CN103841637B - Wireless object localization method, equipment and system - Google Patents
Wireless object localization method, equipment and system Download PDFInfo
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- CN103841637B CN103841637B CN201210486600.4A CN201210486600A CN103841637B CN 103841637 B CN103841637 B CN 103841637B CN 201210486600 A CN201210486600 A CN 201210486600A CN 103841637 B CN103841637 B CN 103841637B
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Abstract
The embodiment of the present invention provides a kind of wireless object localization method, equipment and system, and this is wireless, and object localization method includes：Cluster head node obtains measurement data, decorrelative transformation is carried out to measurement data and generates the effective measurement data of this cluster；Cluster head node carries out signal reconstruction and generates the signal reconstruction information of this cluster the 1st according to the effective measurement data of this cluster；Cluster head node generates this cluster u signal reconstruction information according to the signal reconstruction information of u 1 of other cluster head nodes in the effective measurement data of this cluster, the signal reconstruction information of this cluster u 1 and the observation area for sharing to, the step is repeated, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration；Cluster head node determines the position of the target to be positioned in observation area according to this cluster M signal reconstruction information.Wireless object localization method provided in an embodiment of the present invention, equipment and system, improve the robustness of wireless object locating system and the accuracy of positioning.
Description
Technical field
The present embodiments relate to the communication technology, more particularly to a kind of wireless object localization method, equipment and system.
Background technology
Wirelessly Technology for Target Location is mainly and is measured by the parameter of the radio wave to receiving, and according to surveying
The result for measuring data judges the position of target to be positioned.
A centralized information fusion center (FusionCenter, letter are usually provided with network alignment system
Claim FC) or centerized fusion base station (Base Station, abbreviation BS) and multiple detection nodes.Multiple detection nodes are detected simultaneously
The signal of object being measured radiation, and the characteristic information relevant with measured object body position carried in each signal is reported
FC or BS, calculates measured object body position and is positioned so as to complete many detection node joint objectives by it.This is network fixed
Position system is completely dependent on the FC or BS of centralization, and system robustness is relatively low, and when FC or BS occurs abnormal, whole alignment system will
Cannot run.
The content of the invention
The embodiment of the present invention provides a kind of wireless object localization method, equipment and system, and position system is demarcated to improve Psamminida
The robustness of system and the accuracy of positioning.
In a first aspect, the embodiment of the present invention provides a kind of wireless object localization method, including：
Cluster head node obtains measurement data, carries out decorrelative transformation to the measurement data and generate this cluster effectively to measure number
According to；
The cluster head node carries out signal reconstruction and generates the signal reconstruction of this cluster the 1st letter according to the described effective measurement data of cluster
Breath；
The cluster head node is according to the described effective measurement data of cluster, this cluster u-1 signal reconstructions information and shares to
The u-1 signal reconstruction information of other cluster head nodes in observation area generates this cluster u signal reconstruction information, repeats the step
Suddenly, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration, wherein, u and M is integer, and M >=u ＞ 1；
The cluster head node determines the target to be positioned in the observation area according to described cluster M signal reconstruction information
Position.
In the first possible implementation, the cluster head node carries out signal according to the described effective measurement data of cluster
The generation signal reconstruction information of this cluster the 1st is rebuild, specially：
The cluster head node application below equation generates the described signal reconstruction information of cluster the 1st
Wherein,
hiIt is the call number of the cluster head node, It is the cluster head node in the observation area
Set, H is the number of the cluster head node in the observation area；
It is the described effective measurement data of cluster, ε is error tolerance factor；
It is de-correlation-matrix,It is sampling matrix, ψ is rarefaction representation matrix；
Represent in constraintsUnder；
Represent and solve orderReach minimum value
With reference to the first possible implementation of first aspect or first aspect, in second possible implementation
In, the cluster head node is according to described the effective measurement data of cluster, this cluster u-1 signal reconstructions information and the area of observation coverage for sharing to
The u-1 signal reconstruction information of other cluster head nodes in domain generates this cluster u signal reconstruction information, specially：
The cluster head node application below equation generates described cluster u signal reconstruction information
Wherein,
It is the signal reconstruction information gap weight coefficient between cluster head node；
η is iterative constrained thresholding；
T represents the time, and t is integer, and t ＞ 0, t=u-1.
In the third possible implementation, the stopping criterion for iteration is specially：
The mesh to be positioned in the observation area that the cluster head node is determined according to described cluster u signal reconstructions information
Target position and the position according to the target to be positioned in the described observation area of cluster u-1 signal reconstructions information determination
It is identical.
In the 4th kind of possible implementation, the cluster head node obtains measurement data, specially：
The cluster head node receives the first measurement data that the detection node in the cluster head node coverage is reported, right
The signal of the target emanation to be positioned measures the second measurement data of acquisition, by first measurement data and described second
Measurement and Data Processing generate the measurement data.
