CN104239725B - Dynamic optimal managing method for multisource sensor - Google Patents
Dynamic optimal managing method for multisource sensor Download PDFInfo
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- CN104239725B CN104239725B CN201410484457.4A CN201410484457A CN104239725B CN 104239725 B CN104239725 B CN 104239725B CN 201410484457 A CN201410484457 A CN 201410484457A CN 104239725 B CN104239725 B CN 104239725B
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Abstract
The invention discloses a dynamic optimal managing method for a multisource sensor and belongs to the technical field of data analysis. The method comprises the following steps: confirming the next working sensor according to an established decision table and a target attribute value Vk sensed by a present working sensor Sk on the basis of pretreatment: firstly, respectively calculating the local attribute importance sigl of each sensor Si except Sk; forming a first set of Sk by the targets with Vk in the target attribute values corresponding to Sk on the basis of the system decision table; forming an association class by the targets with same target attribute values in the target attribute values corresponding to Si in the targets contained in the first set; forming a first association set of Si by each association class; defining the quotient of the quantity of the elements of the first association set of Si and the quantity of the elements of the first set of Sk and confirming sigl of Sk related to Si; selecting the sensor with the maximal sigl as the next working sensor. The method provided by the invention is used for scheduling and managing the multisource sensor, the use ratio of resources is high and the detection efficiency is high.
Description
Technical field
The invention belongs to data analysis technique field, and in particular to the management and running to Multiple Source Sensor.
Background technology
Effect of the sensor management to data fusion is constantly paid attention to by researcher, progressively becomes the one of data fusion
Individual control centre is carrying out the planning of many source detection resources with deployment.This Data fusion technique is desirable to be incorporated into intellectuality
Information processing system, its method is to confer to sensor terminal in autonomy, when sensor individuals detect external information it
Afterwards, certain behavior can be made to it, the behavior can change the environment of surrounding or internal system state to reach certain
Purpose is planted, and when sensor individuals are after some enlightenment hint informations are perceived, can be taken action so that the follow-up state of affairs
Developing direction be conducive to the direction of itself to be developed.Simultaneously also by the communication for information between multisensor syste, strengthen
Perception of each sensor terminal to environment, anticipation detects the development trend of event, the resource optimization ability of strengthening system.
Sensor management realizes the configuration to detecting resource usually from time, space and mode of operation.Time manages
Reason is exactly to be matched between the enterprising line sensor of Annual distribution and detection target, to plan and adopt specific biography in special time
Sensor obtains the characteristic information of specific objective.Space management is primarily directed to sensor in the deployment of space to the excellent of target acquisition
Gesture is being optimized deployment.Conventional Multiple Source Sensor way to manage has：The method analyzed using mathematical probabilities is directed to uncertain
Property information environment under sensor management require make optimization method；For the Doppler and angle that are used in terms of target following
Degree detection information, the algorithm using mathematical optimization of proposition is carrying out sensor resource management；Artificial intelligence based on Greedy
Optimized algorithm is carrying out the selection of optimal detection means；Sensor management etc. is carried out using theory of information.It is above-mentioned that multi-source is passed
The way to manage of sensor is fixed schedule mode, low to resource utilization ratio.It is therefore desirable to proposing that a kind of utilization rate is higher
Scheduling mode.
The content of the invention
The present invention goal of the invention be：For above-mentioned problem, there is provided a kind of dynamic Multiple Source Sensor optimization pipe
Reason method.
The dynamic Multiple Source Sensor optimum management method of the present invention, comprises the following steps：
Step 1：Pretreatment：Operation Multiple Source Sensor system, based on the current target information constructing system decision table for perceiving,
In the system decision-making table, there are a corresponding Target Attribute values in each target under each sensor；
Step 2：Sensor S based on work at presentkThe Target Attribute values V of the current goal for being perceivedkAnd the system decision-making
Table, it is determined that perceiving the sensor of the next work of current goal：
Step 201：Calculate respectively and remove sensor Sk(not perceiving all the sensors of current goal) each sensor S outwardi
Part Importance of Attributes degree：
Based on the system decision-making table, in sensor SkIn corresponding Target Attribute values, by with Target Attribute values Vk's
Target configuration sensor SkFirst set；In the sensor SkFirst set included by target in, in sensor SiInstitute
In corresponding Target Attribute values, by one association class of target configuration with same target property value, it is made up of each association class
Sensor SiThe first relation integration；Define sensor SiThe first relation integration element number and sensor SkFirst collection
The business of the element number of conjunction determines sensor SiWith regard to SkPart Importance of Attributes degree；
Step 202：The maximum sensor of part Importance of Attributes degree is taken as the sensor of next work.
