CN106789740A - By the multi-platform sensor synergism management method of the sequential auction of task priority - Google Patents
By the multi-platform sensor synergism management method of the sequential auction of task priority Download PDFInfo
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- CN106789740A CN106789740A CN201611002200.6A CN201611002200A CN106789740A CN 106789740 A CN106789740 A CN 106789740A CN 201611002200 A CN201611002200 A CN 201611002200A CN 106789740 A CN106789740 A CN 106789740A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
- H04L47/62—Queue scheduling characterised by scheduling criteria
- H04L47/625—Queue scheduling characterised by scheduling criteria for service slots or service orders
- H04L47/6275—Queue scheduling characterised by scheduling criteria for service slots or service orders based on priority
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Abstract
The present invention is under the jurisdiction of information fusion research field, it is adaptable to solve the sensor synergism problem of management in multi-platform Multi-sensor collaboration detection tracking.There is provided a kind of multi-platform sensor synergism management method by the sequential auction of task priority, task distributes order of the intelligent body according to task priority, detection tracing task is taken out one by one and is auctioned, enter line sensor using price minimum criteria to select, must be gone out on missions allocation matrix, and task allocation matrix is real-time transmitted to sensor management intelligent body, sensor management intelligent body control sensor completes detection tracing task.The inventive method can automatically real-time draw the allocation matrix between platform, sensor, target three, it is easy to Project Realization；Meanwhile, the priority of task that the method makes priority high occupies resource, and method is easy, Robust Performance, it is adaptable to collaboration detection tracking of the multi-platform networking under Antagonistic Environment.
Description
Technical field
The present invention is under the jurisdiction of information fusion research field, it is adaptable to solve multi-platform Multi-sensor collaboration detection tracking in
Sensor synergism problem of management.
Background technology
The electronic technology such as radar, communication, equipment develop rapidly, for multi-platform sensor network provides condition.For example,
The sensor networks such as radar, the infrared, electronic warfare that the platforms such as multiple operational aircrafts, unmanned plane are carried collaboration detection, tracking target.
When multiple operational aircrafts carry out cooperative combat, the cooperative ability between operational aircraft is extremely important.Cooperative ability is strong, by system
Confrontation, realizes 1+1>2 effect, anyway it is as the same.
During formation cooperation, what is faced first is exactly collaboration detection tracking problem, traditional airborne platform cooperative mode
Based on the traffic guidance of people, such as the commander on formation aircraft leader is in real time to appointing that the issue detection of other wing planes is tracked
Business, commands its a certain orientation of search, tracks, attacks some target.The mode of employment commander has its advantage, task is few, state
In the case that gesture is relatively easy, have the advantages that flexible, motor-driven, adaptive ability is strong.But sensed as airborne platform is carried
Device number increases, and the increase of detection tracking number of targets, task distribution, sensor selection will form multiple shot array, now, manually refer to
The mode of collaboration is waved either in real-time or capacity, actual battlefield demand far can not have all been met.Accordingly, it would be desirable to adopt
With the sensor management mode of intelligence, allow all or part of Target Assignment, sensor management to be completed automatically by machine, liberate
Pilot and commander's brain.
From methodology, moment sensor management method research is concentrated mainly on the research with information theory as theoretical foundation
On, characterization information increment statistic is including Renyi divergences, K-L divergences etc. and its converts, these methods often with particle filter
The maximum likelihood class method of estimation that ripple, PHD are filtered into representative is used in combination.Filtered for the maximum posteriori class based on Kalman
Wave method, often builds comentropy statistic using target following covariance as measure of information.The sensor tube of information theory class
Reason method is mostly after information delta statistic is established, sensor management to be carried out using information delta maximization.Information
It is applied on the sensor management of many operational aircraft cooperations by method, its weak point is embodied in and does not account for different appointing
The demand of business, because often average information increment maximum might not complete mission effectiveness highest.For this consideration, in recent years
Come, occur in that with the Method of Sensor Management of task-driven, these methods mostly according to mission requirements, with track covariance,
Number of targets etc. is injured for optimal index, this optimization problem is solved by genetic algorithm, auction algorithm etc..These methods build
Object function consider factor it is more satisfactory, only considered the priority of target, do not account for the grade of task, also will
Sensor management considers with target priority, tracking accuracy demand, sensor detection accuracy, the reasonability of algorithm and practicality
Property need further raising.
