CN112764429A - Fire interception threat assessment method and device for unmanned aerial vehicle cluster defense - Google Patents
Fire interception threat assessment method and device for unmanned aerial vehicle cluster defense Download PDFInfo
- Publication number
- CN112764429A CN112764429A CN202110084994.XA CN202110084994A CN112764429A CN 112764429 A CN112764429 A CN 112764429A CN 202110084994 A CN202110084994 A CN 202110084994A CN 112764429 A CN112764429 A CN 112764429A
- Authority
- CN
- China
- Prior art keywords
- unmanned aerial
- air defense
- aerial vehicle
- interception
- weapon system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000007123 defense Effects 0.000 title claims abstract description 309
- 238000000034 method Methods 0.000 title claims abstract description 61
- 230000002265 prevention Effects 0.000 claims abstract description 66
- 230000006378 damage Effects 0.000 claims abstract description 39
- 238000004364 calculation method Methods 0.000 claims abstract description 22
- 238000009826 distribution Methods 0.000 claims abstract description 22
- 238000013507 mapping Methods 0.000 claims abstract description 20
- 238000013210 evaluation model Methods 0.000 claims abstract description 12
- 230000035515 penetration Effects 0.000 claims description 110
- 230000008569 process Effects 0.000 claims description 17
- 238000003860 storage Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 9
- 241000257161 Calliphoridae Species 0.000 claims description 5
- 230000006855 networking Effects 0.000 abstract description 10
- 238000011156 evaluation Methods 0.000 description 25
- 238000004088 simulation Methods 0.000 description 13
- 238000004458 analytical method Methods 0.000 description 11
- 230000009471 action Effects 0.000 description 6
- 239000011159 matrix material Substances 0.000 description 6
- 238000005457 optimization Methods 0.000 description 6
- 238000002360 preparation method Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000005553 drilling Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000035484 reaction time Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Aiming, Guidance, Guns With A Light Source, Armor, Camouflage, And Targets (AREA)
Abstract
The invention discloses a fire interception threat assessment method and a device for unmanned aerial vehicle cluster fire prevention, wherein the method comprises the following steps: receiving the sudden flight path setting of the unmanned aerial vehicle cluster, and determining the parameters of the unmanned aerial vehicle cluster; determining interception performance parameters of the air defense weapon system; distributing firepower of each air defense weapon system at different moments when the unmanned aerial vehicle cluster suddenly prevents and attacks according to a preset firepower distribution principle based on the parameters to obtain firepower attack mapping relations between the unmanned aerial vehicle cluster and the air defense weapon systems at different moments; calculating the number of remaining airplanes of the unmanned aerial vehicles of each batch at the corresponding moment under the fire protection interception according to the mapping relation; sending the number of the remaining airplanes at the sudden prevention ending moment into a preset evaluation model for calculation to obtain the average damage probability of the unmanned aerial vehicle completing the sudden prevention flight path; the method can accurately analyze the condition that the unmanned aerial vehicle is intercepted under the networking interception condition of the air defense system, and provides good support for the subsequent optimal regulation of the break-through flight path of the unmanned aerial vehicle or the deployment regulation of the air defense weapon system.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a method and a device for evaluating firepower interception threats of unmanned aerial vehicle cluster defense outburst.
Background
With the continuous progress of the air defense weapon system, the fire interception of various air defense weapon systems is inevitable in the air defense process of the unmanned aerial vehicle, and accurate and reliable fire interception threat assessment is the key for optimizing the air defense path and improving the success probability of the air defense.
At present, in the process of planning a fire protection air route, two types of processing modes are mainly used for the fire interception threat: the method comprises the steps of performing a terrain equivalence method based on killing range analysis, and performing a damage probability modeling analysis method based on residence time.
The terrain equivalence method based on the damage range analysis generates a terrain bump with the same coverage space as the damage range through calculation and analysis of the damage range of the air defense weapon system, and on the basis, the firepower interception threat of the air-ground missile weapon is equivalent to the collision threat caused by the terrain bump.
The damage probability modeling analysis method based on the residence time firstly calculates the residence time of the penetration aircraft in the killing range of the air defense weapon system according to the penetration route, then obtains the impact times of the air defense weapon system according to the residence time, further carries out modeling calculation on the damage probability of the unmanned aerial vehicle under firepower interception according to the impact times, and takes the calculation result as the firepower interception threat evaluation result.
In the two firepower interception threat assessment processing methods, the firepower interception threat is equivalent to the terrain threat by a terrain equivalence method based on the killing range analysis. However, the terrain threat and the fire threat are fundamentally different, the terrain threat needs to be avoided in the penetration flight path planning, otherwise, the penetration aircraft must be crashed, the fire threat is only avoided as much as possible in the penetration flight path planning, the fire killing range sometimes needs to be forcibly penetrated for completing the combat mission, at the moment, if the penetration fire interception threat assessment is carried out by adopting a terrain equivalent method, the assessment result is that the penetration aircraft is intercepted and destroyed, and in practice, the penetration aircraft still has the possibility of penetration success by adopting a reasonable penetration strategy. Therefore, fire interception threat assessment by adopting a terrain equivalent method can cause the planning adjustment of the defense route to be limited and even cause the route planning to fail.
The damage probability modeling analysis method based on the residence time treats the penetration aircraft and the ground-to-air missile weapon system as isolated individuals, defines the attacked damage probability of the single penetration aircraft as a firepower interception threat assessment index, constructs a damage probability model of the penetration aircraft based on the residence time of the penetration aircraft in the killing range of the ground-to-air missile weapon system, and calculates the damage probability index of the penetration aircraft under the ground-to-air missile firepower interception. However, under the environment condition of the modern battlefield, in order to improve the success probability of the penetration of unmanned aerial vehicles, multiple batches of unmanned aerial vehicles are increasingly common in cooperation with penetration, and the damage probability of a single penetration aircraft obviously cannot accurately describe the fire interception threat to the whole penetration cluster under the background. Meanwhile, in order to improve the anti-saturation attack capability of the air defense system, networking interception of a plurality of ground-to-air missile weapon systems gradually becomes a mainstream operation style of air defense operation, and at the moment, factors such as a fire cooperative distribution principle of the air defense system, the number of target channels, the number of reserve missiles, the interception precision, the interception response time, the batch and the number of racks of the air defense unmanned aerial vehicles have important influence on the damage probability of the air defense cluster. Therefore, the accurate analysis of the damage probability of the penetration machine group under the networking interception condition of the air defense system can not be realized by only depending on the residence time, so that the difficulty is brought to the subsequent optimization and adjustment of the penetration flight path, and the provision of the penetration success probability of the unmanned aerial vehicle or the development of the penetration combat training of the unmanned aerial vehicle can not be favorably realized.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a fire interception threat assessment method and a fire interception threat assessment device for unmanned aerial vehicle cluster defense, and aims to solve the technical problem that due to the fact that interception threats suffered in the unmanned aerial vehicle defense process cannot be accurately analyzed under the networking interception condition of the existing air defense system, subsequent defense path optimization and adjustment are difficult. .
