CN111260229B - Combat resource scheduling method for incoming targets - Google Patents
Combat resource scheduling method for incoming targets Download PDFInfo
- Publication number
- CN111260229B CN111260229B CN202010060839.XA CN202010060839A CN111260229B CN 111260229 B CN111260229 B CN 111260229B CN 202010060839 A CN202010060839 A CN 202010060839A CN 111260229 B CN111260229 B CN 111260229B
- Authority
- CN
- China
- Prior art keywords
- target
- area
- incoming
- foot
- attack
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Aiming, Guidance, Guns With A Light Source, Armor, Camouflage, And Targets (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a combat resource scheduling method aiming at an attack target, which comprises the following steps: s1, initializing parameters of at least one incoming target; s2, dividing the defense area into a plurality of foot-drop point areas, and sequentially selecting the foot-drop point areas; s3, acquiring the threat degree of an attack target in the selected foothold area based on the parameters; s4, judging whether an attack target in the foot drop point area meets constraint conditions or not based on the threat degree; and S5, allocating defense weapons for the attack targets meeting the constraint conditions to realize the battle resource scheduling. The invention realizes the fairness scheduling of combat resources aiming at defense positions and optimizes firepower distribution by selecting the foothold areas and judging the threat degree of the attack targets in the foothold areas, and the scheduling method is simple and is beneficial to engineering application.
Description
Technical Field
The invention relates to the field of target tracking, in particular to a combat resource scheduling method for an incoming target.
Background
The battlefield situation is changed instantly and constantly under the informatization condition, the number and the types of the targets attacked are increased rapidly, and the reasonable and effective allocation of fighting resources is the key for effectively defending the success of the battle field of one party. The existing combat resource scheduling algorithm mainly solves two problems: on one hand, the optimal fire distribution problem of a single target is solved, and on the other hand, the optimal fire distribution problem of complex group target interception is solved, but the fire distribution is uneven due to the scheduling method, so that the trend of a war office is influenced.
Therefore, it is necessary to provide a method for scheduling combat resources for an attack target.
Disclosure of Invention
The invention aims to provide a method for scheduling combat resources for an attack target, which aims to solve at least one of the problems in the prior art;
in order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a method for scheduling combat resources for an attack target, which comprises the following steps:
s1, initializing parameters of at least one incoming target;
s2, dividing the defense area into a plurality of foot-drop point areas, and sequentially selecting the foot-drop point areas;
s3, acquiring the threat degree of the attack target in the selected foothold area based on the parameters;
s4, judging whether an attack target in the foot drop point area meets constraint conditions or not based on the threat degree;
and S5, allocating defense weapons for the attack targets meeting the constraint conditions to realize the battle resource scheduling.
Optionally, the parameter target of the incoming target i The format of (A) is:
target i ＝{target i _deadline,target i _address,target i _ID}；
wherein target i "deadline" is the latest intercept time, target, of the incoming target i i The _ address is the landing point information of the incoming target i, target i ID is the threat of i on the incoming target.
Optionally, the foothold information is obtained by using a longge stota one-step extrapolation algorithm.
Optionally, the threat level target of the incoming target i i The formula for calculating _ ID is:
target i _ID＝1/(utarget i _deadline-ctime)；
wherein ctime is the current time.
Optionally, the sequentially selecting the landing foot point areas includes:
setting the initial value of the difference counter of each landing point region, wherein the initial value of the difference counter of the kth landing point region is theta k ；
And sequentially selecting the landing point areas according to the initial value of the difference counter.
Optionally, the sequentially selecting the landing foot point areas includes:
after the foot point area is selected, adjusting the difference counter value D theta of the foot point area k ：Dθ k ＝1-θ k /Θ k ；
Wherein, theta k Is the weight of the kth foothold area.
Optionally, the constraint condition is: target i _deadline-ctime≥lasttime；
Wherein ctime is the current moment, and lasttime is the time required for interception.
The invention has the following beneficial effects:
the invention realizes the fairness scheduling of combat resources aiming at defense positions and optimizes firepower distribution by selecting the foothold areas and judging the threat degree of the attack targets in the foothold areas, and the scheduling method is simple and is beneficial to engineering application.
Drawings
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Fig. 1 shows a flowchart of the battle resource scheduling method shown in this embodiment.