In the 5th kind of possible implementation, the cluster head node carries out signal according to the described effective measurement data of cluster
Rebuild after the generation signal reconstruction information of this cluster the 1st, methods described also includes：
The signal reconstruction information sharing of described cluster the 1st is given described other cluster head nodes by the cluster head node；
The cluster head node is according to other cluster head sections in this cluster u-1 signal reconstructions information and the observation area for sharing to
The u-1 signal reconstruction information of point is generated after this cluster u signal reconstruction information, and methods described also includes：
The information sharing of described cluster u signal reconstruction is given described other cluster head nodes by the cluster head node.
Second aspect, the embodiment of the present invention provides a kind of cluster head node, including：
Measurement data acquiring unit, for obtaining measurement data, decorrelative transformation generation is carried out to the measurement data originally
The effective measurement data of cluster；
First processing units, are connected with the measurement data acquiring unit, for according to the described effective measurement data of cluster
Carry out signal reconstruction and generate the signal reconstruction information of this cluster the 1st；
Second processing unit, is connected, for root with the measurement data acquiring unit and the first processing units respectively
According to other cluster head sections in the described effective measurement data of cluster, this cluster u-1 signal reconstructions information and the observation area for sharing to
The u-1 signal reconstruction information of point generates this cluster u signal reconstruction information, repeats the step, until this cluster M signals for generating
Reconstruction information meets stopping criterion for iteration, wherein, u and M is integer, and M >=u ＞ 1；
Positioning unit, is connected with the second processing unit, for determining institute according to described cluster M signal reconstruction information
State the position of the target to be positioned in observation area.
In the first possible implementation, the first processing units are described specifically for the generation of application below equation
The signal reconstruction information of this cluster the 1st
Wherein,
hiIt is the call number of the cluster head node, It is the cluster head node in the observation area
Set, H is the number of the cluster head node in the observation area；
It is the described effective measurement data of cluster, ε is error tolerance factor；
It is de-correlation-matrix,It is sampling matrix, ψ is rarefaction representation matrix；
Represent in constraintsUnder；
Represent and solve orderReach minimum value
With reference to the first possible implementation of second aspect or second aspect, in second possible implementation
In, the second processing unit generates described cluster u signal reconstruction information specifically for application below equation
Wherein,
It is the signal reconstruction information gap weight coefficient between cluster head node；
η is iterative constrained thresholding；
T represents the time, and t is integer, and t ＞ 0, t=u-1.
In the third possible implementation, the measurement data acquiring unit is additionally operable to receive the cluster head node to be covered
The first measurement data that detection node in the range of lid is reported, the signal to the target emanation to be positioned measures acquisition
Two measurement data, the measurement data is generated by first measurement data and second Measurement and Data Processing.
In the third possible implementation, the first processing units are additionally operable to the described signal reconstruction of cluster the 1st
Described other cluster head nodes are given in information sharing；
The second processing unit is additionally operable to the information sharing of described cluster u signal reconstruction to described other cluster head sections
Point.
The third aspect, the embodiment of the present invention provides a kind of wireless object locating system, including is distributed in observation area
Multiple detection nodes, also include：
At least two cluster head nodes provided in an embodiment of the present invention, at least two cluster head node is evenly distributed on described
In observation area.
As shown from the above technical solution, wireless object localization method provided in an embodiment of the present invention, equipment and system, cluster head
Node obtains measurement data, decorrelative transformation is carried out to measurement data and generates the effective measurement data of this cluster, is effectively surveyed according to this cluster
Amount data carry out signal reconstruction and generate the signal reconstruction information of this cluster the 1st, according to the effective measurement data of this cluster, this cluster u-1 signals
The u-1 signal reconstruction information of other cluster head nodes in reconstruction information and the observation area for sharing to generates this cluster u signals
Reconstruction information, repeats the step, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration, according to this cluster M
Signal reconstruction information determines the position of the target to be positioned in observation area.Due in observation area dispose cluster head node be to
Few two, it is to avoid to a dependence for Centroid, improve the robustness and robustness of wireless object locating system.And
And, cluster head node does not update the reconstruction signal of previous step in iteration in the iteration renewal process of signal reconstruction merely with this cluster
Information, also uses the reconstruction signal information of other cluster head nodes in observation area to improve the reconstruction of itself of this cluster head node
As a result, the global and accurate positioning to the target to be positioned in whole observation area is realized, the accuracy of positioning is improve.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are this hairs
Some bright embodiments, for those of ordinary skill in the art, without having to pay creative labor, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is that Psamminida provided in an embodiment of the present invention demarcates position method flow diagram；
Fig. 2 is that wireless location system provided in an embodiment of the present invention disposes schematic diagram；
Fig. 3 is cluster head node structural representation provided in an embodiment of the present invention；
Fig. 4 is that Psamminida provided in an embodiment of the present invention demarcates position system structure diagram.
