CN106792982A - A kind of direct localization method of multiple target based on self adaptation clustering algorithm - Google Patents
A kind of direct localization method of multiple target based on self adaptation clustering algorithm Download PDFInfo
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- H—ELECTRICITY
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Abstract
The invention belongs to field of signal processing, there is provided a kind of direct localization method of multiple target based on self adaptation clustering algorithm, it is used to solve the problems, such as Multi-target position.Present invention receiver each first receives the discrete reception signal x that its signal for corresponding to emitter transmitting obtains base band respectivelyk[n], then with its neighborhood in belong to a receiver for elementary unit groups together and carry out discrete reception signal exchange；Then each receiver calculates median ApproximationCarry out each receiver again carries out median with all receivers in its neighborhoodExchange and calculate adaptive updates attachment coefficient b 'lk(n), last each receiver calculated target positions estimateThe present invention realizes the sub-clustering of receiver network by adaptive updates attachment coefficient, and then realizes that multiple target is positioned simultaneously.
Description
Technical field
The invention belongs to field of signal processing, the multiple target distributed self-adaption of more particularly to wireless sensor network is straight
Localization method is connect, a kind of direct localization method of the multiple target based on self adaptation clustering algorithm is specifically provided.
Background technology
The passive direct orientation problem of radio frequency sending set, as a signal transacting and the important research side of the communications field
To of increased attention；The localization method of reaching time-difference (TDOA) is wherein based on, because the simplicity of its realization
Receive greatly to pursue with the accuracy for positioning.Traditional location algorithm based on the time difference is main by bipartition, first by receiving
Signal estimates time difference value, then carries out position resolving using the time difference value for estimating；What but traditional two-stage process was obtained
Estimate not optimal estimation, especially in the case of low signal-to-noise ratio, positioning precision is impaired serious.
In order to improve positioning precision, it is proposed that direct localization method, direct localization method can be divided into again batch processing method with
The class of adaptive approach two.Batch processing method needs the grid type that two dimension or three-dimensional are carried out to positioning region to search for, and amount of calculation is very big,
And the ability without target following；Although the method positioning precision of self adaptation is more slightly lower than the method precision of batch processing,
The amount of calculation of the method is fewer than the method for batch processing a lot, and possesses the ability of target following.
And the direct location algorithm of self adaptation be divided into centralization and it is distributed；Method based on centralized architecture, will
The signal that each receiver is received in network is all delivered to fusion center, and does positions calculations in fusion center；However, at centralization
Reason mode autgmentability is poor, communications burden weight, and higher wanting is proposed to the energy supply of fusion center and computing capability
Ask.
Distributed self-adaption directly positions (D-ADPD) algorithm and can preferably solve the inherent shortcoming of centralized approach.Such as
Document《A Noise-Constrained Distributed Adaptive Direct Position Determination
Algorithm(9Si gnal Processing,2016,Wei Xia and Xinglong Xia)》, Publication No.
Shown in the patent document of CN105137392A, the patent document of Publication No. CN105807257A；Because in distributed algorithm
In the absence of special fusion center, each sensor suffers from same importance in network, processes identical computing and asks
Topic, different from centralized algorithm, each receiver is required for being communicated with fusion center, the sensor in distributed structure/architecture lower network
Only need to its neighbours' sensor interactive information, only exist single-hop (single-hop) transmission；Therefore its communications burden will not be with
The expansion for network is exponentially increased, and is in all the time in a controllable scope.Similar, it is all of in centralized algorithm
Calculating process is all completed by fusion center, therefore computing capability to fusion center and energy supply are proposed larger choosing
War, and during computation burden is here divided evenly over network in the distributed algorithm at all the sensors.Then, distributed self-adaption
Direct location algorithm realizes comparatively ideal positioning performance with relatively low communication cost and energy ezpenditure.