Can will be calculated based on step 201 in Sensor scheduling in above-mentioned perception to either objective
The part Importance of Attributes degree of all sensors for not perceiving current goal of system order from high in the end is ranked up and obtains
Sensor scheduling order with regard to perceiving current goal, it is also possible to based on predetermined threshold value, take front M part Importance of Attributes degree most
Big sensor, is ranked up from high in the end.
In order to further lift the scheduling accuracy of the present invention, the step 2 of the present invention also includes：
Step 203：Judge determined by step 202 the part Importance of Attributes degree of sensor of next work whether etc.
In 1；If so, the Sensor scheduling for perceiving current goal, the sensing results and system based on the current sensor for determining then are terminated
Decision table is identified to current goal；Otherwise execution step 204；
Step 204：Calculating does not perceive each sensor S of current goaljPart Importance of Attributes degree：
According to formulaDetermine sensor SjN+1 relation integration C, wherein, set A is represented
The N relation integrations of the sensor of the next work of current selected, set B represents sensor SjThe first relation integration, N's
Value is equal to the number of times of execution step 203；
Define sensor SiN+1 relation integrations element number and sensor SkFirst set element number
Business is sensor SiWith regard to SkPart Importance of Attributes degree；
Step 205：The maximum sensor of part Importance of Attributes degree is taken as the sensor of next work, if currently
There is no the sensor for not perceiving current goal in Jing, then the sensing results and system decision-making table pair based on the current sensor for determining
Current goal is identified；Otherwise continue executing with step 203.
In sum, as a result of above-mentioned technical proposal, the invention has the beneficial effects as follows：It is fixed mode with existing
Scheduling mode is compared, sensing results of the present invention based on the sensor of work at present carrying out the scheduling of other sensors, its money
Source utilization rate is high, and the detection efficient of dynamic Multiple Source Sensor system is high.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, with reference to embodiment, the present invention is made into
One step ground is described in detail.
Embodiment
Multiple Source Sensor system operation for a period of time after, using normalized method by extraterrestrial target in different sensors work
The characteristic information perceived under operation mode is processed, and then forms corresponding sensor senses attribute primary system using fuzzy clustering
Meter information, obtains system decision-making table, and the process step is prior art, is no longer described in detail herein.System decision-making table in the present embodiment
For Space object identification decision table, shown in concrete table 1：
The extraterrestrial target discrete decision table of table 1
Wherein Target Attribute values Vmean1=0.83, corresponding variance is Vvar1=0.21, Target Attribute values Vmean2=0.2,
Corresponding variance is Vvar2=0.12.
Because in follow-up calculating process, can frequently use the first set of each sensor, therefore counted in advance
Calculate, can obtain, the sensor of work at present is respectively S1～S5When, the Target Attribute values for perceiving are respectively Vmean1And Vmean2
When the object element that included of corresponding first set be respectively：
With the sensor of work at present as S1, objective attribute target attribute P1Afterwards, Target Attribute values are obtained for Vmean1, i.e. P1=Vmean1
As a example by, then sensor S2～S5The first relation integration be expressed as follows respectively：
Sensor S2：
Sensor S3：
Sensor S4：
Sensor S5：
Therefore can obtain with regard to each first relation integration and sensor S1First set
Part Importance of Attributes degree siglRespectively：
Wherein card (POS (D)) represents the element number of corresponding set in bracket.