The fire interception threat assessment method for the unmanned aerial vehicle cluster defense includes the following steps:
receiving a sudden defense track setting operation of an unmanned aerial vehicle cluster;
determining the cluster number of the unmanned aerial vehicle cluster, the initial unmanned machine frame number of each batch of the unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster;
receiving a deployment setup operation for an air defense weapons system;
determining interception performance parameters of an air defense weapon system, wherein the interception performance parameters at least comprise a deployment position, an interception range, interception precision, a target channel number, an intercepted projectile flying speed, a loading quantity and a standby projectile quantity;
traversing each batch of unmanned aerial vehicle cluster, calculating the relative distance between the traversed target unmanned aerial vehicle cluster and the air defense weapon systems at different positions in real time, and taking the air defense weapon system with the shortest relative distance with the target unmanned aerial vehicle cluster as the target air defense weapon system;
calculating the interception time of the target air defense weapon system to the target unmanned aerial vehicle cluster based on the speed of the target unmanned aerial vehicle cluster and the relative distance between the target unmanned aerial vehicle cluster and the target air defense weapon system;
distributing firepower of each air defense weapon system at different moments according to a preset firepower distribution principle based on the interception parameters of each air defense weapon system, the interception time of the target unmanned aerial vehicle cluster, the cluster batch number and the unmanned rack number to obtain firepower attack mapping relations between the unmanned aerial vehicle cluster and the air defense weapon systems at different moments;
respectively calculating the number of remaining airplanes of each batch of unmanned aerial vehicle cluster at the current moment under fire interception according to the fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments and by combining the interception precision of the air defense weapon system in real time; sending the number of the remaining airplanes when the unmanned aerial vehicle cluster flies to the sudden prevention flight path end point into a preset evaluation model for calculation to obtain the average unmanned aerial vehicle damage probability of the unmanned aerial vehicle cluster finishing the sudden prevention flight path;
wherein the preset evaluation model is characterized by the following formula (1):
wherein L isPRepresenting the average damage probability of the unmanned aerial vehicle after the target unmanned aerial vehicle cluster finishes the penetration track;
m represents the number of the cluster batches of the unmanned aerial vehicle cluster, wherein the number of the unmanned aerial vehicles of the ith batch of target unmanned aerial vehicle cluster is Ui；
ULiAnd the mathematical expected value represents the number of the remaining airplanes when the ith group of target unmanned aerial vehicles complete the penetration under the fire interception of the air defense weapon system.
Preferably, the preset fire power distribution principle represents the following three ways:
the first method is as follows: and for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a single set of air defense aircraft is in the interception range of a plurality of air defense weapon systems in the air defense airspace of the air defense track, using the air defense weapon system closest to the air defense aircraft to carry out interception, and when the number of available target channels of the air defense weapon system is smaller than the number of airplanes to be attacked of the set of air defense aircraft, carrying out interception on the remaining airplanes to be attacked by the next-nearest air defense weapon system to the set of air defense aircraft until all the available target channels of the airplanes to be attacked or all the ground-air missile weapons are completely distributed, wherein the number of airplanes to be attacked refers to the mathematical expected value of the remaining number of the sets of air defense aircraft at the current moment.
The second method comprises the following steps: and for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a plurality of groups of air defense aircraft exist in the air defense airspace of the air defense track and are positioned in the interception range of one air defense weapon system, the air defense weapon system preferentially attacks the nearest group of air defense aircraft, and when the number of the group of aircraft to be attacked is less than the number of the target channels available for the air defense weapon system, the rest target channels of the air defense weapon system are used for striking the next-close-range group of air defense aircraft until all the available target channels of all the air defense aircraft or ground-air missile weapons to be attacked are completely distributed.
The third method comprises the following steps: for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a plurality of sets of air defense aircraft are positioned in the interception range of a plurality of air defense weapon systems in the air defense airspace of the air defense track, firstly, a pair of air defense aircraft and air defense weapon systems which are closest to each other are searched in all the air defense aircraft and air defense weapon systems, and a fire attack relation is established between the air defense aircraft and the air defense weapon systems; on the basis, if the number of the airplanes to be attacked of the batch of the penetration prevention airplanes is larger than the number of the available target channels of the air defense weapon system, all the available target channels of the air defense weapon system are judged to be used for attacking the batch of the airplanes, meanwhile, the number of the available target channels of the air defense weapon system is subtracted from the number of the airplanes to be attacked of the batch of the penetration prevention airplanes, the air defense weapon system is ignored, a pair of penetration prevention airplanes and air defense weapon systems with the next shortest distance is continuously searched between the rest air defense weapon systems and all the batches of the penetration prevention airplanes, and further, a fire attack relation is established between the rest air defense airplane systems and the air defense weapons; or if the number of the airplanes to be attacked of the batch of the penetration prevention airplanes is smaller than the number of available target channels of the air defense weapon system, judging that all the airplanes to be attacked of the batch of the penetration prevention airplanes are attacked by the air defense weapon system, simultaneously subtracting the number of the batch of the penetration prevention airplanes from the number of the available target channels of the air defense weapon system, neglecting the batch of the penetration prevention airplanes, continuously searching a pair of penetration prevention airplanes and air defense weapon systems with the next shortest distance between the rest of the penetration prevention airplanes and all the air defense weapon systems, and further establishing a fire attack relationship between the rest of the penetration prevention airplanes and the air defense weapon systems; and circularly iterating the process of the third condition until all the available target channels of the airplanes to be attacked or all the ground-to-air missile weapons are completely distributed.
Optionally, the step of determining the cluster number of the drone cluster, the initial drone rack number of the drone cluster of each batch, and the speed of the drone cluster specifically includes:
and responding to the initialization operation of a user, and receiving the cluster number of the unmanned aerial vehicle cluster, the initial unmanned aerial vehicle frame number of each batch of the unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster, which are input by the user.
Optionally, the interception parameters of the air defense weapon system are determined by the air defense weapon system hardware;
correspondingly, the step of traversing the interception parameters of each air defense weapon system, wherein the interception parameters at least include the deployment position, the interception range, the interception precision, the number of target channels, the number of loaded bombs and the number of reserve bombs, specifically includes:
and responding to the initialization operation of the user, and respectively receiving the interception parameters of each air defense weapon system input by the user.
Optionally, the step of calculating, in real time, a relative distance between the traversed target drone swarm and the air defense weapon systems at different positions on the penetration flight path specifically includes:
determining a traversed target unmanned aerial vehicle cluster;
calculating a longitude coordinate, a latitude coordinate and an altitude coordinate of the target unmanned aerial vehicle cluster at the moment t when flying along the penetration track according to the speed of the target unmanned aerial vehicle cluster;
and determining the relative distance between the target unmanned aerial vehicle cluster and the air defense weapon systems at different positions at the time t based on the longitude coordinate, the latitude coordinate and the altitude coordinate at the time t.
In addition, in order to achieve the above object, the present invention further provides a fire interception threat assessment apparatus for unmanned aerial vehicle fleet defense, the apparatus comprising:
the flight path setting unit is used for receiving the sudden defense flight path setting operation of the unmanned aerial vehicle cluster;
the unmanned aerial vehicle parameter setting unit is used for determining the cluster number of the unmanned aerial vehicle cluster, the initial unmanned machine frame number of each batch of unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster;
the air defense weapon parameter setting unit is used for receiving interception parameters of each air defense weapon system, wherein the interception parameters at least comprise deployment positions, interception ranges, interception precision, target channel numbers, loading numbers and standby numbers;
the relative distance calculation unit is used for traversing each batch of unmanned aerial vehicle cluster, calculating the relative distance between the traversed target unmanned aerial vehicle cluster and the air defense weapon systems at different positions in real time, and taking the air defense weapon system with the shortest relative distance with the target unmanned aerial vehicle cluster as the target air defense weapon system;
the intercepting time calculation unit is used for calculating the intercepting time of the target air defense weapon system to the target unmanned aerial vehicle cluster based on the speed of the target unmanned aerial vehicle cluster and the relative distance between the target unmanned aerial vehicle cluster and the target air defense weapon system;
the fire distribution unit is used for distributing fire of each air defense weapon system at different moments according to a preset fire distribution principle based on the interception parameters of each air defense weapon system, the interception time of the target unmanned aerial vehicle cluster, the cluster batch number and the unmanned rack number to obtain a fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments;
the remaining airplane calculation unit is used for calculating the number of remaining airplanes of each batch of unmanned aerial vehicle cluster at the current moment under fire interception respectively according to the fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments in real time and by combining the interception precision of the air defense weapon system;
the assessment unit is used for sending the number of remaining airplanes into a preset assessment model for calculation when the unmanned aerial vehicle cluster flies to the sudden prevention flight path end point, and obtaining the average unmanned aerial vehicle damage probability of the unmanned aerial vehicle cluster finishing the sudden prevention flight path;
wherein the preset evaluation model is characterized by the following formula (1):
wherein L isPRepresenting the average damage probability of the unmanned aerial vehicle after the target unmanned aerial vehicle cluster finishes the penetration track;
m represents the number of the cluster batches of the unmanned aerial vehicle cluster, wherein the number of the unmanned aerial vehicles of the ith batch of target unmanned aerial vehicle cluster is Ui；
ULiRepresenting that the ith group of target unmanned aerial vehicles are in air defense weaponsAnd (3) intercepting the mathematical expected value of the number of the remaining airplanes when the break-through is finished under the firepower of the system.
