CN106054127A - Wireless sensor network intelligent correction range finding positioning method - Google Patents

Wireless sensor network intelligent correction range finding positioning method Download PDF

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Publication number
CN106054127A
CN106054127A CN201610338877.0A CN201610338877A CN106054127A CN 106054127 A CN106054127 A CN 106054127A CN 201610338877 A CN201610338877 A CN 201610338877A CN 106054127 A CN106054127 A CN 106054127A
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Prior art keywords
beaconing nodes
region
unknown node
coordinate
point
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CN106054127B (en
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乔学工
曹建
王华倩
李瑞莲
武娟萍
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Taiyuan University of Technology
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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
    • 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
    • G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
    • G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
    • G01S11/06—Systems for determining distance or velocity not using reflection or reradiation using radio waves using intensity 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

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention relates to a wireless sensor network positioning technology, specifically relates to a wireless sensor network intelligent correction range finding positioning method and solves the problems of the prior art that the positioning precision is low and the algorithm is complex. The method is characterized in that firstly, an area value is utilized to determine the relative positions of an unknown node and a beacon node, the method for coefficients TA, TB, TC and area relations is established, and the coordinate value optimization is carried out on coordinates of the unknown node P; and secondly, a crowd search algorithm (SOA) is utilized to further optimize obtained coordinate values. By means of simulation analysis and comparison with other algorithm, the wireless sensor network intelligent correction range finding positioning method has the advantages that the precision of the algorithm is improved, the complexity of the algorithm is lowered, the energy consumption of the node is reduced, and the life period of the node is prolonged.

Description

Wireless sensor network intelligence correction distance-measuring and positioning method
Technical field
The present invention relates to wireless sensor network location technology, specially wireless sensor network intelligence correction ranging localization Method.It is mainly used in wireless sensor network obtaining sensor node positional information accurately.
Background technology
Technology of Internet of things constantly obtains new achievement in recent years, has applied to national defense and military, environmental monitoring, traffic pipe Reason, health care, manufacturing industry, the field such as provide rescue and relief for disasters and emergencies, as the wireless sensor network of one of Internet of Things bottom important technology Have become as study hotspot.Wherein, obtaining positional information accurately by location algorithm is that wireless sensor network is the heaviest The content wanted.
Intelligent algorithm obtains higher attention recently, is used for optimizing original algorithm, e.g., utilizes immune genetic algorithm to base Trilateration in RSSI is optimized, utilizes particle cluster algorithm to be optimized DV-HOP algorithm, is sought by continuous iteration Excellent improve positioning precision.These intelligent algorithms can be used to improve positioning precision, however it is necessary that and carries out substantial amounts of iteration fortune Calculate." wireless sensor network distance measurement localization method " is combined by the present invention with crowd's searching algorithm so that only need a small amount of changing Just positioning precision is can further improve for computing.
Summary of the invention
The present invention solves the problem that existing algorithmic technique positioning precision is low and relevant intelligent algorithm iterations is many, it is provided that one Plant wireless sensor network intelligence correction distance-measuring and positioning method.
