EP2239533A1 - Attribution d'armes face à des menaces - Google Patents

Attribution d'armes face à des menaces Download PDF

Info

Publication number
EP2239533A1
EP2239533A1 EP09250985A EP09250985A EP2239533A1 EP 2239533 A1 EP2239533 A1 EP 2239533A1 EP 09250985 A EP09250985 A EP 09250985A EP 09250985 A EP09250985 A EP 09250985A EP 2239533 A1 EP2239533 A1 EP 2239533A1
Authority
EP
European Patent Office
Prior art keywords
weapons
threats
data
assignment
weapon
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.)
Ceased
Application number
EP09250985A
Other languages
German (de)
English (en)
Inventor
designation of the inventor has not yet been filed The
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BAE Systems PLC
Original Assignee
BAE Systems PLC
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by BAE Systems PLC filed Critical BAE Systems PLC
Priority to EP09250985A priority Critical patent/EP2239533A1/fr
Priority to US13/256,025 priority patent/US20120000349A1/en
Priority to EP10711928A priority patent/EP2414767A1/fr
Priority to PCT/GB2010/050530 priority patent/WO2010112907A1/fr
Publication of EP2239533A1 publication Critical patent/EP2239533A1/fr
Priority to IL215240A priority patent/IL215240A0/en
Ceased legal-status Critical Current

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F41—WEAPONS
    • F41H—ARMOUR; ARMOURED TURRETS; ARMOURED OR ARMED VEHICLES; MEANS OF ATTACK OR DEFENCE, e.g. CAMOUFLAGE, IN GENERAL
    • F41H11/00—Defence installations; Defence devices
    • F41H11/02—Anti-aircraft or anti-guided missile or anti-torpedo defence installations or systems
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F41—WEAPONS
    • F41G—WEAPON SIGHTS; AIMING
    • F41G3/00—Aiming or laying means
    • F41G3/04—Aiming or laying means for dispersing fire from a battery ; for controlling spread of shots; for coordinating fire from spaced weapons

