline task planning benefit value after the enemy target is increased is used for representing the online intelligent decision-making capability of the cluster after the enemy target is changed, and the larger the ratio is, the better the online decision-making capability is.

Still further, the autonomous dynamic cooperative attack capability is decomposed into cooperative action capability and cooperative attack capability, and is measured by the consistency and hit rate of the time when the cluster arrives at the effective attack range of the target, and the maximum consistency error and hit probability are used as attribute indexes of the autonomous dynamic cooperative attack capability, wherein the maximum consistency error refers to the average level of time difference that the cluster formation arrives and stabilizes in the allocated effective attack range of the target, or the average level of time difference that the cluster formation initiates the attack to the allocated target, so as to represent the level of consistency in the time when the cluster formation initiates the cooperative attack; hit probability refers to the percentage of the number of hit targets to the total number of targets; the acquisition method in actual application is the same as the target detection rate acquisition method.

And further, the off-line task planning test is to complete the task allocation randomly without any task planning algorithm, and the task planning benefit value is recorded under the conditions of considering the distance between the single object and the target, the oil consumption required by the target, the threat degree of the analysis target, the target value and other factors.

And further, the task planning benefit value is the benefit obtained in the theory of task planning by comprehensively considering the number of clusters, the types of targets, the number of targets, the distance of targets, the threat level of targets, the oil consumption of hit targets and the like, the quantification of the benefit value is characterized by a plurality of optimization models, and the algorithm is directly collected and recorded after being embedded in a simulation deduction system.

Compared with the prior art, the construction method of the intelligent cluster system combat effectiveness evaluation index system disclosed by the invention is used for refining combat effectiveness influence factors according to the combat process and the sequence of events in the combat process, combining the combat characteristics of the intelligent cluster system, following the principle of level-by-level decomposition from top to subsystem from top to bottom, refining and quantifying indexes to the extent that engineering can be realized, and finally establishing comprehensive standards for assessing combat effectiveness.

Detailed Description

The intelligent cluster system combat effectiveness index system research process is as follows:

firstly, analyzing the characteristics of the intelligent cluster system,

whatever the monomer in the intelligent cluster is, the most essential characteristics of the intelligent cluster are that the individual is simple, the cost is low, the intelligent cooperative function is high-efficient, and the like;

the single intelligent cluster can be transmitted by means of various transmitting platforms, the combination of the transmitting distance of the transmitting platform and the flight time of the single intelligent cluster can form a novel weapon system with long range and wide coverage range, and the single intelligent cluster is simple in function, low in cost, strong in concealment, aggressiveness and robustness, and can be used for acquiring comprehensive information integrally through the cooperation of a plurality of single intelligent clusters, so that complex tasks can be completed with low cost and high efficiency, future battlefield maneuvering, high efficiency and flexible operation demands are met, and the mission capability of army is greatly improved;

The intelligent cooperative function is mainly represented by that the single bodies can cooperate with task planning, cooperative flight, cooperative reconnaissance, cooperative attack and the like, and the single bodies and the transmitting platform can cooperate with each other, so that the system can energize the whole army combat system, the dependence on the system and the platform can be greatly reduced, and the autonomous combat under the high-countermeasure complex environment can be realized; based on the intelligent characteristics of the system, unmanned operation can be realized in the combat, and the combat idea of 'zero casualties' emphasized by modern informatization combat is satisfied;

by introducing the concept theory of the intelligent agent, each monomer in the cluster can be regarded as an intelligent agent which can be calculated and controlled easily, not only can be in a decentralized form in physics and geography to independently execute the same or different combat tasks, but also can realize combat instruction sharing, battlefield situation sharing and command means sharing through network information interaction, thereby completing the established combat target in a 'class whole'; the "intelligent cluster" concept studied by the present invention may be considered as: the system comprises a plurality of organic whole bodies formed by isomorphic or heterogeneous monomers with intelligent body functions, wherein the monomers in the system realize non-centralized distribution through networked coordination to form intelligent body sets capable of autonomously completing behaviors such as situation awareness, path planning, formation flying, dynamic decision, cooperative striking and the like;