Specific embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
Fig. 1 is that Psamminida provided in an embodiment of the present invention demarcates position method flow diagram.As shown in figure 1, the present embodiment is provided
The wireless object localization method wireless location process that specifically can apply to the target to be positioned in observation area, this implementation
The wireless object localization method that example is provided is specifically included：
Step 10, cluster head node obtain measurement data, and decorrelative transformation is carried out to the measurement data, and to generate this cluster effective
Measurement data；
Specifically, the quantity of the target to be positioned in observation area can be one or more, can be in advance in the area of observation coverage
At least two cluster head nodes and multiple detection nodes are disposed in domain.Cluster head node is specifically as follows wireless sensor node or wireless
The Wireless Communication Equipment such as routing device, it is preferable that at least two cluster head nodes are uniformly deployed in observation area, cluster head node
Quantity can be set according to the size of the coverage of each cluster head node and the observation area, to cause uniformly to be deployed in
Cluster head node in the observation area can be by the observation area all standing.Detection node is specifically as follows wireless sensor node
Deng with radiation signal is measured and reporting ability Wireless Communication Equipment, detection node deployment but random, example
Such as, can make great efforts be distributed according to Gaussian Profile, shellfish, the random distribution rule such as be uniformly distributed to realize.When having been deposited in observation area
In multiple Wireless Communication Equipment, can also be configured by Wireless Communication Equipment, Wireless Communication Equipment is configured to
Cluster head node or detection node.Preferably, Connected degree Wireless Communication Equipment higher can be selected as cluster head node, to protect
Card cluster head node can obtain the measurement data of abundance.
Detection node can be measured to the signal that the target to be positioned in observation area is radiated, and obtain local measurement
Measurement data is reported data, detection node the cluster head node for covering the detection node, when detection node is at least two clusters
When in the coverage of first node, local measurement data are reported at least two cluster head node by the detection node respectively.Cluster
First node itself can also have the measurement capability of the signal radiated to target to be positioned, then cluster head node is receiving detection section
While the measurement data that point is reported, the signal that the target to be positioned in observation area is radiated can also be measured to obtain
To measurement data.The measurement data that detection node or cluster head node are measured specially received signal strength (Received
SignalStrength, abbreviation RSS), by taking detection node as an example, by k-th signal of target emanation to be positioned, through radio transmission
The RSS that l-th detection node is reached after channel is：
RSS(dK, l)=Pt+Ke-10ηlg(dK, l/d0)+α+β；
Wherein, PtIt is the radiant power of target to be positioned, KeIt is envirment factor, η is the path loss factor, dK, lIt is to be treated from k-th
The distance at l-th detection node coordinate position is reached at positioning target coordinate positiond0
It is reference distance, α is the rapid fading factor, and β is the shadow fading factor.
It will be appreciated by those skilled in the art that in addition to above-mentioned wireless channel propagation model, the present disclosure applies equally to other
The wireless channel propagation model of species.And, for target positioning measurement data in addition to the RSS at each detection node, may be used also
To be that other can be used for the measurement data that target is positioned, the present invention is not limited thereto.
Fig. 2 is that wireless location system provided in an embodiment of the present invention disposes schematic diagram.As shown in Fig. 2 for convenience of description,
Whole observation area is expressed as a grid of n × n, included grid number is N, and numerically N=n2, below with observation
Region be two dimensional surface application scenarios as a example by illustrate, it will be appreciated by those skilled in the art that the present invention is simultaneously
It is not limited to the application scenarios of two dimensional surface, it may also be used for the application scenarios of three dimensions.
As shown in Fig. 2 deploying 4 cluster head nodes 81 and L detection node 82 (L ＜ ＜ N), 4 altogether in observation area
Individual cluster head node 81 is uniformly deployed in observation area, and the Connected degree of cluster head node 81 is higher.The covering model of cluster head node 81
The border circular areas that can be but be not limited to cluster head node 81 as the center of circle are enclosed, such as coverage of cluster head node 81 can also be
The other shapes such as sector.The coordinate of the position of cluster head node 81 is Wherein, hiIt is cluster head
The call number of node 81,It is the set of cluster head node 81, the gesture of setEqual to the number of cluster head node 81, as in Fig. 2 institutes
Under the application scenarios for showing, the number of cluster head node 81 is 4.The coordinate of the position of detection node 82 is { (xl, yl),When the coverage of cluster head node 81 is for circle, judge detection node 82 whether in certain cluster head node
In 81 coverage, can be by judging the distance between detection node 82 and the cluster head node 81 whether less than or equal to the cluster
The radius of the coverage of first node 81 determines, i.e.,：
Wherein,It is with hiFor the cluster of cluster head is indexed,It is the radius of the cluster.When detection node 82 and cluster head node 81
Distance meets above-mentioned condition, and the measurement data that detection node 82 will be measured reports cluster head node 81.
Cluster head node 81 realizes that the process positioned to target to be positioned 83 can be based on compressed sensing according to measurement data
(Compressive Sensing, abbreviation CS) technology.Cluster head node 81 carries out decorrelative transformation and is effectively surveyed to measurement data
Amount data, effective measurement data can specifically be expressed asWherein,It is sampling matrix, the sampling
For 1, other elements are element position (the row rope that value in 0, and each row is 1 to every a line only one of which element value of matrix
Draw position) correspond to cluster head node 81hiAnd the detection node 82 in the clusterPosition within a grid, that is, represent cluster
First node 81hiObtain at its own position and cluster in the measurement that detects at other each local node positions
Data,It is de-correlation-matrix,Wherein, orth () is orthogonalization, ()T
For transposition is operated,It is pseudo- inverse operation.It is measurement additive noise, represents in the collection of measurement data and visitor during reporting
See the noise for existing.
