CN110167124A - A kind of underwater wireless sensor network method for tracking target of Adaptive Transmission power - Google Patents
A kind of underwater wireless sensor network method for tracking target of Adaptive Transmission power Download PDFInfo
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- CN110167124A CN110167124A CN201910425415.6A CN201910425415A CN110167124A CN 110167124 A CN110167124 A CN 110167124A CN 201910425415 A CN201910425415 A CN 201910425415A CN 110167124 A CN110167124 A CN 110167124A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
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- H04W52/20—TPC being performed according to specific parameters using error rate
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Abstract
The invention belongs to Multi-sensor Fusions to estimate field, propose a kind of underwater wireless sensor network method for tracking target of transimission power automatic adjusument.Due to the complexity of underwater environment, the environment of underwater sound communication is compared to land and aerial more severe, and the data transmission fault probability between network node is bigger, in order to improve the accuracy of data, it needs to improve the transimission power that node sends data, reduces the influence of adverse circumstances by improving signal-to-noise ratio.It is consumed excessively however, improving transimission power and will lead to node energy, influences network life.In order to solve the contradiction between data accuracy and network energy consumption, algorithm joint proposed by the invention considers the demand of target tracking accuracy and network energy consumption, while guaranteeing tracking accuracy, it is adaptively adjusted the power of node-node transmission metric data, improves network operating efficiency.Therefore, the present invention has important theory significance and practical value for the practical problem for solving underwater target tracking.
Description
Technical field
The invention belongs to Multi-sensor Fusions to estimate field, be related to the Multi-Sensor Target of Adaptive Transmission power a kind of with
Track algorithm.
Background technique
Underwater target tracking is that the essential part of modern marine defence system and maritime rights and interests maintenance are pacified with ocean
One of the key technology of all risk insurance barrier.Either to the defence of torpedo and submarine launched missile, or to water surface naval vessel and underwater submarine
Attack all be unable to do without Tracking of Underwater Object.Other than military field, Tracking of Underwater Object also has in civil field
Important function, such as search and rescue and salvaging, the navigation of underwater robot and control, the traffic of intelligent transportation system of submarine target are supervised
Control, tracking of marine organisms etc..Past, in order to realize underwater target tracking, scholars mainly concentrate under water at
As technology and sonar array detection technology.But Underwater Imaging technology is larger by the interference of turbidity, to distant object
It is difficult to obtain satisfied tracking effect.Sonar array is usually worked in a manner of installing alow or by ship tows again, is led
The region area that enable reaches real-time monitoring tracking is very limited.In order to solve traditional Tracking of Underwater Object in the time and space
On limitation, rely on underwater wireless sensor network (Underwater Wireless Sensor Networks,
UWSNs Tracking of Underwater Object) is by its wide coverage, observation time is long and the advantage of real time information fusion at
For a new research hotspot.UWSNs is wireless sensor network (Wireless Sensor Networks, WSNs) for water
The extension of lower environment, it is by the underwater sensor node of integrated different function, under water unmanned autonomous navigation device (Autonomous
Underwater Vehicle, AUV) and water surface base station composition.These underwater nodes can be perceived with AUV in its investigative range
The information of target, and fusion center is passed to after processing locality by way of underwater sound communication or base station carries out fusion and obtains more
For status informations such as accurate target position, velocity and accelerations.
The node of UWSNs can be deployed in the water layer of ocean different depth, when each node obtains the metric data of target
Afterwards, need to send data to fusion center with carrying out depth Target state estimator.In view of UWSNs communication, energy resource ten
Point limited, the mode for generalling use central fusion carries out UWSNs target following.Each node by original measurement boil down to compared with
Then the data of few digit transmit it to fusion center and carry out target following task.However, since underwater sound communication environment is multiple
Miscellaneous, data will appear error code problem in transmission process.The accuracy measured is received in order to improve fusion center, needs to increase section
The power of point transmission data reduces the efficiency of network however, this will lead to the increase of node energy consumption.