The present invention adopts the following technical scheme that realization: wireless sensor network intelligence correction distance-measuring and positioning method, is Realized by following steps:
Z1: unknown node P accepts the signal of beaconing nodes around, and the signal strength values received is converted into unknown joint Distance value between point and beaconing nodes；
Z2: set this unknown node P and receive the anchor node number of signal as m, m 3, with wantonly 3 position not conllinear Beaconing nodes be one group, k group altogether；
Z3: from first group of beaconing nodes until kth group beaconing nodes calculates the coordinate of unknown node P successively, one there are To k coordinate, it is expressed as (xp1,yp1) ... (xpk,ypk).Choosing wherein u group beaconing nodes, u value is 1 to k, will This group beaconing nodes is set as A, B, C, calculates the coordinate (x of unknown node Ppu,ypu), for one of above-mentioned k coordinate.3 letters Whole plane is divided into seven regions by mark node A, B, C:
The triangle interior region that 1:3, region beaconing nodes A, B, C are constituted；
Region 2: straight line, beaconing nodes A and the beacon beyond the A point of the ray BA that beaconing nodes B and beaconing nodes A is constituted The region that straight line beyond the C point of the ray BC that line segment AC, the beaconing nodes B of node C composition and beaconing nodes C are constituted surrounds；
Region 3: straight line, beaconing nodes A and the beacon beyond the B point of the ray CB that beaconing nodes C and beaconing nodes B is constituted The region that straight line beyond the A point of the ray CA that line segment AB, the beaconing nodes C of node B composition and beaconing nodes A are constituted surrounds；
Region 4: straight line, beaconing nodes B and the beacon beyond the B point of the ray AB that beaconing nodes A and beaconing nodes B is constituted The region that straight line beyond the C point of the ray AC that line segment BC, the beaconing nodes A of node C composition and beaconing nodes C are constituted surrounds；
Region 5: straight line, beaconing nodes A and the beacon beyond the C point of the ray BC that beaconing nodes B and beaconing nodes C is constituted The region that straight line beyond the C point of the ray AC that node C is constituted surrounds；
Region 6: straight line, beaconing nodes A and the beacon beyond the B point of the ray CB that beaconing nodes C and beaconing nodes B is constituted The region that straight line beyond the B point of the ray AB that node B is constituted surrounds；
Region 7: straight line, beaconing nodes C and the beacon beyond the A point of the ray BA that beaconing nodes B and beaconing nodes A is constituted The region that straight line beyond the A point of the ray CA that node A is constituted surrounds；
Z4: determine region residing for unknown node P:
Meet formula: SABC=SABP+SACP+SBCPUnknown node P is in region 1；
Meet formula: SABP+SBCP=SABC+SACPUnknown node P is in region 2；
Meet formula: SACP+SBCP=SABC+SABPUnknown node P is in region 3；
Meet formula: SACP+SABP=SABC+SBCPUnknown node P is in region 4；
Meet formula: SABP=SACP+SABC+SBCPUnknown node P is in region 5；
Meet formula: SACP=SABP+SABC+SBCPUnknown node P is in region 6；
Meet formula: SBCP=SACP+SABC+SABPUnknown node P is in region 7；
Wherein S is the area of the corresponding triangle using Heron's formula to calculate, and three letters in S subscript are triangle Three summits；
The u coordinate (x of Z5: unknown node Ppu,ypu) computing formula as follows:
xpu=TA·xa+TB·xb+TC·xc
ypu=TA·ya+TB·yb+TC·yc
Wherein, (xa,ya) it is the coordinate of beaconing nodes A, (xb,yb) it is the coordinate of beaconing nodes B, (xc,yc) it is beacon joint The coordinate of some C；TA、TB、TCFor coefficient of region, relevant with P point region.
When unknown node P is in region 1,
When unknown node P is in region 2,
When unknown node P is in region 3,
When unknown node P is in region 4,
When unknown node P is in region 5,
When unknown node P is in region 6,
When unknown node P is in region 7,
Z6: use the crowd's searching algorithm improved k the coordinate (x to obtainingp1,yp1) ... (xpk,ypk) be optimized, The coordinate of unknown node P after being optimized.
Crowd's searching algorithm of described improvement is fitness with the difference of existing known crowd's searching algorithm (SOA) Function is different, and the step-length in existing known crowd's searching algorithm (SOA) is reduced 50%；People's group hunting of described improvement The fitness function of algorithm is:
F = 1 - Σ i = 1 m [ ( ( x s - x i ) 2 + ( y s - y i ) 2 - Σ i = 1 m ( x s - x i ) 2 + ( y s - y i ) 2 m ) × ( d i - Σ i = 1 m d i m ) ] Σ i = 1 m ( ( x s - x i ) 2 + ( y s - y i ) 2 - Σ i = 1 m ( x s - x i ) 2 + ( y s - y i ) 2 m ) 2 × Σ i = 1 m ( d i - Σ i = 1 m d i m ) 2
Coordinate (x in formulas,ys) represent k coordinate (xp1,yp1) ..., (xpk,ypkAny one coordinate in), coordinate (xi, yi) it is any one coordinate in m beaconing nodes；diRepresent the distance value described in step Z1；At k the fitness letter obtained In numerical value F, select minima.