However, needing sensor network in many practical applications while being positioned to multiple emitter targets.At this
Plant under scene, a part of receiver receives a signal for emitter transmitting in network, estimates the emitter geographical position.And with
This simultaneously another part receiver receive another emitter transmitting signal, position its corresponding emitter.Alignment system thing
Do not have emitter target number to be positioned first, sensor divides relevant information in network.Therefore towards individual transmitter target
The direct location algorithm of distributed self-adaption of orientation problem can not well process what this multi-transmitter target was positioned simultaneously
Problem.Based on this, a kind of direct localization method of the multiple target based on self adaptation clustering algorithm is provided in the present invention.
The content of the invention
It is an object of the invention to provide a kind of direct localization method of the multiple target based on self adaptation clustering algorithm, it is used to solve
Certainly Multi-target position problem.The present invention realizes sub-clustering by the attachment coefficient between each receiver in adaptive updates network
Function, so as to realize that multiple target is positioned simultaneously.
To achieve the above object, technical scheme：
A kind of direct localization method of multiple target based on self adaptation clustering algorithm, comprises the following steps：
Step 1：Gathered data, each receiver receives the signal of its correspondence emitter transmitting respectively, and docks the collection of letters and number enter
Row demodulates, samples, obtaining the discrete reception signal of base band, specially：
The receiver that K space of setting separates, the baseband signal x that receiver k is receivedkT () is expressed as：
xk(t)=sk(t-τk)+vk(t), k=1,2 ..., K；
Wherein, skT () is the baseband signal of receiver k correspondence emitter transmittings；vkT () is the measurement noise of receiver k,
The orthogonal zero-mean additive white Gaussian noise in space is may be considered, its power is usedRepresent；τkIt is signal by emitter
To the propagation delay time of receiver, it is expressed as follows：
Wherein,Represent the position of receiver k correspondence emitters, be parameter to be estimated, pkThe position of expression receiver k,
Known a priori, c is known electromagnetic wave signal spread speed；
In moment tn=nTs, n=1,2 ..., N sample strip noises receive signal xk(t), TsThe sampling period is represented, is obtained
To discrete reception signal：
xk[n]=sk(nTs-τk)+vk(nTs), k=1,2 ..., K；
Step 2：Belonging to a receiver for elementary unit groups together in first time data exchange, each receiver and its neighborhood is carried out
Discrete reception signal xk[n] is exchanged；
Step 3：Self adaptation computing, each receiver calculates medianK=1,2 ..., K,
Wherein, λkRepresent iteration step length,At the beginning of representing target location estimates of the receiver k at the n-1 moment, its iteration
Initial value isK=1,2 ..., K,Represent middle estimates of the receiver k in moment n, parameter a 'i,kMeet：
Elementary unit groups where receiver k are represented,Represent that receiver k's removes the neighborhood of itself,Expression connects
The neighborhood comprising itself of receipts machine k；
ei,k[n] represents the estimation error signal between receiver k and its neighbours' receiver i：
Wherein, sinc (t)=sin (π t)/(π t),Represent reaching time-difference τk,iEstimate, filtering wave by prolonging time device exponent number
It is 2M+1；
Step 4：Each receiver is calculatedApproximation：
Step 5：Second data exchange：Each receiver carries out median with all receivers in its neighborhoodExchange；
Step 6：Each receiver adaptive updates attachment coefficient：
Step 7：Associative operation, each receiver calculated target positions estimate
Step 8：Iteration is to target location estimateConvergence, that is, obtain transmitter site estimate.