Lance in order to solve in object tracking process, between each node metric data transmission accuracy and transmission power consumption
Shield, the invention proposes a kind of underwater wireless sensor network method for tracking target based on Adaptive Transmission power.For biography
Influence of the defeated power to metric data accuracy and node energy consumption, method by assessment by being measured in object tracking process
Value, obtain the quantitative relationship between node transmission power and target tracking accuracy and energy consumption, establish comprising target with
The Efficiency Function of track precision and network energy consumption, by the adaptive adjustment of method of value solving real-time perfoming node transmission power,
Improve the precision of target following and the efficiency of network energy.
Summary of the invention
The invention proposes a kind of underwater wireless sensor network method for tracking target based on Adaptive Transmission power.Needle
Influence to transimission power to metric data accuracy and node energy consumption, the method for the present invention is by building in object tracking process
The vertical Efficiency Function for comprehensively considering target tracking accuracy and network energy consumption adaptively adjusts node-node transmission tracking, is improved
The precision of target following and the efficiency of network energy.
To achieve the goals above, the technical solution of the present invention is as follows:
Underwater wireless sensor network method for tracking target based on Adaptive Transmission power proposed by the invention considers
Limited to UWSNs communication and energy resource, each node is usually required the less digit of metric data boil down to reduce communication
Burden.Due to communication condition complexity, data will appear error code problem in transmission process, in order to reduce bit error probability, need to increase
The power of big transmission signal, and increase transimission power and will lead to excessive energy consumption.Therefore, how to solve to measure transmission process
Contradiction between middle data accuracy and energy consumption is the emphasis of the mentioned method of the present invention.
Lance in order to solve in object tracking process, between each node metric data transmission accuracy and transmission power consumption
Shield, core of the invention thinking are as follows: for the metric data of high value, increase transimission power to retain more effective informations；It is right
In the metric data of low value, reduce transimission power to reduce energy consumption.It is carried out firstly, being worth to the metric data of each node
Assessment, node transmission power can have an impact the bit error rate of transmission process, under given transimission power, can calculate measurement
The Fei Sheer information of data can assess measurement value, obtain transimission power and measure the quantitative relationship between value；Secondly, meter
The energy consumption for calculating each node-node transmission procedure obtains the quantitative relationship between transimission power and energy consumption；Finally, foundation includes
The objective function of value and transmission power consumption is measured, and calculates the optimal transmission power of each node based on harmonic search algorithm,
Metric data is transmitted to fusion center, Target state estimator is carried out by particle filter.
Specifically, the method for the present invention includes following steps:
Step 1 establishes the objective function comprising measuring value and transmission power consumption, obtains node transmission power and mesh
Quantitative relationship between scalar functions；
Step 2 solves the optimal transmission power of k+1 moment each node based on harmonic search algorithm
Step 3, each node obtain the metric data at k+1 momentAfterwards, it is quantified as 0 or 1
Binary system measures, and with corresponding transimission powerMeasurement is sent to fusion center；
Step 4, fusion center are measured using each node is receivedUsing particle filter algorithm
The fusion estimation for carrying out dbjective state, obtains the estimated value of dbjective state and covarianceWith
Step 5 repeats step 1 to four, until target following task terminates into the circulation of subsequent time.
Target following scheme based on Adaptive Transmission power proposed by the invention can efficiently solve each node amount
Measured data transmits the contradiction between accuracy and transmission power consumption, carries out each node transmission power by the method for numerical solution
Real-time adjustment, maximumlly retain effective measurement information, while avoiding unnecessary energy consumption, for improve UWSNs
The precision and energy efficiency of target following have great significance.
Detailed description of the invention
Fig. 1 is the underwater wireless sensor network method for tracking target proposed by the invention based on Adaptive Transmission power
Flow chart.
Specific embodiment
1 pair of implementation of the invention is described in detail with reference to the accompanying drawing, and provides specific mode of operation and reality
Apply step.
As shown in Figure 1, each node can all obtain the metric data of target, and will measure number in each sampling instant
According to the data fusion for being sent to fusion center progress multinode.After nodal test to target in UWSNs, need wake up target all
The node enclosed carries out lasting tracking to target.The state model of underwater movement objective is commonly described as:
xk+1=Fkxk+wk (1)
WhereinIndicate motion state of the target at the k moment, (xk,yk,zk) indicate the k moment
Position of the target in space coordinates,Then indicate target in the speed of respective direction, FkIndicate moving target in k
The state-transition matrix at moment, wkIndicate Gaussian distributedProcess noise.