Described existing known crowd's searching algorithm (SOA) is at least " MATLAB optimized algorithm analysis of cases at title With application ", publishing house of Tsing-Hua University publish, author is Yu Shengwei, and the publication date is to have on the publication of in JIUYUE, 2014 in detail Thin open.
The method of the invention determines the relative position of unknown node and beaconing nodes first with area value, by foundation is Number TA、TB、TCWith the method for regional relation, the coordinate of direct solution unknown node P has also carried out coordinate optimizing.Secondly, the present invention The coordinate figure of use crowd's searching algorithm (SOA) unknown node P to having obtained has carried out further optimization；People's group hunting is calculated Method is a kind of heuristic random searching algorithm based on population.The localization method that the present invention proposes, is improving the same of positioning precision Time also reduce the iterations of algorithm.Present invention uses new fitness function, by Pearson came distance (mathematical statistics: skin Er Xun distance deducts Pearson's correlation coefficient equal to 1) as fitness function value F, fitness function value F is the least, the seat solved Scale value is closer to actual value.
Contrasting by simulation analysis and with some other algorithms, the method for the invention improves the essence of algorithm Degree, reduces the complexity of algorithm, reduces the energy expenditure of node, extends the life cycle of node.
Accompanying drawing explanation
Fig. 1 is that whole plane is divided into seven area schematic by step Z3 tri-beaconing nodes A, B, C.
Detailed description of the invention
Wireless sensor network intelligence correction distance-measuring and positioning method, is realized by following steps:
Z1: unknown node P accepts the signal of beaconing nodes around, and the signal strength values received is converted into unknown joint Distance value between point and beaconing nodes；Here convert and use known logarithm constant wireless signal propagation model.
Z2: set this unknown node P and receive the anchor node number of signal as m, m 3, with wantonly 3 position not conllinear Beaconing nodes be one group, k group altogether；
Z3: from first group of beaconing nodes until kth group beaconing nodes calculates the coordinate of unknown node P successively, one there are To k coordinate, it is expressed as (xp1,yp1) ... (xpk,ypk).Choosing wherein u group beaconing nodes, u value is 1 to k, will This group beaconing nodes is set as A, B, C, calculates the coordinate (x of unknown node Ppu,ypu), for one of above-mentioned k coordinate.3 letters Whole plane is divided into seven regions by mark node A, B, C:
The triangle interior region that 1:3, region beaconing nodes A, B, C are constituted；
Region 2: straight line, beaconing nodes A and the beacon beyond the A point of the ray BA that beaconing nodes B and beaconing nodes A is constituted The region that straight line beyond the C point of the ray BC that line segment AC, the beaconing nodes B of node C composition and beaconing nodes C are constituted surrounds；
Region 3: straight line, beaconing nodes A and the beacon beyond the B point of the ray CB that beaconing nodes C and beaconing nodes B is constituted The region that straight line beyond the A point of the ray CA that line segment AB, the beaconing nodes C of node B composition and beaconing nodes A are constituted surrounds；
Region 4: straight line, beaconing nodes B and the beacon beyond the B point of the ray AB that beaconing nodes A and beaconing nodes B is constituted The region that straight line beyond the C point of the ray AC that line segment BC, the beaconing nodes A of node C composition and beaconing nodes C are constituted surrounds；
Region 5: straight line, beaconing nodes A and the beacon beyond the C point of the ray BC that beaconing nodes B and beaconing nodes C is constituted The region that straight line beyond the C point of the ray AC that node C is constituted surrounds；
Region 6: straight line, beaconing nodes A and the beacon beyond the B point of the ray CB that beaconing nodes C and beaconing nodes B is constituted The region that straight line beyond the B point of the ray AB that node B is constituted surrounds；
Region 7: straight line, beaconing nodes C and the beacon beyond the A point of the ray BA that beaconing nodes B and beaconing nodes A is constituted The region that straight line beyond the A point of the ray CA that node A is constituted surrounds；
Z4: determine region residing for unknown node P:
Meet formula: SABC=SABP+SACP+SBCPUnknown node P is in region 1；
Meet formula: SABP+SBCP=SABC+SACPUnknown node P is in region 2；
Meet formula: SACP+SBCP=SABC+SABPUnknown node P is in region 3；
Meet formula: SACP+SABP=SABC+SBCPUnknown node P is in region 4；
Meet formula: SABP=SACP+SABC+SBCPUnknown node P is in region 5；
Meet formula: SACP=SABP+SABC+SBCPUnknown node P is in region 6；
Meet formula: SBCP=SACP+SABC+SABPUnknown node P is in region 7；
Wherein S is the area of the corresponding triangle using Heron's formula to calculate, and three letters in S subscript are triangle Three summits；
Described Heron's formula is common knowledge:
L = L 1 + L 2 + L 3 2
S = L ( L - L 1 ) ( L - L 2 ) ( L - L 3 )
In formula: S is triangle area, and it is long that L1, L2, L3 represent three sides of a triangle.