Under in view of multiple target, multi-platform, multisensor " more than three " environment, the distribution of task that sensor management is related to,
Sensor selection, resource allocation, information fusion belong to a complexity N-P hard problem, hardly result in the majorized function of closure.
The market theory thought such as price mechanism, auction algorithm in economics is appropriate for the resource-adaptive distribution under complex situations,
Therefore, a new thinking is, with task-driven, under multiple agent framework, to be solved by the sequential auction of task priority
Target Assignment and sensor management problem in certainly many airborne platform collaboration detection tracking.
The content of the invention
For the sensor management problem in multi-platform networking collaboration detection tracking, there is provided one kind presses task priority sequence
The multi-platform sensor synergism management method of auction is passed through, by the price mechanism in market theory, according to the suitable of task priority
Sequence, detection tracing task is taken out auctioned one by one, the task distribution realizing being related in multi-platform networking collaboration detection tracking,
Sensor selection, resource allocation.The present invention solves the technical problem, as follows using technical scheme steps：
1. by the multi-platform sensor synergism management method of the sequential auction of task priority, it is characterised in that including following skill
Art step：
Step (1), the setting different intelligent body function module first in different platform, including：Set on maneuvering platform
The intelligent module of task distribution, is responsible for task distribution and the selection of sensor；Sensor management intelligence is set on member's platform
Module, is responsible for collecting each platform sensor state, the working condition of management and control sensor, pattern；
The communication linkage that step (2), task distribution intelligent body pass through each platform, sends mobile intelligence to each platform in real time
Energy body, for detecting communication link, and collecting platform position, movable information, sensor type, mode of operation, work at present
State, sensor detection accuracy；
Step (3), task distribution intelligent body are according to the position of the target for having obtained, movable information and each platform
The detection angle scope of position, movable information and sensor is slightly matched to target and sensor, is determined on each platform
The state x of sensorijk, wherein xijkSubscript i represent target designation, i=1,2,3 ..., I, I represent the sum of target, j tables
Show that platform is numbered, j=1,2,3 ..., J, J represent the sum of platform, k represents the numbering of sensor, k=1,2,3 ..., K, K
Represent the sum of sensor, xijk∈ { 0,1 }, if xijkK-th sensor of=1 j-th platform of expression can be arranged to target i,
If xijk=0, expression can not be arranged；Task distributes intelligent body according to acquired target location, movable information and other information
Information input, divides to goal task, and main task includes monitoring, tracking, identification, fire control, draws the essence of different task
True demand thresholding ηi, wherein, ηiSubscript i represent target designation；
Step (4), hypothesis current time are tk, to subsequent time tk+1Planned, task distribution intelligent body and sensing
Device manages the common co-ordination of intelligent body, and sensor selection and target point are realized according to the priority orders auction system of task
Match somebody with somebody；
Task allocation result is transmitted to sensor management intelligence by step (5), task distribution intelligent body using communication link
Body, sensor management intelligent body is distributed according to the sensor of task intelligent body, and control sensor carries out detection tracking to target, complete
The measurement of distribution target in pairs；Each sensor receives measurement, by agreement in advance, sends a mark or flight path to information fusion
Center, fusion center carries out a mark or Track Fusion, sends the related precision result for merging to task distribution intelligent body；
Step (6), task distribution intelligent body are compared to fusion results and mission requirements, are assessed, if target following
Result meets mission requirements precision, then wait until time tk+1Arrive, then carry out sensor of interest reallocation；If target following result
Mission requirements accuracy requirement is unsatisfactory for, target reallocation also can be in advance carried out, step (2) is returned to.