Secondly, researching the intelligent cluster combat mission, analyzing applicable combat operation scenes and combat missions by combining the characteristics of the intelligent cluster, researching intelligent cluster combat capability requirements under different scenes, and laying a foundation for subsequently refining key influencing factors of intelligent cluster combat effectiveness;

under the high-contrast battlefield environment, the intelligent cluster can rely on the advantages of a large number, small volume, easiness in concealment, target searching, accurate positioning, dynamic tracking and other functions, and can complete the fight tasks of rapid burst prevention, wide-area coverage reconnaissance, concealed approaching maneuver, immediate attack and the like in the early stage of battlefield, and meanwhile, the intelligent cluster has the functions of dynamic situation sensing and dynamic evaluation, so that the intelligent cluster can obtain the optimal survival probability and fight hitting effect under different task instructions, and the possibility is provided for completing the task of continuous approaching reconnaissance monitoring hitting evaluation; when executing the combat mission of the type, the cluster is required to have stronger sudden prevention capability, situation awareness capability and mission planning capability;

the intelligent cluster can rapidly deliver a large amount of monomers to the ground of the enemy array by virtue of the transmitting platform, dense rapid scattering is implemented, burst prevention is implemented, attack is rapidly initiated on key targets on the ground of the enemy array, time-sensitive targets in the countermeasure environment can be effectively hit and monitored, and the rapid breakthrough of the hit task is facilitated; the combat task has high requirements on formation flying capacity, formation adjustment capacity, dynamic task planning capacity and the like of the cluster in the formation flying process; for a plurality of targets with discrete and higher value in hidden, small and distributed areas, the targets are difficult to find in time by adopting a firepower coverage mode in the traditional firepower, and even if the parabolic firepower is found to have poor striking effect on the targets by even improved guided shells, the sparse targets are difficult to be completely destroyed in short time;

The intelligent cluster can quickly perform large-scale reconnaissance monitoring, multipoint intensive compression attack and diffraction attack, and perform instant attack and guide attack on discrete small targets; in order to improve the task target killing probability, a multi-batch and multi-frame attack mode can be used for simultaneously carrying out firepower attack on the target from different flying heights and attack angles at a certain time point to form the saturation attack capability on the regional discrete target; the battle task requires that the intelligent cluster has higher overall collaborative capability, for example, the cluster can dynamically sense the target, conduct task planning in real time according to battlefield conditions and target information, and the attack initiating time has higher consistency.

After analysis and research of the intelligent cluster system, the invention provides a construction method of an intelligent cluster system combat effectiveness evaluation index system, which specifically comprises the following steps:

analyzing an intelligent cluster, providing an evaluation requirement, defining an evaluation purpose, and constructing a combat effectiveness index system according to the evaluation requirement and the evaluation purpose;

step two, constructing a simulation test platform on the basis, collecting simulation test data, researching a combat effectiveness evaluation method, processing and analyzing the simulation test data to complete intelligent cluster combat effectiveness evaluation, and analyzing an evaluation result.

The specific operation method of the first step is as follows:

the first step, analysis of the intelligent cluster combat process and combat effectiveness influence factors,

A. the intelligent cluster fight process comprises four stages of pre-shooting task planning, cooperative formation flying, cooperative perception decision making and dynamic cooperative attack;

(1) In the pre-shooting task planning stage, a collaborative task planning technology is applied to complete initial task allocation and corresponding path planning; specifically, the intelligent cluster analyzes and judges the distance between each monomer and the target according to the current battlefield situation, oil consumption required by reaching the target, threat degree of the target and target value are analyzed, and the like, and the battlefield information is synthesized to make a task planning algorithm on the basis of the principle that the task planning benefit value reaches the optimum, and task allocation is carried out on the monomers in the cluster system according to the made algorithm, so that a pre-shooting task planning scheme is finally obtained;

(2) In the cooperative formation flight stage, the cluster system realizes patrol flight by forming flight and approaching to a target area; specifically, when the monomers in the cluster fly in formation, a plurality of formations are generally formed according to the number of the monomers, one of the monomers is selected in each formation to bear the function of the long machine, the other monomers are equivalent to the roles of the plane, and the plane cooperatively forms the flight under the driving of the long machine;

