CN107801168A - A kind of localization method of the adaptive passive type target in outdoor - Google Patents
A kind of localization method of the adaptive passive type target in outdoor Download PDFInfo
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Abstract
A kind of localization method of the adaptive passive type target in outdoor of the present invention, the cluster of target is realized using Clustering, then the final position coordinate of passive type target is calculated using RSSI rangings model and the polygon centroid algorithm of weighting, reduce the error of passive type Multi-target position, the mean error of simulation result is 1.18, and the positioning result track of multiple target and physical location track trend are coincide substantially.The field studies scene of extensive random scatter is can be applied to, each sensing node simultaneously need not be positioned accurately, utilize the beaconing nodes positioning as a reference point for realizing target organism.Each sensing node can adaptively establish the relative position coordinates of each node in wireless sense network in initial phase, you can meet practical application request, and realize that low of hardware cost, the communication overhead of position fixing process of requirement are small, low in energy consumption.
Description
Technical field
The invention belongs to wireless communication field, more particularly to a kind of localization method of the adaptive passive type target in outdoor.
Background technology
Radio sensing network is widely used in military affairs, security protection, environment prison as the core technology under the Internet of things era
The various application scenarios of the short-distance wireless networking such as survey, searching rescue, target tracking.Interaction based on each sensing node and environment
Scene, node are generally randomly dispersed in certain monitored area, therefore the positioning of itself is the base under most of application scenarios
Plinth and premise.
At present, Technology for Target Location is broadly divided into active target positioning and passive type target positions two classes, its essential area
Be not target whether Portable device participate in wireless signal reception or transmission.Active location technology usually requires that positioning target
Signal sending and receiving equipment is carried, positioning is realized by the decay of signal or the change of phase；Passive type positioning does not require target then
Any data transmitting/receiving equipment is carried, this carrys out extreme difficulties to the research of passive type location feasibility with positioning precision elevator belt.
And from location algorithm, it can also be divided into based on ranging and based on two non-ranging major classes.Being located through based on ranging
The distance or angle information of point-to-point between measuring node, and use trilateration, triangulation or maximum likelihood estimate
Calculate node position.Conventional ranging technology has RSSI, TOA, TDOA and AOA.In ranging technology based on RSSI models, wirelessly
Sensor Network obtains the distance between the packet information, calculate node received by the signal strength values RSSI received, from
And determine the position of each destination node.Without in the location algorithm of ranging, then need not distance and angle information, algorithm according to
The information such as the connectedness of network realize the positioning of node.During above-mentioned location technology and positioning is calculated, for the passive of multiple target
Formula positioning does not then temporarily have ripe algorithm also.
The content of the invention
It is an object of the invention to propose a kind of localization method of the adaptive passive type target in outdoor, by based on
The node self-localization of RSSI ranging models, coagulation type level target clusters and three sides and polygon centroid algorithm, realizes passive type
The positioning of random targets.
A kind of localization method of the adaptive passive type target in outdoor of the present invention, comprises the following steps：
Step 1, the distance between beaconing nodes are calculated based on RSSI
Between beaconing nodes are calculated by the way of free space propagation model and logarithm-normal distribution model are combined away from
From free space radio propagation loss model is as follows：
()
Wherein,dFor at a distance of the distance of information source, fIt is wireless frequency,kFor the path attenuation factor；
Logarithm-normal distribution radio transmission loss model is：
(2)
Wherein,It is by distancedPath loss afterwards,It is gaussian random distribution parameter, takes d0=1m, substitute into formula
（1）, try to achievelossAsValue, according to formula（2）Each unknown node and the signal intensity of beaconing nodes can be drawn
RSSI value is：
（3）
According to formula（1）Extremely（3）, the signal intensity RSSI of any one node is received according to beaconing nodes, you can try to achieve the section
The distance between point and beaconing nodes；
Step 2, reference mode are self-positioning
Each node being made up of in wireless sense network wireless module and sensing module is referred to as reference mode, and reference mode is divided into
The distance between Centroid and monitoring node, each node are calculated by the RSSI of reception and tried to achieve；By reference to making by oneself for node
Position, adaptively establishes each node location information, positional information in wireless sense network and is represented with plane coordinates；
2.1 each reference modes receive the signal intensity RSSI value of other reference modes according to it, establish itself and other reference nodes
The distance mapping of point, establish following two set：
Reference mode set：, wherein,Identify Centroid,Mark
Monitoring node；
Distance set between reference mode：, wherein,Represent ginseng
The distance between node i and reference mode j are examined, n represents the number of reference mode in wireless sense network；
After 2.2 establish above-mentioned two set, each reference mode starts self-positioning process, establishes respective position coordinates：
CentroidCoordinate be initialized as（0,0）, as plane coordinate system origin, CentroidAccording to reference mode
Between distance set, two nearest monitoring nodes of chosen distance itself,, withWithCompany
Line is X-axis, establishes plane coordinate system,Coordinate is,Coordinate is,For straight lineAnd straight lineBetween angle,；
Try to achieve any one monitoring nodeCoordinate be, whereinFor straight lineAnd straight lineBetween angle, monitoring nodeAxial coordinate sign passes throughIt is determined that if
, thenCoordinate be
, otherwise, monitoring nodeCoordinate be；
Step 3, target positioning
Target positioning refers to monitor random biology by wireless sense network, and then provides position of the random biofacies to reference mode
The process of confidence breath, target is clustered first with clustering algorithm, then the final of different classes of target is determined by weighted mass center method
Position coordinates.
In addition, described cluster first with clustering algorithm to target, then different classes of target is determined by weighted mass center method
Final position coordinate, comprise the following steps：
3.1 targets cluster
Using coagulation type hierarchical clustering algorithm, target is classified, using ultimate range measure as distance metric between cluster
Method, i.e. cluster ultimate range two-by-two,WithRespectively clusterIn pair
As being somebody's turn to doUpper limit value is,For the monitoring radius of monitoring node in wireless sense network, it is provided withIndividual monitoring
Node monitors target, and specific target cluster process is as follows：
WillIndividual monitoring node is all individually considered as a cluster, calculates the ultimate range between cluster two-by-two；
All ultimate ranges are less thanTwo clusters be merged into a new cluster；
The distance between new cluster and all clusters are calculated respectively again；
Above-mentioned 2,3 are repeated, is less than until in the absence of distance between clusterSituation；In for the cluster that this step is formed with cluster
Number represents the number of target that current time needs to position, it is meant that all nodes in each cluster have monitored target,
Different clusters has monitored different targets；
3.2 target location Calculations
Target positioning is then after above-mentioned target cluster, calculates the process per class goal end position coordinate, uses weighting
Three sides and polygon centroid method are calculated per classification target barycenter, so that it is determined that the final position coordinate of the target；Utilize infrared distance measurement
Model, distance of the target away from all monitoring nodes in its corresponding target cluster is calculated, as weights when positioning；Individual monitoring section
Point forms several clusters by cluster, and the monitoring node number in each cluster is represented with n, n≤1：
If n=1, with the coordinate of the monitoring node in the clusterAs the coordinate position of target, i.e.,；
If n=2, the coordinate of target is the average of two monitoring node coordinates in cluster, i.e.,；
If, thenIndividual node may make upIndividual triangle, according to infrared distance measurement model, target range triangle can be tried to achieve
The distance on summit is respectively、With, first obtained with three side centroid methods of weightingThe barycenter of individual triangle, three side barycenter formula
For, wherein、、The positioning factor is represented, represents that distance objective is got over
The influence power of the coordinate of near monitoring node is bigger；Then utilizeIndividual triangle barycenter, is calculated by polygon centroid method
The final coordinate of target。
The present invention is applied to the field studies scene of extensive random scatter, and each sensing node simultaneously need not accurately be determined
Position, utilizes the beaconing nodes positioning as a reference point for realizing target organism.Each sensing node can be adaptively in initial phase
Establish the relative position coordinates of each node in wireless sense network, you can meet practical application request, and realize the hard of requirement
Low of part cost, the communication overhead of position fixing process are small, low in energy consumption.
Embodiment
A kind of localization method of the adaptive passive type target in outdoor of the present invention, comprises the following steps：
Step 1, it is wirelessly transferred loss model
The precision of RSSI location algorithms is heavily dependent on radio propagation path loss.Conventional radio propagation path damage
Consumption model has free space propagation model（free space propagation model）, logarithm is apart from road strength loss model
（log-distance path loss model）, breathe out its model（Hata model）, logarithm-normal distribution model（log-
distance distribution）Deng.Under the actual environment of field, due to the influence of the factors such as multipath, diffraction, barrier, wirelessly
Electricity is worn thin loss and can changed compared with the theoretical value propagated under free space.
The present invention by the way of free space propagation model and logarithm-normal distribution model are combined, free space without
Line propagation loss model is as follows：
()
Wherein,dTo be at a distance of the distance of information source, unitkm ；fIt is wireless frequency, unit MHZ；kFor the path attenuation factor；
Logarithm-normal distribution radio transmission loss model is：
(2)
Wherein,It is by distancedPath loss afterwards, unit dB；It is that gaussian random is distributed parameter, standard deviation model
It is trapped among 410；kIt is path attenuation factor range 2 ~ 5；Taked=1m, substitute into formula（1）, try to achievelossAsValue, root
According to formula（2）The signal intensity that each unknown node and beaconing nodes can be drawn is：
（3）
According to formula（1）Extremely（3）, beaconing nodes receive the RSSI of any one node, you can try to achieve the node and beaconing nodes
The distance between；
In wireless sense network, measured by the Euclidean distance between destination node and multiple beaconing nodes in theory
The position of destination node, commonly use trilateration.In the field studies scene of the present invention, destination node refers to can be by pyroelectricity
The random targets of infrared sensor sensing, itself does not simultaneously have wireless signal, therefore the positional information of destination node can only lead to
Cross the positional information of reference mode and the detection range of sensor is tried to achieve.The present invention passes through cluster and three sides of weighting and polygon barycenter
Algorithm, realize the calculating of target cluster and goal end position coordinate；
Step 2, reference mode are self-positioning
Each node being made up of in wireless sense network wireless module and sensing module is referred to as reference mode, and reference mode is divided into
The distance between Centroid and monitoring node, each node are calculated by the RSSI of reception and tried to achieve；
Reference mode it is self-positioning, in order to adaptively establish each node location information, position in wireless sense network
Information is represented with plane coordinates.
Each reference mode, the RSSI value of other reference modes is received according to it, establish itself with other reference modes away from
From mapping, following two set are established：
Reference mode set：, wherein,Identify Centroid,Mark
Monitoring node；
Distance set between reference mode：, wherein,Represent reference
The distance between node i and reference mode j, n represent the number of reference mode in wireless sense network；
After establishing above-mentioned two set, reference mode starts self-positioning process, establishes respective position coordinates；
CentroidCoordinate be initialized as（0,0）, as plane coordinate system origin, CentroidAccording to reference mode
Between distance set, two nearest monitoring nodes of chosen distance itself,, withWithCompany
Line is X-axis, establishes plane coordinate system,Coordinate is,Coordinate is,For straight lineAnd straight lineBetween angle,；
Try to achieve any one monitoring nodeCoordinate be, whereinFor straight lineAnd straight lineBetween angle, monitoring nodeAxial coordinate sign passes throughIt is determined that if
, thenCoordinate be,
Otherwise, monitoring nodeCoordinate be；
Step 3, target positioning
Target positioning refers to monitor random biology by wireless sense network, and then provides position of the random biofacies to reference mode
The process of confidence breath.In the application environment of reality, the monitoring of monitoring node half in the positional precision and wireless sense network of target
The random distribution in footpath, the RSSI value with random component and wireless sense network is related, can be estimated with centroid method or maximum likelihood
Meter method improves the positioning precision of target.But in the application scenarios of reality, may occur multiple targets simultaneously, therefore simply
The correctness of positioning is not ensured that using centroid method or maximum likelihood estimate.The present invention gathers first with clustering algorithm to target
Class, then determine by weighted mass center method the final position coordinate of different classes of target.
3.1 targets cluster
There is substantial amounts of clustering algorithm at present.And for concrete application, the selection of clustering algorithm is depending on the types of data, cluster
Purpose.Main clustering algorithm can be divided into following several classes：Division methods, hierarchical method, the method based on density, based on net
The method of lattice and the method based on model.The present invention uses coagulation type hierarchical clustering algorithm, and target is classified, cluster spacing
From measure using ultimate range measure,, wherein,WithRespectively
For clusterIn object, ultimate range between clusterUpper limit value is,For monitoring node in wireless sense network
Monitoring radius, be provided withIndividual monitoring node monitors target, and specific target cluster process is as follows：
WillIndividual monitoring node is all individually considered as a cluster, calculates the ultimate range between cluster two-by-two；
All ultimate ranges are less thanTwo clusters be merged into a new cluster；
The distance between new cluster and all clusters are calculated respectively again；
Above-mentioned 2,3 are repeated, is less than until in the absence of distance between clusterSituation；In for the cluster that this step is formed with cluster
Number represents the number of target that current time needs to position, it is meant that all nodes in each cluster have monitored target,
Different clusters has monitored different targets；
3.2 target location Calculations
Target positioning is after above-mentioned target cluster, calculates the process per classification target final position coordinate.Use weighting three
Side and polygon centroid method are calculated per classification target barycenter, so that it is determined that the final position coordinate of the target.Utilize infrared distance measurement mould
Type, distance of the target away from all monitoring nodes in its corresponding target cluster is calculated, as weights when positioning.
Infrared distance measurement can be used for temperature to be higher than the target of absolute zero, and electromagnetic radiation energy is detection
The important parameter of target range, it depends on target surface temperature T and wavelength.According to Planck law, it is known that ripple
Long λ, temperature T, emissivityWith spoke out-degreeBetween relation.
But then range measurement principle measures the phase difference between echo and transmitted wave generally by the infrared ray of a lower frequency, the echo time is calculated according to phasometer, i.e.,：
Finally try to achieve target range.For the infrared signal cycle.
Assuming thatIndividual monitoring node forms several clusters by cluster, and the monitoring node number in cluster is usedTable
Show：
If n=1, with the coordinate of the monitoring node in the clusterAs the coordinate position of target, i.e.,；
If n=2, the coordinate of target is the coordinate average of two monitoring nodes in cluster, i.e.,；
If, thenIndividual monitoring node may make upIndividual triangle, according to infrared distance measurement model, try to achieve target range triangle
The distance on shape summit is respectively、With, first obtained with three side centroid methods of weightingThe barycenter of individual triangle, the three sides barycenter
Formula is：
, wherein、、The positioning factor is represented, represents that distance objective is got over
Near monitoring node, the influence power of its coordinate are bigger；Then recycleIndividual triangle barycenter, is calculated by polygon centroid method
To the final position coordinate of target。
Passive type Multi-target position is the problem in location technology in current wireless sense network, the present invention based on cluster and
RSSI outdoor adaptive location algorithm, propose to realize the cluster of target using Clustering, then utilize RSSI ranging models
The final position coordinate of passive type target is calculated with the polygon centroid algorithm of weighting, reduces the error of passive type Multi-target position,
The mean error of simulation result is 1.18, and the positioning result track of multiple target and physical location track trend are coincide substantially.It is close
The error of localization method of the invention is within 0.8m under 85% probability, better than traditional RSSI and infrared positioning method, and
When cumulative probability distribution tends to 1, error of the invention is significantly greater than traditional two methods, and these larger errors all occur monitoring
The border in region, it is caused by because the intersecting density of the monitoring range of the boundary node of wireless sense network is low, therefore this also increases
The mean error of method, but can pass through to expand Sensor Network monitoring range and improve the monitoring range of node and intersect the side of density
Formula solves, that is, allows the monitoring range of wireless sense network to be more than actual monitoring border.
It is described above, only it is present pre-ferred embodiments, is not intended to limit the scope of the present invention, therefore
Any subtle modifications, equivalent variations and modifications that every technical spirit according to the present invention is made to above example, still belong to
In the range of technical solution of the present invention.
Claims (2)
1. the localization method of the adaptive passive type target in a kind of outdoor, it is characterised in that comprise the following steps：
Step 1, the distance between beaconing nodes are calculated based on RSSI
Between beaconing nodes are calculated by the way of free space propagation model and logarithm-normal distribution model are combined away from
From free space radio propagation loss model is as follows：
()
Wherein,dFor at a distance of the distance of information source, fIt is wireless frequency,kFor the path attenuation factor；
Logarithm-normal distribution radio transmission loss model is：
(2)
Wherein,It is by distancedPath loss afterwards,It is gaussian random distribution parameter, takes d0=1m, substitute into formula
（1）, try to achievelossAsValue, according to formula（2）Each unknown node and the signal intensity of beaconing nodes can be drawn
RSSI value is：
（3）
According to formula（1）Extremely（3）, the signal intensity RSSI of any one node is received according to beaconing nodes, you can try to achieve the section
The distance between point and beaconing nodes；
Step 2, reference mode are self-positioning
Each node being made up of in wireless sense network wireless module and sensing module is referred to as reference mode, and reference mode is divided into
The distance between Centroid and monitoring node, each node are calculated by the RSSI of reception and tried to achieve；By reference to making by oneself for node
Position, adaptively establishes each node location information, positional information in wireless sense network and is represented with plane coordinates；
2.1 each reference modes receive the signal intensity RSSI value of other reference modes according to it, establish itself and other reference nodes
The distance mapping of point, establish following two set：
Reference mode set：, wherein,Identify Centroid,Mark prison
Survey node；
Distance set between reference mode：, wherein,Represent ginseng
The distance between node i and reference mode j are examined, n represents the number of reference mode in wireless sense network；
After 2.2 establish above-mentioned two set, each reference mode starts self-positioning process, establishes respective position coordinates：
CentroidCoordinate be initialized as（0,0）, as plane coordinate system origin, CentroidAccording between reference mode
Distance set, two nearest monitoring nodes of chosen distance itself ,, withWithCompany
Line is X-axis, establishes plane coordinate system,Coordinate is,Coordinate is,For straight lineAnd straight lineBetween angle,；
Try to achieve any one monitoring nodeCoordinate be, whereinFor straight lineAnd straight lineBetween angle, monitoring nodeAxial coordinate sign passes throughIt is determined that if
, thenCoordinate be,
Otherwise, monitoring nodeCoordinate be；
Step 3, target positioning
Target positioning refers to monitor random biology by wireless sense network, and then provides position of the random biofacies to reference mode
The process of confidence breath, target is clustered first with clustering algorithm, then the final of different classes of target is determined by weighted mass center method
Position coordinates.
A kind of 2. localization method of the adaptive passive type target in outdoor according to claim 1, it is characterised in that：It is described
Target is clustered first with clustering algorithm, then determine by weighted mass center method the final position of different classes of target, including such as
Lower step：
3.1 targets cluster
Using coagulation type hierarchical clustering algorithm, target is classified, using ultimate range measure as distance metric between cluster
Method, i.e. cluster ultimate range two-by-two,WithRespectively clusterIn pair
As being somebody's turn to doUpper limit value is,For the monitoring radius of monitoring node in wireless sense network, it is provided withIndividual monitoring
Node monitors target, and specific target cluster process is as follows：
WillIndividual monitoring node is all individually considered as a cluster, calculates the ultimate range between cluster two-by-two；
All ultimate ranges are less thanTwo clusters be merged into a new cluster；
The distance between new cluster and all clusters are calculated respectively again；
Above-mentioned 2,3 are repeated, is less than until in the absence of distance between clusterSituation；In the number for the cluster that this step is formed with cluster
To represent the number of target that current time needs to position, it is meant that all nodes in each cluster have monitored target, no
Same cluster has monitored different targets；
3.2 target location Calculations
Target positioning is then after above-mentioned target cluster, calculates the process per class goal end position coordinate, uses weighting
Three sides and polygon centroid method are calculated per classification target barycenter, so that it is determined that the final position coordinate of the target；Utilize infrared distance measurement
Model, distance of the target away from all monitoring nodes in its corresponding target cluster is calculated, as weights when positioning；Individual monitoring section
Point forms several clusters by cluster, and the monitoring node number in each cluster is represented with n, n≤1：
If n=1, with the coordinate of the monitoring node in the clusterAs the coordinate position of target, i.e.,；
If n=2, the coordinate of target is the average of two monitoring node coordinates in cluster, i.e.,；
If, thenIndividual node may make upIndividual triangle, according to infrared distance measurement model, target range triangle top can be tried to achieve
Point distance be respectively、With, first obtained with three side centroid methods of weightingThe barycenter of individual triangle, three side barycenter formula are：
WhereinThe positioning factor is represented, represents the influence power of the coordinate of the nearer monitoring node of distance objective
It is bigger；Then utilizeIndividual triangle barycenter, the final position coordinate of target is calculated by polygon centroid method。
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| CN112883999A (en) * | 2021-01-13 | 2021-06-01 | 安徽大学 | Pedometer system and method for detecting abnormal movement of dairy cow |
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