Specifically, realizing sensor using unilateral auction system according to the priority orders of task in described step (four)
Selection and target assignment method specifically can be divided into following steps again：
(21) in tkMoment task distribution intelligent body is sorted by priority to target, and determines i-th target tracking accuracy
Demand ηi；Relative position relation, threat level and platform sensor investigative range, angle according to each target and each platform
Degree, the limitation of detection accuracy determine price p of the different platform different sensors to different targetijk, wherein, i represents that target is compiled
Number, j represents that platform is numbered, and k represents sensor number；
By the price matrix P of different sensors in the corresponding different platforms of target iiIt is defined as
Task distribute intelligent body to each platform send intelligent mobile agent, intelligent mobile agent by with platform on sensor
Management intelligent body interaction, collects the sensor resource information of member's platform, determines that sensor resource matrix X, X are a three-dimensional square
Battle array, each element xijk, xijk∈ { 0,1 }, xijkThe kth kind sensor of=1 expression j platforms can be arranged to target i, xijk=0
For that can not arrange, by the corresponding sensor resource matrix X of target iiIt is defined as
(22) according to target prioritization, according to priority order from high to low takes out target i carries out auction, traversal
Sensor resource matrix XiMiddle correspondence xijk=1 all the sensors combination Sim, wherein, SimRepresent the corresponding m of i-th target
Individual sensor combinations, m=1,2 ..., sum that M, M are all combinations, respectively measure corresponding to each sensor combinations miss
Difference matrix is compressed fusion, obtains fusion accuracy Rim
Wherein, RimRepresent the fusion error co-variance matrix of corresponding m-th combination of target i, RjkRepresent target i correspondences
M-th sensor combinations SimIn j-th platform, k-th sensor error be transformed into the error covariance square after fusion center
Battle array；If sensor is comprising infrared, electronic warfare passive sensor in platform, can be by infrared and electronic warfare angular error and radar
Fusion is compressed, then is changed；If flight path can be obtained during tracking, also can be by error in measurement matrix filtering error
Covariance replaces；
Respectively by the corresponding fusion error co-variance matrix R of each sensor combinationsimTracking accuracy corresponding with target i
Thresholding ηiCompare, judge
Wherein, Matrix Calculating mark in bracket is sought in trace () expressions, when above formula is set up, then it represents that sensor combinations SimCan be full
The detection tracing task demand of foot-eye i, the combination that will can meet mission requirements is stored in allocation matrix DinIn,
Wherein, DinIn matrix, row represents platform numbering, and from 1 to J, J is maximum platform numbering, and it is corresponding that row represent platform
Sensor number, from 1 to K, K is numbered for maximum sensor；dik∈ { 0,1 }, dik=1 represents that the sensor distributes to target i,
dik=0 represents that the sensor is not allocated to target i；
p′in=sum (Pi·Din)
Wherein, p 'inExpression meets the corresponding price sum of combination of accuracy requirement for n-th, and sum () is represented to matrix institute
There is element to sue for peace；
[p′iI,ni]=min (p 'in, n=1,2,3 ..., N)
Wherein, p 'iIRepresent p 'inMiddle minimum price, niExpression obtains the numbering of the corresponding n of minimum price, min () table
Show and seek minimum value in bracket, N represents i-th maximum sensor number of combinations of aimed at precision demand of satisfaction；
By p 'iICompare with thresholding,
p′iI≤ηp
If above formula is set up, by niCorresponding distributionDistribute to target i；
(23) target that priority is taken second place, it is assumed that numbering is i ', takes out and is auctioned, first according to target i ' auctions
Allocation matrix beforeJudge whether the use of some sensors has reached maximum size, specific method is：Calculate and pass
Sensor absorption matrix Dtotal,
Wherein,
By DtotalWith sensor tracking capacity matrix DhCorresponding element is compared one by one, wherein, Dh
Wherein, DhIn element hjkRepresent the maximum target number that k-th sensor in j-th platform can be tracked；
Calculate both only poor
Element in D is compared with 0, if a certain element is more than or equal to 0, if this element jth row and kth in D are arranged, then
Think that target label target in i ' afterwards can not be allocated k-th sensor determined on j platform, make in price matrix
J rows and kth row price be equal to one level off to infinity real number, thus k-th sensor on j-th platform will no longer
By other target selections；
(24) (23rd) step is returned to, after traveling through all targets, corresponding allocation matrix is obtainedAccording to
MatrixSet up K sensor in j-th platform and distribute to the I allocation matrix B of targetj,
The corresponding sensor allocation matrix B of similar all platforms1,B2,...,BJ, will be therein using intelligent mobile agent
BjSend the sensor management intelligent body of corresponding j-th platform to, allow sensor management intelligent body according to allocation matrix BjManagement
Sensor scan, completes the detection to target.
