CN108055636A - A kind of method of the 3D wireless sensor networks positioning based on unmanned plane auxiliary - Google Patents
A kind of method of the 3D wireless sensor networks positioning based on unmanned plane auxiliary Download PDFInfo
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- CN108055636A CN108055636A CN201711383700.3A CN201711383700A CN108055636A CN 108055636 A CN108055636 A CN 108055636A CN 201711383700 A CN201711383700 A CN 201711383700A CN 108055636 A CN108055636 A CN 108055636A
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- unmanned plane
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- 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
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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
- 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
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- 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
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- 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 present invention relates to a kind of methods of the 3D wireless sensor networks positioning based on unmanned plane auxiliary.The unmanned plane broadcast signal strength that the present invention receives first according to blind node measures the positional distance with reference point, recycles multilateration, calculates the position of blind node.And utilize real-time, freedom topology unmanned plane path planning algorithm（RT‑TF）, realize the selection of unmanned plane optimization path.Finally unmanned plane path planning algorithm is simulated and analyzed under 3D deployment and the more scenes in 3D surfaces, is finally drawn a conclusion.The positioning for making 3D wireless sensor network nodes using the method for the present invention is more efficient, and with very strong adaptability and autgmentability.
Description
Technical field
The present invention relates to wireless sensor technology, unmanned plane application technology and location technologies, are that a kind of unmanned plane that is based on aids in
3D wireless sensor networks positioning method.
Background technology
In the wireless sensor network based on Internet of Things, sensor node is disposed, and is collected respectively as intelligent terminal
The multi-medium data of class.Since most Internet of Things service is all position sensing, it is seen that correctly obtain sensor network
The position of interior joint is very necessary.However, in the wireless sensor network of 3D, most of existing sensor network nodes are determined
The precision of position algorithm is seriously affected by complex topology structure.Although existing some effective methods of largely having researched and proposed are come
The complexity of topology is reduced, but its performance still has much room for improvement.
With 3D deployment wireless sensor network compare, the positioning of the wireless sensor network node on 3D surfaces it is more complicated and
Challenge with bigger.Existing solution such as cuts and sews, layered approach etc..Usually using triangular mesh
Segmentation or the scheme of projection, to minimize the difficulty of topology generation, but the calculating of these methods is extremely complex, therefore existing side
Case is not suitable for the positioning of large-scale 3D surface probes network node.Complex topology structure is led to the problem of still urgently
It solves, how to realize the high applicability of node positioning method, inexpensive and high benefit remains present hot issue.
It is increasingly complete with the radio propagation environment between the rapid development of unmanned plane and sensor node and unmanned plane
It is kind.The idea of unmanned plane auxiliary positioning, is suggested.Nearest research is able to validate only in some specific topologys, and unmanned plane is auxiliary
Help positioning that can be implemented, however there are still challenges in some complicated 3D wireless sensor networks.Therefore, it is auxiliary based on unmanned plane
The positioning of the 3D wireless sensor network nodes helped is still a novel research direction, since unmanned plane is subject to the energy to limit
System, for 3D deployment and 3D surfaces wireless sensor network, when better unmanned plane auxiliary positioning is provided, one it is efficient nobody
Machine path planning algorithm be also there is an urgent need to.
Bibliography：
[1]Y.Yang,M.Jin,and H.Wu.3D Surface Localization with Terrain
Model.In proc.of IEEE INFOCOM,2014.
[2]S.Chu,C.Lien,W.Lin,Y.Huang and C.Pan.A Survey of Localization
inWireless Sensor Network.International Journal of Distributed
SensorNetworks,(4):385-391,2012.
[3]I.Ahmad,N.Bergmann,R.Jurdak and B.Kusy.Experiments on
Localizationof Wireless Sensors using Airborne Mobile Anchors.In proc.OfIEEE
Conference on Wireless Sensors,2015.
The content of the invention
In view of the deficiencies of the prior art, the present invention provides a kind of 3D wireless sensor networks based on unmanned plane auxiliary are determined
The method of position.
The signal strength that the present invention receives unmanned plane broadcast according to blind node first calculates and unmanned plane reference point locations
Distance recycles multilateration, calculates the position of blind node.Finally using real-time, freedom Topology Algorithm (RT-TF), nothing is carried out
The selection of man-machine optimization path.