All n × n coordinate points in whole grid are arranged successively, and constitutes the target location vector θ of N × 1
(wherein N=n2), because potential K target is only occurred on K position in all N number of coordinate points, and these are to be positioned
The coordinate of the position of target 83 is { (x(k), y(k)),Because the number of target to be positioned 83 is much small
In the length (K ＜ ＜ N) of target location vector, therefore, only K nonzero element in target location vector θ and remaining N-K is individual
Element value is zero, so target location vector θ is sparse space.In the target positioning application scenarios based on CS, though
Right target location vector is sparse, but forms reception signal through the RSS that radio propagation channel is reached at each mesh point
Vectorial s is not directly sparse, but is embodied by rarefaction representation matrix ψ, and ψ is a matrix of N × N, and ψ reflects spoke
All potential site k ∈ [1, N] places that signal is likely to occur from all targets are penetrated to be passed through to all grid position l ∈ [1, N] places
The wireless channel influence gone through.Due in target positioning scene ψ andIt is that, in spatial domain, need be carried out by measurement data
Decorrelative transformation so that ψ andIt is orthogonal.
Step 20, the cluster head node carry out signal reconstruction and generate the letter of this cluster the 1st according to the described effective measurement data of cluster
Number reconstruction information；
Specifically, cluster head node 81 performs the initializing signal weight based on compressed sensing according to the effective measurement data of this cluster
Build, generate the signal reconstruction information of this cluster the 1st, the signal reconstruction information of this cluster the 1st is signal reconstruction in the cluster that initialization is obtained
Information.
Step 30, the cluster head node are according to the described effective measurement data of cluster, this cluster u-1 signal reconstructions information and are total to
The u-1 signal reconstruction information of other cluster head nodes in observation area enjoyed generates this cluster u signal reconstruction information, repeats
The step, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration, wherein, u and M is integer, and M >=u
＞ 1；
Specifically, each cluster head node 81 in observation area can be by initializing signal process of reconstruction and follow-up
The signal reconstruction information sharing generated in iteration renewal process.Cluster head node 81 can perform based on average homogeneity data fusion and
The iteration of compressed sensing signal reconstruction updates, in the iteration renewal process, by the effective measurement data of this cluster, this cluster u-1
The u-1 signal reconstruction information of other cluster head nodes in signal reconstruction information and the observation area for sharing to generates this cluster u
Signal reconstruction information, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration.The stopping criterion for iteration is specific
Can be true by the position of the target to be positioned of this cluster u-1 signal reconstructions information determination and this cluster u signal reconstruction information
The position of fixed target to be positioned is identical or essentially identical.
Step 40, the cluster head node determine treating in the observation area according to described cluster M signal reconstruction information
Position the position of target.
The wireless object localization method that the present embodiment is provided, cluster head node obtains measurement data, and measurement data is gone
Relevant treatment generates the effective measurement data of this cluster, and carrying out signal reconstruction according to the effective measurement data of this cluster generates the signal of this cluster the 1st
Reconstruction information, according to other in the effective measurement data of this cluster, this cluster u-1 signal reconstructions information and the observation area for sharing to
The u-1 signal reconstruction information of cluster head node generates this cluster u signal reconstruction information, repeats the step, until this cluster for generating
M signal reconstruction information meets stopping criterion for iteration, is determined according to this cluster M signal reconstruction information to be positioned in observation area
The position of target.Because the cluster head node disposed in observation area is at least two, it is to avoid to a dependence for Centroid,
Improve the robustness and robustness of wireless object locating system.And, iteration renewal process of the cluster head node in signal reconstruction
In, the reconstruction signal information of previous step in iteration is not updated merely with this cluster, also use other cluster head nodes in observation area
Reconstruction signal information improve the reconstructed results of itself of this cluster head node, realize to be positioned in whole observation area
The global and accurate positioning of target, improves the accuracy of positioning.
In the present embodiment, step 20, the cluster head node carries out signal reconstruction according to the described effective measurement data of cluster
The signal reconstruction information of this cluster the 1st is generated, is specifically as follows：
The cluster head node application below equation generates the described signal reconstruction information of cluster the 1st
Wherein,
hiIt is the call number of the cluster head node, It is the cluster head node in the observation area
Set, H is the number of the cluster head node in the observation area；
It is the described effective measurement data of cluster, ε is error tolerance factor；
It is de-correlation-matrix,It is sampling matrix, ψ is rarefaction representation matrix；
Represent in constraintsUnder；
Represent and solve orderReach minimum value
Specifically, the signal reconstruction information of this cluster the 1st is signal reconstruction information, initial runtime t in the initial cluster for obtaining
=0,It is the signal reconstruction information of this cluster the 1st.Above-mentioned formula is represented in constraintsUnder ask orderMinimumIt is specific solve can with convex optimization class algorithm or it is greedy follow the trail of class algorithm, the present invention not as
Limit, wherein, with the constraints of two normal formsFor the mistake of effective measurement data in about fascicle
Difference, wherein ε is error tolerance factor, such as ε=10-3, the object function of a normal formFor characterizing target location
Vectorial θ's is openness.Cluster head node can also be by the 1st signal reconstruction information sharing to other cluster head sections in observation area
Point.