The beneficial effects of the invention are as follows：
Contrast prior art, the multi-platform sensor synergism pipe by the sequential auction of task priority described in the technical program
Reason method, beneficial effect is：
1) the inventive method is easy to Project Realization.Method give maneuvering platform and member's platform intelligent body information Perception with
Interactive mode, by the sensor allocation matrix of each target, allows command centre intuitively to see the biography that different target is obtained
Sensor distribution condition, by platform to the allocation matrix of target, allow each platform can easily the selection of each sensor of management and control and
Target Assignment, completes the detection tracking to target.
2) this method can be directed to the precision of different task, be auctioned according to priority orders, it is ensured that priority is high
Priority of task selects sensor resource, is a kind of method of easy and Robust Performance；Meanwhile, the price of sensor can in the method
, come flexible pricing, can overcome simply with detection accuracy as condition with according to sensor accuracy, threat estimating, multifactor limitation etc.
Target Assignment, is particularly well-suited to multiple platform system Antagonistic Environments.
The above, specific embodiment only of the invention, but protection scope of the present invention is not limited thereto, and it is any
Be familiar with the people of the technology disclosed herein technical scope in, may extend into other modifications, change and apply, should all contain
Cover within the scope of of the invention including.
Brief description of the drawings
The method of the present invention flow chart of steps of accompanying drawing 1；
Accompanying drawing 2 is the not allocation result of sensor target in the same time in emulation experiment；
Accompanying drawing 3 is not task tracking accuracy demand thresholding and distribution sensor combinations fusion accuracy in the same time in emulation experiment
Relation；
Specific embodiment
Below in conjunction with the accompanying drawings, technical scheme is described in detail, referring to the drawings 1, specific steps of the invention include：
Step (1), the setting different intelligent body function module first in different platform, including：Set on maneuvering platform
The intelligent module of task distribution, is responsible for task distribution and the selection of sensor；Sensor management intelligence is set on member's platform
Module, is responsible for collecting each platform sensor state, the working condition of management and control sensor, pattern；
The communication linkage that step (2), task distribution intelligent body pass through each platform, sends mobile intelligence to each platform in real time
Energy body, for detecting communication link, and collecting platform position, movable information, sensor type, mode of operation, work at present
State, sensor detection accuracy；
Step (3), task distribution intelligent body are according to the position of the target for having obtained, movable information and each platform
The detection angle scope of position, movable information and sensor is slightly matched to target and sensor, is determined on each platform
The state x of sensorijk, wherein xijkSubscript i represent target designation, i=1,2,3 ..., I, I represent the sum of target, j tables
Show that platform is numbered, j=1,2,3 ..., J, J represent the sum of platform, k represents the numbering of sensor, k=1,2,3 ..., K, K
Represent the sum of sensor, xijk∈ { 0,1 }, if xijkK-th sensor of=1 j-th platform of expression can be arranged to target i,
If xijk=0, expression can not be arranged；Task distributes intelligent body according to acquired target location, movable information and other information
Information input, divides to goal task, and main task includes monitoring, tracking, identification, fire control, draws the essence of different task
True demand thresholding ηi, wherein, ηiSubscript i represent target designation；