The definition of term：
Blind node -- do not know the node of its position in the 3 d space.
In reference point-flight course, unmanned plane, the physical location to fly in the 3 d space i.e. reference point can be used to position
Blind node.
Candidate collects -- the set of the possible position of next step in unmanned plane during flying.
The method of the present invention comprises the concrete steps that：
The coverage that step (1), unmanned plane rest on certain point is limited be subject to communication radius r.It is covered included in this
The quantity of blind node in cover area, which can be easily calculated, to be come.What these blind nodes can be broadcasted by receiving unmanned plane
Signal calculates the distance between itself and unmanned plane reference point d further according to the signal strength (RSSI) of unmanned plane broadcast message,
Calculation formula is as follows.
Wherein A is signal strength when transmitting terminal and receiving terminal are separated by 1 meter, and n is the environmental attenuation factor
(xj-x1)2+(yj-y1)2+(zj-z1)2=d1 2
(xj-x2)2+(yj-y2)2+(zj-z2)2=d2 2
…
(xj-xn)2+(yj-yn)2+(zj-zn)2=dn 2
(x in above formulaj,yj,zj) be blind node j physical location in the 3 d space；(j=1；2；... m), { (x1,y1,
z1)……(xn,yn,zn) it is the GPS offers that the position of n unmanned plane reference point is carried by unmanned plane.
Step (2) utilizes real-time, freedom Topology Algorithm (RT-TF), the selection of progress unmanned plane optimization path.
2-1. candidate prepares.Be evenly dividing 12 directions, be arranged to candidate, at the same RT-TF will to each direction into
Row verification.Check that program includes avoiding repeating to quote the reference point in flight path and intrinsic conllinear sex chromosome mosaicism.
2-2. victors select.Greedy algorithm is used, iteration performs, and is concentrated from next candidate and selects a covering
Flag>The most victor of 0 blind node quantity, as the moving direction of next step, in addition, the wireless sensing on 3D surfaces
In device network, flag>The position of 0 blind node is also required to be considered, particularly the borderline region in 3D topologys.
It further may be incorporated into real-time rollback mechanism.The selection of victor is based on effective Candidate Set.If prepare
It is invalid Candidate Set after program, then next reference position cannot obtain.It is this special in real test
Situation will cause path planning failure and the hovering of unmanned plane.Can effective candidate's collection can be rolled back to by rollback mechanism, from
And the situation of path dependent options is solved, improve the adaptability of algorithm.
It, can also be to unmanned plane path planning algorithm under 3D deployment and the more scenes in 3D surfaces after the completion of the above process
Simulation and analysis.Rectangular area and c-type region are devised under the wireless sensor network of 3D deployment, the wireless biography on 3D surfaces
Saddle-shape and mountain type region are devised under sensor network, generates 500 nodes at random in region, when starting, all nodes
It is evenly distributed on around region surface.Afterwards, some nodes, which are selected, deliberately removes, to ensure to sense on such 3D surfaces
The distribution of device node is not fully consistent, is closer to actual conditions.In simulation, unmanned plane broadcast singal time interval is set
It is set to 30ms, it is ensured that each moving step length is about 6 meters, and reasonable variable separation solutions avoid reference point excessively intensive.
The beneficial effects of the invention are as follows：
(1), assisted with unmanned plane, realize the positioning of the wireless sensor network in 3D deployment and 3D surfaces.
(2), using RT-TF real-time, freedom topology unmanned plane path planning algorithm, can in unmanned plane auxiliary positioning
To further improve the efficiency of positioning, while reduce cost.
(3), the simulation of the topological scene of the wireless sensor network on multiple 3D deployment and 3D surfaces has been carried out.
Description of the drawings
Fig. 1 is unmanned plane auxiliary positioning overall flow figure；
Fig. 2 is unmanned plane coverage area diagram；
Fig. 3 is candidate direction segmentation figure；
Fig. 4 is the wireless sensor network assignment test result figure under different 3D deployment and 3D surfaces scene.
Specific embodiment
Below in conjunction with attached drawing, the invention will be further described.