In the present embodiment, step 30, the cluster head node is believed according to the described effective measurement data of cluster, this cluster u-1
The u-1 signal reconstruction information of other cluster head nodes in number reconstruction information and the observation area for sharing to generates this cluster u letters
Number reconstruction information, is specifically as follows：
The cluster head node application below equation generates described cluster u signal reconstruction information
Wherein,
It is the signal reconstruction information gap weight coefficient between cluster head node；
η is iterative constrained thresholding；
T represents the time, and t is integer, and t ＞ 0, t=u-1.
Specifically, cluster head node other following instants t=1 after initialization, 2 ..., using average homogeneity data fusion
Constraints be iterated renewal, respectively obtain this cluster u signal reconstruction information, t can be used to indicate iterative steps, t=
u-1。It is last moment this cluster head node hiSignal reconstruction result,It is last moment another cluster head node hj
Signal reconstruction result, its be between cluster head by last iteration moment Mo information sharing and obtain, introduce based on average
The effect of the constraints of consistent data fusion is, using this cluster head node in previous step iteration and other cluster head nodes
Signal reconstruction difference updates this cluster head node h to constrainiIn the signal reconstruction result that this is walked, η is iterative constrained thresholding, such as η
=10-3。
WhereinIt is the signal reconstruction information gap weight coefficient between cluster head node,Can be expressed as：
Wherein, hiRepresent this cluster head node, hjOther cluster head nodes in observation area are represented,Represent in observation area
Cluster head node set,Represent the number of the cluster head node in observation area.
After cluster head node iteration at a time updates operation, information sharing can also be carried out between cluster head node, with cluster
First node hiAs a example by, broadcast its this step signal reconstruction information vector to other cluster head nodesAnd receive other each simultaneously
Cluster head nodeThis step signal reconstruction information vector that broadcast comesIn this, as in next step renewal iteration
The reference information of previous step signal reconstruction.After this step iteration updates and terminates, if to carry out iteration next time update, it is necessary to
Be iterated end condition judgement, and according to court verdict come decide whether terminate the iteration renewal process.
In the present embodiment, the stopping criterion for iteration is specifically as follows：
The mesh to be positioned in the observation area that the cluster head node is determined according to described cluster u signal reconstructions information
Target position and the position according to the target to be positioned in the described observation area of cluster u-1 signal reconstructions information determination
It is identical.
Specifically, still according to above-mentioned u and the corresponding relation of moment t, stopping criterion for iteration can specifically be expressed as：
Wherein, λ is that target positions decision threshold, can be according to sparse vectorMiddle nonzero element amplitude sets, and for example may be used
It is set as the half of nonzero element average.Represent cluster head node hiIn previous step (i.e. during t-1
Carve) the middle coordinate position set for positioning target,Represent cluster head node hiIn this step (i.e. t)
The coordinate position set of middle positioned target, double equal signs "==" represent whether judgement left and right two ends are equal.Above-mentioned iteration updates
In each step position the coordinate position set of target in potentially include multiple elements, ifWithIncluded in element number and numerical value it is essentially equal, then the two is equal.In actual application
In, in the range of positioning accuracy request, stopping criterion for iteration it can also be provided thatWithEqual number exceedes preset value, Huo Zheyuan in approximately equal, such as the two included element
The difference of element is within preset range, it is believed that approximately equal.
If meeting stopping criterion in iteration condition, stop iteration renewal process, in the present embodiment, step 40, with last
The position of target to be positioned is determined as final determined by the M signal reconstruction information of the generation in an iteration renewal process
Position result, cluster head node can also notify that the detection node in the cluster head node coverage positions the positional information of target：
In the present embodiment, step 10, the cluster head node obtains measurement data, is specifically as follows：
The cluster head node receives the first measurement data that the detection node in the cluster head node coverage is reported, right
The signal of the target emanation to be positioned measures the second measurement data of acquisition, by first measurement data and described second
Measurement and Data Processing generate the measurement data.
Specifically, detection node is only used for measurement data and reports, and does not perform specific target localization process step, can
To reduce intra-system communication expense and computing cost, execution efficiency is improved.
In the present embodiment, in step 20, the cluster head node carries out signal weight according to the described effective measurement data of cluster
Build after the generation signal reconstruction information of this cluster the 1st, methods described also includes：
The signal reconstruction information sharing of described cluster the 1st is given described other cluster head nodes by the cluster head node；
In step 30, the cluster head node is according in this cluster u-1 signal reconstructions information and the observation area for sharing to
The u-1 signal reconstruction information of other cluster head nodes is generated after this cluster u signal reconstruction information, and methods described also includes：
The information sharing of described cluster u signal reconstruction is given described other cluster head nodes by the cluster head node.