Step (4), hypothesis current time are tk, to subsequent time tk+1Planned, task distribution intelligent body and sensing
Device manages the common co-ordination of intelligent body, and sensor selection and target point are realized according to the priority orders auction system of task
Match somebody with somebody；Specific method is：
(41) in tkMoment task distribution intelligent body is sorted by priority to target, and determines i-th target tracking accuracy
Demand ηi；Relative position relation, threat level and platform sensor investigative range, angle according to each target and each platform
Degree, the limitation of detection accuracy determine price p of the different platform different sensors to different targetijk, wherein, i represents that target is compiled
Number, j represents that platform is numbered, and k represents sensor number；
By the price matrix P of different sensors in the corresponding different platforms of target iiIt is defined as
Task distribute intelligent body to each platform send intelligent mobile agent, intelligent mobile agent by with platform on sensor
Management intelligent body interaction, collects the sensor resource information of member's platform, determines that sensor resource matrix X, X are a three-dimensional square
Battle array, each element xijk, xijk∈ { 0,1 }, xijkThe kth kind sensor of=1 expression j platforms can be arranged to target i, xijk=0
For that can not arrange, by the corresponding sensor resource matrix X of target iiIt is defined as
(42) according to target prioritization, according to priority order from high to low takes out target i carries out auction, traversal
Sensor resource matrix XiMiddle correspondence xijk=1 all the sensors combination Sim, wherein, SimRepresent the corresponding m of i-th target
Individual sensor combinations, m=1,2 ..., sum that M, M are all combinations, respectively measure corresponding to each sensor combinations miss
Difference matrix is compressed fusion, obtains fusion accuracy Rim
Wherein, RimRepresent the fusion error co-variance matrix of corresponding m-th combination of target i, RjkRepresent target i correspondences
M-th sensor combinations SimIn j-th platform, k-th sensor error be transformed into the error covariance square after fusion center
Battle array；If sensor is comprising infrared, electronic warfare passive sensor in platform, can be by infrared and electronic warfare angular error and radar
Fusion is compressed, then is changed；If flight path can be obtained during tracking, also can be by error in measurement matrix filtering error
Covariance replaces；
Respectively by the corresponding fusion error co-variance matrix R of each sensor combinationsimTracking accuracy corresponding with target i
Thresholding ηiCompare, judge
Wherein, Matrix Calculating mark in bracket is sought in trace () expressions, when above formula is set up, then it represents that sensor combinations SimCan be full
The detection tracing task demand of foot-eye i, the combination that will can meet mission requirements is stored in allocation matrix DinIn,
Wherein, DinIn matrix, row represents platform numbering, and from 1 to J, J is maximum platform numbering, and it is corresponding that row represent platform
Sensor number, from 1 to K, K is numbered for maximum sensor；dik∈ { 0,1 }, dik=1 represents that the sensor distributes to target i,
dik=0 represents that the sensor is not allocated to target i；
p′in=sum (Pi·Din)
Wherein, p 'inExpression meets the corresponding price sum of combination of accuracy requirement for n-th, and sum () is represented to matrix institute
There is element to sue for peace；
[p′iI,ni]=min (p 'in, n=1,2,3 ..., N)
Wherein, p 'iIRepresent p 'inMiddle minimum price, niExpression obtains the numbering of the corresponding n of minimum price, min () table
Show and seek minimum value in bracket, N represents i-th maximum sensor number of combinations of aimed at precision demand of satisfaction；
By p 'iICompare with thresholding,
p′iI≤ηp
If above formula is set up, by niCorresponding distributionDistribute to target i；
(43) target that priority is taken second place, it is assumed that numbering is i ', takes out and is auctioned, first according to target i ' auctions