Operation principle of the present invention is：
In single goal positioning scene, all receivers all receive the signal of same emitter transmitting, positioning in network
The single emitter；The direct location algorithm formula of distributed self-adaption is as follows：
Wherein, weight coefficient { blkTrusting degrees of the receiver k to the median from its neighbours' receiver i is characterized,
Meet following condition：
And in Multi-target position scene, whole sensor network needs to position multiple emitter targets simultaneously；Each hair
The machine of penetrating has oneself specific but unknown sphere of action, without common factor, each emitter between the sphere of action of different transmitters
The signal energy of transmitting and can only be received by the receiver in its sphere of action.Based on this, the present invention is by comprising a certain of receiver k
The sphere of action of emitter is designated as cluster Ck, cluster CkInterior all receivers all position identical emitter target.In Multi-target position side
Without the prior information of cluster complete and accurate in method calculating process, then it is possible that neighbours' receiver belongs to the feelings of different clusters
Condition, receives the signal of different emitter transmittings respectively, and the information exchange between such neighbours' receiver is to target positioning
Nonsensical, even harmful；However, the information sharing of neighbours' receiver and cooperation are based on reaching time-difference in network
Location algorithm in be required；Therefore concept is set in the present invention：Elementary unit groups, by belong to three of same cluster and more than
Interconnected receiving mechanism is into the elementary unit groups comprising receiver k are usedRepresent, and set the division elder generation of elementary unit groups
Test, it is known that the information exchange in elementary unit groups can be trust.
The present invention provides a kind of self adaptation clustering algorithm, in the direct localization method of distributed self-adaption towards single goal
On the basis of realize Multi-target position, the direct location algorithm formula of its distributed self-adaption is as follows：
Wherein, coefficient a 'ikMeet：
Self adaptation attachment coefficient b 'lkMeet：
The present invention adjusts attachment coefficient b ' in real time by minimum deflection (MSD) Optimality Criterialk, obtain following belt restraining
Optimization problem：
In conjunction with coefficient b 'lkFundamental property, by simply mathematic(al) manipulation, finally give MSD tables as follows
Up to formula：
In actual applications,It is unknown priori, approximation is used in the present inventionTo substituteIn addition, in order to allow
Problem is easier treatment, there is a closed solutions, the cross term in above formula has been lost herein and has been expected with instantaneous value mathematical；
Obtain the simplified approximate version of the optimization problem of belt restraining：
Above mentioned problem is solved, temporarily ignores nonnegativity restriction condition, obtain corresponding to the Lagrangian of equality constraint,
And then the solution of the constrained optimization problem being simplified：
Observation above-mentioned formula, it meets nonnegativity restriction condition；Therefore, it is the solution of Constrained Optimization.Receiving
On machine k, during nth iteration, the denominator of above formula is a constant, can't be changed with the conversion of parameter l；And molecule is then
The inverse of the middle estimate distance on the transmitter site and receiver l that receiver k is positioned；Therefore, when receiver k is positioned
Target location and receiver l at obtain in the middle of estimate difference it is larger when, i.e. its inverse distance is a value for very little, then connect
Receipts machine k assigns the attachment coefficient b ' of receiver llkA less value will be obtained；Conversely, when the target position of receiver k positioning
Put during with obtaining middle estimate at receiver l closely, its inverse distance is a larger value, then attachment coefficient b 'lk
A larger value will be obtained；Therefore, with the carrying out of algorithm, receiver k can gradually be assigned and be positioned same target with it
The larger attachment coefficient of neighbours' receiver, and give from the less trust value of the median of its receiver for adhering to different clusters separately, from
And realize the function of self adaptation sub-clustering.
Meanwhile, the present invention builds one to obtain preferable self adaptation sub-clusteringRational approximationThis is near
Seemingly it is worth most important；In order to reduce because of MSD deviations caused by the neighbours' receiver information interaction for performing different estimation tasks,
The present invention uses a local step and updates approximation,
In sum, effective effect of the invention is：There is provided a kind of multiple target based on self adaptation clustering algorithm direct
Localization method, by adaptive updates attachment coefficient, realizes the sub-clustering of receiver network, and then realizes that multiple target is positioned simultaneously.
Brief description of the drawings
Fig. 1 is the direct localization method works schematic flow sheet of the multiple target based on self adaptation clustering algorithm of the invention.
Fig. 2 is the exemplary plot of embodiment transmitter receiver network topology structure of the present invention.