The method of 3D wireless sensor networks positioning based on unmanned plane auxiliary comprises the concrete steps that：
Step (1), as depicted in figs. 1 and 2, the coverage that unmanned plane rests on certain point is limited be subject to communication radius r
System.The quantity of blind node included in this overlay area, which can be easily calculated, to be come.These blind nodes can pass through
Receive the broadcast singal of unmanned plane, according to the signal strength (RSSI) of the unmanned plane broadcast message received, come calculate itself with
The distance between unmanned plane reference point.
(xj-x1)2+(yj-y1)2+(zj-z1)2=d1 2
(xj-x2)2+(yj-y2)2+(zj-z2)2=d2 2
…
(xj-xn)2+(yj-yn)2+(zj-zn)2=dn 2
(x in above formulaj,yj,zj) be blind node j position；(j=1；2；…；M), { (x1,y1,z1)……(xn,yn,zn)}
It is the location sets of reference point, is provided by unmanned plane.Blind node j just exists when receiving the signal of the reference point from unmanned plane
It is used in corresponding equation.Otherwise, this position will be replaced with (0；0；0), when blind node receives at least four reference point letter
During breath, can the positioning of blind node be realized according to the multilateration of above formula.
Step (2), the path planning algorithm (RT-TF) using real-time, freedom topology realize unmanned plane optimization path
Selection.
2-1. candidate prepares.As shown in figure 3, be evenly dividing up and down front and rear 12 directions of grade as candidate, RT-
TF algorithms will verify each direction.Check that program includes avoiding repeating to quote the reference point in flight path and intrinsic
Conllinear sex chromosome mosaicism.As shown in algorithm 1, in order to reach the two conditions, introduce taboo list U is introduced.First, with it is non-colinear requirement come
Ensure that blind node receives four RSSI signals, and then correctly obtain its position.Secondly, using non-overlapping pattern, leading will be worked as
Position is added in introduce taboo list.So all existing reference points can be all added in introduce taboo list U, so keep away
Exempt from the repetition to reference point to quote.If the position of the next movement of unmanned plane is not present in introduce taboo list, would not be with it
He is overlapped reference point.Otherwise, this direction j will be ignored, clijIt will be assigned to (- 1；-1；- 1) mark its invalid,
The position in this direction also will no longer be candidate.
2-2. victors select.Greedy algorithm is used, iteration performs.The value of each blind node flag is initialized first,
Equal to 4, it is ensured that each blind node is at least 4 times capped.Blind node receives the signal of a reference point, the flag's of blind node
Value will subtract 1.Work as flag<When 0, just no longer receive extra broadcast singal.The weight w of the candidate of calculatingijFrom the point of candidate
A victor is selected, as mobile direction, in addition, flag>The position of 0 blind node is also required to be considered.Consider
The influence of covering problem and boundary position, victor's selection algorithm are adjusted to as shown in algorithm 2, and Xun Huan candidate concentrates, legal
And clijNot equal to (- 1；-1；- 1) position, works as clijBelong to borderline region, while clijWith max { ci1；ci2；…；cinBetween
Distance if less than threshold value δ, wijPeak, and direction cl will be endowedijAs the point of next movement.
The real-time rollback mechanisms of 2-3..The selection of victor is based on effective Candidate Set.If it is nothing after preparation routine
Candidate's set of effect, next reference position cannot be acquired.In real test, this special situation will cause
The failure of unmanned plane path planning and the hovering of unmanned plane.Can effective candidate's collection be found by real-time rollback mechanism.Such as algorithm
Shown in 3, when effective Candidate Set is found, abstain from list U will not rollback at once, still, after step performs,
Element in temps will be refreshed.To ensure that introduce taboo list U will not be refreshed at once during rollback, once nobody
Machine moves, and current reference point i will follow UiAnd Ui-1Variation and refresh.Last unmanned plane can oneself selection one it is optimal
The flight path of change goes to tackle real-time exception, and carries out correct route adjustment.
Step (3) carries out sunykatuib analysis under 3D deployment and the more scenes in 3D surfaces to unmanned plane path planning algorithm.Such as figure
Shown in 4, rectangular area and c-type region are devised under the wireless sensor network scene of 3D deployment, in 3D surfaces wireless sensing
Saddle-shape region and mountain type region are devised under the scene of device network, 500 nodes is generated at random in each area, is starting
When, all nodes are evenly distributed on around region surface.Afterwards, some nodes, which are selected, deliberately removes, to ensure such
The distribution of sensor node is not fully consistent on 3D surfaces, is closer to actual conditions.In simulation, unmanned plane is broadcasted and is believed
Number time interval is arranged to 30ms, it is ensured that each moving step length is about 6 meters, rationally separates unmanned plane reference point.