Allocation matrix beforeJudge whether the use of some sensors has reached maximum size, specific method is：Calculate and pass
Sensor absorption matrix Dtotal,
Wherein,
By DtotalWith sensor tracking capacity matrix DhCorresponding element is compared one by one, wherein, Dh
Wherein, DhIn element hjkRepresent the maximum target number that k-th sensor in j-th platform can be tracked；
Calculate both only poor
Element in D is compared with 0, if a certain element is more than or equal to 0, if this element jth row and kth in D are arranged, then
Think that target label target in i ' afterwards can not be allocated k-th sensor determined on j platform, make in price matrix
J rows and kth row price be equal to one level off to infinity real number, thus k-th sensor on j-th platform will no longer
By other target selections；
(44) (43rd) step is returned to, after traveling through all targets, corresponding allocation matrix is obtainedAccording to
MatrixSet up K sensor in j-th platform and distribute to the I allocation matrix B of targetj,
The corresponding sensor allocation matrix B of similar all platforms1,B2,...,BJ；
Step (5), using intelligent mobile agent by B1,B2,...,BJIn BjIt is respectively transmitted to corresponding j-th platform
Sensor management intelligent body, allows sensor management intelligent body according to allocation matrix BjManagement of sensor is scanned, and is completed to target
Detection；Sensor management intelligent body is distributed according to the sensor of task intelligent body, and control sensor carries out detection tracking to target,
Complete the measurement to distributing target；Each sensor receives measurement, by agreement in advance, sends a mark or flight path to information and melts
Conjunction center, fusion center carries out a mark or Track Fusion, sends the related precision result for merging to task distribution intelligent body；
Step (6), task distribution intelligent body are compared to fusion results and mission requirements, are assessed, if target following
Result meets mission requirements precision, then wait until time tk+1Arrive, then carry out sensor of interest reallocation；If target following result
Mission requirements accuracy requirement is unsatisfactory for, target reallocation also can be in advance carried out, step (2) is returned to.
Effect of the invention can be further illustrated by following matlab emulation experiments：
Emulation experiment scene setting
Assuming that airborne platform 4, carries 1 radar on each platform, distance by radar precision is 75m, and azimuth accuracy is
0.2 °, position of platform coordinate is respectively (0,0), (20km, 0), (40km, 0), (60km, 0), platform formation flight, x, y direction
Speed is (100m/s, 100m/s)；Target changing coordinates be respectively (30km, 170km), (10km, 150km), (20km,
157km), (70km, 143km), x, y direction speed be respectively (150m/s, 100m/s), (100m/s, 150m/s), (150m/s,
100m/s), (100m/s, 150m/s), 4 target acquisition accuracy requirement thresholdings are 500m, 500m, 450m, 400m, 4 platforms
The maximum target capacity of upper radar is respectively 1,2,2,2；Matlab emulation experiments are carried out using the inventive method, accompanying drawing 2 is obtained
With the experimental result shown in accompanying drawing 3, wherein accompanying drawing 2 is the not allocation result of sensor target, accompanying drawing 3 in the same time in emulation experiment
It is the not relation of task tracking accuracy demand thresholding and distribution sensor combinations fusion accuracy in the same time in emulation experiment.
Simulation result and analysis：
The distribution for having obtained sensor of all targets is can be seen that by accompanying drawing 2, while the use of each sensor is equal
It is not above the limitation of itself maximum target capacity；By accompanying drawing 3 as can be seen that the distribution of sensor, allows all allocation results pair
The target acquisition precision answered can meet detection mission accuracy requirement in the vicinity of demand thresholding.