Fig. 3 is estimation condition of each receiver to target location in embodiment network of the present invention.
Fig. 4 is embodiment receiver network self adaptation sub-clustering design sketch of the present invention.
Fig. 5 for the present invention from the direct localization method of distributed self-adaption under different priori conditions positioning performance comparison diagram.
Fig. 6 is the comparison diagram of the present invention and distributed self-adaption direct localization method positioning performance when single goal is positioned.
Specific embodiment
The present invention is described in further details with embodiment below in conjunction with the accompanying drawings.
The present embodiment provides a kind of direct localization method of multiple target based on self adaptation clustering algorithm, comprises the following steps：
1. initialize：Each receiver carries out initialization preparation, the initial value of setting position iterationK=1,2 ...,
K, wherein p0=(4950,5000), set iteration step length λ=3.2 × 10 on each receiver-3, two transmitter sites it is true
Value is respectivelyWithWeight coefficient ai'kIt is set to
WhereinRepresent scopeInterior receiver number；The initial value of attachment coefficientSetting is such as
Under
Wherein NkRepresent the neighborhood of receiver kComprising receiver number；
2. gathered data：Each receiver receives the signal of each correspondence emitter transmitting simultaneously, and signal is demodulated,
Sampling, obtains discrete baseband signal；
3. initial data is exchanged：The discrete baseband signal that each receiver receives itself is transmitted in its neighborhood and belongs to it
In the receiver of same elementary unit groups, while receiving the information that corresponding receiver is transmitted through coming；
4. self adaptation computing：The information that each receiver is got using exchange, the position estimation value as obtained by previous iteration is more
Newly arrive new middle estimate
5. approximation is calculated：Each receiver reuses the information for exchanging and obtaining, and on the basis of median, obtains approximate
Value
6. second data exchange：The middle estimate that each receiver is calculatedIt is transferred to the neighbours of oneself
Receiver, while receiving the result that neighbours' receiver is transmitted；
7. attachment coefficient is updated：Using gained approximation in step 5Adaptive updates attachment coefficient b 'lk(n)
8. combine：Each receiver is added all middle estimate in its neighborhood using the attachment coefficient obtained in step 7
Power combination, obtains the new transmitter site estimate of current iteration；
9. output result：According to threshold value set in advance, whether judgement positioning interative computation enters stable state (convergence), if not
Stable state is reached, then repeat step 2-8, until reaching stable state, export transmitter site estimate.
In this embodiment, sensor network is made up of the K=30 sensor for being randomly dispersed in specific geographical area
, the signal that they can be launched with receiver/transmitter is in communication with each other with neighbours' receiver, and cooperation is common to complete parameter Estimation target
The problem of positioning, topological structure is as shown in Figure 2；Wherein solid line represents reliable neighboring communication link, i.e., the neighbour for being connected by solid line
Occupying receiver has same positioning target, belongs to same elementary unit groups, and ellipse encloses part dashed lines, on basic
The division of unit group is in simulations known a priori；Straight dashed line divides for two clusters sensor network in topological diagram, often
There are two targets to be positioned simultaneously in one specific emitter target of individual cluster correspondence, i.e. this emulation, accurately drawing on cluster
Point Information locating algorithm is priori unknown, it is necessary to pass through to learn estimation to obtain；And between receiver dotted line then represent it is common
Neighboring communication link, may belong to same cluster, such as receiver 12 and receiver 13 with the receiver being connected, it is also possible to be connected
Receiver adhere to different clusters separately and position different targets, such as receiver 12 and receiver 18.