Detailed Description
In order to more clearly illustrate the invention, the invention is further described below with reference to preferred embodiments and the accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. It is to be understood by persons skilled in the art that the following detailed description is intended to be illustrative and not restrictive, and is not intended to limit the scope of the invention.
As shown in fig. 1, an embodiment of the present invention discloses a method for scheduling combat resources for an attack target, including:
s1, initializing parameters of at least one incoming target;
s2, dividing the defense area into a plurality of foot-drop point areas, and sequentially selecting the foot-drop point areas;
s3, acquiring the threat degree of an attack target in the selected foothold area based on the parameters;
s4, judging whether the attacking target meets constraint conditions or not based on the threat degree;
and S5, allocating defense weapons for the attack targets meeting the constraint conditions to realize the battle resource scheduling.
Because the battle resource scheduling method in the prior art is only analyzed from the perspective of battle resource allocation and attack capacity of an attack target, but the fairness of field defense is not researched, and the failure of a war bureau is easily caused by uneven distribution of defense fire power, the invention realizes the fairness scheduling of the battle resources for the defense field and optimizes the fire power allocation by selecting the foothold area of the defense area and judging the threat degree of the attack target in the foothold area, and the scheduling method is simple and is beneficial to engineering application.
In some optional implementations of this embodiment, the target parameter of the incoming target i Is in the format of target i ＝{target i _deadline,target i _address,target i _ID}；
Wherein target i "deadline" is the latest intercept time, target, of the incoming target i i The _ address is the landing point information of the incoming target i, target i And _IDis the threat degree of i of the incoming target, and i is more than or equal to 1 and less than or equal to M.
In this embodiment, taking the number of the incoming targets as M (M is greater than or equal to 1), intercepting a single incoming target in sequence as an example, after the incoming targets are acquired in sequence, the incoming targets are represented in a uniform parameter format, that is, the 1 st incoming target 1 Can be represented as target 1 ＝{target 1 _deadline,target 1 _address,target 1 ID }. After the data is expressed in a uniform parameter format, the incoming target i can be effectively and quickly called and selected.
In some optional implementations of this embodiment, the foothold information is obtained using a longge stota one-step extrapolation algorithm. The Runge Kuta one-step extrapolation algorithm is a high-precision single-step algorithm widely applied to engineering, is high in algorithm precision, and can obtain high-precision foot drop point information.
In some optional implementations of this embodiment, the threat level target of the incoming target i i The formula for calculating _ ID is:
target i _ID＝1/(target i _deadline-ctime)；
and ctime is the current moment.
If the threat degree of the incoming target i is negative, the incoming target is out of the selection range.
In some optional implementations of this embodiment, the sequentially selecting the landing point regions in S2 includes:
setting the initial value of the difference counter of each landing point region, wherein the initial value of the difference counter of the kth landing point region is theta k ；
And sequentially selecting the foot point areas according to the initial value of the difference counter.
In a specific example, the defense area is divided into N (N is more than or equal to 1 and less than or equal to M) foot-drop point areas, and the division of the foot-drop point areas can be selected by a user, can be divided according to the terrain of the defense area, and can be randomly divided according to the setting.
After dividing the defense area into a plurality of foot landing areas, setting the initial value of the difference counter of each foot landing area, wherein the initial value of the difference counter of the kth foot landing area in the N foot landing areas is set to be theta k (ii) a And sequentially selecting the landing point areas from the order of magnitude according to the initial value of the difference counter. In one specific example, the drop point region may also be selected according to the WRR algorithm, with the drop point region having a high difference counter value being preferred.
In some optional implementations of this embodiment, after the landing point region is selected, the difference counter value D θ of the landing point region is adjusted k ：Dθ k ＝1-θ k /Θ k ；
Wherein, theta k Is the weight of the kth foothold area.
In some optional implementations of this embodiment, the determining whether an attack target in the foothold area meets the constraint condition is: target i _deadline-ctime≥lasttime；
Wherein ctime is the current time, and lasttime is the time required for interception.
When the attack target in the foothold area meets the constraint condition, it proves that defense weapons need to be distributed to the attack target to realize the battle resource scheduling.
When the attack target in the foothold area does not meet the constraint condition, the defense weapon does not need to be distributed to the attack target.
In another specific example, there is a case that at least one incoming target appears in the same footdrop area, in this case, whether the incoming target meets the constraint condition is sequentially judged according to the threat degree of the incoming target in the footdrop area until all the incoming targets in the current footdrop area are judged completely, and then the step returns to S2 again to select the next footdrop area.
