CN108848443A - The bacterium of the unknown sensor node of wireless sensor network is looked for food optimum position method - Google Patents
The bacterium of the unknown sensor node of wireless sensor network is looked for food optimum position method Download PDFInfo
- Publication number
- CN108848443A CN108848443A CN201810572680.2A CN201810572680A CN108848443A CN 108848443 A CN108848443 A CN 108848443A CN 201810572680 A CN201810572680 A CN 201810572680A CN 108848443 A CN108848443 A CN 108848443A
- Authority
- CN
- China
- Prior art keywords
- node
- coordinate
- unknown
- beaconing nodes
- unknown node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The present invention relates to wireless sensor network location technology, the bacterium of the specially unknown sensor node of wireless sensor network is looked for food optimum position method, is mainly used for obtaining the accurate location information of the unknown sensor node of wireless sensor network.Solve the problems, such as that the existing location algorithm positioning accuracy based on ranging is low and algorithm is complicated.The method of the invention is converted into euclidean distance between node pair value first with the signal strength indication received between node, finds out two possible coordinates of unknown node using the known location coordinate of 2 beaconing nodes A, B any around unknown node by distance intersection principle、, and it is determined, it is finally optimized using bacterial foraging algorithm (BFO), determines that unknown node coordinate completes positioning.The method of the invention improves the precision of algorithm, reduces the complexity of algorithm, reduces the energy consumption of node, extends the life cycle of node.
Description
Technical field
The present invention relates to wireless sensor network location technology, the specially unknown sensor node of wireless sensor network
Bacterium is looked for food optimum position method, is mainly used for obtaining the accurate location information of the unknown sensor node of wireless sensor network.
Background technique
Technology of Internet of things constantly obtains new achievement in recent years, has applied to defense military, environmental monitoring, traffic pipe
Reason, health care, manufacturing industry, the fields such as provide rescue and relief for disasters and emergencies, the wireless sensor network as one of Internet of Things bottom important technology
Have become research hotspot.Wherein, obtaining accurate location information by location algorithm is that wireless sensor network is very heavy
The content wanted.
Location algorithm is divided into based on non-ranging location algorithm (e.g., DV-HOP algorithm) and based on the location algorithm of ranging.
The positioning accuracy of location algorithm based on ranging is higher than based on non-ranging location algorithm.It is related to the location algorithm based on ranging
Some algorithms have, three in location algorithm, three centroid localization algorithm, population location algorithm etc..These existing algorithms are wanted
Positioning accuracy lower (e.g., centroid localization algorithm) or algorithm need to carry out a large amount of interative computation and excessively it is complicated (e.g.,
Population location algorithm).
Summary of the invention
The present invention solves the problems, such as that the existing location algorithm positioning accuracy based on ranging is low and algorithm is complicated, provides a kind of nothing
The bacterium of the unknown sensor node of line sensor network is looked for food optimum position method.
The present invention adopts the following technical scheme that realization:The bacterium of the unknown sensor node of wireless sensor network is looked for food
Optimum position method is realized by following steps:
S1:Unknown node P receives the signal of surrounding beaconing nodes, and converts unknown section for the signal strength indication received
The distance between point and beaconing nodes value;
S2:Setting unknown node P can receive the anchor node number of signal as m, m >=2, with wantonly 2 positions
Beaconing nodes are one group, share k group, and two beaconing nodes in any group are with A, B representative;
S3:Acquire the coordinate A (x of two beaconing nodes A, B in any groupA,yA), B (xB,yB);Calculate beaconing nodes A
To the distance between beaconing nodes B LAB;It is denoted as according to the distance between step S1 obtained beaconing nodes A to unknown node P
LAP, the distance between unknown node P to beaconing nodes B is denoted as LPB;
S4:Judge unknown node P, beaconing nodes A and 3 points of beaconing nodes B it is whether conllinear:Work as LAB=LAP+LPBOr LAB=|
LAP-LPB| when, it is judged as three point on a straight line,
LAB=LAP+LPBWhen, between beaconing nodes A, B, the coordinate of unknown node P is unknown node P
LAB=LAP-LPBWhen, unknown node P is located at beaconing nodes A, B extended line, and the coordinate of unknown node P is
LAB=LPB-LAPWhen, unknown node P is located at beaconing nodes B, A extended line, and the coordinate of unknown node P is
Work as LAB≠LAP+LPBOr LAB≠|LAP-LPB| when, judge 3 points it is not conllinear, unknown node P be node PR, node PLTwo
One in a, interior joint PRPositioned at the 3 points of anticlockwise positions A, B, P, node PLIt is square clockwise positioned at 3 points of A, B, P
To position, set node PR, node PLCoordinate is respectively PR(xPR,yPR)、PL(xPL,yPL);
S5:Egress P is obtained according to distance intersection principleRCoordinate PR(xPR,yPR):xPR=xA+L·(xB-xA)+H·(yB-
yA)
yPR=yA+L·(yB-yA)+H·(xA-xB)
According to the equation of the connected straight line of beaconing nodes A and beaconing nodes B:Ax+by+c=0, then node PLCoordinate PL
(xPL,yPL):
Wherein,
Meet xB≠xA, yA≠yBWhen,
Meet xB=xA, yA≠yBWhen,
A=1, b=0, c=-xAOr-xB;
Meet xB≠xA, yA=yBWhen,
A=0, b=1, c=-yAOr-yB
The distance intersection principle is at least in title《Surveying》, published by Mapping Press, author is land state
Victory, the publication date be in June, 1991 publication on have detailed disclosure.