It can be seen that objective attribute target attribute P2Part Importance of Attributes degree it is maximum (when there is two or more maximum arranged side by side
When, arbitrary selection one), so next step sensor S2 removes the Target Attribute values for perceiving current goal, and because mesh
Mark attribute P2Relative priority P1=Vmean1Part Importance of Attributes degree be 1, so current goal no longer needs other sensors
Go to obtain other property values, it is already possible to correct identification：P1=Vmean1→P2=Vmean1→T1If (sensor S2 is perceived
Target Attribute values are Vmean1, can determine that current goal is real goal T based on table 11), or P1=Vmean1→P2=Vmean2→
T2.The Sensor scheduling order of correspondence current goal is S1→S2。
With the sensor of work at present as S1, objective attribute target attribute P1Afterwards, P1=Vmean2As a example by, then the of sensor S2～S5
One relation integration is expressed as follows respectively：
Sensor S2：
Sensor S3：
Sensor S4：
Sensor S5：
Obtain with regard to above-mentioned first relation integration and sensor S1First set
Part Importance of Attributes degree siglRespectively：
It is thus determined that next step sensor S2Or S3、S5(S is selected in the present embodiment2) go to perceive the target of current goal
Property value, due to its siglEqual to 2/3, therefore according to formulaDetermine sensor Sj(N+
1) relation integration C, wherein set A respective sensors S2N (because currently only perform once judge determined by next step
The sig of sensorlWhether be equal to 1, so when N=1) relation integration, set B represents sensor Sj(j=3,4,5) first
Relation integration.SjThe second relation integration C be listed below respectively：
Sensor S3：
Wherein：SetEqual to any two unit in the two set
The set of the common factor composition of element；It is the objective attribute target attribute (P described above that subscript is identified2、P3To goal set
Divide (there is same alike result value to be divided into a class).
Sensor S4：
Sensor S5：
Based on SjThe second relation integration and S1First setSiglRespectively
For：
From the foregoing, it will be observed that only needing reusable sensor S3Or S5(S is selected in the present embodiment3) obtain objective attribute target attribute P3, you can with just
Really differentiate target, i.e.,：
P1=Vmean2→P2=Vmean2→P3=Vmean2→T3
P1=Vmean2→P2=Vmean1→P3=Vmean1→T4
P1=Vmean2→P2=Vmean2→P3=Vmean1→T5
The invention is not limited in aforesaid specific embodiment.The present invention is expanded to and any in this manual disclosed
New feature or any new combination, and the arbitrary new method that discloses or the step of process or any new combination.
Claims (2)
1. a kind of dynamic Multiple Source Sensor optimum management method, it is characterised in that comprise the following steps：
Step 1：Pretreatment：Operation Multiple Source Sensor system, it is described based on the current target information constructing system decision table for perceiving
In system decision-making table, there are a corresponding Target Attribute values in each target under each sensor；
Step 2：Sensor S based on work at presentkThe Target Attribute values V of the current goal for being perceivedkWith system decision-making table, really
Surely the sensor of the next work of current goal is perceived：
Step 201：Calculate respectively and remove sensor SkOuter each sensor SiPart Importance of Attributes degree：
Based on the system decision-making table, in sensor SkIn corresponding Target Attribute values, by with Target Attribute values VkTarget
Constitute sensor SkFirst set；In the sensor SkFirst set included by target in, in sensor SiIt is corresponding
Target Attribute values in, by one association class of target configuration with same target property value, sensing is constituted by each association class
Device SiThe first relation integration；
Define sensor SiThe first relation integration element number and sensor SkFirst set element number business determine
Sensor SiWith regard to SkPart Importance of Attributes degree；
Step 202：The maximum sensor of part Importance of Attributes degree is taken as the sensor of next work.
2. the method for claim 1, it is characterised in that the step 2 also includes：
Step 203：Whether the part Importance of Attributes degree for judging the sensor of next work determined by step 202 is equal to 1；
If so, the Sensor scheduling for perceiving current goal, the sensing results and the system decision-making based on the current sensor for determining then are terminated
Table is identified to current goal；Otherwise execution step 204；
Step 204：Calculating does not perceive each sensor S of current goaljPart Importance of Attributes degree：
According to formulaDetermine sensor SjN+1 relation integration C, wherein, set A is represented
The N relation integrations of the sensor of the next work of current selected, set B represents sensor SjThe first relation integration, N's
Value is equal to the number of times of execution step 203；
Define sensor SiN+1 relation integrations element number and sensor SkThe business of element number of first set be
Sensor SiWith regard to SkPart Importance of Attributes degree；
Step 205：The maximum sensor of part Importance of Attributes degree is taken as the sensor of next work, if currently not
Presence does not perceive the sensor of current goal, then the sensing results and system decision-making table based on the current sensor for determining are to current
Target is identified；Otherwise continue executing with step 203.
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Address after: No.3, 11th floor, building 6, no.599, shijicheng South Road, Chengdu hi tech Zone, China (Sichuan) pilot Free Trade Zone, Chengdu, Sichuan 610041 Patentee after: Houpu clean energy (Group) Co.,Ltd. Address before: 610041 China (Sichuan) pilot Free Trade Zone No.3, 11th floor, building 6, no.599, shijicheng South Road, Chengdu high tech Zone Patentee before: Houpu clean energy Co.,Ltd. |
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