Definitions

  • the present invention relates to assigning weapons to threats.
  • FIG. 1 is a schematic illustration of a hostile environment/battlespace including a plurality of weapons and threats.
  • a battlespace can be thought of as a set of assets with weapons for countering a set of threats.
  • An asset may be associated with/have one or more weapons, e.g. W1 and W2 in the Figure are co-located on the same asset.
  • the asset may include a vehicle such as a submarine having different types of weapons, e.g. torpedoes with different payloads, or tanks.
  • an asset may include a static structure, e.g. a missile launch base, or even a troop of soldiers.
  • Weapons have associated values/costs, the units of which can be monetary, tactical, or some other. Threats have the potential to cause damage to assets and defended areas. The units of these defended assets can be monetary, tactical, etc. Success in a battlespace requires good allocation of weapons to threats. This is a balance between minimising losses by using more and better weapons to effect a maximal amount of damage whilst retaining some weapons for later use. However, the effectiveness of a weapon can vary according to the threat it faces, the dynamics of the platform it resides upon, or any number of other complicating factors.
  • Embodiments of the present invention are intended to address at least some of the problems discussed above and can result in efficient computation of an assignment solution distributed across a number of weapons platforms.
  • a method of assigning at least one weapon of a plurality of weapons to at least one threat of a plurality of threats including:
  • the weapons assignment technique may include a Max Sum technique or a Probability Collectives-based technique.
  • the weapons data may include data representing a cost of using each said weapon.
  • the threats data may include data representing a cost associated with each said threat, the cost typically being a measure of potential damage causable by each said threat.
  • the use costs in the weapons data and the use costs in the threats data will normally be expressed in identical units.
  • the weapons and/or threats data may be output by a threat evaluation process.
  • the method can further include a step of receiving user input/parameter(s) and processing the user input/parameter(s) as part of the selection of the at least one weapons assignment technique.
  • the user input/parameter(s) may relate to weapon accuracy or weapon use timing.
  • the method may include further analysing the data describing the assignment produced by the applying of the at least one selected weapon assignment technique and modifying the data describing the assignment.
  • the further analysis may include checking use of the assigned weapons for a cross-fire state, and modifying the data describing the assignment so that the cross-fire state is avoided.
  • the analysis may include checking appropriateness of a said assigned weapon(s) for use with the threat to which the weapon(s) has been assigned, and modifying the data describing the assignment if the weapon(s) is not appropriate.
  • the analysis may include checking geographical proximity of a said assigned weapon(s) to the threat to which the weapon(s) has been assigned, and modifying the data describing the assignment to assign another to the threat if the assigned weapon is not the weapon that is geographically closest to the threat.
  • a system configured to assign at least one weapon of a plurality of weapons to at least one threat of a plurality of threats, the system including:
  • a computer program product comprising computer readable medium, having thereon computer program code means, when the program code is loaded, to make the computer execute a method of assigning at least one weapon of a plurality of weapons to at least one threat of a plurality of threats substantially as described herein.
  • a method of assigning at least one weapon of a plurality of weapons to at least one threat of a plurality of threats including:
  • the problem posed is which weapon(s) to assign to which of the threats.
  • Data can be produced describing characteristics of each asset, e.g. geographic location, speed, weapon fit.
  • the weapon fit of an asset is specified by the types of weapon it has available, the cost (monetary or otherwise) of firing a particular weapon type, and the number of weapons of each type. It will be appreciated that the number, types and characteristics of the assets described herein are exemplary only.
  • each threat may have associated with it a geographic location, a bearing, a speed and a score.
  • the score (in units commensurate with the cost of firing a weapon) defines the value of the threat in terms of its capability to cause damage to the assets. For example, a cheap cruise missile may be more threatening than an expensive transport aircraft.
  • These scores will normally be an output of a threat evaluation process that may be performed by human assessors reviewing the scenario/battlespace, or may at least be partially retrieved from a data store or automatically calculated based on known information about at least some of the threats.
  • a command management system 200 is shown in communication with a weapons assignment component 201.
  • the command management system may be, for example, the CMS-1 produced by BAE Systems. That system can visualise situational awareness in a ship-based air defence scenario to render data (geography, location of threats, location of assets, etc) for an operator on the bridge of a ship. More generally, the management system can comprise any (dynamic) data storage and visualisation system that is able to feed the location of assets (weapons), threats, threat levels, rules of engagement/standing orders, and other relevant matters, to an operator in order to provide the best "view" of the battlespace.
  • the system can be partially automated and may receive inputs from radars/cameras for detection, threat evaluation modules, weapons, health monitoring, etc.
  • the component 201 can include a computing device having a processor and internal memory configured to execute steps as described herein.
  • the component 201 receives the data describing the weapons and the threats from the management system 200 and process that data in order to provide the system 200 with a list of assignments, i.e. which weapons are to be used against which threats, which can be thought of as the solution to the weapons assignment problem.
  • the weapons assignment problem can be formulated as a graph with weapons connected to threats to which they can be assigned.
  • a cost function can be created that reflects the costs of assigning weapons to threats with the potential to cause a specified amount of damage.
  • the units of this function can be user-selected, e.g. monetary or casualty/safety-based.
  • the component 201 is capable of executing more than one type of allocation algorithm/technique and the decision regarding which algorithm to use is made by an "intelligent switch" process, which can take into account parameters (e.g. number of weapons, time constraints, etc.) that may have been chosen by an operator.
  • the algorithm outputs data representing an assignment and a reassignment check can then be performed made to try to ensure that the best (e.g. geographically closest) weapon of the type specified in the assignment is assigned to its threat.