S6:The selection of unknown node P coordinate value
I-th, 1≤i≤m of de (i, P) expression, distance of the beaconing nodes to unknown node P;de(i,PR) indicate i-th
Beaconing nodes are to node PRDistance, de (i, PL) indicate i-th of beaconing nodes to node PLDistance, definition:
DIS(i,PR)=| de (i, P)-de (i, PR) | (i=1,2 ... m)
DIS(i,PL)=| de (i, P)-de (i, PL) | (i=1,2 ... m)
When
PRCoordinate be exactly unknown node P coordinate, otherwise PLCoordinate be exactly unknown node P coordinate;
S7:Coordinate optimizing
Each group in k group beaconing nodes, the coordinate of a unknown node P is obtained using step S3-S6, in this way, there are
Coordinate (the x of k unknown node P outP1,yP1),(xP2,yP2)......(xPk,yPk), using based on bacterial foraging algorithm (BFO)
The coordinate of k obtained unknown node P is optimized, the fitness function of the bacterial foraging algorithm (BFO) is:
(x in formulas,ys) represent the k coordinate (x of unknown node PP1,yP1),(xP2,yP2)......(xPk,yPk) in appoint
One coordinate, coordinate (xi,yi) be any of m beaconing nodes coordinate;In this way, obtaining k fitness function value F
(s), in k obtained fitness function value F (s), minimum value is selected, it is corresponding with the fitness function value of minimum value unknown
The coordinate of node P is exactly the coordinate of the unknown node P after optimization, that is, the final positioning coordinate of unknown sensor node.
The conventionally known bacterial foraging algorithm (BFO) is at least in title《MATLAB optimization algorithm analysis of cases
With application》(an advanced piece), is published by publishing house of Tsinghua University, author Yu Shengwei, and the publication date is the publication in June, 2015
There is detailed disclosure on object.
The method of the invention is converted into euclidean distance between node pair value first with the signal strength indication received between node, passes through survey
Side intersection principle finds out the two of unknown node using the known location coordinate of 2 beaconing nodes A, B any around unknown node
A possible coordinate PR、PL, and it is determined, it is finally optimized using bacterial foraging algorithm (BFO), determines unknown section
Point coordinate completes positioning.The method of the invention improves the precision of algorithm, reduces the complexity of algorithm, reduces node
Energy consumption extends the life cycle of node.Bacterial foraging algorithm (BFO) is a kind of based on Escherichia coli foraging behavior model
A kind of biological cluster algorithm, bacterial foraging algorithm (BFO) has the characteristics that simply to be easily achieved, ability of searching optimum is strong.Cause
This, selects bacterial foraging algorithm (BFO) to optimize and has highlighted protrusion substantive distinguishing features of the invention.
Detailed description of the invention
Fig. 1 is the schematic illustration of the method for the invention.