The sensor combinations of different target distribution can be in real time given due to the inventive method, also corresponding difference can be obtained
The target designation of sensor distribution, accordingly, it is capable to easily be transplanted to the information fusion system of multi-platform networking collaboration detection tracking
In, for manned platform provides Tactic selection and reference, for unmanned platform provides Based Intelligent Control.
Claims (2)
1. by the multi-platform sensor synergism management method of the sequential auction of task priority, it is characterised in that arranged including following technology
Apply：
Step (1), the setting different intelligent body function module first in different platform, including：Task is set on maneuvering platform
The intelligent module of distribution, is responsible for task distribution and the selection of sensor；Sensor management intelligent body mould is set on member's platform
Block, is responsible for collecting each platform sensor state, the working condition of management and control sensor, pattern；
The communication linkage that step (2), task distribution intelligent body pass through each platform, sends intelligent mobile agent to each platform in real time,
For detecting communication link, and collecting platform position, movable information, sensor type, mode of operation, current operating state,
Sensor detection accuracy；
Step (3), task distribution intelligent body according to the position of the target for having obtained, the position of movable information and each platform,
The detection angle scope of movable information and sensor is slightly matched to target and sensor, determines sensor on each platform
State xijk, wherein xijkSubscript i represent target designation, i=1,2,3 ..., I, I represent the sum of target, j represents platform
Numbering, j=1,2,3 ..., J, J represent the sum of platform, k represents the numbering of sensor, k=1,2,3 ..., K, K represent biography
The sum of sensor, xijk∈ { 0,1 }, if xijkK-th sensor of=1 j-th platform of expression can be arranged to target i, if xijk=
0, expression can not be arranged；Task distribution intelligent body is defeated according to acquired target location, movable information and other informations
Enter, goal task is divided, main task includes monitoring, tracking, identification, fire control, draws the precision demand of different task
Thresholding ηi, wherein, ηiSubscript i represent target designation；
Step (4), hypothesis current time are tk, to subsequent time tk+1Planned, task distribution intelligent body and sensor management
The common co-ordination of intelligent body, sensor selection and Target Assignment are realized according to the sequential auction system of the priority of task；
Task allocation result is transmitted to sensor management intelligent body by step (5), task distribution intelligent body using communication link, is passed
Sensor manages intelligent body and is distributed according to the sensor of task intelligent body, and control sensor carries out detection tracking to target, and it is right to complete
Distribute the measurement of target；Each sensor receives measurement, by agreement in advance, in sending a mark or flight path to information fusion
The heart, fusion center carries out a mark or Track Fusion, sends the related precision result for merging to task distribution intelligent body；
Step (6), task distribution intelligent body are compared to fusion results and mission requirements, are assessed, if target following result
Meet mission requirements precision, then wait until time tk+1Arrive, then carry out sensor of interest reallocation；If target following result is discontented with
Sufficient mission requirements accuracy requirement, also can in advance carry out target reallocation, return to step (2).