Fig. 3 is cluster head node structural representation provided in an embodiment of the present invention.As shown in figure 3, the cluster that the present embodiment is provided
First node can specifically realize each step for the wireless object localization method that any embodiment of the present invention is provided, and implement
Journey will not be repeated here.The cluster head node that the present embodiment is provided can be through but not limited to wireless sensor node or wireless routing
The Wireless Communication Equipment such as equipment are realized.
The cluster head node that the present embodiment is provided specifically includes measurement data acquiring unit 11, first processing units 12, second
Processing unit 13 and positioning unit 14.The measurement data acquiring unit 11 is used to obtain measurement data, to the measurement data
Carry out decorrelative transformation and generate the effective measurement data of this cluster.The first processing units 12 and the measurement data acquiring unit 11
It is connected, the signal reconstruction information of this cluster the 1st is generated for carrying out signal reconstruction according to the described effective measurement data of cluster.Described second
Processing unit 13 is connected with the measurement data acquiring unit 11 and the first processing units 12 respectively, for according to described
The u-1 of other cluster head nodes in the effective measurement data of cluster, this cluster u-1 signal reconstructions information and the observation area for sharing to
Signal reconstruction information generates this cluster u signal reconstruction information, repeats the step, until this cluster M signal reconstruction information for generating
Meet stopping criterion for iteration, wherein, u and M is integer, and M >=u ＞ 1.The positioning unit 14 and the second processing unit
13 are connected, the position for determining the target to be positioned in the observation area according to described cluster M signal reconstruction information.
The cluster head node that the present embodiment is provided, measurement data acquiring unit 11 obtains measurement data, and measurement data is carried out
Decorrelative transformation generates the effective measurement data of this cluster, and first processing units 12 carry out signal reconstruction according to the effective measurement data of this cluster
The signal reconstruction information of this cluster the 1st is generated, second processing unit 13 is according to the effective measurement data of this cluster, this cluster u-1 signal reconstructions
The u-1 signal reconstruction information of other cluster head nodes in information and the observation area for sharing to generates this cluster u signal reconstructions
Information, repeats the step, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration, the basis of positioning unit 14
This cluster M signal reconstruction information determines the position of the target to be positioned in observation area.Due to the cluster head disposed in observation area
Node is at least two, it is to avoid to a dependence for Centroid, improves robustness and the Shandong of wireless object locating system
Rod.And, cluster head node does not update the weight of previous step in iteration in the iteration renewal process of signal reconstruction merely with this cluster
Build signal message, also use the reconstruction signal information of other cluster head nodes in observation area improve this cluster head node itself
Reconstructed results, realize the global and accurate positioning to the target to be positioned in whole observation area, improve positioning
Accuracy.
In the present embodiment, the first processing units 12 specifically can be used for generating described cluster using below equation
1 signal reconstruction information
Wherein,
hiIt is the call number of the cluster head node, It is the cluster head node in the observation area
Set, H is the number of the cluster head node in the observation area；
It is the described effective measurement data of cluster, ε is error tolerance factor；
It is de-correlation-matrix,It is sampling matrix, ψ is rarefaction representation matrix；
Represent in constraintsUnder；
Represent and solve orderReach minimum value
Specifically, the signal reconstruction information of this cluster the 1st is signal reconstruction information, initial runtime t in the initial cluster for obtaining
=0,It is the signal reconstruction information of this cluster the 1st.Above-mentioned formula is represented in constraintsUnder ask orderMinimumIt is specific solve can with convex optimization class algorithm or it is greedy follow the trail of class algorithm, the present invention not as
Limit, wherein, with the constraints of two normal formsFor the mistake of effective measurement data in about fascicle
Difference, wherein ε is error tolerance factor, such as ε=10-3, the object function of a normal formFor characterizing target location
Vectorial θ's is openness.Cluster head node can also be by the 1st signal reconstruction information sharing to other cluster head sections in observation area
Point.
In the present embodiment, the second processing unit 13 specifically can be used for generating described cluster using below equation
U signal reconstruction information
Wherein,
It is the signal reconstruction information gap weight coefficient between cluster head node；
η is iterative constrained thresholding；
T represents the time, and t is integer, and t ＞ 0, t=u-1.
Specifically, cluster head node other following instants t=1 after initialization, 2 ..., using average homogeneity data fusion
Constraints be iterated renewal, respectively obtain this cluster u signal reconstruction information, t can be used to indicate iterative steps, t=
u-1。It is last moment this cluster head node hiSignal reconstruction result,It is last moment another cluster head node hj
Signal reconstruction result, its be between cluster head by last iteration moment Mo information sharing and obtain, introduce based on average
The effect of the constraints of consistent data fusion is, using this cluster head node in previous step iteration and other cluster head nodes
Signal reconstruction difference updates this cluster head node h to constrainiIn the signal reconstruction result that this is walked, η is iterative constrained thresholding, such as η
=10-3。
WhereinIt is the signal reconstruction information gap weight coefficient between cluster head node,Can be expressed as：
Wherein, hiRepresent this cluster head node, hjOther cluster head nodes in observation area are represented,Represent in observation area
Cluster head node set,Represent the number of the cluster head node in observation area.