As shown in figure 3, when there is two emitter targets simultaneously in sensor network, towards the distribution of single goal scene
Be present very large deviation in the direct location algorithm of formula self adaptation estimated result in the case of without any priori, do not converge to
Where locations of real targets.And the direct location algorithm of the multiple target based on self adaptation clustering algorithm proposed by the invention is well
Solve the problems, such as that multiple target is positioned simultaneously, and realize the function of self adaptation sub-clustering.As shown in figure 4, here by single reality
The attachment coefficient for testing last 500 iteration into after stable state has been done averagely, as b 'lkDuring (n) ＜ 0.0001, it is believed that receiver k with
Communication link between receiver l has not had practical significance, is not embodied in figure.Algorithm self adaptation sub-clustering knot as shown in Figure 4
Fruit and actual sub-clustering situation perfect matching, illustrate that the algorithm can accurately realize self adaptation sub-clustering function.
Fig. 5 and Fig. 6 then compared for being based on many of self adaptation clustering algorithm under single goal scene and under multiple target scene respectively
The steady-state behaviour of the direct localization method of target and the direct localization method of distributed self-adaption.
The above, specific embodiment only of the invention, any feature disclosed in this specification, except non-specifically
Narration, can alternative features equivalent by other or with similar purpose replaced；Disclosed all features or all sides
Method or during the step of, in addition to mutually exclusive feature and/or step, can be combined in any way.
Claims (2)
1. a kind of direct localization method of multiple target based on self adaptation clustering algorithm, comprises the following steps：
Step 1：Gathered data, each receiver receives the signal of its correspondence emitter transmitting respectively, and docks the collection of letters and number solved
Adjust, sample, obtaining the discrete reception signal of base band；
Step 2：Belonged to together in first time data exchange, each receiver and its neighborhood a receiver for elementary unit groups carry out it is discrete
Receive signal exchange；
Step 3：Self adaptation computing, each receiver calculates medianK is receiver sum,
Wherein, λkIteration step length is represented, c is electromagnetic wave signal spread speed, TsIt is the sampling period；Represent receiver k in n-
The target location estimate at 1 moment, its iteration initial value is Represent receiver k at the moment
The middle estimate of n, parameter a 'i,kMeet：
Elementary unit groups where receiver k are represented,Represent that receiver k's removes the neighborhood of itself,Represent receiver k
The neighborhood comprising itself；
ei,k[n] represents the estimation error signal between receiver k and its neighbours' receiver i：
Wherein, sinc (t)=sin (π t)/(π t),Represent reaching time-difference τk,iEstimate, filtering wave by prolonging time device exponent number be 2M
+1；
Step 4：Each receiver is calculatedApproximation：
Step 5：Second data exchange：Each receiver carries out median with all receivers in its neighborhoodExchange；
Step 6：Each receiver adaptive updates attachment coefficient：
Step 7：Associative operation, each receiver calculated target positions estimate
Step 8：Iteration is to target location estimateConvergence, that is, obtain transmitter site estimate.
2. the direct localization method of multiple target of self adaptation clustering algorithm is based on as described in claim 1, it is characterised in that the step
Rapid 1 concretely comprises the following steps：
The receiver that K space of setting separates, the baseband signal x that receiver k is receivedkT () is expressed as：
xk(t)=sk(t-τk)+vk(t), k=1,2 ..., K；
Wherein, skT () is the baseband signal of receiver k correspondence emitter transmittings；vkT () is the measurement noise of receiver k, τkIt is
Signal is expressed as follows by the propagation delay time of transmitted from transmitter to receiver：
Wherein,Represent the position of receiver k correspondence emitters, pkThe position of receiver k is represented, c is propagated for electromagnetic wave signal
Speed；
In moment tn=nTs, n=1,2 ..., N sample strip noises receive signal xk(t), TsThe sampling period is represented, obtains discrete
Receive signal：
xk[n]=sk(nTs-τk)+vk(nTs), k=1,2 ..., K.
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| CN111337879A (en) * | 2020-03-31 | 2020-06-26 | 西北工业大学 | Weighted MUSIC sound source direct positioning method based on multiple clusters |
| CN115119142A (en) * | 2022-06-22 | 2022-09-27 | 杭州电子科技大学 | Distributed direct positioning method based on sensor network |
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