For the UWSNs being deployed in waters, measurement model of the node s at the k+1 moment can be indicated are as follows:
Wherein, (xs,ys,zs) indicate node s position,Indicate the measurement equation of node s,It indicates to obey Gauss
DistributionMeasurement noise.Measurement equationFor the range-only measurement of target:
Since UWSNs communication bandwidth is limited, need that original measurement is turned to binary to progress quantification treatment is measured
It surveys:
Wherein γ=[γ0,γ1,γ2] it is preset quantization threshold.
Assuming that UWSNs interior joint has been found that target and obtains the Initial state estimation of target by Track initialization algorithm
And its evaluated error covarianceSo according to model above and referring to Fig.1, the specific implementation step of the method for the present invention is as follows:
Step 1 establishes the objective function comprising measuring value and transmission power consumption.The first part of objective function is
Value is measured, the value to target tracking accuracy is measured by Fei Sheer information evaluation.According to the quantization measurement model of node, phase
The measurement likelihood answered are as follows:
Wherein,It is corresponding measuring noise square difference, Q () indicates the right tail function of standard gaussian distribution:
When quantization measurement is transmitted to fusion center, since underwater sound communication environment is complicated, in fact it could happen that error code phenomenon.It is assumed that
The bit error probability at k+1 moment is in node s measurement transmission processThen fusion center, which receives, measuresCorresponding probability
Are as follows:
Therefore, fusion center receives the joint likelihood function of all measurements are as follows:
WhereinBy the bit error rateIt determines.With transimission powerAdjustment, information transmission noise
ThanAnd the bit error rateIt changes correspondingly, measure likelihood and then is affected:
Wherein, AjIt indicates attenuation coefficient of the node j signal in transmission, is determined by transmission range and signal frequency, due to
The distance between each node and fusion center are kept fixed, and signal frequency is constant, therefore attenuation coefficient is usually fixed value.
PambIndicate the jamming power of ambient noise, αsIndicate the probability that node signal is interfered by other node signals.Obviously, pass through
Adjust the transimission power of each nodeIt can change the accuracy and transmission process of each measurement that fusion center receives
Energy consumption.
Based on the joint likelihood function of formula (9), criterion of the Fei Sheer information of measurement as measurement value can be calculated,
That is:
Wherein:
Therefore, composite type (5)-(14) can establish the measurement value part of objective function:
f1(Pk+1)=- trace (Jk+1)(15)
And for energy consuming components, for the metric data and transmission rate B of fixed digit L, the energy of each node disappears
Consumption are as follows:
Therefore, optimal transmission power can be calculated by objective function (17):
Step 2, at every sampling moment, each node wish the adjustment according to the different progress transimission powers for measuring value,
High value is measured, transimission power can be increased to reduce the bit error rate, guarantee measurement information；And the node that low value measures can
To reduce transimission power, to save energy consumption.By solving objective function (17), optimal transimission power P can be obtainedk+1。
Due to objective function nonlinearity, in order to calculate and guarantee to solve quality with faster speed, here by didactic and
Sound searching algorithm solves optimal transmission power.Using the transimission power of each node as and acoustic vectorIt is logical
Cross initialization, improvement, update harmony process searches problem optimal solution.
V. it initializes: generating multiple and acoustic vector at random in node transmission power adjusting range, form a harmony library,
Wherein each one group of feasible solution corresponding with acoustic vector；
Vi. improve harmony: in order to find optimal solution, need to and acoustic vector improve.According to preset parameter to
Some harmony improves, and obtains a new and acoustic vector；
Vii. harmony is updated:, will new and acoustic vector based on objective function (17) evaluation provided in step 1 and acoustic vector
It is compared with harmony worst in harmony library, retains wherein preferable harmony, harmony library is updated；
Viii. terminate search: continuous repetitive process i-iii stops search when searching times reach the upper limit, will
Best and transimission power of the acoustic vector as the moment in harmony library
Step 3, each node obtain the metric data at k+1 momentAfterwards, by formula (4) by its amount
0 or 1 binary system measurement is turned to, and with corresponding transimission powerMeasurement is sent to fusion center；
Step 4, by transmission channel, fusion center receives each node and measuresIn fusion
The heart carries out the fusion estimation of dbjective state using particle filter algorithm.The process of particle filter algorithm is as follows:
V. it particle propagation: after the target state estimator for completing the k moment, needs to propagate particle based on target state equation (1), obtain
The sampling particle at k+1 moment:
Vi. particle right value update: the joint for calculating multinode measures the right value update that likelihood function (9) carry out particle,
In the bit error probability that measures of each node by corresponding transimission powerIt calculates.The right value update of each particle
It is as follows:
Particle weight after normalized are as follows:
Vii. particle resampling: according to particle weightAgain particle is sampled, obtains final intended particle,
And the weight of all particles is set as
Viii. dbjective state updates: utilize the particle estimation dbjective state and covariance after resampling:
So far, the Target state estimator at k+1 moment is completed.