2. the multi-platform sensor synergism management method by the sequential auction of task priority according to claim 1, it is special
Levy be task in step (4) priority it is sequential using unilateral auction system realize sensor selection and target assignment method
It is specific to be divided into following steps again：
(21) in tkMoment task distribution intelligent body is sorted by priority to target, and determines i-th target tracking accuracy demand
ηi；Relative position relation, threat level and platform sensor investigative range, angle according to each target and each platform,
The limitation of detection accuracy determines price p of the different platform different sensors to different targetijk, wherein, i represents target designation, j
Platform numbering is represented, k represents sensor number；
By the price matrix P of different sensors in the corresponding different platforms of target iiIt is defined as
Task distribute intelligent body to each platform send intelligent mobile agent, intelligent mobile agent by with platform on sensor management
Intelligent body is interacted, and collects the sensor resource information of member's platform, determines that sensor resource matrix X, X are a three-dimensional matrice,
Each element xijk, xijk∈ { 0,1 }, xijkThe kth kind sensor of=1 expression j platforms can be arranged to target i, xijk=0 for not
Can arrange, by the corresponding sensor resource matrix X of target iiIt is defined as
(22) according to target prioritization, according to priority order from high to low takes out target i carries out auction, traversal sensing
Device resource matrix XiMiddle correspondence xijk=1 all the sensors combination Sim, wherein, SimRepresent that i-th target is passed for corresponding m-th
Sensor is combined, m=1, and 2 ..., sum that M, M are all combinations, respectively to the corresponding error in measurement square of each sensor combinations
Battle array is compressed fusion, obtains fusion accuracy Rim
Wherein, RimRepresent the fusion error co-variance matrix of corresponding m-th combination of target i, RjkRepresent the corresponding m of target i
Individual sensor combinations SimIn j-th platform, k-th sensor error be transformed into the error co-variance matrix after fusion center；If flat
When sensor is comprising infrared, electronic warfare passive sensor in platform, infrared and electronic warfare angular error can be pressed with radar
Contracting fusion, then changed；If flight path can be obtained during tracking, also can be by error in measurement matrix filtering error covariance
Instead of；
Respectively by the corresponding fusion error co-variance matrix R of each sensor combinationsimTracking accuracy thresholding corresponding with target i
ηiCompare, judge
Wherein, Matrix Calculating mark in bracket is sought in trace () expressions, when above formula is set up, then it represents that sensor combinations SimMesh can be met
The detection tracing task demand of i is marked, the combination that will can meet mission requirements is stored in allocation matrix DinIn,
Wherein, DinIn matrix, row represents platform numbering, and from 1 to J, J is maximum platform numbering, and row represent the corresponding sensing of platform
Device is numbered, and from 1 to K, K is numbered for maximum sensor；dik∈ { 0,1 }, dik=1 represents that the sensor distributes to target i, dik=0
Represent that the sensor is not allocated to target i；
p′in=sum (Pi·Din)
Wherein, p 'inExpression meets the corresponding price sum of combination of accuracy requirement for n-th, and sum () is represented to all units of matrix
Element summation；
[p′iI,ni]=min (p 'in, n=1,2,3 ..., N)
Wherein, p 'iIRepresent p 'inMiddle minimum price, niExpression obtains the numbering of the corresponding n of minimum price, and min () is represented and asked
Minimum value in bracket, N represents i-th maximum sensor number of combinations of aimed at precision demand of satisfaction；
By p 'iICompare with thresholding,
p′iI≤ηp
If above formula is set up, by niCorresponding distributionDistribute to target i；
(23) target that priority is taken second place, it is assumed that numbering is i ', takes out and is auctioned, first according to target i ' auctions before
Allocation matrixJudge whether the use of some sensors has reached maximum size, specific method is：Calculate sensor
Absorption matrix Dtotal,
Wherein,
By DtotalWith sensor tracking capacity matrix DhCorresponding element is compared one by one, wherein, Dh
Wherein, DhIn element hjkRepresent the maximum target number that k-th sensor in j-th platform can be tracked；
Calculate both only poor
Element in D is compared with 0, if a certain element is more than or equal to 0, if this element jth row and kth in D are arranged, then it is assumed that
Target of the target label in i ' afterwards can not be allocated k-th sensor determined on j platform, make the jth row in price matrix
With kth arrange price be equal to one level off to infinity real number, thus k-th sensor on j-th platform will no longer by
Other target selections；
(24) (23rd) step is returned to, after traveling through all targets, corresponding allocation matrix is obtainedAccording to matrixSet up K sensor in j-th platform and distribute to the I allocation matrix B of targetj,
The corresponding sensor allocation matrix B of similar all platforms1,B2,...,BJ, using intelligent mobile agent by B thereinjTransmission
To the sensor management intelligent body of corresponding j-th platform, sensor management intelligent body is allowed according to allocation matrix BjManagement sensing
Device is scanned, and completes the detection to target.
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