In addition, to achieve the above object, the present invention further provides a storage medium, which is a computer-readable storage medium, and the storage medium stores a computer program, and the computer program is configured to execute the steps of the fire interception threat assessment method for drone swarm defense according to the above claims.
The invention has the beneficial effects that: the defects that fire interception threats are difficult to accurately evaluate and analyze under the situation of cooperative defense burst of a plurality of batches of unmanned aerial vehicles and multi-system networking interception in the prior art are overcome, and good support is provided for the subsequent optimization of a defense burst route of an unmanned aerial vehicle cluster;
by using the evaluation method and the evaluation device, the condition that the unmanned aerial vehicle is intercepted can be accurately analyzed under the networking interception condition of the air defense system, and good support is provided for subsequent anti-riot exercises of the unmanned aerial vehicle or prevention of the anti-riot exercises of the unmanned aerial vehicle.
Drawings
Fig. 1 is a schematic flow chart illustrating an embodiment of a fire interception threat assessment method for unmanned aerial vehicle fleet defense according to the present invention;
fig. 2 is a block diagram of an embodiment of a fire interception threat assessment apparatus for unmanned aerial vehicle fleet defense.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention conception of the application is as follows: receiving a sudden flight path setting operation of an unmanned aerial vehicle cluster, and determining parameters of the unmanned aerial vehicle cluster; receiving deployment setting operation of an air defense weapon system and determining interception performance parameters of the air defense weapon system; distributing firepower of each air defense weapon system at different moments when the unmanned aerial vehicle cluster suddenly prevents and attacks according to a preset firepower distribution principle based on the parameters to obtain firepower attack mapping relations between the unmanned aerial vehicle cluster and the air defense weapon systems at different moments; calculating the number of remaining airplanes of the unmanned aerial vehicles of each batch at the corresponding moment under fire protection interception according to the fire attack mapping relation at different moments; sending the number of remaining airplanes under firepower interception at the fire prevention ending moment into a preset evaluation model for calculation to obtain the average damage probability of the unmanned aerial vehicle cluster for completing the fire prevention track; the method can accurately analyze the condition that the unmanned aerial vehicle is intercepted under the networking interception condition of the air defense system, and provides good support for the subsequent optimal regulation of the break-through flight path of the unmanned aerial vehicle or the deployment regulation of the air defense weapon system.
Referring to fig. 1, a first embodiment of the present invention provides a fire interception threat assessment method for unmanned aerial vehicle fleet defense, where the method includes:
step S10, receiving the sudden defense track setting operation of the unmanned aerial vehicle cluster;
it can be understood that the fire interception threat assessment method for unmanned aerial vehicle fleet defense disclosed by the embodiment of the invention can represent a computer program, wherein the computer program is loaded in computer equipment (corresponding to a fire interception threat assessment device for unmanned aerial vehicle fleet defense);
it should be noted that the execution subject of the evaluation method of this embodiment is a computer device (i.e., the above evaluation apparatus), and the evaluation apparatus may receive the operation of the operator on the sudden defense track setting of the drone swarm;
in this embodiment, after the sudden flight path is set, the evaluation device may automatically calculate some processing steps of the unmanned aerial vehicle fleet in the sudden flight path process according to the parameters of the unmanned aerial vehicle fleet and the interception parameters of the air defense weapon system, and finally obtain the average damage probability of the unmanned aerial vehicle after the unmanned aerial vehicle fleet completes the sudden flight path
Step S20: determining the cluster number of the unmanned aerial vehicle cluster, the initial unmanned machine frame number of each batch of the unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster;
in a specific implementation, the evaluation device may respond to an initialization operation of a user, and receive a cluster number of the drone swarm, an initial drone rack number of the drone swarm of each batch, and a speed of the drone swarm, which are input by the user.
It can be understood that, each time a user carries out the sudden prevention deduction of the unmanned aerial vehicle or prevents the unmanned aerial vehicle from performing sudden attack drilling, the previous parameters of the sudden prevention cluster of the unmanned aerial vehicle and the parameters of the ground-air missile weapon of the air defense weapon system need to be initialized so as to facilitate the execution of the drilling;
for m batches of unmanned aerial vehicle clusters appearing in one exercise and the number of unmanned racks of each batch of unmanned aerial vehicle clusters, the parameters are counted by an operator (namely a user) in advance, and then the user manually inputs the parameters of the unmanned aerial vehicles into an evaluation device;
the flight speeds of the unmanned aerial vehicle clusters in the same batch are the same, and the flight speeds of the unmanned aerial vehicle clusters in different batches may be the same or different.
Step S30: receiving a deployment setup operation for an air defense weapons system; determining interception performance parameters of an air defense weapon system, wherein the interception parameters at least comprise a deployment position, an interception range, interception precision, a target channel number, an intercepted projectile flying speed, a loading quantity and a standby projectile quantity;
it should be noted that the interception parameters of the air defense weapon system are determined by the hardware of the air defense weapon system, and the interception parameters of the air defense weapon systems in different position areas may be the same or different; for example, the interception accuracy of an air defense weapon system is related to the technical performance of the air defense weapon system, and the interception accuracy of an air defense weapon system with advanced technology is generally higher than that of an air defense weapon system with lagged technology.
In a specific implementation, the evaluation device respectively receives the interception parameters of each air defense weapon system input by the user in response to the initialization operation of the user.
Step S40: traversing each batch of unmanned aerial vehicle cluster, calculating the relative distance between the traversed target unmanned aerial vehicle cluster and the air defense weapon systems at different positions in real time, and taking the air defense weapon system with the shortest relative distance with the target unmanned aerial vehicle cluster as a target air defense weapon system;
it will be appreciated that for each batch of drone swarm, the present embodiment performs the following operations:
determining a traversed target unmanned aerial vehicle cluster;
calculating a longitude coordinate, a latitude coordinate and an altitude coordinate of the target unmanned aerial vehicle cluster at the moment t when flying along the penetration track according to the speed of the target unmanned aerial vehicle cluster;
determining the relative distance between the target unmanned aerial vehicle cluster and the air defense weapon systems at different positions at the time t based on the longitude coordinate, the latitude coordinate and the altitude coordinate at the time t;
taking the air defense weapon system with the shortest relative distance (closest relative distance) with the target unmanned aerial vehicle cluster as a target air defense weapon system;
step S50: calculating the interception time of the target air defense weapon system to the target unmanned aerial vehicle cluster based on the speed of the target unmanned aerial vehicle cluster and the relative distance between the target unmanned aerial vehicle cluster and the target air defense weapon system;
in a specific implementation, for each batch of unmanned aerial vehicle cluster, the calculation method of the interception time of the target unmanned aerial vehicle cluster by the target air defense weapon system is as follows: the relative distance between the target drone swarm and the target air defense weapon system is divided by the speed of the target drone swarm.