As shown in figure 4, being positioned to all blind nodes being distributed in 120 meters of * 80 meters of * 5 meters of rectangular areas, 94 are only needed
Step to a c-type region, need to select 151 with continuing reference to point to build its flight path.All nodes are in saddle-shape region
Cover at least four subsurfaces.On mountain type surface, it is only necessary to which 62 steps go to provide its reference information, massif table is deployed in position
All nodes in face.In the wireless sensor network scene on 3D surfaces, due to border priority principle proposed by the present invention, significantly
Rollback amount cost is reduced, while step number relatively minimal in unmanned plane during flying path can be kept.
Such as Fig. 4, in the topological structure of different 3D wireless sensor networks the analog result of flight path show RT-TF without
Man-machine auxiliary positioning path planning algorithm not only effectively but also has very strong autgmentability, and according to RSSI in free space
The characteristics of communication environments and four spaces of points position, it is free topology to show scheme proposed by the present invention.
Claims (2)
- A kind of 1. method of the 3D wireless sensor networks positioning based on unmanned plane auxiliary, it is characterised in that comprise the following steps：Step (1) receives the signal strength calculating of unmanned plane broadcast and the distance of unmanned plane reference point locations according to blind node, then Using multilateration, the position of blind node is calculated：The coverage that unmanned plane i rests on certain point is limited be subject to communication radius r；It is blind included in this overlay area The quantity of node can be calculated；The signal that these blind nodes can be broadcasted by receiving unmanned plane i, further according to unmanned plane i The signal strength RSSI of broadcast message calculates the distance between itself and unmanned plane i reference points di：<mrow> <msub> <mi>d</mi> <mi>i</mi> </msub> <mo>=</mo> <msup> <mn>10</mn> <mrow> <mo>(</mo> <mi>a</mi> <mi>b</mi> <mi>s</mi> <mo>(</mo> <mrow> <msub> <mi>RSSI</mi> <mi>i</mi> </msub> </mrow> <mo>)</mo> <mo>-</mo> <mi>A</mi> <mo>)</mo> <mo>/</mo> <mo>(</mo> <mn>10</mn> <mo>*</mo> <mi>n</mi> <mo>)</mo> </mrow> </msup> </mrow>Wherein A is signal strength when transmitting terminal and receiving terminal are separated by 1 meter, and n is the environmental attenuation factor, then：(xj-x1)2+(yj-y1)2+(zj-z1)2=d1 2(xj-x2)2+(yj-y2)2+(zj-z2)2=d2 2…(xj-xn)2+(yj-yn)2+(zj-zn)2=dn 2(x in above formulaj, yj, zj) be blind node j physical location in the 3 d space, { (x1, y1, z1)……(xn, yn, zn) be The position of n unmanned plane reference point, the GPS carried by unmanned plane are provided, and the blind node is not know its position in 3d space The wireless senser put；Step (2) utilizes real-time, freedom Topology Algorithm, the selection of progress unmanned plane optimization path：Candidate prepares：Totally 12 directions front and rear up and down are evenly dividing, is arranged to candidate, while each direction is carried out Verification；Check that program includes avoiding repeating to quote the reference point in flight path and intrinsic conllinear sex chromosome mosaicism；Victor selects：With greedy algorithm, iteration performs, and the flag ＞ 0 for selecting a covering are concentrated from next candidate The most victor of blind node quantity, as the moving direction of next step, in addition, the wireless sensor network on 3D surfaces In, the position of the blind node of flag ＞ 0 is also required to be considered, particularly the borderline region in 3D topologys, candidate collection Refer to the set of the possible position of next step in unmanned plane during flying.
- 2. a kind of method of 3D wireless sensor networks positioning based on unmanned plane auxiliary according to claim 1, special Sign is：The selection of victor is based on effective Candidate Set；If it is invalid Candidate Set after preparation routine, then next A reference position cannot obtain；Can effective candidate's collection be rolled back to, so as to solve path dependent options by rollback mechanism at this time Situation.
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