Step 5 repeats step 1 to four, until target following task terminates into the circulation of subsequent time.
The invention proposes a kind of underwater wireless sensor network method for tracking target of Adaptive Transmission power.Pass through expense
She Er information matrix assesses the value of metric data in target following, and establishes node transmission power and measurement valence
Quantitative relationship between value, comprehensively considers target information that fusion center can obtain and corresponding energy penalty establishes efficiency
Function realizes the adaptive adjustment of each node transmission power by numerical method.For the metric data of high value, node can be with
Increase transimission power, guarantees that fusion center obtains accurate effective information, for the metric data of low value, node be can reduce
Transimission power realizes the balance of tracking accuracy and energy consumption to reduce the energy consumption of transmission process.It is existing compared at present
Underwater wireless sensor network Target Tracking Problem, this method consider transimission power for the first time and disappear to target tracking accuracy and energy
More energy are used for transmission high value metric data by the influence of consumption, improve the utilization efficiency of energy, are solved underwater wireless and are passed
Contradiction in the tracking of sensor network objectives between energy resource and target tracking accuracy.
Claims (5)
1. a kind of underwater wireless sensor network method for tracking target based on Adaptive Transmission power, which is characterized in that include
Following steps:
Step 1 establishes the objective function comprising measuring value and transmission power consumption, obtains node transmission power and target letter
Quantitative relationship between number；
Step 2 solves the optimal transmission power of k+1 moment each node based on harmonic search algorithm
Step 3, each node obtain the metric data at k+1 momentAfterwards, be quantified as the two of 0 or 1 into
System measures, and with corresponding transimission powerMeasurement is sent to fusion center；
Step 4, fusion center are measured using each node is receivedIt is carried out using particle filter algorithm
The fusion of dbjective state is estimated, the estimated value of dbjective state and covariance is obtainedWith
Step 5 repeats step 1 to four, until target following task terminates into the circulation of subsequent time.
2. the underwater wireless sensor network method for tracking target according to claim 1 based on Adaptive Transmission power,
It is characterized in that the step one specifically:
The state model of underwater movement objective describes are as follows:
xk+1=Fkxk+wk (1)
WhereinIndicate motion state of the target at the k moment, (xk,yk,zk) indicate k moment target
Position in space coordinates,Then indicate target in the speed of respective direction, FkIndicate moving target in k
The state-transition matrix at quarter, wkIndicate Gaussian distributedProcess noise；
For the UWSNs being deployed in waters, measurement model of the node s at the k+1 moment is indicated are as follows:
Wherein, (xs,ys,zs) indicate node s position,Indicate the measurement equation of node s,Indicate Gaussian distributedMeasurement noise；Measurement equationFor the range-only measurement of target:
Since UWSNs communication bandwidth is limited, need that original measurement is turned to binary system and is measured to progress quantification treatment is measured:
Wherein γ=[γ0,γ1,γ2] it is preset measurement quantization threshold；
Assuming that UWSNs interior joint has been found that target and obtains the Initial state estimation of target by Track initialization algorithmAnd its
Evaluated error covariance P0The first part of objective function is to measure value, is measured by Fei Sheer information evaluation to target following
The value of precision；According to the quantization measurement model of node, likelihood is measured accordingly are as follows:
Wherein,It is corresponding measuring noise square difference, Q () indicates the right tail function of standard gaussian distribution:
When quantization measurement is transmitted to fusion center, since underwater sound communication environment is complicated, in fact it could happen that error code phenomenon；It is assumed that node
The bit error probability at k+1 moment is in s measurement transmission processThen fusion center, which receives, measuresCorresponding probability are as follows:
Therefore, fusion center receives the joint likelihood function of all measurements are as follows:
WhereinBy the bit error rateIt determines；With transimission powerAdjustment, information transmission signal-to-noise ratioAnd the bit error rateIt changes correspondingly, measure likelihood and then is affected:
Wherein, AjIt indicates attenuation coefficient of the node j signal in transmission, is determined by transmission range and signal frequency, due to each node
The distance between fusion center is kept fixed, and signal frequency is constant, therefore attenuation coefficient is usually fixed value.PambIt indicates
The jamming power of ambient noise, αsIndicate the probability that node signal is interfered by other node signals；Obviously, by adjusting each section
The transimission power of pointIt can change the accuracy for each measurement that fusion center receives and the energy consumption of transmission process；
Based on the joint likelihood function of formula (9), the Fei Sheer information of measurement can be calculated as the criterion for measuring value, it may be assumed that
Wherein:
Therefore, composite type (5)-(14) can establish the measurement value part of objective function:
f1(Pk+1)=- trace (Jk+1) (15)
And for energy consuming components, for the metric data and transmission rate B of fixed digit L, the energy consumption of each node are as follows:
Therefore, optimal transmission power can be calculated by objective function (17):
3. the underwater wireless sensor network method for tracking target according to claim 2 based on Adaptive Transmission power,
It is characterized in that the step two specifically:
At every sampling moment, each node is wished according to the different adjustment for carrying out transimission power for measuring value, by solving mesh
Scalar functions (17) can obtain optimal transimission power Pk+1；
Optimal transmission power is solved by didactic harmonic search algorithm；Using the transimission power of each node as and acoustic vectorBy initialization, improvement, update harmony process searches problem optimal solution, specifically:
I. it initializes: generating multiple and acoustic vector at random in node transmission power adjusting range, form a harmony library, wherein
Each one group of feasible solution corresponding with acoustic vector；
Ii. it improves harmony: existing harmony being improved according to preset parameter, obtain a new and acoustic vector；
Iii. update harmony: based on provided in step 1 objective function (17) evaluation and acoustic vector, will newly and acoustic vector and and
Worst harmony is compared in sound library, is retained wherein preferable harmony, is updated to harmony library；
Iv. terminate search: continuous repetitive process i-iii stops search when searching times reach the upper limit, by harmony library most
Good and transimission power of the acoustic vector as the moment
4. the underwater wireless sensor network method for tracking target according to claim 1 based on Adaptive Transmission power,
It is characterized in that in the step three:
Each node is obtained to the metric data at k+1 moment by formula (4)It is quantified as 0 or 1 binary system
It measures；
5. the underwater wireless sensor network method for tracking target according to claim 2 based on Adaptive Transmission power,
It is characterized in that the fusion estimation of dbjective state is carried out in the step four using particle filter algorithm, particle filter algorithm
Process is as follows:
I. it particle propagation: after the target state estimator for completing the k moment, needs to propagate particle based on target state equation (1), obtains k+1
The sampling particle at moment:
Ii. particle right value update: the joint for calculating multinode measures the right value update that likelihood function (9) carry out particle, wherein respectively
The bit error probability that node measures is by corresponding transimission powerIt calculates；The right value update of each particle is as follows:
Particle weight after normalized are as follows:
Iii. particle resampling: according to particle weightAgain particle is sampled, obtains final intended particle, and will
The weight of all particles is set as
Iv. dbjective state updates: utilize the particle estimation dbjective state and covariance after resampling:
So far, the Target state estimator at k+1 moment is completed.
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| CN114142931A (en) * | 2021-12-13 | 2022-03-04 | 北京邮电大学 | Complex channel communication method based on BIC-DAF-MOEA |
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| CN116300621A (en) * | 2023-03-22 | 2023-06-23 | 浙江大学 | Unmanned surface ship rudder stabilization system safety control method and device and electronic equipment |
| CN117858042A (en) * | 2023-12-21 | 2024-04-09 | 杭州亿亿德传动设备有限公司 | Intelligent transmission method for automatic monitoring information of speed reducer special for hoisting equipment |
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