  • the data is first received by a scenario parser process 202 executing on the component 201.
  • the general weapons assignment problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete.
  • a further input used by the process is an engagement parameter matrix.
  • the ( i , j ) th element of this matrix is the probability p ij of destroying target j by a single weapon of type i.
  • q ij 1- p ij denotes the probability of survival of target j if it gets assigned by a single weapon of type i.
  • x ij is the number of weapons of type i assigned to target j
  • survival probability of target j is given by q ij xij .
  • a target may be assigned weapons of different types.
  • the weapons assignment problem is to determine the x ij values that minimise the expected survival value of all targets.
  • N the number of targets
  • M the number of weapon types
  • C j the cost of damage caused by target j
  • C i the cost of firing weapon type i
  • W i the number of weapons of type i available to be assigned to targets.
  • This formulation expresses an objective to minimise the expected cost of an engagement plan while ensuring the total number of weapons used is no more than those available.
  • the scenario parser 202 effectively processes the data it receives in order to formulate a cost function that can be used by the weapons assignment techniques described below and also by an intelligent switch 204.
  • Figure 3 illustrates steps that provide the intelligent switch functionality.
  • data produced by the scenario parser 202 is received.
  • data representing user inputs/parameters may be received.
  • Step 304 may not be performed by all embodiments of the system, but can be useful when at least one additional/variable factor, such as the desired accuracy level of a weapon, the amount of computational power available and/or a "time to launch" constraint, etc, need be taken into account.
  • step 306 the data received at step 302 (and, optionally, step 304) is processed in order to select a weapons assignment algorithm/technique in combination with data describing characteristics of the algorithms/techniques that are available.
  • this step can involve various types of computations. For example, if the user-defined parameter specifies a certain time frame for producing the weapons assignment then the step can include selecting an algorithm/technique that is expected to produce a result within that time frame. Alternatively, if no time constraint has been specified then the step may select the algorithm/technique that is expected to produce the most effective assignment. In another case, the complexity of the cost function may be taken into account and any algorithm/technique not capable of dealing with that level of complexity is eliminated.
  • data indicating the algorithm/technique selected is output. It will be appreciated that in some cases more than one algorithm/technique may be selected, e.g. for results comparison during testing.
  • Items 206A and 206B of Figure 2 represent two different weapons assignment algorithms/techniques, one of which will normally be selected by the intelligent switch 204. It will be appreciated that the type and number of algorithms/techniques shown is exemplary only and in alternative embodiments more than two may be available. A description of the two algorithms/techniques will now be given:
  • the basis of the Max-Sum algorithm is to represent a global cost or utility function as a factor graph and then to optimise it in a decentralised manner via local message passing.
  • an agent is represented as a function with a variable representing its state and utility.
  • An agent may be used to represent a decision maker and can be ascribed to an asset.
  • a set of interacting agents is known as a Multi-Agent System (MAS).
  • MAS can employ Game Theory to develop interaction strategies for agent-negotiation that lead to equilibrium solutions for multi-agent decision making and resource management.
  • the utility of any agent is a function of its own state and the state of a small number of neighbouring agents.
  • the function node of a single agent is connected to its own variable node, and the variable nodes of a number of neighbouring agents.
  • the Max-Sum algorithm calculates the messages that should be exchanged between the agents to maximise the global utility.
  • the Max-Sum algorithm can have good scaling properties because the largest calculation any agent performs is exponential only in its number of neighbours, which is typically much less than the total number of agents in the system.
  • the algorithm involves transmitting and updating messages between neighbouring agents until the states of all agents converge to fixed states that represent either the optimal solution, or a solution that is close to optimal.
  • the global cost function i.e. the expected cost of an engagement plan
  • the actions of the individual agents i.e. the assignment of weapons to targets. If the global cost can be factored, scalable decentralised solutions should be possible. If it cannot be factored, solutions may still be available but they will not be scalable.
  • Other key issues are the convergence time of the algorithm and the quality of the solution to which the algorithm converges. The results are likely to be strongly scenario-dependent.
  • PC Probability Collectives
  • the PC-based algorithm is explicitly decentralised because the assets are running separate computer programs and only interacting with each other via the oracle.
  • the main communication overhead in PC is the transmission of sample blocks from the agents to the oracle. The size of these blocks will be problem dependent as will the number of communications with the oracle that are required before the solution converges.
  • the output of the selected algorithm is data describing a weapons-to-threats assignment, e.g. in the form of a matrix.
  • the component 201 includes an optional process 208 for checking the assignment and possibly modifying it before it is transferred to the command management system 200.
  • the process 208 can involve performing checks based on the data received by the scenario parser 202 and/or other parameter data provided by a user. The intention is to check that the assignment does not result in illogical or even dangerous weapons use on a practical level. It will be appreciated that this process can involve various types of computations.
  • data representing the geographical location of the weapons and threats can be processed to check if there is a weapon of the same type as specified by the assignment located nearer the assigned threat than the one specified in the assignment. If so then the process 208 can modify the assignment data to allocate the geographically-closer weapon to the threat. Additionally or alternatively, the process may involve computing if firing the weapons in accordance with the assignment will result in harmful cross-fire and, if so, amend the assignment to avoid that situation.
  • the assignment data (possibly modified by process 208) is then transferred to an assignment parser process 210 that set the assignment data into a format that can be directly used by the command management system 200.
  • the system 200 can implement it, e.g. by direct remote control of the weapons and/or by informing a controller of an asset of which threat its weapon(s) is to target.

Landscapes

  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Aiming, Guidance, Guns With A Light Source, Armor, Camouflage, And Targets (AREA)
EP09250985A 2009-03-31 2009-03-31 Attribution d'armes face à des menaces Ceased EP2239533A1 (fr)

Priority Applications (5)

Application Number Priority Date Filing Date Title
EP09250985A EP2239533A1 (fr) 2009-03-31 2009-03-31 Attribution d'armes face à des menaces
US13/256,025 US20120000349A1 (en) 2009-03-31 2010-03-29 Assigning weapons to threats
EP10711928A EP2414767A1 (fr) 2009-03-31 2010-03-29 Attribution d'armes en fonction de menaces
PCT/GB2010/050530 WO2010112907A1 (fr) 2009-03-31 2010-03-29 Attribution d'armes en fonction de menaces
IL215240A IL215240A0 (en) 2009-03-31 2011-09-19 Assigning weapons to threats

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP09250985A EP2239533A1 (fr) 2009-03-31 2009-03-31 Attribution d'armes face à des menaces

Publications (1)

Publication Number Publication Date
EP2239533A1 true EP2239533A1 (fr) 2010-10-13

Family

ID=40902018

Family Applications (1)

Application Number Title Priority Date Filing Date
EP09250985A Ceased EP2239533A1 (fr) 2009-03-31 2009-03-31 Attribution d'armes face à des menaces

Country Status (1)

Country Link
EP (1) EP2239533A1 (fr)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013153471A1 (fr) 2012-04-11 2013-10-17 Aselsan Elektronik Sanayi Ve Ticaret Anonim Sirketi Système d'essai et d'analyse et procédé d'évaluation de menace et algorithmes d'affectation de capteur/arme
EP2482026B1 (fr) 2011-01-26 2018-05-02 Diehl Defence GmbH & Co. KG Procédé de défense contre l'attaque d'un missile
CN110826877A (zh) * 2019-10-24 2020-02-21 四川航天系统工程研究所 一种针对多个点目标的火力分配方法
US10677564B2 (en) * 2017-09-27 2020-06-09 Mitsubishi Heavy Industries, Ltd. Target assignment system, command system, and target assignment method
US11781835B2 (en) * 2020-06-10 2023-10-10 David H. Sitrick Automatic weapon subsystem comprising a plurality of automated weapons subsystems
FR3141761A1 (fr) * 2022-11-09 2024-05-10 Mbda France Procédé et dispositif de détermination d'un plan d'engagement pour un système de défense aérienne.

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5153366A (en) * 1988-12-23 1992-10-06 Hughes Aircraft Company Method for allocating and assigning defensive weapons against attacking weapons
WO1999023443A1 (fr) * 1997-11-03 1999-05-14 Raytheon Company Evaluation automatique de la menace et attribution d'armes sur une base de connaissances
US20070244673A1 (en) * 2006-04-14 2007-10-18 Deepak Khosla Methods and apparatus for optimal resource allocation

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5153366A (en) * 1988-12-23 1992-10-06 Hughes Aircraft Company Method for allocating and assigning defensive weapons against attacking weapons
WO1999023443A1 (fr) * 1997-11-03 1999-05-14 Raytheon Company Evaluation automatique de la menace et attribution d'armes sur une base de connaissances
US20070244673A1 (en) * 2006-04-14 2007-10-18 Deepak Khosla Methods and apparatus for optimal resource allocation

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
A. WALDOCK; D. NICHOLSON: "Cooperative decentralised data fusion using probability collectives", FIRST INTERNATIONAL WORKSHOP ON AGENT TECHNOLOGY FOR SENSOR NETWORKS, 2007, pages 47 - 54, XP002542035 *
A. WALDOCK; D. NICHOLSON; A ROGERS: "Cooperative Control using the Max-Sum Algorithm", SECOND INTERNATIONAL WORKSHOP ON AGENT TECHNOLOGY FOR SENSOR NETWORKS, 22 April 2008 (2008-04-22), Portugal, pages 1 - 6, XP002542036 *
D.H. WOLPERT: "Collective Intelligence, Computational Intelligence Beyond 2001: Real and Imagined", 2001, WILEY

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2482026B1 (fr) 2011-01-26 2018-05-02 Diehl Defence GmbH & Co. KG Procédé de défense contre l'attaque d'un missile
WO2013153471A1 (fr) 2012-04-11 2013-10-17 Aselsan Elektronik Sanayi Ve Ticaret Anonim Sirketi Système d'essai et d'analyse et procédé d'évaluation de menace et algorithmes d'affectation de capteur/arme
US9779185B2 (en) 2012-04-11 2017-10-03 Aselsan Elektronik Sanayi Ve Ticaret Anonim Sirketi Test and analysis system and a method for threat evaluation and sensor/weapon assignment algorithms
US10677564B2 (en) * 2017-09-27 2020-06-09 Mitsubishi Heavy Industries, Ltd. Target assignment system, command system, and target assignment method
CN110826877A (zh) * 2019-10-24 2020-02-21 四川航天系统工程研究所 一种针对多个点目标的火力分配方法
CN110826877B (zh) * 2019-10-24 2023-05-02 四川航天系统工程研究所 一种针对多个点目标的火力分配方法
US11781835B2 (en) * 2020-06-10 2023-10-10 David H. Sitrick Automatic weapon subsystem comprising a plurality of automated weapons subsystems
FR3141761A1 (fr) * 2022-11-09 2024-05-10 Mbda France Procédé et dispositif de détermination d'un plan d'engagement pour un système de défense aérienne.
EP4368940A1 (fr) * 2022-11-09 2024-05-15 MBDA France Procédé et dispositif de détermination d'un plan d'engagement pour un système de défense aérienne
WO2024099625A1 (fr) * 2022-11-09 2024-05-16 Mbda France Procédé et dispositif de détermination d'un plan d'engagement pour un système de défense aérienne

Similar Documents

Publication Publication Date Title
US20120000349A1 (en) Assigning weapons to threats
US9726460B2 (en) System and method for asymmetric missile defense
EP2239533A1 (fr) Attribution d'armes face à des menaces
US20110271822A1 (en) Automatic Real Time Command and Control System
RU2662920C2 (ru) Способ и устройство многоцелевой оптимизации
RU2679213C2 (ru) Способ и устройство для оптимизации плана распределения ресурсов
US9544326B2 (en) Digital weapons factory and digital operations center for producing, deploying, assessing, and managing digital defects
Cha et al. Fire scheduling for planned artillery attack operations under time-dependent destruction probabilities
RU2585724C2 (ru) Устройство для оценки эффективности войск противовоздушной обороны оперативного уровня
Darrah et al. Using genetic algorithms for tasking teams of raven UAVs
Najgebauer et al. The qualitative and quantitative support method for capability based planning of armed forces development
Naseem et al. A real-time man-in-loop threat evaluation and resource assignment in defense
Nguyen Assessment of a ballistic missile defense system
Johnson et al. Game theory and prescriptive analytics for naval wargaming battle management aids
Sumari et al. A Knowledge Growing System-based Decision Making-Support System Application for Forces Command and Control in Military Operations
US20190188342A1 (en) Methods and apparatus for hazard abatement using normalized effect analysis
DeStefano Agent based simulation SEAS evaluation of DoDAF architecture
Warren et al. An analysis of how the us government can effectively tackle supply chain barriers to scale up the low cost unmanned aerial vehicle (UAV) swarming technology (locust) program
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
Giachetti System of systems capability needs analysis via a stochastic network model
Connors Agent-based Modeling Methodology for Analyzing Weapons Systems
Vijay Rao Design and development of intelligent military training systems and wargames
Radulov et al. A Screening Method for C2 Expert Assessment
Naeem et al. A novel two-staged decision support based threat evaluation and weapon assignment algorithm, asset-based dynamic weapon scheduling using artificial intelligence techinques
Deleon Navy operational planner

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO SE SI SK TR

AX Request for extension of the european patent

Extension state: AL BA RS

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION HAS BEEN REFUSED

18R Application refused

Effective date: 20110130