(3) In the collaborative awareness decision stage, the cluster system carries out intelligent collaborative situation awareness on the target area, determines a hit target, carries out intelligent online planning and decision technology, and distributes attack, seal control and continuous reconnaissance monomers; specifically, firstly, after a cluster system flies against a battle area through intelligent collaborative situation awareness, the cluster system carries out intelligent autonomous detection and identification on a ground suspicious target in a target space based on an area situation awareness technology of a battlefield information distributed awareness and tracking method; then, according to situation awareness information, the intelligent cluster needs to establish a task planning scheme according to the principle that the current situation still reaches the optimal value of the task planning benefit, and meanwhile, when the cluster system encounters emergency situations, such as the situation that a monomer in the cluster is damaged, the situation that the number of enemy targets is increased, and the like, task decision deployment is timely adjusted, and the task planning scheme is updated;

(4) In the dynamic collaborative attack stage, the clusters update the single flight path according to the changed task state, and autonomous dynamic collaborative attack is carried out to form a combat closed loop; specifically, after a task planning scheme is formulated, the cluster system deploys cooperative attack according to the distributed hit targets and the planning paths;

B. Analysis of the factors affecting the effectiveness of the combat,

(1) Analyzing the pre-shooting task planning, wherein the evaluation of the quality of the pre-shooting task planning actually requires the evaluation of the quality of a pre-shooting task planning algorithm, and the key parameter reflecting the quality of the task allocation algorithm is a task planning benefit value; the larger the task planning benefit value is, the better the pre-shooting task allocation scheme is; however, only the task benefit value result can only indicate the quality of the task planning result of different times under the same task planning algorithm, and the quality of the pre-shooting task planning algorithm cannot be indicated, so that a reliable reference standard is needed to verify the quality of the pre-shooting task planning; therefore, 100 offline task planning tests are carried out, and based on the offline task planning tests, the ratio of the pre-shooting task planning benefit value to the offline task planning benefit value is calculated, and the larger the ratio of the pre-shooting task planning benefit value to the offline task planning benefit value is, the better the pre-shooting task planning effect is; in addition, the time for completing task planning shows the timeliness of task planning, and the shorter the task planning time is, the higher the timeliness for completing task planning is, which is an important parameter for reflecting the task planning effect;

(2) The analysis of the cooperative formation flying is that the cooperative formation flying capability runs through the whole process of the combat operation, is a necessary condition for the cluster system to complete the combat task, and is an important factor influencing the cluster combat effect; in the flight process, the most ideal flight environment is that battlefield information is not changed, and long aircraft does not need to give any maneuvering command in the flight process, so that the current technical level is that the cluster formation flight capability can completely meet the combat requirement; however, in actual flight, battlefield information is always changed, the long aircraft needs to adjust the flight altitude and the flight route in time according to the current battlefield situation, a maneuvering command for pulling up or lowering is issued to the bureau aircraft, the degree of the bureau aircraft responding to the maneuvering command is an important capability index of the cluster cooperative formation flying capability, and the time of the bureau aircraft responding to the maneuvering command reflects the degree of the bureau aircraft responding to the maneuvering command in response to the maneuvering command; on the other hand, when the intensive fire interception condition of the enemy is met in the formation flight process, whether the cluster is burst-proof is successful or not can directly influence the subsequent combat action, and index parameters influencing the burst-proof capability mainly comprise average maximum and minimum flight speeds, air time and the like which can be achieved by the cluster;

(3) The method comprises the steps of analyzing collaborative perception decisions, wherein main influencing factors of intelligent collaborative situation perception capability are target detection probability, target recognition probability and target positioning error, wherein the target detection rate is the capability of a cluster situation perception to obtain a ground target, the target recognition rate is the capability of a cluster not recognizing an enemy target from among the perceived targets, and the positioning error refers to a capability index of a cluster system for accurately positioning the enemy target after the identification; the important index of the intelligent decision capability is still a task planning benefit value, and particularly, the task planning benefit value after a plurality of monomers in the cluster system are damaged or the number of enemy targets is detected to be increased is mainly inspected, so that the aim of inspecting whether the cluster system can timely formulate an optimal strategy of task planning according to the current situation is achieved;

(4) The analysis of dynamic collaborative attack has the advantages that although any monomer in the cluster cannot finish the damage to the target, the target can be damaged when all monomers in the formation exert force together, so that the key of whether the cluster can kill the target efficiently is whether the monomers in the cluster exert force together, namely, whether the collaborative action and the collaborative attack can be unfolded, and therefore, the collaborative action capacity and the collaborative attack capacity are important factors influencing the final attack effect; the quality of the cooperative mobility is thinned to be the consistency of time when the clusters reach the target effective attack range according to the actual combat process, and the consistency of the detonation time of the same formation attack target is achieved after the clusters reach the effective attack range; on the premise of the same monomer performance, the smaller the time difference in reaching the effective attack range is, the smaller the detonation time difference is, and the better the synergistic attack effect is; the most direct method for representing the cooperative striking effect is to count the hit condition of the enemy target, and the higher the hit ratio of the target is, the better the cooperative striking effect is, so that the hit probability is an important index for checking the cooperative striking effect;

Second, constructing an intelligent cluster combat effectiveness evaluation index system,

in comprehensive analysis, the intelligent cluster combat effectiveness is examined by focusing on the characteristics of 'intellectualization' and 'cooperative assimilation', and decomposing the characteristics into pre-shooting cooperative task planning capability, cooperative formation flying capability, intelligent cooperative situation perception decision-making capability and autonomous dynamic cooperative attack capability;

the intelligent cluster cooperative combat effectiveness evaluation index system is finally formed through the decomposition of pre-shooting cooperative task planning capability, cooperative formation flying capability, intelligent cooperative situation perception decision capability and autonomous dynamic cooperative attack capability, and takes the intelligent cluster combat effectiveness as a primary index and decomposes the intelligent cluster combat effectiveness into four secondary capability indexes as shown in table 1: the system comprises a pre-shooting cooperative task planning capability, a cooperative formation flying capability, an intelligent cooperative situation awareness decision-making capability and an autonomous dynamic cooperative attack capability, wherein each secondary capability index is quantized into a plurality of tertiary attribute indexes, and the total of the secondary capability indexes comprises 4 secondary indexes and 12 tertiary indexes.

Table 1 Intelligent Cluster combat effectiveness evaluation index system

The pre-shooting cooperative task planning capability is decomposed into a ratio of a pre-shooting cooperative task planning benefit value to an off-line cooperative task planning benefit value and pre-shooting cooperative task planning time, and the pre-shooting cooperative task planning capability is respectively characterized by the goodness of a task planning scheme and the time effectiveness of completing task planning under the condition of considering factors such as distance, oil consumption, target threat degree, target value and the like, wherein the off-line cooperative task planning means that a cluster is completely and randomly allocated with a hitting task without adopting any task allocation algorithm; the pre-shooting collaborative task planning refers to the allocation of hitting tasks to the clusters according to a certain task planning algorithm; the ratio of the pre-shooting cooperative task planning benefit value to the off-line cooperative task planning benefit value reflects the advantages and disadvantages of the pre-shooting cooperative task planning effect, and the bigger the result is, the better the effect of the pre-shooting task planning algorithm is; the time for planning the pre-shooting cooperative task refers to the time for distributing the single hit targets and binding the distributed information before the cluster is launched, and the shorter the time is, the higher the timeliness of the pre-shooting task planning is, and the time is used for collecting records in simulation deduction. The coordinated formation flying capability is decomposed into timeliness of a cluster response command and precision of a response position after battlefield information is changed, and the maximum adjustment time, steady state error and maximum/small average flying speed are used as attribute indexes of the coordinated formation flying capability, wherein the maximum adjustment time refers to a time difference between the moment when the last monomer in the cluster reaches and is stabilized within a range of +/-5% of an expected height (or other stability standards) and the moment when the cluster sends out a high maneuvering instruction, and the smaller difference indicates that the shorter the adjustment time is, the more flexible the cluster maneuvering is; the steady-state error is the average level of the ratio of the actual maneuvering height of the cluster to the maneuvering instruction value of the height, and the smaller the steady-state error is, the better the flight stability of the cluster is; meanwhile, the flight speed of the clusters is required to be continuously adjusted according to battlefield environments, the relative positions in the clusters are changed, enemy firepower is avoided, meanwhile, the cluster system architecture is kept relatively stable, the quantification method is to record the maximum/small flight speed of each monomer in the clusters in each simulation deduction process respectively, and then the average value is calculated to represent the average level of the maneuvering speed of the clusters. The intelligent collaborative situation awareness decision-making capability is decomposed into target detection probability, target recognition probability and target positioning accuracy; the intelligent decision-making ability is quantized into a task planning benefit value index after a plurality of monomers are damaged or the target number of enemy is detected to be increased; the target detection rate, the target recognition rate, the ratio of the task planning benefit value after the damage of a part of bullets and the offline task planning benefit value after the damage of a part of bullets, and the ratio of the task planning benefit value after the increase of the enemy targets and the offline task planning benefit value after the increase of the enemy targets are used as attribute indexes of intelligent collaborative situation perception decision-making capability, wherein the target detection rate refers to an objective limit value determined by the percentage of the detected number of targets to the total number of targets, the performance of equipment and the like, and the approximate value of the target detection rate can be obtained through experience statistics of mass use of equipment or statistics deduced through mass simulation in actual application; the target recognition rate refers to the percentage of the number of recognition targets to the total number of targets; the acquisition method in actual application is the same as the target detection rate acquisition method; the ratio of the task planning benefit value after the damage of the partial bullet to the off-line task planning benefit value after the damage of the partial bullet is characterized by the on-line intelligent decision-making capability of the cluster after the damage of the individual in the cluster, and the larger the ratio is, the better the on-line decision-making capability is; the ratio of the task planning benefit value after the enemy target is increased to the offline task planning benefit value after the enemy target is increased is used for representing the online intelligent decision-making capability of the cluster after the enemy target is changed, and the larger the ratio is, the better the online decision-making capability is. The autonomous dynamic cooperative attack capability is decomposed into cooperative action capability and cooperative attack capability, and is measured by the consistency and hit rate of time when the cluster reaches the effective attack range of the target, and the maximum consistency error and hit probability are used as attribute indexes of the autonomous dynamic cooperative attack capability, wherein the maximum consistency error refers to the average level of time difference when the cluster formation reaches and stabilizes in the effective attack range of the allocated target, or the average level of time difference when the cluster formation initiates attack to the allocated target, and is used for representing the level of consistency in the time when the cluster formation initiates the cooperative attack; hit probability refers to the percentage of the number of hit targets to the total number of targets; the acquisition method in actual application is the same as the target detection rate acquisition method.

The off-line task planning test is that no task planning algorithm exists, task allocation is performed completely randomly, and task planning benefit values are recorded under the conditions that the distance between a single object and a target is considered, the oil consumption required by the target is reached, the threat degree of the target is analyzed, the target value and other factors are analyzed. The task planning benefit values are benefits obtained in the theory of task planning by comprehensively considering the number of clusters, the types of targets, the number of targets, the distance of targets, the threat level of targets, the oil consumption of hit targets and the like, the quantification of the benefit values is described by various optimization models, and algorithms are directly collected and recorded after being embedded in a simulation deduction system.

According to the construction method of the intelligent cluster system combat effectiveness evaluation index system, the combat effectiveness evaluation index system of the intelligent cluster system is constructed and generated by combing the equipment characteristics of the intelligent cluster system, surrounding the characteristics of intelligent and cooperative of the cluster system, and clinging to four combat stages of pre-shooting cooperative task planning, cooperative formation flying, intelligent cooperative situation sensing decision and autonomous dynamic cooperative attack of the cluster system, the combat effectiveness influence factors of the intelligent cluster system are condensed, and the index meaning and the quantization model are provided.