Therefore, through analyzing and judging the footfall area and the attack targets in the footfall area, the judgment and resource allocation of all the attack targets in the whole defense area are effectively and quickly realized, and the fairness scheduling of the position defense and the fairness allocation of the defense weapons are effectively ensured.
The following explains embodiments of the present invention with specific examples:
s1, initializing parameters of at least one incoming target;
parameter target of coming target i The format of (A) is:
target i ＝{target i _deadline,target i _address,target i _ID}；
wherein target i _ deadline is the latest intercept time, target, of the incoming target i i "Address" is the landing point information of the incoming target i, target i ID is the threat of i on the incoming target.
Landing point information target i The _IDis obtained using the Runge Kutta one-step extrapolation algorithm.
Threat degree target of attack target i i The equation for _ ID is:
target i _ID＝1/(utarget i a deadline-ctime); wherein ctime is the current time.
Taking the 1 st incoming target as an example, the 1 st incoming target 1 The format of (d) can be expressed as: target 1 ＝{target 1 _deadline,target 1 _address,target 1 _ID}，
The latest interception time of the incoming target 1 is target 1 A skirt line, the landing point information of the incoming target 1 is target i A _ address, the threat degree of the incoming target 1 is target i _ID。
The 2 nd to 6 th attack targets are respectively:
target 2 ：target 2 ＝{target 2 _deadline,target 2 _address,target 2 _ID}；
target 3 ：target 3 ＝{target 3 _deadline,target 3 _address,target 3 _ID}；
target 4 ：target 4 ＝{target 4 _deadline,target 4 _address,target 4 _ID}；
target 5 ：target 5 ＝{target 5 _deadline,target 5 _address,target 5 _ID}；
target 6 ：target 6 ＝{target 6 _deadline,target 6 _address,target 6 _ID}。
s2, dividing the defense area into a plurality of foot-drop point areas, and sequentially selecting the foot-drop point areas;
taking the example of dividing the defense area into A, B and C3 foothold areas,
s21, setting the initial value of the difference counter in the 3 landing point areas;
the initial value of the difference counter in the A foothold area is theta A The initial value of the difference counter in the B foot-falling point region is theta B And the initial value of the difference counter in the C foot-falling point area is theta C ；
S22, sequentially selecting a foot point area according to the initial value of the difference counter;
assuming that the incoming target 1, the incoming target 2 and the incoming target 4 belong to the area of the a foothold,
the incoming target 5 and the incoming target 6 belong to the B-drop area, an
The attack target 3 belongs to the C foothold area; the priority sequence of the difference counters in the 3 foot-landing point areas from large to small is A > B > C, and the foot-landing point areas are selected according to the priority sequence;
s23, after the foot point area is selected, adjusting the difference counter value D theta of the foot point area k ：Dθ k ＝1-θ k /Θ k (ii) a Wherein, theta k Is the weight of the kth foothold area.
S3, acquiring the threat degree of an attack target in the selected foothold area based on the parameters;
s4, judging whether an attack target in the foot drop point area meets constraint conditions or not based on the threat degree;
the constraint conditions are as follows: target i _deadline-ctime≥lasttime；
Wherein ctime is the current moment, and lasttime is the time required for interception.
Because three different attack targets, namely an attack target 1, an attack target 2 and an attack target 4, exist in the area of the foothold A,
in one example, the attack targets 1, 2 and 4 are sorted in descending order based on the threat degree of each attack target, and the attack targets with higher threat degree are preferentially judged according to the constraint condition to carry out timely and rapid resource scheduling, assuming target 1 _ID＞target 3 _ID＞target 2 ID, the constraint condition judgment is firstly carried out on the incoming target 1,then, the target 3 is the incoming target, and finally, the target 2 is the incoming target, until the constraint condition judgment of all the incoming targets in the A foothold area is completed, then the selection of the foothold area in S2 is repeated, the B foothold area is selected to carry out the constraint condition judgment of all the incoming targets in the B foothold area, and the target in the B foothold area is assumed 5 _ID＞target 6 The ID is used for judging the incoming target 5 firstly and judging the incoming target 6 secondly; and finally, selecting the C foothold area to judge the constraint conditions of all the incoming targets in the C foothold area, namely judging the incoming target 3.
In another example, three different targets, namely the attack target 1, the attack target 2 and the attack target 4, exist in the area of the foothold a, but the threat degrees of the attack target 1, the attack target 2 and the attack target 4 do not need to be sorted, and the threat degrees are sequentially judged according to the labels of the attack targets, that is, the judgment sequence is as follows: the incoming target 1 is more than the incoming target 2 is more than the incoming target 4.
After the three incoming targets located in the area of the foothold A are all judged, the area of the selected foothold in S2 is repeated, the area of the foothold B is selected to judge the constraint conditions of all the incoming targets in the area of the foothold B, and finally the area of the foothold C is selected to judge the constraint conditions of all the incoming targets in the area of the foothold C.
And S5, allocating defense weapons for the attacking targets meeting the constraint conditions to realize the battle resource scheduling.
After three different incoming targets, namely an incoming target 1, an incoming target 2 and an incoming target 4, exist in the foothold area A and are respectively judged, if the incoming target 1 and the incoming target 2 meet constraint conditions, corresponding defense weapons are respectively allocated to the incoming target 1 and the incoming target 2, and if the incoming target 3 does not meet the constraint conditions, the defense weapons do not need to be allocated, so that the battle resource scheduling of all the incoming targets meeting the constraint conditions in the foothold area A is realized.
When the combat resources of all the attack targets meeting the constraint conditions in the area of the foothold A are distributed, defense weapons are continuously distributed for the attack targets meeting the constraint conditions in the area of the foothold B, and finally, the defense weapons of the attack targets meeting the constraint conditions in the area of the foothold C are distributed, so that the combat resources of all the attack targets meeting the constraint conditions in the whole defense area are scheduled.
The invention realizes the fairness scheduling of battle resources aiming at defense locations and optimizes fire distribution by selecting the foothold areas of the defense areas and judging the threat degree of the attack targets in the foothold areas, and the scheduling method is simple and is beneficial to engineering application.
It should be understood that the above-described embodiments of the present invention are examples for clearly illustrating the invention, and are not to be construed as limiting the embodiments of the present invention, and it will be obvious to those skilled in the art that various changes and modifications can be made on the basis of the above description, and it is not intended to exhaust all embodiments, and obvious changes and modifications can be made on the basis of the technical solutions of the present invention.
Claims (4)
1. A method for scheduling combat resources for an attack target is characterized by comprising the following steps:
s1, initializing parameters of at least one incoming target, wherein the format of the parameters of the incoming target is target i ＝{target i _deadline,target i _address,target i _ID}；target i "deadline" is the latest intercept time, target, of the incoming target i i The _ address is the landing point information of the incoming target i, target i The _ ID is the threat degree of the i of the incoming target;
s2, dividing the defense area into a plurality of foot-drop point areas, and sequentially selecting the foot-drop point areas;
s3, acquiring the threat degree of an attack target in the selected foothold area based on the parameters;
s4, judging whether an attack target in the foot drop point area meets constraint conditions or not based on the threat degree;
s5, allocating defense weapons for the attack targets meeting the constraint conditions to realize the battle resource scheduling;
wherein, the sequentially selecting the foot-landing point areas comprises:
setting the initial value of the difference counter of each landing point area, wherein the initial value of the difference counter of the kth landing point area is theta k ；
Sequentially selecting a foot point area according to the initial value of the difference counter;
wherein, the sequentially selecting the landing foot point areas further comprises:
after the foot point area is selected, adjusting the difference counter value D theta of the foot point area k ：Dθ k ＝1-θ k /Θ k ；
Wherein, theta k Is the weight of the kth foothold area.
2. The method of claim 1, wherein the foothold information is obtained using a Runge Kutta one-step extrapolation algorithm.
3. The method of claim 1, wherein the threat level target of an incoming target i i The formula for calculating _ ID is:
target i _ID＝1/(utarget i _deadline-ctime)；
wherein ctime is the current time.
4. The method of claim 1, wherein the constraint is: target i _deadline-ctime≥lasttime；
Wherein ctime is the current time, and lasttime is the time required for interception.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010060839.XA CN111260229B (en) | 2020-01-19 | 2020-01-19 | Combat resource scheduling method for incoming targets |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010060839.XA CN111260229B (en) | 2020-01-19 | 2020-01-19 | Combat resource scheduling method for incoming targets |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111260229A CN111260229A (en) | 2020-06-09 |
| CN111260229B true CN111260229B (en) | 2022-09-23 |
Family
ID=70949042
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010060839.XA Active CN111260229B (en) | 2020-01-19 | 2020-01-19 | Combat resource scheduling method for incoming targets |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111260229B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116432872B (en) * | 2023-06-13 | 2023-09-22 | 中国人民解放军战略支援部队航天工程大学 | HHO algorithm-based multi-constraint resource scheduling method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103336885A (en) * | 2013-06-03 | 2013-10-02 | 北京航空航天大学 | Method for solving weapon-target assignment problem based on differential evolution algorithm |
| WO2013169148A1 (en) * | 2012-05-11 | 2013-11-14 | Saab Ab | A method for resource allocation in mission planning |
| CN108829904A (en) * | 2018-03-09 | 2018-11-16 | 中国人民解放军海军大连舰艇学院 | The calculation method in enemy plane and missile threat area in a kind of surface ship air-defense |
-
2020
- 2020-01-19 CN CN202010060839.XA patent/CN111260229B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013169148A1 (en) * | 2012-05-11 | 2013-11-14 | Saab Ab | A method for resource allocation in mission planning |
| CN103336885A (en) * | 2013-06-03 | 2013-10-02 | 北京航空航天大学 | Method for solving weapon-target assignment problem based on differential evolution algorithm |
| CN108829904A (en) * | 2018-03-09 | 2018-11-16 | 中国人民解放军海军大连舰艇学院 | The calculation method in enemy plane and missile threat area in a kind of surface ship air-defense |
Non-Patent Citations (2)
| Title |
|---|
| "基于威胁判断的舰载多传感器射频保障优先度研究";王龙涛;《兵器装备工程学报》;20191130;第40卷(第11期);全文 * |
| 舰空导弹武器系统加权射击效能优化模型;刘博等;《海军航空工程学院学报》;20130120(第01期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111260229A (en) | 2020-06-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105844068B (en) | A kind of Q learning attack target assignment methods of Simulation-Oriented | |
| CN111260229B (en) | Combat resource scheduling method for incoming targets | |
| CN109255491A (en) | A kind of cooperative air-defense mission planning method and system of many types of antiaircraft weapon | |
| CN106685441A (en) | Radio frequency stealth radar networking power distribution method based on cooperative game | |
| CN108260198B (en) | Radar networking power control method based on non-cooperative game under spectrum sharing | |
| CN112702208B (en) | Relationship-based method for generating striking link of heterogeneous multi-layer combat system | |
| CN108548538A (en) | Method and system for multi-station multi-unmanned aerial vehicle task allocation and flight path planning | |
| CN114330715A (en) | Intelligent ammunition co-evolution task allocation method | |
| CN116681223A (en) | Multi-stage combat resource collaborative allocation method based on enhanced MOEA/D | |
| CN112149959A (en) | Distributed sensor-weapon-target joint distribution method | |
| US20060095909A1 (en) | Adaptive cooperative scheduling | |
| Kwon et al. | Lagrangian relaxation approach to the targeting problem | |
| CN113792985A (en) | Sensor-weapon dynamic joint task multi-target allocation method | |
| CN107800690B (en) | Task allocation method of distributed vulnerability scanning system | |
| CN110782062A (en) | Many-to-many packet interception target distribution method and system for air defense system | |
| CN110163502A (en) | A kind of more bullet collaboration multistage target assignment methods | |
| CN115328189B (en) | Multi-unmanned plane cooperative game decision-making method and system | |
| CN110597199A (en) | Helicopter weapon scheduling method and system based on optimal model of shooting vector | |
| CN112838905B (en) | Interference suppression method, device and equipment | |
| CN108540257A (en) | Distributed intelligence interference system determines position model jamming resource method for optimizing scheduling | |
| CN114897267A (en) | Fire power distribution method and system for many-to-many intelligent agent cooperative battlefield scene | |
| CN111274524A (en) | Combat resource scheduling method for emergency alarm event | |
| CN109548129B (en) | Multichannel power distribution method based on signal-to-noise-and-interference ratio | |
| CN110046040A (en) | Distributed task scheduling processing method and system and storage medium | |
| Chen et al. | Research on multiple kill vehicles firepower distribution strategy based on adjust genetic algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |