CN108508403A - A kind of wireless sensor network locating method based on RSS - Google Patents
A kind of wireless sensor network locating method based on RSS Download PDFInfo
- Publication number
- CN108508403A CN108508403A CN201710514630.4A CN201710514630A CN108508403A CN 108508403 A CN108508403 A CN 108508403A CN 201710514630 A CN201710514630 A CN 201710514630A CN 108508403 A CN108508403 A CN 108508403A
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- Prior art keywords
- node
- rss
- sensor network
- nodes
- beaconing nodes
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0278—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves involving statistical or probabilistic considerations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/10—Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements, e.g. omega or decca systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Abstract
The invention discloses a kind of wireless sensor network locating methods based on RSS, are included in the monitoring required amount of sensor network nodes of deployed in areas；For all the sensors network node, by the information exchange between ambient sensors network node, coarse positioning is carried out to sensor network node to be measured using DV HoP methods；Establish the mixed Gauss model of node R SS values to be measured；The background RSS values in RSS values are separated by Background learning method, background RSS values are further converted by the range information between node according to path loss model, and the final position information of node to be measured is calculated using Bayesian Estimation method；The method overcome in the prior art due to error of the respective nodes in power level measurement is excessive and caused by the excessive defect of final positioning result error, low to the density requirements of node, and be not easy by environmental disturbances, positioning accuracy greatly improves.
Description
Technical field
The present invention relates to wireless communication technology field, more particularly to a kind of wireless sensor network positioning side based on RSS
Method.
Background technology
Wireless sensor network (WSN, Wireless Sensor Network) will be given birth to the mankind after internet
Mode living generates an IT technology of significant impact.It combine sensor technology, embedded technology, MEMS (MEMS,
Microelectronic mechanical system) technology and modern times network and wireless communication technique.In sensor network
In network, all kinds of integrated microsensors are monitored, perceived and are acquired various environment or monitoring objective in real time by cooperation
Information, and processing carried out to these information, then by it is random from group cordless communication network in a multi-hop fashion by information
It is transmitted to user terminal, to realize the connection of physical world, PC World and the human society ternary world.Not due to it
Fixed network is needed to support, power consumption and cost are all very low, have in military affairs, environmental monitoring, medical treatment, agricultural and field of mining wide
Application prospect.Difficult, the region and some interim occasions that personnel cannot reach particularly suitable for wiring and power supply supply.
Location technology as a core technology in wireless sensor network, for sensor network monitoring activity extremely
It closes important.The optimization of routing algorithm, effective configuration of resource, positioning and tracking to specific objective calculate the covering model of network
It is all carried out on the basis of accurate location information in terms of enclosing and controlling communication overhead and network load.Due to by
The limitation of the problems such as sheet, power consumption, autgmentability, all nodes of manual placement or for each node be equipped with global positioning system
The method of (GPS, GlobalPositioning System) module is unpractical.
Become the one of the field by limited information transmission between node to obtain the location information of node in recent years
A important application direction.The unknown node of location information is known as node to be measured, and location information has been grasped and can be used to assist
Node to be measured realizes that the node of positioning is known as anchor node.Location technology wherein based on received signal strength indicator ranging is one
More representational implementation.RSSI is the optional part for transmitting wirelessly layer, can be right by the signal strength received
Distance between two communication nodes is estimated, and then is positioned according to corresponding data.Since its positioning principle is simple, and
Without additional hardware spending and cost on network communication, the pro-gaze of people has been obtained.
However existing evaluation method, it can only realize the coarse localization to unknown node；Have to the density of node higher
It is required that positioning accuracy is also undesirable, and it is easy, by environmental disturbances, to influence its positioning accuracy.
Invention content
The purpose of the present invention is to provide a kind of wireless sensor network locating methods based on RSS, to solve the above-mentioned back of the body
The problem of being proposed in scape technology.
The present invention provides a kind of wireless sensor network locating methods based on RSS, include the following steps：
(1) in the monitoring required amount of sensor network nodes of deployed in areas；
(2) all the sensors network node is obtained by the information exchange between ambient sensors network node
Hop count relationship between sensor network nodes carries out coarse positioning using DV-HoP methods to sensor network node to be measured；
Pass through formula：
Calculate average bounce distance Ci, in formula：J is other beaconing nodes in the tables of data of beaconing nodes i, hopsij
For the hop count between beaconing nodes i and j, CiFor Average hop distance, (xi, yi) be beaconing nodes i coordinate value, (xj, yj) be
The coordinate value of other beaconing nodes in the tables of data of beaconing nodes i；
Pass through formula：
Cc=∑s Ci/n
Calculate that the whole network is average often to jump away from cc, in formula：N is the number of beaconing nodes in wireless sensor network；
Pass through formula：
In formula：N is the number of beaconing nodes, (x1, y1) be first beaconing nodes coordinate value, (xn, yn) it is n-th
The coordinate value of beaconing nodes, (x, y) are the coordinate of unknown node P, d1, dnIt is illustrated respectively in the logical of nodes of locations P and beaconing nodes
Believe the distance between two nodes in range.It can be obtained by transformation：
And then equation can be expressed as：
AX=B
Wherein：
To which the result X of coarse positioning can be obtained；
(3) mixed Gauss model of node R SS values to be measured is established；
(4) the background RSS values in RSS values are separated by Background learning method, further according to path loss mould
Type converts background RSS values to the range information between node, and node to be measured is calculated most using Bayesian Estimation method
Whole location information.
Preferably, the mathematical model of the mixed Gauss model is：
Wherein, RtIt is the RSS values of moment t, uk,δkRespectively mean value and variance, wkIt is the weighted value of k-th of Gaussian Profile,
g(Rt；uk,δk) it is k-th of Gaussian Profile：
Preferably, the mean value, variance and weight in the mixed Gauss model are carried out using adaptive line filter
Update.
Preferably, the DV-Hop location algorithms are determined according to the hop count information between anchor node and sensor node
Position is non-ranging location algorithm.
Compared to the prior art the present invention, the advantage is that：
A kind of wireless sensor network locating method based on RSS provided by the invention can be obtained from limited information
To more location informations, overcomes and caused in the prior art since error of the respective nodes in power level measurement is excessive
The excessive defect of final positioning result error, low to the density requirements of node, and be not easy by environmental disturbances, positioning accuracy is significantly
It improves, position error is down between 20% to 50%.
Specific implementation mode
The specific embodiment of the present invention is described in detail below, it is to be understood that protection scope of the present invention
It is not restricted by specific implementation.
An embodiment of the present invention provides a kind of wireless sensor network locating methods based on RSS, include the following steps：
(1) in the monitoring required amount of sensor network nodes of deployed in areas；
(2) all the sensors network node is obtained by the information exchange between ambient sensors network node
Hop count relationship between sensor network nodes carries out coarse positioning using DV-HoP methods to sensor network node to be measured；
Pass through formula：
Calculate average bounce distance Ci, in formula：J is other beaconing nodes in the tables of data of beaconing nodes i, hopsij
For the hop count between beaconing nodes i and j, CiFor Average hop distance, (xi, yi) be beaconing nodes i coordinate value, (xj, yj) be
The coordinate value of other beaconing nodes in the tables of data of beaconing nodes i；
Pass through formula：
Cc=∑s Ci/n
Calculate that the whole network is average often to jump away from cc, in formula：N is the number of beaconing nodes in wireless sensor network；
Pass through formula：
In formula：N is the number of beaconing nodes, (x1, y1) be first beaconing nodes coordinate value, (xn, yn) it is n-th
The coordinate value of beaconing nodes, (x, y) are the coordinate of unknown node P, d1, dnIt is illustrated respectively in the logical of nodes of locations P and beaconing nodes
Believe the distance between two nodes in range.It can be obtained by transformation：
And then equation can be expressed as：
AX=B
Wherein：
To which the result X of coarse positioning can be obtained；
(3) mixed Gauss model of node R SS values to be measured is established；
(4) the background RSS values in RSS values are separated by Background learning method, further according to path loss mould
Type converts background RSS values to the range information between node, and node to be measured is calculated most using Bayesian Estimation method
Whole location information.
Preferably, the mathematical model of the mixed Gauss model is：
Wherein, RtIt is the RSS values of moment t, uk,δkRespectively mean value and variance, wkIt is the weighted value of k-th of Gaussian Profile,
g(Rt；uk,δk) it is k-th of Gaussian Profile：
Preferably, the mean value, variance and weight in the mixed Gauss model are carried out using adaptive line filter
Update.
Preferably, the DV-Hop location algorithms are determined according to the hop count information between anchor node and sensor node
Position is non-ranging location algorithm.
In conclusion a kind of wireless sensor network locating method based on RSS provided in an embodiment of the present invention, Neng Goucong
More location informations are obtained in limited information, are overcome in the prior art since respective nodes are in power level measurement
Error it is excessive and caused by the excessive defect of final positioning result error, it is low to the density requirements of node, and be not easy dry by environment
It disturbs, positioning accuracy greatly improves, and position error is down between 20% to 50%.
Disclosed above is only several specific embodiments of the present invention, and still, the embodiment of the present invention is not limited to this, is appointed
What what those skilled in the art can think variation should all fall into protection scope of the present invention.
Claims (4)
1. a kind of wireless sensor network locating method based on RSS, which is characterized in that include the following steps：
(1) in the monitoring required amount of sensor network nodes of deployed in areas；
(2) all the sensors network node is sensed by the information exchange between ambient sensors network node
Hop count relationship between device network node carries out coarse positioning using DV-HoP methods to sensor network node to be measured；
Pass through formula：
Calculate average bounce distance Ci, in formula：J is other beaconing nodes in the tables of data of beaconing nodes i, hopsijFor letter
Mark the hop count between node i and j, CiFor Average hop distance, (xi, yi) be beaconing nodes i coordinate value, (xj, yj) it is beacon
The coordinate value of other beaconing nodes in the tables of data of node i；
Pass through formula：
Cc=∑s Ci/n
Calculate that the whole network is average often to jump away from cc, in formula：N is the number of beaconing nodes in wireless sensor network；
Pass through formula：
In formula：N is the number of beaconing nodes, (x1, y1) be first beaconing nodes coordinate value, (xn, yn) it is n-th of beacon section
The coordinate value of point, (x, y) are the coordinate of unknown node P, d1, dnIt is illustrated respectively in the communication range of nodes of locations P and beaconing nodes
Distance between two interior nodes；It can be obtained by transformation：
And then equation can be expressed as：
AX=B
Wherein：
To which the result X of coarse positioning can be obtained；
(3) mixed Gauss model of node R SS values to be measured is established；
(4) the background RSS values in RSS values are separated by Background learning method, it further will according to path loss model
Background RSS values are converted into the range information between node, and the most final position of node to be measured is calculated using Bayesian Estimation method
Confidence ceases.
2. a kind of wireless sensor network locating method based on RSS as described in claim 1, which is characterized in that described mixed
Close Gauss model mathematical model be：
Wherein, RtIt is the RSS values of moment t, uk,δkRespectively mean value and variance, wkIt is the weighted value of k-th of Gaussian Profile, g (Rt；
uk,δk) it is k-th of Gaussian Profile：
3. a kind of wireless sensor network locating method based on RSS as claimed in claim 2, which is characterized in that described mixed
Mean value, variance and the weight closed in Gauss model are updated using adaptive line filter.
4. a kind of wireless sensor network locating method based on RSS as claimed in claim 2, which is characterized in that the DV-
Hop location algorithms are positioned according to the hop count information between anchor node and sensor node, are non-ranging location algorithms.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110766700A (en) * | 2019-10-23 | 2020-02-07 | 吉林大学 | ICP-AES spectral image processing method based on digital micromirror |
| CN111447579A (en) * | 2020-01-14 | 2020-07-24 | 长江大学 | DV-hop indoor positioning method based on RSSI average hop distance and path loss |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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Application publication date: 20180907 |