The objective of intelligent cluster combat effectiveness evaluation is to evaluate the merits of the cluster combat effect through the combat operation result of the system, and the evaluation process is roughly divided into: (1) Analyzing the intelligent cluster, providing an evaluation requirement, definitely evaluating the objective, and constructing a combat effectiveness index system according to the evaluation requirement and the evaluation objective; (2) Setting up a simulation test platform on the basis, collecting simulation test data, researching a combat effectiveness evaluation method, processing and analyzing the simulation test data to complete intelligent cluster combat effectiveness evaluation, and analyzing an evaluation result;

the intelligent cluster collaborative combat effectiveness index system is an objective basis for carrying out a simulation test and collecting simulation test data, and is a precondition for obtaining a reliable evaluation result, so that the systematicness, pertinence, feasibility and conciseness of the index system are fully considered in the construction of the index system; for the unmanned aerial vehicle intelligent cluster, systematicness aims at comprehensively considering factors influencing the combat effectiveness, and aims at establishing an index system to be closely attached to the evaluation requirement and the evaluation purpose; the feasibility is to ensure that the combat effectiveness index can be obtained by means of mathematical logic deduction or experiment and the like, so that quantitative analysis and application are convenient; meeting the conciseness can lead the indexes to be concise and clear in meaning, and finally, a set of combat effectiveness index system which can reflect the typical characteristics of intelligent cluster equipment, is comprehensive and clear, highlights key points and is independent and has no intersection is established; the realization of the above objective requires comprehensive and scientific analysis of intelligent cluster equipment characteristics, system key technology, system combat mission requirements and system combat processes, and on the basis of the comprehensive and scientific analysis, the influence factors of the intelligent cluster combat effectiveness are accurately positioned, and the combat effectiveness index system is refined and formed;

Therefore, the invention refines the impact factors of the combat effectiveness according to the combat process and the sequence of events in the combat process, combines the combat characteristics of the intelligent cluster system, follows the principle of gradual layer-by-layer decomposition from top to bottom from top to sub-system, refines and quantifies the indexes to the extent that engineering can be realized, and finally establishes the comprehensive standard for assessing the combat effectiveness.

The above embodiments are merely preferred embodiments of the present invention, and all changes and modifications that come within the meaning and range of equivalency of the structures, features and principles of the invention are therefore intended to be embraced therein.

Claims (8)

1. The construction method of the intelligent cluster system combat effectiveness evaluation index system is characterized by comprising the following steps of:

analyzing an intelligent cluster, providing an evaluation requirement, defining an evaluation purpose, and constructing a combat effectiveness index system according to the evaluation requirement and the evaluation purpose;

step two, constructing a simulation test platform on the basis, collecting simulation test data, researching a combat effectiveness evaluation method, processing and analyzing the simulation test data to complete intelligent cluster combat effectiveness evaluation, and analyzing an evaluation result.

2. The method for constructing the intelligent cluster system combat effectiveness evaluation index system according to claim 1, wherein the specific operation method in the first step is as follows:

the first step, analysis of the intelligent cluster combat process and combat effectiveness influence factors,

A. the intelligent cluster fight process comprises four stages of pre-shooting task planning, cooperative formation flying, cooperative perception decision making and dynamic cooperative attack;

(1) In the pre-shooting task planning stage, a collaborative task planning technology is applied to complete initial task allocation and corresponding path planning; specifically, the intelligent cluster analyzes and judges the distance between each monomer and the target according to the current battlefield situation, oil consumption required by reaching the target, threat degree of the target and target value are analyzed, and the like, and the battlefield information is synthesized to make a task planning algorithm on the basis of the principle that the task planning benefit value reaches the optimum, and task allocation is carried out on the monomers in the cluster system according to the made algorithm, so that a pre-shooting task planning scheme is finally obtained;

(2) In the cooperative formation flight stage, the cluster system realizes patrol flight by forming flight and approaching to a target area; specifically, when the monomers in the cluster fly in formation, a plurality of formations are generally formed according to the number of the monomers, one of the monomers is selected in each formation to bear the function of the long machine, the other monomers are equivalent to the roles of the plane, and the plane cooperatively forms the flight under the driving of the long machine;

(3) In the collaborative awareness decision stage, the cluster system carries out intelligent collaborative situation awareness on the target area, determines a hit target, carries out intelligent online planning and decision technology, and distributes attack, seal control and continuous reconnaissance monomers; specifically, firstly, after a cluster system flies against a battle area through intelligent collaborative situation awareness, the cluster system carries out intelligent autonomous detection and identification on a ground suspicious target in a target space based on an area situation awareness technology of a battlefield information distributed awareness and tracking method; then, according to situation awareness information, the intelligent cluster needs to establish a task planning scheme according to the principle that the current situation still reaches the optimal value of the task planning benefit, and meanwhile, when the cluster system encounters emergency situations, such as the situation that a monomer in the cluster is damaged, the situation that the number of enemy targets is increased, and the like, task decision deployment is timely adjusted, and the task planning scheme is updated;

(4) In the dynamic collaborative attack stage, the clusters update the single flight path according to the changed task state, and autonomous dynamic collaborative attack is carried out to form a combat closed loop; specifically, after a task planning scheme is formulated, the cluster system deploys cooperative attack according to the distributed hit targets and the planning paths;

B. Analysis of the factors affecting the effectiveness of the combat,

(1) Analyzing the pre-shooting task planning, wherein the evaluation of the quality of the pre-shooting task planning actually requires the evaluation of the quality of a pre-shooting task planning algorithm, and the key parameter reflecting the quality of the task allocation algorithm is a task planning benefit value; the larger the task planning benefit value is, the better the pre-shooting task allocation scheme is; however, only the task benefit value result can only indicate the quality of the task planning result of different times under the same task planning algorithm, and the quality of the pre-shooting task planning algorithm cannot be indicated, so that a reliable reference standard is needed to verify the quality of the pre-shooting task planning; therefore, 100 offline task planning tests are carried out, and based on the offline task planning tests, the ratio of the pre-shooting task planning benefit value to the offline task planning benefit value is calculated, and the larger the ratio of the pre-shooting task planning benefit value to the offline task planning benefit value is, the better the pre-shooting task planning effect is; in addition, the time for completing task planning shows the timeliness of task planning, and the shorter the task planning time is, the higher the timeliness for completing task planning is, which is an important parameter for reflecting the task planning effect;

(2) The analysis of the cooperative formation flight is that the most ideal flight environment is that battlefield information is not changed in any way in the flight process, and the long aircraft does not need to give any maneuvering command in the flight process, so that the current technology level is that the cluster formation flight capability can completely meet the combat requirement; however, in actual flight, battlefield information is always changed, the long aircraft needs to adjust the flight altitude and the flight route in time according to the current battlefield situation, a maneuvering command for pulling up or lowering is issued to the bureau aircraft, the degree of the bureau aircraft responding to the maneuvering command is an important capability index of the cluster cooperative formation flying capability, and the time of the bureau aircraft responding to the maneuvering command reflects the degree of the bureau aircraft responding to the maneuvering command in response to the maneuvering command; on the other hand, when the intensive fire interception condition of the enemy is met in the formation flight process, whether the cluster is burst-proof is successful or not can directly influence the subsequent combat action, and index parameters influencing the burst-proof capability mainly comprise average maximum and minimum flight speeds, air time and the like which can be achieved by the cluster;

(3) The method comprises the steps of analyzing collaborative perception decisions, wherein main influencing factors of intelligent collaborative situation perception capability are target detection probability, target recognition probability and target positioning error, wherein the target detection rate is the capability of a cluster situation perception to obtain a ground target, the target recognition rate is the capability of a cluster not recognizing an enemy target from among the perceived targets, and the positioning error refers to a capability index of a cluster system for accurately positioning the enemy target after the identification; the important index of the intelligent decision capability is still a task planning benefit value, and particularly, the task planning benefit value after a plurality of monomers in the cluster system are damaged or the number of enemy targets is detected to be increased is mainly inspected, so that the aim of inspecting whether the cluster system can timely formulate an optimal strategy of task planning according to the current situation is achieved;