The u coordinate (x of Z5: unknown node Ppu,ypu) computing formula as follows:
xpu=TA·xa+TB·xb+TC·xc
ypu=TA·ya+TB·yb+TC·yc
Wherein, (xa,ya) it is the coordinate of beaconing nodes A, (xb,yb) it is the coordinate of beaconing nodes B, (xc,yc) it is beacon joint The coordinate of some C；TA、TB、TCFor coefficient of region, relevant with P point region.
When unknown node P is in region 1,
When unknown node P is in region 2,
When unknown node P is in region 3,
When unknown node P is in region 4,
When unknown node P is in region 5,
When unknown node P is in region 6,
When unknown node P is in region 7,
Z6: use the crowd's searching algorithm improved k the coordinate (x to obtainingp1,yp1) ... (xpk,ypk) be optimized, The coordinate of unknown node P after being optimized；
Crowd's searching algorithm of described improvement is fitness with the difference of existing known crowd's searching algorithm (SOA) Function is different, and the step-length in existing known crowd's searching algorithm (SOA) is reduced 50%；People's group hunting of described improvement The fitness function of algorithm is:
F = 1 - Σ i = 1 m [ ( ( x s - x i ) 2 + ( y s - y i ) 2 - Σ i = 1 m ( x s - x i ) 2 + ( y s - y i ) 2 m ) × ( d i - Σ i = 1 m d i m ) ] Σ i = 1 m ( ( x s - x i ) 2 + ( y s - y i ) 2 - Σ i = 1 m ( x s - x i ) 2 + ( y s - y i ) 2 m ) 2 × Σ i = 1 m ( d i - Σ i = 1 m d i m ) 2
Coordinate (x in formulas,ys) represent k coordinate (xp1,yp1) ..., (xpk,ypkAny one coordinate in), coordinate (xi, yi) it is any one coordinate in m beaconing nodes；diRepresent the distance value described in step Z1；At k the fitness letter obtained In numerical value F, select minima.

Claims (1)

1. a wireless sensor network intelligence correction distance-measuring and positioning method, it is characterised in that realized by following steps:
Z1: unknown node P accepts the signal of beaconing nodes around, and the signal strength values received is converted into unknown node and Distance value between beaconing nodes；
Z2: set this unknown node P and receive the anchor node number of signal as m, m 3, with the letter of wantonly 3 position not conllinear Mark node is one group, k group altogether；
Z3: from first group of beaconing nodes until kth group beaconing nodes calculates the coordinate of unknown node P successively, obtain altogether k Coordinate, is expressed as (xp1,yp1) ... (xpk,ypk)；Choosing wherein u group beaconing nodes, u value is 1 to k, by this group Beaconing nodes is set as A, B, C, calculates the coordinate (x of unknown node Ppu,ypu), for one of above-mentioned k coordinate；3 beacon joints Whole plane is divided into seven regions by some A, B, C:
The triangle interior region that 1:3, region beaconing nodes A, B, C are constituted；
Region 2: straight line, beaconing nodes A and the beaconing nodes beyond the A point of the ray BA that beaconing nodes B and beaconing nodes A is constituted The region that straight line beyond the C point of the ray BC that line segment AC, the beaconing nodes B of C composition and beaconing nodes C are constituted surrounds；
Region 3: straight line, beaconing nodes A and the beaconing nodes beyond the B point of the ray CB that beaconing nodes C and beaconing nodes B is constituted The region that straight line beyond the A point of the ray CA that line segment AB, the beaconing nodes C of B composition and beaconing nodes A are constituted surrounds；
Region 4: straight line, beaconing nodes B and the beaconing nodes beyond the B point of the ray AB that beaconing nodes A and beaconing nodes B is constituted The region that straight line beyond the C point of the ray AC that line segment BC, the beaconing nodes A of C composition and beaconing nodes C are constituted surrounds；
Region 5: straight line, beaconing nodes A and the beaconing nodes beyond the C point of the ray BC that beaconing nodes B and beaconing nodes C is constituted The region that straight line beyond the C point of the ray AC that C is constituted surrounds；
Region 6: straight line, beaconing nodes A and the beaconing nodes beyond the B point of the ray CB that beaconing nodes C and beaconing nodes B is constituted The region that straight line beyond the B point of the ray AB that B is constituted surrounds；
Region 7: straight line, beaconing nodes C and the beaconing nodes beyond the A point of the ray BA that beaconing nodes B and beaconing nodes A is constituted The region that straight line beyond the A point of the ray CA that A is constituted surrounds；
Z4: determine region residing for unknown node P:
Meet formula: SABC=SABP+SACP+SBCPUnknown node P is in region 1；
Meet formula: SABP+SBCP=SABC+SACPUnknown node P is in region 2；
Meet formula: SACP+SBCP=SABC+SABPUnknown node P is in region 3；
Meet formula: SACP+SABP=SABC+SBCPUnknown node P is in region 4；
Meet formula: SABP=SACP+SABC+SBCPUnknown node P is in region 5；
Meet formula: SACP=SABP+SABC+SBCPUnknown node P is in region 6；
Meet formula: SBCP=SACP+SABC+SABPUnknown node P is in region 7；
Wherein S is the area of the corresponding triangle using Heron's formula to calculate, three that three letters are triangle in S subscript Summit；
The u coordinate (x of Z5: unknown node Ppu,ypu) computing formula as follows:
xpu=TA·xa+TB·xb+TC·xc
ypu=TA·ya+TB·yb+TC·yc
Wherein, (xa,ya) it is the coordinate of beaconing nodes A, (xb,yb) it is the coordinate of beaconing nodes B, (xc,yc) it is beaconing nodes C's Coordinate；TA、TB、TCIt is for coefficient of region, relevant with P point region,
When unknown node P is in region 1,
When unknown node P is in region 2,
When unknown node P is in region 3,
When unknown node P is in region 4,
When unknown node P is in region 5,
When unknown node P is in region 6,
When unknown node P is in region 7,
Z6: use the crowd's searching algorithm improved k the coordinate (x to obtainingp1,yp1) ... (xpk,ypk) be optimized, obtain The coordinate of unknown node P after optimization；
Crowd's searching algorithm of described improvement is fitness function with the difference of existing known crowd's searching algorithm (SOA) Difference, and the step-length in existing known crowd's searching algorithm (SOA) is reduced 50%；Crowd's searching algorithm of described improvement Fitness function be:
F = 1 - Σ i = 1 m [ ( ( x s - x i ) 2 + ( y s - y i ) 2 - Σ i = 1 m ( x s - x i ) 2 + ( y s - y i ) 2 m ) × ( d i - Σ i = 1 m d i m ) ] Σ i = 1 m ( ( x s - x i ) 2 + ( y s - y i ) 2 - Σ i = 1 m ( x s - x i ) 2 + ( y s - y i ) 2 m ) 2 × Σ i = 1 m ( d i - Σ i = 1 m d i m ) 2
Coordinate (x in formulas,ys) represent k coordinate (xp1,yp1) ..., (xpk,ypkAny one coordinate in), coordinate (xi,yi) For any one coordinate in m beaconing nodes；diRepresent the distance value described in step Z1；At k the fitness function obtained In value F, select minima.
CN201610338877.0A 2016-05-20 2016-05-20 Wireless sensor network intelligently corrects distance-measuring and positioning method Expired - Fee Related CN106054127B (en)

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