After cluster head node iteration at a time updates operation, information sharing can also be carried out between cluster head node, with cluster
First node hiAs a example by, broadcast its this step signal reconstruction information vector to other cluster head nodesAnd receive other each simultaneously
Cluster head nodeThis step signal reconstruction information vector that broadcast comesIn this, as in next step renewal iteration
The reference information of previous step signal reconstruction.After this step iteration updates and terminates, if to carry out iteration next time update, it is necessary to
Be iterated end condition judgement, and according to court verdict come decide whether terminate the iteration renewal process.
In the present embodiment, the measurement data acquiring unit 11 is additionally operable to receive in the cluster head node coverage
The first measurement data that detection node is reported, the signal to the target emanation to be positioned measures the measurement number of acquisition second
According to by first measurement data and second Measurement and Data Processing generation measurement data.
Specifically, detection node is only used for measurement data and reports, and does not perform specific target localization process step, can
To reduce intra-system communication expense and computing cost, execution efficiency is improved.
In the present embodiment, the first processing units 12 can be also used for being total to the described signal reconstruction information of cluster the 1st
Enjoy to described other cluster head nodes.The second processing unit 13 can be also used for being total to described cluster u signal reconstruction information
Enjoy to described other cluster head nodes.
Fig. 4 is that Psamminida provided in an embodiment of the present invention demarcates position system structure diagram.As shown in figure 4, the present embodiment
The wireless object locating system for providing can specifically realize each of the wireless object localization method that any embodiment of the present invention is provided
Individual step, the process of implementing will not be repeated here.The wireless object locating system that the present embodiment is provided, including it is distributed in observation
Multiple detection nodes in region, also include：The cluster head node that at least two any embodiments of the present invention are provided, described at least two
Individual cluster head node is evenly distributed in the observation area.
Wireless object locating system shown in Fig. 4 includes 2 cluster head nodes and 6 detection nodes, 2 cluster head node difference
Detected for 812,6 detection nodes of the first cluster head node 811 and the second cluster head node are respectively the first detection node 821, second
Node 822, the 3rd detection node 823, the 4th detection node 824, the 5th detection node 825 and the 6th detection node 826.Its
In, the covering model of the first detection node 821, the second detection node 822 and the 3rd detection node 823 in the first cluster head node 811
In enclosing, the 3rd detection node 823, the 4th detection node 824, the 5th detection node 825 and the 6th detection node 826 are in the second cluster
In the coverage of first node 812, i.e. the 3rd detection node 823 is not only in the coverage of the first cluster head node 811 but also
In the coverage of two cluster head nodes 812.
The wireless object locating system that the present embodiment is provided, by least two cluster head sections of uniform deployment in observation area
Point, each cluster head node obtains measurement data, decorrelative transformation is carried out to measurement data and generates the effective measurement data of this cluster, according to
The effective measurement data of this cluster carries out signal reconstruction and generates the signal reconstruction information of this cluster the 1st, according to the effective measurement data of this cluster, this cluster
The u-1 signal reconstructions information generation of other cluster head nodes in u-1 signal reconstructions information and the observation area for sharing to is originally
Cluster u signal reconstruction information, repeats the step, until this cluster M signal reconstruction information for generating meets stopping criterion for iteration, root
The position of the target to be positioned in observation area is determined according to this cluster M signal reconstruction information.Avoid to Centroid
Rely on, improve the robustness and robustness of wireless object locating system.And, cluster head node updates in the iteration of signal reconstruction
During, the reconstruction signal information of previous step in iteration is not updated merely with this cluster, also use other cluster heads in observation area
The reconstruction signal information of node improves the reconstructed results of itself of this cluster head node, realizes to treating in whole observation area
The global and accurate positioning of target is positioned, the accuracy of positioning is improve.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above method embodiment can pass through
Programmed instruction related hardware is completed, and foregoing program can be stored in a computer read/write memory medium, the program
Upon execution, the step of including above method embodiment is performed；And foregoing storage medium includes：ROM, RAM, magnetic disc or light
Disk etc. is various can be with the medium of store program codes.
Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
The present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those within the art that：It still may be used
Modified with to the technical scheme described in foregoing embodiments, or equivalent is carried out to which part technical characteristic；
And these modifications or replacement, do not make the scope of the essence disengaging various embodiments of the present invention technical scheme of appropriate technical solution.