Step S60: distributing firepower of each air defense weapon system at different moments according to a preset firepower distribution principle based on the interception parameters of each air defense weapon system, the interception time of the target unmanned aerial vehicle cluster, the cluster batch number and the unmanned rack number to obtain firepower attack mapping relations between the unmanned aerial vehicle cluster and the air defense weapon systems at different moments;
step S70: respectively calculating the number of remaining airplanes of each batch of unmanned aerial vehicle cluster at the current moment under fire interception according to the fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments and by combining the interception precision of the air defense weapon system in real time;
step S80: sending the number of the remaining airplanes when the unmanned aerial vehicle cluster flies to the sudden prevention flight path end point into a preset evaluation model for calculation to obtain the average unmanned aerial vehicle damage probability of the unmanned aerial vehicle cluster finishing the sudden prevention flight path;
wherein the preset evaluation model is characterized by the following formula (1):
wherein L isPRepresenting the average damage probability of the unmanned aerial vehicle after the target unmanned aerial vehicle cluster finishes the penetration track;
m represents the number of the cluster batches of the unmanned aerial vehicle cluster, wherein the number of the unmanned aerial vehicles of the ith batch of target unmanned aerial vehicle cluster is Ui；
ULiAnd the mathematical expected value represents the number of the remaining airplanes when the ith group of target unmanned aerial vehicles complete the penetration under the fire interception of the air defense weapon system.
It can be understood that in the existing fire prevention fire interception threat assessment method, the terrain threat and the fire interception threat are essentially different, the fire prevention route planning is limited when the terrain threat and the fire interception threat are used as fire interception threat assessment indexes, and the attack damage probability of a single fire prevention aircraft is only suitable for a simple fire prevention operation scene, so that the fire attack threat faced by the cooperative fire prevention of a plurality of unmanned aerial vehicles cannot be accurately reflected. Therefore, fire interception threat assessment indexes need to be designed reasonably, and a new fire interception threat assessment index is introduced and provided in the invention: and the average damage probability when the sudden prevention cluster finishes the sudden prevention action. Suppose that the penetration cluster is divided into m groups, wherein the quantity of the ith group of penetration aircrafts is UiIf so, the average damage probability L of the sudden prevention cluster when completing the sudden prevention actionPIs defined as
U in formula (1)LiThe mathematic expected value of the number of the rest frames when the ith set of unmanned aerial vehicles finish the penetration under the fire interception of the ground-air missile weapon system is shown, and when the penetration is finished, the number of the rest frames is the mathematic expected valueWhen the group is only 1 batch 1 frame, LPNamely the damage probability when the monovalent unmanned plane completes the sudden prevention action.
Further, how to calculate and analyze the fire interception threat assessment index is as follows:
as can be seen from the formula (1), the evaluation index LPThe key of the calculation is to obtain the mathematical expected value U of the residual number of the aircraft in each batch of the penetration protection aircraft when the penetration protection is finishedLi(i ═ 1, …, m). Under the complex penetration countermeasure situation of cooperative penetration of multiple unmanned aerial vehicles and mesh interception of multiple ground-air missile weapon systems, U is adoptedLiThe method is not only related to the ith set of penetration resistant aircraft, but also related to various factors such as fire cooperative distribution principle, target channel number, reserve bomb quantity, interception precision, interception reaction time and the like of other sets of penetration resistant aircraft and air defense weapon systems. Therefore, the method introduces a fire distribution principle based on the nearest priority, and based on the principle, synthesizes factors such as the number of target channels, the number of loaded missiles, the number of reserve missiles, the interception time of each ground-air missile weapon system, the batch and the number of frames of the unmanned aerial vehicles for fire prevention, and the like to carry out simulation deduction on the fire prevention process of the unmanned aerial vehicles, so as to obtain the fire distribution mode of each ground-air missile weapon system at any moment of fire prevention attack, then obtains the mathematical expected value of the number of the remaining airplanes of each batch of unmanned aerial vehicles under fire prevention at the current moment by combining the interception precision of the ground-air missile weapon system, and finally obtains the corresponding average damage probability L by calculating the mathematical expected value of the remaining number of frames of each batch of unmanned aerial vehicles at the moment of fire prevention ending according toPAnd therefore, the assessment of fire interception threat of fire prevention is completed.
As mentioned above, in order to accurately describe the fire interception threat suffered by the penetration unmanned aerial vehicle under the complex countermeasure situation, the fire interception threat is defined as the average damage probability L when the penetration action is completedP(as shown in formula (1)). To calculate LPIn the embodiment of the present invention, the following distance closest priority power distribution rule is proposed (the above-described step S60 is explained):
(1) for different moments when the unmanned aerial vehicle breaks through the air defense weapon system to attack, when a single set of air defense aircraft is located in the intercepting range of a plurality of air defense weapon systems in the air defense airspace of the air defense track, the ground-air missile weapon system closest to the air defense aircraft is preferentially used for intercepting, and when the number of available target channels of the air missile weapon system is smaller than the number of airplanes to be attacked of the set of air defense aircraft (the number of airplanes to be attacked is the mathematical expected value of the rest number of frames of the set of air defense aircraft at the current moment), the ground-air missile weapon system next closest to the set of air defense aircraft is used for intercepting the rest of air defense aircraft to be attacked, and so on until all the available target channels of the air defense aircraft to be attacked or all the ground-air missiles are completely distributed.
(2) And for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a plurality of groups of air defense aircraft are positioned in the interception range of one air defense weapon system in the air defense airspace of the air defense track, the ground-to-air missile weapon system preferentially attacks the nearest group of air defense aircraft, when the number of the group of aircraft to be attacked is less than the number of available target channels of the ground-to-air missile weapon system, the rest target channels of the ground-to-air missile weapon system are used for hitting the next short-range group of air defense aircraft, and the rest is repeated until all the available target channels of all the air defense aircraft to be attacked or the ground-to-air missile weapons are completely distributed.
(3) For different moments when the unmanned aerial vehicle breaks through the air defense weapon system to attack, when a plurality of sets of air defense aircraft are located in the interception range of a plurality of air defense weapon systems in the air defense airspace of the air defense track, firstly, a pair of air defense aircraft and ground-air missile weapon systems which are closest to each other are searched in all the air defense aircraft and ground-air missile weapon systems, and a fire attack relation is established between the air defense aircraft and the ground-air missile weapon systems. On the basis, if the number of the to-be-attacked airplanes of the batch of penetration resistant airplanes is larger than the number of available target channels of the ground-to-air missile weapon system, judging that all the available target channels of the ground-to-air missile weapon system are used for attacking the batch of airplanes, simultaneously subtracting the number of the available target channels of the ground-to-air missile weapon system from the number of the to-be-attacked airplanes of the batch of penetration resistant airplanes, neglecting the ground-to-air missile weapon system, continuously searching a pair of penetration resistant airplanes and ground-to-air missile weapon systems which are next closest in distance between the rest ground-to-air missile weapon system and all the batches of penetration resistant airplanes, and further establishing a fire attack relationship between the surplus ground-to; on the contrary, if the number of the to-be-attacked aircraft of the set of penetration resistant aircraft is smaller than the number of the available target channels of the ground-to-air missile weapon system, all the to-be-attacked aircraft of the set of penetration resistant aircraft are judged to be attacked by the ground-to-air missile weapon system, the number of the penetration resistant aircraft is subtracted from the number of the available target channels of the ground-to-air missile weapon system, the set of penetration resistant aircraft is ignored, a pair of penetration resistant aircraft and ground-to-air missile weapon system with the next shortest distance is continuously searched between the rest penetration resistant aircraft and all the ground-to-air missile weapon systems, and a fire attack relation is established between the two systems. And circularly iterating the process until all the available target channels of the to-be-attacked aircraft or all the ground-to-air missile weapons are completely distributed.
The embodiment of the invention overcomes the defect that fire interception threats are difficult to accurately evaluate and analyze under the situation of cooperative defense burst of a plurality of batches of unmanned aerial vehicles and multi-system networking interception, and provides good support for the subsequent optimization of the unmanned aerial vehicle fleet defense burst routes.