Specific embodiment
The bacterium of the unknown sensor node of wireless sensor network is looked for food optimum position method, is realized by following steps
's:
S1:Unknown node P receives the signal of surrounding beaconing nodes, and converts unknown section for the signal strength indication received
The distance between point and beaconing nodes value;
S2:Setting unknown node P can receive the anchor node number of signal as m, m >=2, with wantonly 2 positions
Beaconing nodes are one group, share k group, and two beaconing nodes in any group are with A, B representative;
S3:Acquire the coordinate A (x of two beaconing nodes A, B in any groupA,yA), B (xB,yB);Calculate beaconing nodes A
To the distance between beaconing nodes B LAB;It is denoted as according to the distance between step S1 obtained beaconing nodes A to unknown node P
LAP, the distance between unknown node P to beaconing nodes B is denoted as LPB;
S4:Judge unknown node P, beaconing nodes A and 3 points of beaconing nodes B it is whether conllinear:Work as LAB=LAP+LPBOr LAB=|
LAP-LPB| when, it is judged as three point on a straight line,
LAB=LAP+LPBWhen, between beaconing nodes A, B, the coordinate of unknown node P is unknown node P
LAB=LAP-LPBWhen, unknown node P is located at beaconing nodes A, B extended line, and the coordinate of unknown node P is
LAB=LPB-LAPWhen, unknown node P is located at beaconing nodes B, A extended line, and the coordinate of unknown node P is
Work as LAB≠LAP+LPBOr LAB≠|LAP-LPB| when, judge 3 points it is not conllinear, unknown node P be node PR, node PLTwo
One in a, interior joint PRPositioned at the 3 points of anticlockwise positions A, B, P, node PLIt is square clockwise positioned at 3 points of A, B, P
To position, set node PR, node PLCoordinate is respectively PR(xPR,yPR)、PL(xPL,yPL);
S5:Egress P is obtained according to distance intersection principleRCoordinate PR(xPR,yPR):xPR=xA+L·(xB-xA)+H·(yB-
yA)
yPR=yA+L·(yB-yA)+H·(xA-xB)
According to the equation of the connected straight line of beaconing nodes A and beaconing nodes B:Ax+by+c=0, then node PLCoordinate PL
(xPL,yPL):
Wherein,
Meet xB≠xA, yA≠yBWhen,
Meet xB=xA, yA≠yBWhen,
A=1, b=0, c=-xAOr-xB;
Meet xB≠xA, yA=yBWhen,
A=0, b=1, c=-yAOr-yB
The distance intersection principle is at least in title《Surveying》, published by Mapping Press, author is land state
Victory, the publication date be in June, 1991 publication on have detailed disclosure.
S6:The selection of unknown node P coordinate value
I-th, 1≤i≤m of de (i, P) expression, distance of the beaconing nodes to unknown node P;de(i,PR) indicate i-th
Beaconing nodes are to node PRDistance, de (i, PL) indicate i-th of beaconing nodes to node PLDistance, definition:
DIS(i,PR)=| de (i, P)-de (i, PR) | (i=1,2 ... m)
DIS(i,PL)=| de (i, P)-de (i, PL) | (i=1,2 ... m)
When
PRCoordinate be exactly unknown node P coordinate, otherwise PLCoordinate be exactly unknown node P coordinate;
S7:Coordinate optimizing
Each group in k group beaconing nodes, the coordinate of a unknown node P is obtained using step S3-S6, in this way, there are
Coordinate (the x of k unknown node P outP1,yP1),(xP2,yP2)......(xPk,yPk), using based on bacterial foraging algorithm (BFO)
The coordinate of k obtained unknown node P is optimized, the fitness function of the bacterial foraging algorithm (BFO) is:
(x in formulas,ys) represent the k coordinate (x of unknown node PP1,yP1),(xP2,yP2)......(xPk,yPk) in appoint
One coordinate, coordinate (xi,yi) be any of m beaconing nodes coordinate;In this way, obtaining k fitness function value F
(s), in k obtained fitness function value F (s), minimum value is selected, it is corresponding with the fitness function value of minimum value unknown
The coordinate of node P is exactly the coordinate of the unknown node P after optimization, that is, the final positioning coordinate of unknown sensor node.
The conventionally known bacterial foraging algorithm (BFO) is at least in title《MATLAB optimization algorithm analysis of cases
With application》(an advanced piece), is published by publishing house of Tsinghua University, author Yu Shengwei, and the publication date is the publication in June, 2015
There is detailed disclosure on object.
Claims (1)
- A kind of optimum position method 1. bacterium of the unknown sensor node of wireless sensor network is looked for food, it is characterised in that be by such as What lower step was realized:S1:Unknown node P receive surrounding beaconing nodes signal, and by the signal strength indication received be converted into unknown node and The distance between beaconing nodes value;S2:Setting unknown node P can receive the anchor node number of signal as m, m >=2, with the beacon of wantonly 2 positions Node is one group, shares k group, and two beaconing nodes in any group are with A, B representative;S3:Acquire the coordinate A (x of two beaconing nodes A, B in any groupA,yA), B (xB,yB);Beaconing nodes A is calculated to beacon The distance between node B LAB;L is denoted as according to the distance between step S1 obtained beaconing nodes A to unknown node PAP, not Know that the distance between node P to beaconing nodes B is denoted as LPB;S4:Judge unknown node P, beaconing nodes A and 3 points of beaconing nodes B it is whether conllinear:Work as LAB=LAP+LPBOr LAB=| LAP- LPB| when, it is judged as three point on a straight line,LAB=LAP+LPBWhen, between beaconing nodes A, B, the coordinate of unknown node P is unknown node PLAB=LAP-LPBWhen, unknown node P is located at beaconing nodes A, B extended line, and the coordinate of unknown node P isLAB=LPB-LAPWhen, unknown node P is located at beaconing nodes B, A extended line, and the coordinate of unknown node P isWork as LAB≠LAP+LPBOr LAB≠|LAP-LPB| when, judge 3 points it is not conllinear, unknown node P be node PR, node PLIn two One, interior joint PRPositioned at the 3 points of anticlockwise positions A, B, P, node PLIt is clockwise positioned at 3 points of A, B, P Position sets node PR, node PLCoordinate is respectively PR(xPR,yPR)、PL(xPL,yPL);S5:Egress P is obtained according to distance intersection principleRCoordinate PR(xPR,yPR):xPR=xA+L·(xB-xA)+H·(yB-yA)yPR=yA+L·(yB-yA)+H·(xA-xB)According to the equation of the connected straight line of beaconing nodes A and beaconing nodes B:Ax+by+c=0, then node PLCoordinate PL(xPL, yPL):Wherein,Meet xB≠xA, yA≠yBWhen,B=-1,Meet xB=xA, yA≠yBWhen,A=1, b=0, c=-xAOr-xB;Meet xB≠xA, yA=yBWhen,A=0, b=1, c=-yAOr-yB;S6:The selection of unknown node P coordinate valueI-th, 1≤i≤m of de (i, P) expression, distance of the beaconing nodes to unknown node P;de(i,PR) indicate i-th of beacon section Point arrives node PRDistance, de (i, PL) indicate i-th of beaconing nodes to node PLDistance, definition:DIS(i,PR)=| de (i, P)-de (i, PR) | (i=1,2 ... m)DIS(i,PL)=| de (i, P)-de (i, PL) | (i=1,2 ... m)WhenPRCoordinate be exactly unknown node P coordinate, otherwise PLCoordinate be exactly unknown node P coordinate;S7:Coordinate optimizingEach group in k group beaconing nodes, the coordinate of a unknown node P is obtained using step S3-S6, in this way, there are out k Coordinate (the x of a unknown node PP1,yP1),(xP2,yP2)......(xPk,yPk), using based on bacterial foraging algorithm to obtained k The coordinate of a unknown node P optimizes, and the fitness function of the bacterial foraging algorithm is:(x in formulas,ys) represent the k coordinate (x of unknown node PP1,yP1),(xP2,yP2)......(xPk,yPkAny of) Coordinate, coordinate (xi,yi) be any of m beaconing nodes coordinate;In this way, k fitness function value F (s) is obtained, In k obtained fitness function value F (s), minimum value, unknown node P corresponding with the fitness function value of minimum value are selected Coordinate be exactly the unknown node P after optimization coordinate, that is, the final positioning coordinate of unknown sensor node.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810572680.2A CN108848443B (en) | 2018-06-05 | 2018-06-05 | Bacterial foraging optimal positioning method for unknown sensor nodes of wireless sensor network |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810572680.2A CN108848443B (en) | 2018-06-05 | 2018-06-05 | Bacterial foraging optimal positioning method for unknown sensor nodes of wireless sensor network |
Publications (2)
Publication Number | Publication Date |
---|---|
CN108848443A true CN108848443A (en) | 2018-11-20 |
CN108848443B CN108848443B (en) | 2021-01-26 |
Family
ID=64210435
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810572680.2A Expired - Fee Related CN108848443B (en) | 2018-06-05 | 2018-06-05 | Bacterial foraging optimal positioning method for unknown sensor nodes of wireless sensor network |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108848443B (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112055303A (en) * | 2020-08-28 | 2020-12-08 | 太原理工大学 | Artificial fish swarm optimization positioning method for unknown sensor nodes of wireless sensor network |
CN112055305A (en) * | 2020-08-28 | 2020-12-08 | 太原理工大学 | Two-circle intersection point positioning method for unknown sensor nodes of wireless sensor network |
CN112055304A (en) * | 2020-08-28 | 2020-12-08 | 太原理工大学 | Optimal positioning method for two circle intersection points of unknown sensor nodes of wireless sensor network |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101545964A (en) * | 2008-03-28 | 2009-09-30 | 中国人民解放军信息工程大学 | One-dimensional positioning method and device based on wireless sensor network |
CN107071726A (en) * | 2017-03-15 | 2017-08-18 | 南京邮电大学 | A kind of DV HOP indoor positioning innovatory algorithms optimized based on flora |
-
2018
- 2018-06-05 CN CN201810572680.2A patent/CN108848443B/en not_active Expired - Fee Related
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101545964A (en) * | 2008-03-28 | 2009-09-30 | 中国人民解放军信息工程大学 | One-dimensional positioning method and device based on wireless sensor network |
CN107071726A (en) * | 2017-03-15 | 2017-08-18 | 南京邮电大学 | A kind of DV HOP indoor positioning innovatory algorithms optimized based on flora |
Non-Patent Citations (2)
Title |
---|
ANNU: ""Optimized WSN using EBFOA"", 《2015 INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHHNIQUES AND IMPLEMENTATIONS》 * |
PUSHPALATHA,N: ""Range-free Sensor Positioning based Bacterial Foraging Algorithm(BFO) in Wireless Sensor Networks"", 《INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112055303A (en) * | 2020-08-28 | 2020-12-08 | 太原理工大学 | Artificial fish swarm optimization positioning method for unknown sensor nodes of wireless sensor network |
CN112055305A (en) * | 2020-08-28 | 2020-12-08 | 太原理工大学 | Two-circle intersection point positioning method for unknown sensor nodes of wireless sensor network |
CN112055304A (en) * | 2020-08-28 | 2020-12-08 | 太原理工大学 | Optimal positioning method for two circle intersection points of unknown sensor nodes of wireless sensor network |
Also Published As
Publication number | Publication date |
---|---|
CN108848443B (en) | 2021-01-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108848474A (en) | The localization method of the not conllinear unknown sensor node of wireless sensor network | |
CN108848443A (en) | The bacterium of the unknown sensor node of wireless sensor network is looked for food optimum position method | |
CN101860959B (en) | Locating method of wireless sensor network based on RSSI (Received Signal Strength Indicator) | |
CN103415072B (en) | Based on the localization method estimating distance in a kind of radio sensing network | |
CN108848559A (en) | The localization method of the unknown sensor node of wireless sensor network | |
CN102890263B (en) | Self-adaptive positioning method and system based on resonance gradient method of received signal strength indicator (RSSI) | |
CN103885030A (en) | Locating method of mobile node in wireless sensor network | |
CN101835259A (en) | Wireless sensor network node positioning method based on distance assistance | |
CN107708202A (en) | A kind of wireless sensor network node locating method based on DV Hop | |
CN104502891A (en) | RSSI (received signal strength indicator) technique based hospital patient positioning method | |
CN102984797A (en) | Wireless ad hoc network node positioning method and wireless ad hoc network node positioning system | |
CN102494685A (en) | H infinity information fusion method for WSN (Wireless Sensors Network)/INS (Inertial Navigation System) high-precision real-time combination and navigation | |
CN108668256A (en) | The distance difference localization method of the unknown sensor node of wireless sensor network | |
CN102547973B (en) | RSSI (received signal strength indicator)-based multi-sensor fusion mobile node tracking method | |
CN104023390A (en) | WSN node positioning method based on combination of PSO and UKF | |
CN105824007B (en) | Wireless sensor network distance measurement localization method | |
Habaebi et al. | RSS based localization techniques for ZigBee wireless sensor network | |
CN108259597A (en) | A kind of farm environment monitoring system of high-precision low cost | |
Pushpalatha et al. | Shortest path position estimation between source and destination nodes in wireless sensor networks with low cost | |
CN112055305A (en) | Two-circle intersection point positioning method for unknown sensor nodes of wireless sensor network | |
CN104093206A (en) | Underwater sensor network node self-positioning method based on mixed constraint satisfaction | |
CN105050168B (en) | Based on non-ranging underwater wireless sensor network node localization method and system | |
CN106019219A (en) | Intelligent range-finding positioning method of wireless sensor network (WSN) | |
CN106714107A (en) | Node localization method based on irregular topology wireless sensor network | |
CN103929810B (en) | DV Hop wireless sensor network node positioning methods based on wavelet neural |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210126 Termination date: 20210605 |
|
CF01 | Termination of patent right due to non-payment of annual fee |