Claims (10)
1. a kind of wireless object localization method, it is characterised in that including：
Cluster head node obtains measurement data, decorrelative transformation is carried out to the measurement data and generates the effective measurement data of this cluster；
The cluster head node carries out signal reconstruction and generates the signal reconstruction information of this cluster the 1st according to the described effective measurement data of cluster；
The cluster head node is according to described the effective measurement data of cluster, this cluster u-1 signal reconstructions information and the observation for sharing to
The u-1 signal reconstruction information of other cluster head nodes in region generates this cluster u signal reconstruction information, repeats the step, directly
This cluster M signal reconstruction information to generation meets stopping criterion for iteration, wherein, u and M is integer, and M >=u ＞ 1；
The cluster head node determines the position of the target to be positioned in the observation area according to described cluster M signal reconstruction information
Put；
The cluster head node carries out signal reconstruction and generates the signal reconstruction information of this cluster the 1st according to the described effective measurement data of cluster,
Specially：
The cluster head node application below equation generates the described signal reconstruction information of cluster the 1st
Wherein,
hiIt is the call number of the cluster head node,| H |=H, H are the set of the cluster head node in the observation area,
H is the number of the cluster head node in the observation area；
It is the described effective measurement data of cluster, ε is error tolerance factor；
It is de-correlation-matrix,It is sampling matrix, Ψ is rarefaction representation matrix；
Represent in constraintsUnder；
Represent and solve orderReach minimum value
2. wireless object localization method according to claim 1, it is characterised in that the cluster head node is according to described cluster
The u-1 letters of other cluster head nodes in effective measurement data, this cluster u-1 signal reconstructions information and the observation area for sharing to
Number reconstruction information generates this cluster u signal reconstruction information, specially：
The cluster head node application below equation generates described cluster u signal reconstruction information
Wherein,
It is the signal reconstruction information gap weight coefficient between cluster head node；
η is iterative constrained thresholding；
T represents the time, and t is integer, and t ＞ 0, t=u-1.
3. wireless object localization method according to claim 1, it is characterised in that the stopping criterion for iteration is specially：
The target to be positioned in the observation area that the cluster head node is determined according to described cluster u signal reconstructions information
Position and the position phase according to the target to be positioned in the described observation area of cluster u-1 signal reconstructions information determination
Together.
4. wireless object localization method according to claim 1, it is characterised in that the cluster head node obtains measurement number
According to specially：
The cluster head node receives the first measurement data that the detection node in the cluster head node coverage is reported, to described
The signal of target emanation to be positioned measures the second measurement data of acquisition, by first measurement data and second measurement
Data processing generates the measurement data.
5. wireless object localization method according to claim 1, it is characterised in that：
The cluster head node according to the described effective measurement data of cluster carry out signal reconstruction generate the signal reconstruction information of this cluster the 1st it
Afterwards, methods described also includes：
The signal reconstruction information sharing of described cluster the 1st is given described other cluster head nodes by the cluster head node；
The cluster head node is according to other cluster head nodes in this cluster u-1 signal reconstructions information and the observation area for sharing to
U-1 signal reconstruction information is generated after this cluster u signal reconstruction information, and methods described also includes：
The information sharing of described cluster u signal reconstruction is given described other cluster head nodes by the cluster head node.
6. a kind of cluster head node, it is characterised in that including：
Measurement data acquiring unit, for obtaining measurement data, carries out decorrelative transformation and generates this cluster having to the measurement data
Effect measurement data；
First processing units, are connected with the measurement data acquiring unit, for being carried out according to the described effective measurement data of cluster
Signal reconstruction generates the signal reconstruction information of this cluster the 1st；
Second processing unit, is connected, for according to institute with the measurement data acquiring unit and the first processing units respectively
State other cluster head nodes in the effective measurement data of this cluster, this cluster u-1 signal reconstructions information and the observation area that shares to
U-1 signal reconstruction information generates this cluster u signal reconstruction information, repeats the step, until this cluster M signal reconstructions for generating
Information meets stopping criterion for iteration, wherein, u and M is integer, and M >=u ＞ 1；
Positioning unit, is connected with the second processing unit, for determining the sight according to described cluster M signal reconstruction information
The position of the target to be positioned surveyed in region；
The first processing units generate the described signal reconstruction information of cluster the 1st specifically for application below equation
Wherein,
hiIt is the call number of the cluster head node,| H |=H, H are the set of the cluster head node in the observation area,
H is the number of the cluster head node in the observation area；
It is the described effective measurement data of cluster, ε is error tolerance factor；
It is de-correlation-matrix,It is sampling matrix, Ψ is rarefaction representation matrix；
Represent in constraintsUnder；
Represent and solve orderReach minimum value
7. cluster head node according to claim 6, it is characterised in that：The second processing unit is following specifically for application
Formula generates described cluster u signal reconstruction information
Wherein,
It is the signal reconstruction information gap weight coefficient between cluster head node；
η is iterative constrained thresholding；
T represents the time, and t is integer, and t ＞ 0, t=u-1.
8. cluster head node according to claim 6, it is characterised in that：
The measurement data acquiring unit is additionally operable to detection node is reported first received in the cluster head node coverage
Measurement data, the signal to the target emanation to be positioned measures the second measurement data of acquisition, and number is measured by described first
The measurement data is generated according to second Measurement and Data Processing.
9. cluster head node according to claim 6, it is characterised in that：
The first processing units are additionally operable to the signal reconstruction information sharing of described cluster the 1st to described other cluster head nodes；
The second processing unit is additionally operable to the information sharing of described cluster u signal reconstruction to described other cluster head nodes.
10. a kind of wireless object locating system, including it is distributed in the multiple detection nodes in observation area, it is characterised in that also
Including：
At least two cluster head nodes as described in claim 6-9 is any, at least two cluster head node is evenly distributed on institute
State in observation area.
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