In addition, referring to fig. 2, fig. 2 is a schematic diagram of a fire interception threat assessment apparatus for unmanned aerial vehicle fleet defense, where the apparatus includes:
a track setting unit 10, configured to receive a sudden flight path setting operation of the drone swarm;
it can be understood that the method for evaluating fire-preventive interception threat of an unmanned aerial vehicle cluster according to the embodiment of the present invention can represent a computer program, and the computer program is loaded in a computer device (corresponding to an evaluation device for fire-preventive interception threat of an unmanned aerial vehicle cluster);
it should be noted that the execution subject of the evaluation method of this embodiment is a computer device (i.e., the above evaluation apparatus), and the evaluation apparatus may receive the operation of the operator on the sudden defense track setting of the drone swarm;
in this embodiment, after the sudden flight path is set, the evaluation device may automatically calculate some processing steps of the unmanned aerial vehicle fleet in the sudden flight path process according to the parameters of the unmanned aerial vehicle fleet and the interception parameters of the air defense weapon system, and finally obtain the average damage probability of the unmanned aerial vehicle after the unmanned aerial vehicle fleet completes the sudden flight path
An unmanned aerial vehicle parameter setting unit 20, configured to determine a cluster number of the unmanned aerial vehicle cluster, an initial unmanned aerial vehicle rack number of each cluster of the unmanned aerial vehicle cluster, and a speed of the unmanned aerial vehicle cluster;
in a specific implementation, the evaluation device may respond to an initialization operation of a user, and receive a cluster number of the drone swarm, an initial drone rack number of the drone swarm of each batch, and a speed of the drone swarm, which are input by the user.
It can be understood that each time a user carries out unmanned aerial vehicle fire-fighting interception threat assessment, initialization operation needs to be carried out on parameters of an unmanned aerial vehicle fire-fighting cluster and ground-air missile weapon parameters of an air defense weapon system, so that the exercise can be conveniently executed;
for m batches of unmanned aerial vehicle clusters appearing in one-time defense outburst and the number of unmanned racks of each batch of unmanned aerial vehicle clusters, the parameters are counted by an operator (namely a user) in advance, and then the user manually inputs the parameters of the unmanned aerial vehicles into an evaluation device;
the flight speeds of the unmanned aerial vehicle clusters in the same batch are the same, and the flight speeds of the unmanned aerial vehicle clusters in different batches may be the same or different.
The air defense weapon parameter setting unit 30 is configured to receive interception parameters of each air defense weapon system, where the interception parameters at least include a deployment position, an interception range, an interception precision, a target channel number, a loading number, and a reserve number;
it should be noted that the interception parameters of the air defense weapon system are determined by the hardware of the air defense weapon system, and the interception parameters of the air defense weapon systems in different position areas may be the same or different; for example, the interception accuracy of an air defense weapon system is related to the technical performance of the air defense weapon system, and the interception accuracy of an advanced air defense weapon system may be higher than that of a lagged air defense weapon system.
In a specific implementation, the evaluation device respectively receives the interception parameters of each air defense weapon system input by the user in response to the initialization operation of the user.
The relative distance calculation unit 40 is configured to traverse each batch of unmanned aerial vehicle cluster, calculate, in real time, a relative distance between the traversed target unmanned aerial vehicle cluster and the air defense weapon systems at different positions, and use the air defense weapon system with the shortest relative distance to the target unmanned aerial vehicle cluster as the target air defense weapon system;
it will be appreciated that for each batch of drone swarm, the present embodiment performs the following operations:
determining a traversed target unmanned aerial vehicle cluster;
calculating a longitude coordinate, a latitude coordinate and an altitude coordinate of the target unmanned aerial vehicle cluster at the moment t when flying along the penetration track according to the speed of the target unmanned aerial vehicle cluster;
determining the relative distance between the target unmanned aerial vehicle cluster and the air defense weapon systems at different positions at the time t based on the longitude coordinate, the latitude coordinate and the altitude coordinate at the time t;
taking the air defense weapon system with the shortest relative distance (closest relative distance) with the target unmanned aerial vehicle cluster as a target air defense weapon system;
an intercept time calculation unit 50, configured to calculate an intercept time of the target air defense weapon system to the target drone cluster based on a speed of the target drone cluster and a relative distance between the target drone cluster and the target air defense weapon system;
in a specific implementation, for each batch of unmanned aerial vehicle cluster, the calculation method of the interception time of the target unmanned aerial vehicle cluster by the target air defense weapon system is as follows: the relative distance between the target drone swarm and the target air defense weapon system is divided by the speed of the target drone swarm.
The fire power distribution unit 60 is configured to distribute fire power of each air defense weapon system at different times according to a preset fire power distribution principle based on the interception parameters of each air defense weapon system, the interception time of the target unmanned aerial vehicle cluster, the cluster batch number and the unmanned aerial vehicle rack number, so as to obtain a fire power attack mapping relationship between the unmanned aerial vehicle cluster and the air defense weapon system at different times;
the remaining aircraft calculating unit 70 is configured to calculate, according to the mapping relationship of fire attack between the unmanned aerial vehicle fleet and the air defense weapon system at different times, the number of remaining aircraft in fire interception of each batch of unmanned aerial vehicle fleet at the current time in real time by combining the interception accuracy of the air defense weapon system;
the evaluation unit 80 is configured to send the number of remaining airplanes when the drone swarm flies to the sudden prevention flight path end point into a preset evaluation model for calculation, so as to obtain an average drone damage probability of the drone swarm completing the sudden prevention flight path;
wherein the preset evaluation model is characterized by the following formula (1):
wherein L isPRepresenting the average damage probability of the unmanned aerial vehicle after the target unmanned aerial vehicle cluster finishes the penetration track;
m represents the number of the cluster batches of the unmanned aerial vehicle cluster, wherein the number of the unmanned aerial vehicles of the ith batch of target unmanned aerial vehicle cluster is Ui；
ULiAnd the mathematical expected value represents the number of the remaining airplanes when the ith group of target unmanned aerial vehicles complete the penetration under the fire interception of the air defense weapon system.
The evaluation device has the advantages that: the defects that fire interception threats are difficult to accurately evaluate and analyze under the situation of cooperative defense burst of a plurality of batches of unmanned aerial vehicles and multi-system networking interception in the prior art are overcome, and good support is provided for the subsequent optimization of a defense burst route of an unmanned aerial vehicle cluster;
by using the evaluation device provided by the invention, the condition that the unmanned aerial vehicle is intercepted can be accurately analyzed under the networking interception condition of the air defense system, and a good support is provided for the subsequent sudden prevention exercise of the unmanned aerial vehicle or the prevention of the sudden attack exercise of the unmanned aerial vehicle.
It should be noted that, for further explanation of the above embodiments of the evaluation method and the evaluation apparatus, the present invention illustrates a simulation example,
simulation example:
based on the principle of closest priority fire distribution, the process for evaluating the fire interception threat of the simulation example of the invention consists of two parts, namely fire situation initialization and fire action simulation deduction.
(1) Sudden defense situation initialization
The part is mainly used for carrying out initialization setting on states of a penetration cluster and an air-ground missile weapon system according to equipment deployment of both penetration countermeasures.
a. Surge cluster initialization
According to the sudden prevention action scheme, the number m of batches of sudden prevention unmanned aerial vehicles and the number U of frames of each batch of sudden prevention unmanned aerial vehiclesiAnd sudden flight path (L)Pi(t),APi(t),HPi(t)) initializing and making the ith group of the aircraft for emergency protection remain ULiIs equal to UiI is 1, …, m. Here LPi(t)、APi(t)、HPiAnd (t) longitude, latitude and altitude coordinates of the ith group of the penetration unmanned aerial vehicle at the moment t when flying along a preset penetration track are obtained by recursion of the flying speed of the unmanned aerial vehicle.
b. Ground-to-air missile weapon system initialization
According to the air defense deployment of the penetration target, the number n of ground-air missile weapon systems in the penetration area and the target channel number C of each ground-air missile weapon systemjThe maximum loading number of the launching device is MFjThe remaining number of shots loaded by the launching device is MLFjThe total reserve ammunition number of the system is MCjThe number of the remaining reserve shots in the system is MLCjSystem kill probability PjDeployment location (L)Mj,AMj,hMj) And killing range phijPerforming an initialization assignment, wherein MLFjIs taken as MFj，MLCjIs taken as MCjJ is 1, … n. On the basis, let t for the jth ground-to-air missile system in the penetration areaPj(h) Representing the residual preparation time required for the h-th target channel to initiate next round of attack, and initializing tPj(h) Value equal to 0, h-1, … CjNamely, each target channel of the ground-air missile weapon system is in an idle available state at the initial moment;
it should be noted that the system killing probability P is described abovejRepresenting the interception precision, the probability of destruction, P, of an air defense weapon systemjDetermined by the air weapon system hardware.