(4) The analysis of dynamic collaborative attack has the advantages that although any monomer in the cluster cannot finish the damage to the target, the target can be damaged when all monomers in the formation exert force together, so that the key of whether the cluster can kill the target efficiently is whether the monomers in the cluster exert force together, namely, whether the collaborative action and the collaborative attack can be unfolded, and therefore, the collaborative action capacity and the collaborative attack capacity are important factors influencing the final attack effect; the quality of the cooperative mobility is thinned to be the consistency of time when the clusters reach the target effective attack range according to the actual combat process, and the consistency of the detonation time of the same formation attack target is achieved after the clusters reach the effective attack range; on the premise of the same monomer performance, the smaller the time difference in reaching the effective attack range is, the smaller the detonation time difference is, and the better the synergistic attack effect is; the most direct method for representing the cooperative striking effect is to count the hit condition of the enemy target, and the higher the hit ratio of the target is, the better the cooperative striking effect is, so that the hit probability is an important index for checking the cooperative striking effect;

Second, constructing an intelligent cluster combat effectiveness evaluation index system,

and finally forming an intelligent cluster collaborative combat effectiveness evaluation index system through the decomposition of pre-shooting collaborative task planning capability, collaborative formation flying capability, intelligent collaborative situation perception decision-making capability and autonomous dynamic collaborative attack capability.

3. The construction method of the intelligent cluster system combat effectiveness evaluation index system according to claim 2, wherein the pre-shooting cooperative task planning capability is decomposed into a ratio of a pre-shooting cooperative task planning benefit value to an off-line cooperative task planning benefit value and a pre-shooting cooperative task planning time, and the pre-shooting cooperative task planning benefit value and the off-shooting cooperative task planning benefit value are respectively characterized in that the goodness of a task planning scheme and the time effectiveness of completing task planning under the condition of considering factors such as distance, oil consumption, target threat level and target value are respectively represented.

4. The method for constructing the intelligent cluster system operational effectiveness evaluation index system according to claim 2, wherein the coordinated formation flying ability is decomposed into timeliness of a cluster response command after change of battlefield information and accuracy of a response position, and the maximum adjustment time, steady state error and maximum/small average flying speed are used as attribute indexes of the coordinated formation flying ability.

5. The construction method of the intelligent cluster system combat effectiveness evaluation index system according to claim 2, wherein the intelligent collaborative situation awareness decision-making capability is decomposed into target detection probability, target recognition probability and target positioning accuracy; the intelligent decision-making ability is quantized into a task planning benefit value index after a plurality of monomers are damaged or the target number of enemy is detected to be increased; the target detection rate, the target recognition rate, the ratio of the task planning benefit value after the partial bullet is damaged to the offline task planning benefit value after the partial bullet is damaged, and the ratio of the task planning benefit value after the enemy target is increased to the offline task planning benefit value after the enemy target is increased are used as attribute indexes of the intelligent collaborative situation perception decision-making capability.

6. The construction method of intelligent cluster system combat effectiveness evaluation index system according to claim 2, wherein the autonomous dynamic cooperative attack capability is decomposed into cooperative action capability and cooperative attack capability, and is measured by consistency and hit rate of time when the clusters reach the target effective attack range, respectively, and the maximum consistency error and hit probability are used as attribute indexes of the autonomous dynamic cooperative attack capability.

7. The method for constructing the intelligent cluster system combat effectiveness evaluation index system according to claim 2, wherein the offline task planning test is to record the task planning benefit value under the condition that the distance between the monomer and the target is considered, the required oil consumption of the target is reached, the threat level of the target is analyzed, the target value and other factors are also considered, and the task planning algorithm is omitted.

8. The construction method of the intelligent cluster system combat effectiveness evaluation index system according to claim 7, wherein the task planning benefit value is a benefit obtained in theory by comprehensively considering the number of clusters, the target type, the target number, the target distance, the target threat level, the oil consumption of hitting targets and the like, the benefit value quantization is characterized by various optimization models, and the algorithm is directly collected and recorded after being embedded in the simulation deduction system.