(2) Simulation deduction of penetration
The average damage probability of the penetration machine group when the penetration action is completed is obtained mainly through simulation deduction, so that the accurate assessment of the penetration firepower interception threat is realized, and the support is provided for the subsequent penetration track optimization adjustment. In this example, after the sudden flight path is set, the evaluation device may automatically calculate some processing steps of the unmanned aerial vehicle fleet in the sudden flight path process according to the parameters of the unmanned aerial vehicle fleet and the interception parameters of the air defense weapon system, and finally obtain the average damage probability of the unmanned aerial vehicle after the unmanned aerial vehicle fleet completes the sudden flight path:
and recording the initial value of the simulation deduction iteration number l as 0, wherein the time step of the simulation deduction is delta t, and the value of the delta t is 1/5-1/10 of the target interception and tracking time of the ground-air missile system. Based on this, the specific process of simulation deduction is as follows.
Step a, updating the spatial position of the penetration aircraft
And (3) obtaining the space position coordinates (L) of each set of penetration prevention airplanes at the current moment according to the preset penetration prevention route with the current moment t being equal to L delta tPi(lΔt),APi(lΔt),HPi(l Δ t)), i is 1, … m. Meanwhile, the remaining preparation time of the next round of attack of all target channels of the ground-air missile weapon system is updated according to the formula (2)
tPj(h)＝max(tPj(h)-Δt,0) (2)
Wherein j is 1, …, n, h is 1, …, Cj. After the treatment is finished, the step b is carried out to construct firepower interception distance mark momentAnd (5) arraying.
B, constructing a firepower interception distance mark matrix
Constructing an m multiplied by n dimensional firepower interception distance mark matrix F according to the space position information of the penetration aircraft at the current moment, wherein the (i, j) th element F in the matrix Fi,jIs taken as
In the formula ri,jAnd the distance from the ith batch of unmanned aerial vehicles to the jth ground-air missile system at the current moment is shown. And c, after the treatment is finished, the step is shifted to the step c to set the interception fire power density.
Step c. intercept fire power density setting
The interception fire power density refers to the number of missiles which are simultaneously launched to a single target when the air defense system intercepts the target. The greater the fire density, the higher the probability of killing, but the greater the number of missiles required.
According to the principle of improving the fire density as much as possible on the premise of full coverage of the target, for the jth (j is 1, …, N) ground-air missile system, the fire density N is intercepted in the simulation processAjThe method comprises the following steps:
in the formula (4)
Which represents a rounding-down operation, the rounding-down operation,
represents the maximum fire density that the jth ground-air missile system can adopt,
represents the sum of the penetration planes in the killing range of the jth ground-air missile system at the current moment, and the value of the sum can be represented by the following formula
And (d) after the steps are finished, the step is shifted to the step d to construct a firepower attack map.
Fire attack mapping
And searching the minimum non-zero element from the fire interception distance mark matrix F according to the closest priority fire distribution principle. If the smallest non-zero element in F is located at the second
Line and first
Column, the first one can be determined according to the closest priority fire power distribution rule
The primary attack target of the part-ground-air missile system is the first
Batching unmanned aerial vehicles, establishing firepower attack mapping
While simultaneously applying a second of the matrices F
Line and first
Setting the column element to 0, and proceeding to step e to count
And the number of current available target channels of the part-ground-to-air missile system.
If all elements in the matrix F are equal to 0, the fact that all possible fire attack analysis is completed at the current moment under the principle of closest priority fire distribution is indicated, and the step i is directly carried out.
Available target channel statistics
Statistics of
Aerial missile system
Remaining preparation time of next round of attack in each target channel
Target number of channels equal to 0, denoted Ncr. If N is presentcrWhen 0, it indicates the first
And e, if the local air missile system does not have an idle available target channel, returning to the step d to reconstruct the firepower attack mapping. If N is presentcrIf > 0, it indicates the first
Partially airborne missile system presence NcrOne free target channel is available for the second
And f, turning to the step f to analyze the damage condition of the penetration aircraft in the attack.
F, analyzing the attack loss of the penetration plane
According to the first
Number of remaining aircraft frames
First, the
Root of herbaceous plantNumber N of idle available target channels of air-missile systemcrThe remaining number of shots loaded by the launching device
The relative magnitude relationship between the three is divided into the following 5 cases to the current time
The batched penetration plane is on
Analyzing the residual number of the racks under the fire interception of the aerial missile system:
case 1: when in use
And is
Time of flight
First, the
Partially airborne missile system utilization
A target channel pair
The unmanned aerial vehicle carries out firepower interception, and firepower interception in the current round is carried out
The expected remaining number of the batched penetration aircraft is updated to
At the same time, first
Residual charge of partially guided system
Become into
Case 2: when in use
And is
Time of flight
First, the
Partially airborne missile system utilization NcrA target channel pair
The unmanned aerial vehicle carries out firepower interception, and firepower interception in the current round is carried out
The expected remaining number of the batched penetration aircraft is updated to
At the same time, first
Residual charge of partially guided system
Is updated to
Case 3: when in use
And is
Time of flight
First, the
Partially airborne missile system utilization
A target channel pair
The unmanned aerial vehicle is batched to implement single firepower interception, and the firepower is intercepted in the current round
The expected remaining number of the batched penetration aircraft is updated to
At the same time, first
Residual charge of partially guided system
Is updated to 0.
Case 4: when in use
And is
Time of flight
First, the
Partially airborne missile system utilization NcrA target channel, to
The unmanned aerial vehicle carries out firepower interception, and firepower interception in the current round is carried out
The expected remaining number of the batched penetration aircraft is updated to
At the same time, first
Residual charge of partially guided system
Is updated to
Case 5: when in use
And is
Time of flight
First, the
Partially airborne missile system utilization
A target channel pair
Batched unmanned aerial vehicle for implementing single fire interceptionAfter the wheel fire is intercepted, the
The expected remaining number of the batched penetration aircraft is updated to
At the same time, first
Residual charge of partially guided system
Is updated to 0.
On the basis of completing the analysis, the step h is carried out
And updating the state of each target channel of the local guidance system.
Step h. target channel status update
If after the attack
If the value is more than 0, assigning the remaining preparation time of the next round of attack of all target channels for the current round of attack as
In the formula, tsfThe time for intercepting and launching the target refers to the time for the ground guidance system to finish intercepting and tracking the target and control missile launching; t is tsbThe guided missile guidance and interception time refers to the time for the guided missile to fly to a target under the control of a guidance system and meet the target to complete system interception; t is tzyIndicating the fire transfer time of the ground lead weapon system.
If after the attack
Equal to 0, then it is necessary to
Partially guiding the system for refilling, after filling
Value is updated to
After refilling, the
The remaining reserve ammunition number of the partially guided system is updated to
After the attack, the first time
Assigning the next round of attack remaining preparation time of all targets of the partially guided system as
tztIndicating the missile loading time of the ground-borne weapon system.
And on the basis of completing the analysis, the step d is carried out again to construct a new fire attack mapping until all elements in the matrix F are equal to 0, namely all possible attacks at the current moment are completed.
Step i. penetration process judgment
If (L)Pi(lΔt),APi(lΔt),HPi(l Δ t)) is the sudden flight path end point, the simulation deduction is ended, andthe number U of the expected residual frames of each batch of the penetration prevention unmanned aerial vehicle at the current momentLiAnd (i-1, … m) substituting the formula (1) to obtain a final firepower interception threat assessment result and outputting the result.
If (L)Pi(lΔt),APi(lΔt),HPi(l Δ t)) is not the anti-collision track end point, let l be l +1, and go to step a to perform simulation deduction at the next time.
In addition, the present invention further provides a storage medium, where the storage medium is a computer-readable storage medium, and the storage medium stores a computer program, where the computer program is configured to execute the steps of the fire interception threat assessment method for unmanned aerial vehicle fleet defense.
It should be noted that, in this document, 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 like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (7)
1. A fire interception threat assessment method for unmanned aerial vehicle cluster defense is characterized by comprising the following steps:
receiving a sudden defense track setting operation of an unmanned aerial vehicle cluster;
determining the cluster number of the unmanned aerial vehicle cluster, the initial unmanned machine frame number of each batch of the unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster;
receiving a deployment setup operation for an air defense weapons system;
determining interception performance parameters of an air defense weapon system, wherein the interception performance parameters at least comprise a deployment position, an interception range, interception precision, a target channel number, an intercepted projectile flying speed, a loading quantity and a standby projectile quantity;
traversing each batch of unmanned aerial vehicle cluster, calculating the relative distance between the traversed target unmanned aerial vehicle cluster and the air defense weapon systems at different positions in real time, and taking the air defense weapon system with the shortest relative distance with the target unmanned aerial vehicle cluster as the target air defense weapon system;
calculating the interception time of the target air defense weapon system to the target unmanned aerial vehicle cluster based on the speed of the target unmanned aerial vehicle cluster and the relative distance between the target unmanned aerial vehicle cluster and the target air defense weapon system;
distributing firepower of each air defense weapon system at different moments according to a preset firepower distribution principle based on the interception parameters of each air defense weapon system, the interception time of the target unmanned aerial vehicle cluster, the cluster batch number and the unmanned rack number to obtain firepower attack mapping relations between the unmanned aerial vehicle cluster and the air defense weapon systems at different moments;
respectively calculating the number of remaining airplanes of each batch of unmanned aerial vehicle cluster at the current moment under fire interception according to the fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments and by combining the interception precision of the air defense weapon system in real time; sending the number of the remaining airplanes when the unmanned aerial vehicle cluster flies to the sudden prevention flight path end point into a preset evaluation model for calculation to obtain the average unmanned aerial vehicle damage probability of the unmanned aerial vehicle cluster finishing the sudden prevention flight path;
wherein the preset evaluation model is characterized by the following formula (1):
wherein L isPRepresenting the average damage probability of the unmanned aerial vehicle after the target unmanned aerial vehicle cluster finishes the penetration track;
m represents the number of the cluster batches of the unmanned aerial vehicle cluster, wherein the number of the unmanned aerial vehicles of the ith batch of target unmanned aerial vehicle cluster is Ui；
ULiAnd the mathematical expected value represents the number of the remaining airplanes when the ith group of target unmanned aerial vehicles complete the penetration under the fire interception of the air defense weapon system.
2. The method of claim 1, wherein the preset fire distribution rule represents three ways:
the first method is as follows: and for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a single set of air defense aircraft is in the interception range of a plurality of air defense weapon systems in the air defense airspace of the air defense track, using the air defense weapon system closest to the air defense aircraft to carry out interception, and when the number of available target channels of the air defense weapon system is smaller than the number of airplanes to be attacked of the set of air defense aircraft, carrying out interception on the remaining airplanes to be attacked by the next-nearest air defense weapon system to the set of air defense aircraft until all the available target channels of the airplanes to be attacked or all the ground-air missile weapons are completely distributed, wherein the number of airplanes to be attacked refers to the mathematical expected value of the remaining number of the sets of air defense aircraft at the current moment.
The second method comprises the following steps: and for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a plurality of groups of air defense aircraft exist in the air defense airspace of the air defense track and are positioned in the interception range of one air defense weapon system, the air defense weapon system preferentially attacks the nearest group of air defense aircraft, and when the number of the group of aircraft to be attacked is less than the number of the target channels available for the air defense weapon system, the rest target channels of the air defense weapon system are used for striking the next-close-range group of air defense aircraft until all the available target channels of all the air defense aircraft or ground-air missile weapons to be attacked are completely distributed.
The third method comprises the following steps: for different moments when the unmanned aerial vehicle breaks through the air defense weapon system, when a plurality of sets of air defense aircraft are positioned in the interception range of a plurality of air defense weapon systems in the air defense airspace of the air defense track, firstly, a pair of air defense aircraft and air defense weapon systems which are closest to each other are searched in all the air defense aircraft and air defense weapon systems, and a fire attack relation is established between the air defense aircraft and the air defense weapon systems; on the basis, if the number of the airplanes to be attacked of the batch of the penetration prevention airplanes is larger than the number of the available target channels of the air defense weapon system, all the available target channels of the air defense weapon system are judged to be used for attacking the batch of the airplanes, meanwhile, the number of the available target channels of the air defense weapon system is subtracted from the number of the airplanes to be attacked of the batch of the penetration prevention airplanes, the air defense weapon system is ignored, a pair of penetration prevention airplanes and air defense weapon systems with the next shortest distance is continuously searched between the rest air defense weapon systems and all the batches of the penetration prevention airplanes, and further, a fire attack relation is established between the rest air defense airplane systems and the air defense weapons; or if the number of the airplanes to be attacked of the batch of the penetration prevention airplanes is smaller than the number of available target channels of the air defense weapon system, judging that all the airplanes to be attacked of the batch of the penetration prevention airplanes are attacked by the air defense weapon system, simultaneously subtracting the number of the batch of the penetration prevention airplanes from the number of the available target channels of the air defense weapon system, neglecting the batch of the penetration prevention airplanes, continuously searching a pair of penetration prevention airplanes and air defense weapon systems with the next shortest distance between the rest of the penetration prevention airplanes and all the air defense weapon systems, and further establishing a fire attack relationship between the rest of the penetration prevention airplanes and the air defense weapon systems; and circularly iterating the process of the third condition until all the available target channels of the airplanes to be attacked or all the ground-to-air missile weapons are completely distributed.
3. The method according to claim 1, wherein the step of determining the cluster number of the drone cluster, the initial drone rack number of the drone cluster of each batch, and the speed of the drone cluster specifically comprises:
and responding to the initialization operation of a user, and receiving the cluster number of the unmanned aerial vehicle cluster, the initial unmanned aerial vehicle frame number of each batch of the unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster, which are input by the user.
4. The method of claim 1, wherein the interception parameters of the air defense weapon system are determined by the air defense weapon system hardware.
5. The method of claim 1, wherein the step of calculating in real time the relative distances between the traversed target drone swarm and the different-location air defense weapon systems comprises:
determining a traversed target unmanned aerial vehicle cluster;
calculating a longitude coordinate, a latitude coordinate and an altitude coordinate of the target unmanned aerial vehicle cluster at the moment t when flying along the penetration track according to the speed of the target unmanned aerial vehicle cluster;
and determining the relative distance between the target unmanned aerial vehicle cluster and the air defense weapon systems at different positions at the time t based on the longitude coordinate, the latitude coordinate and the altitude coordinate at the time t.
6. A fire interception threat assessment device for unmanned aerial vehicle cluster defense, characterized in that the device comprises:
the flight path setting unit is used for receiving the sudden defense flight path setting operation of the unmanned aerial vehicle cluster;
the unmanned aerial vehicle parameter setting unit is used for determining the cluster number of the unmanned aerial vehicle cluster, the initial unmanned machine frame number of each batch of unmanned aerial vehicle cluster and the speed of the unmanned aerial vehicle cluster;
the air defense weapon parameter setting unit is used for receiving interception parameters of each air defense weapon system, wherein the interception parameters at least comprise deployment positions, interception ranges, interception precision, target channel numbers, loading numbers and standby numbers;
the relative distance calculation unit is used for traversing each batch of unmanned aerial vehicle cluster, calculating the relative distance between the traversed target unmanned aerial vehicle cluster and the air defense weapon systems at different positions in real time, and taking the air defense weapon system with the shortest relative distance with the target unmanned aerial vehicle cluster as the target air defense weapon system;
the intercepting time calculation unit is used for calculating the intercepting time of the target air defense weapon system to the target unmanned aerial vehicle cluster based on the speed of the target unmanned aerial vehicle cluster and the relative distance between the target unmanned aerial vehicle cluster and the target air defense weapon system;
the fire distribution unit is used for distributing fire of each air defense weapon system at different moments according to a preset fire distribution principle based on the interception parameters of each air defense weapon system, the interception time of the target unmanned aerial vehicle cluster, the cluster batch number and the unmanned rack number to obtain a fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments;
the remaining airplane calculation unit is used for calculating the number of remaining airplanes of each batch of unmanned aerial vehicle cluster at the current moment under fire interception respectively according to the fire attack mapping relation between the unmanned aerial vehicle cluster and the air defense weapon system at different moments in real time and by combining the interception precision of the air defense weapon system;
the assessment unit is used for sending the number of remaining airplanes into a preset assessment model for calculation when the unmanned aerial vehicle cluster flies to the sudden prevention flight path end point, and obtaining the average unmanned aerial vehicle damage probability of the unmanned aerial vehicle cluster finishing the sudden prevention flight path;
wherein the preset evaluation model is characterized by the following formula (1):
wherein L isPRepresenting the average damage probability of the unmanned aerial vehicle after the target unmanned aerial vehicle cluster finishes the penetration track;
m represents the number of the cluster batches of the unmanned aerial vehicle cluster, wherein the number of the unmanned aerial vehicles of the ith batch of target unmanned aerial vehicle cluster is Ui；
ULiAnd the mathematical expected value represents the number of the remaining airplanes when the ith group of target unmanned aerial vehicles complete the penetration under the fire interception of the air defense weapon system.
7. A storage medium, wherein the storage medium is a computer-readable storage medium, and the storage medium stores a computer program for executing the steps of the fire interception threat assessment method for drone swarm defense according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110084994.XA CN112764429A (en) | 2021-01-22 | 2021-01-22 | Fire interception threat assessment method and device for unmanned aerial vehicle cluster defense |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110084994.XA CN112764429A (en) | 2021-01-22 | 2021-01-22 | Fire interception threat assessment method and device for unmanned aerial vehicle cluster defense |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112764429A true CN112764429A (en) | 2021-05-07 |
Family
ID=75702579
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110084994.XA Pending CN112764429A (en) | 2021-01-22 | 2021-01-22 | Fire interception threat assessment method and device for unmanned aerial vehicle cluster defense |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112764429A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113325876A (en) * | 2021-06-21 | 2021-08-31 | 四川大学 | Unmanned aerial vehicle induced penetration strategy |
| CN113703479B (en) * | 2021-08-26 | 2022-05-17 | 中国人民解放军国防科技大学 | Weapon configuration method and system based on high-density value and large depth |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160097621A1 (en) * | 2014-10-06 | 2016-04-07 | The Charles Stark Draper Laboratory, Inc. | Multi-hypothesis fire control and guidance |
| CN110782062A (en) * | 2019-03-07 | 2020-02-11 | 北京航空航天大学 | Many-to-many packet interception target distribution method and system for air defense system |
| CN111046343A (en) * | 2019-12-31 | 2020-04-21 | 中国人民解放军海军大连舰艇学院 | Method for determining horizontal distance of ship-air missile weapons based on minimum demand damage target probability |
-
2021
- 2021-01-22 CN CN202110084994.XA patent/CN112764429A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160097621A1 (en) * | 2014-10-06 | 2016-04-07 | The Charles Stark Draper Laboratory, Inc. | Multi-hypothesis fire control and guidance |
| CN110782062A (en) * | 2019-03-07 | 2020-02-11 | 北京航空航天大学 | Many-to-many packet interception target distribution method and system for air defense system |
| CN111046343A (en) * | 2019-12-31 | 2020-04-21 | 中国人民解放军海军大连舰艇学院 | Method for determining horizontal distance of ship-air missile weapons based on minimum demand damage target probability |
Non-Patent Citations (4)
| Title |
|---|
| K.HARIHARAN: "A PERSPECTIVE MATHEMATICAL MODEL FOR WEAPON TO TARGET ALLOCATION PROBLEM USING RANDOMIZED TECHNIQUE", 《JOURNAL OF THEORETICAL AND APPLIED INFORMATION TECHNOLOGY》, 30 September 2013 (2013-09-30) * |
| 刘剑豪: "无人机蜂群对未来战争的影响及其对应措施分析", 《飞航导弹》, 10 September 2020 (2020-09-10) * |
| 刘己斌: "防空兵抗击无人机蜂群能力分析与评估", 《军事运筹与系统工程》, 31 December 2019 (2019-12-31) * |
| 张永芳;张安;张莉;汤志荔;史志富;: "防区外发射飞机武器系统突防效能分析", 火力与指挥控制, no. 10, 15 October 2007 (2007-10-15) * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113325876A (en) * | 2021-06-21 | 2021-08-31 | 四川大学 | Unmanned aerial vehicle induced penetration strategy |
| CN113703479B (en) * | 2021-08-26 | 2022-05-17 | 中国人民解放军国防科技大学 | Weapon configuration method and system based on high-density value and large depth |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11669110B2 (en) | Control system based on multi-unmanned aerial vehicle cooperative strategic confrontation | |
| CN111880563A (en) | Multi-unmanned aerial vehicle task decision method based on MADDPG | |
| CN109658770B (en) | Air condition simulation system for civil air defense training | |
| CN112764429A (en) | Fire interception threat assessment method and device for unmanned aerial vehicle cluster defense | |
| EP1901144B1 (en) | Arrangement and method for generating input information to a simulation device | |
| CN113791634A (en) | Multi-aircraft air combat decision method based on multi-agent reinforcement learning | |
| CN112580221B (en) | Attack and defense confrontation simulation system | |
| CN109857145B (en) | Extended-range type intercepting missile prediction guidance method based on iterative prediction hit point | |
| CN114239728A (en) | Multi-domain battlefield situation assessment and threat ranking method | |
| CN110928329A (en) | Multi-aircraft track planning method based on deep Q learning algorithm | |
| CN111766901B (en) | Multi-unmanned aerial vehicle cooperative target distribution attack method | |
| Wang et al. | Multiple UAVs routes planning based on particle swarm optimization algorithm | |
| CN112308422A (en) | Task planning and solving simulation system and method for remote aerial support carrier | |
| CN111859541A (en) | PMADDPG multi-unmanned aerial vehicle task decision method based on transfer learning improvement | |
| Fu et al. | The overview for UAV air-combat decision method | |
| CN110377054B (en) | Unmanned aerial vehicle cluster control system and method based on airborne platform | |
| CN115951695A (en) | Dynamic tactical control domain resolving method based on three-party game in air combat simulation environment | |
| CN108089456A (en) | A kind of aircraft Information System mathematics simulation system based on Attack Defence | |
| CN114357742A (en) | Multi-machine air assault cooperative behavior simulation method under interference machine coordination | |
| Wyatt | The DARPA/air force unmanned combat air vehicle (UCAV) program | |
| GB2522110A (en) | System integration | |
| CN113435005B (en) | Automatic airplane design parameter sensitivity analysis and optimization method | |
| CN112818496B (en) | Anti-ground-defense strategy based on ant colony algorithm | |
| RU2690234C1 (en) | Method of automatic group target allocation of fighters based on priority of targets | |
| Fedunov et al. | The real-time approach to solving the problems for the multicriterial choice of alternatives in the knowledge bases of onboard real-time advisory expert systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |