Post on 23-Jul-2020
Localization in Wireless Sensor NetworksPart 2: Localization techniques
Lukasz Mazurek
Department of InformaticsUniversity of Oslo
Cyber Physical Systems, 11.10.2011
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Localization problem in WSN
In a localization problem in WSN we have two groups ofsensors:
Anchors — nodes of the network with known positions.Non-anchors — nodes of the network to be localized.
There are many algotihms leading to localize the non-anchors.
These algorithms use different physical measurements toinvestigate the position of a non-anchor.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Angle-of-arrival measurement
In this method we measurethe angle between thetransmitter–receiver line andthe reference direction.
In order to do this we mustuse an anisotropic antenna.
Actually AOA measurementsuse either amplitude orphase response of theantenna.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
AOA measurement using antenna’s amplitude response
The rotated beam of the receiveranisotropic antenna
The direction corresponding to themaximum signal strength is takenas the direction of the transmitter
Problem: varying signal strength
Second non-rotating isotropicantenna to normalize the signalstrength.
Use a minimum of two (typically atleast four) stationary antennas withknown, anisotropic antennapatterns.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
AOA measurement using antenna’s phase response
Large receiver antenna (relativeto λ) or antenna array.
Phase difference betweenadjacent antenna elements:
2πd cos θ
λ
Problems in case of:
Weak (relative to noise) signals
Strong co-channel interference
Multipath signals
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Limitations of AOA measurements
Directivity of the antenna — measurement strongly dependsof antenna angular resolution.
Shadowing — transmitters and receivers must lie inline-of-sight.
Multipath reflections
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Distance-related measurement techniques
Propagation time measurement techniques
Time-difference-of-arrival (TDOA) measurement techniques
Lighthouse approach to distance measurement
Distance estimation using received signal strength (RSS)measurement
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Propagation time measurements
One-way propagation time measurements
Measure the difference between the sending time of a signalat the transmitter and the receiving time of the signal at thereceiver.
Requires synchronized local times at the transmitter andreceiver.
Interesting approach: two signals (RF and ultrasonic) sentsimultaneously. Since vsound � c, the time difference betweenthe receipt of signals can be used to calculate the distance.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Propagation time measurements
Roundtrip propagation time measurements
Measure the difference between the time when a signal is sentby a sensor and the time when the returned signal is received.
No synchronization problem.
The major error source: the dalay required for handling thesignal in the second sensor.
A priori known internal delay.Delay measured by the second sensor and sent to the firstsensor to be substracted.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Time-difference-of-arrival measurements
In this method we measure thetime-difference-of-arrival foreach pair of receivers.
TDOA between receiver i andreceiver j is given by:
∆ti ,j = ti − tj ,
where ti , tj — the time when asignal is received at receivers iand j respectively
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Time-difference-of-arrival measurements
The accuracy of TDOA measurements will improve when theseparation between receivers increases.
Closely spaced multiple receivers may give rise to multiplereceived signals that cannot be separated.
Overlapping signals due to multipath often cannot be resolved.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Lighthouse approach to distance measurements
Parallel rotating opticalbeam
By measuring the timeduration t that the receiverdwells in the beam we cancalculate the distance fromthe rotational axis of theoptical beam.
d ≈ b
2 sin(ωt/2).
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Lighthouse approach to distance measurements
The unknown angular velocity ω can be derived from the timeinterval between the two consecutive detections of the beam.
Adventage: The optical receiver can be of a very small size.
However the transmitter may be large.
This approach requires a direct line-of-sight between theoptical receiver and the transmitter.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Distance estimation using RSS measurements
These techniques are based on a received signal strengthindicator (RSSI).
Advantage: They require no additional hardware.
They are unlikely to significantly impact local powerconsumption, sensor size and cost.
In free space the received power of signal varies as the inversesquare of the distance d between the transmitter and thereceiver
P(d) ∼ 1
d2
In fact the propagation of a signal is affected by reflection,diffraction and scattering.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA measurementsDistance-related measurementsRSS profiling measurements
RSS profiling measurements
In addition to anchor nodes, a large number of sample pointsare distributed throughout the coverage area of the sensornetwork.
At each sample point, a vector of RSS from all the anchors isobtained.
The collection of all these vectors provides (by extrapolation)a map of the whole region, stored in a central location.
By referring to this map, a non-anchor node can estimate itslocation.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
One-hop and multi-hop localization techniques
One-hop localization technique
The non-anchor node to be localized is the one-hop neighborof a sufficient number of anchors with known positions.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
AOA-based localization techniques
Measured angles βi
Known functions θi (x)
Maximum likelihoodestimator method tofind xt .
In the simpliest caseit’s equivalent to leastsquares method:
xt = arg minn∑
i=1
ε2i
= arg minn∑
i=1
(θi (x)− βi )2
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
AOA maximum likelihood estimator (MLE)
xt minimizes the following sum:
xt = arg minn∑
i=1
(θi (x)− βi )2
In general, εi = (θi (x)− βi ) are assumed to be zero-meanGaussian noises with variance σ2
i . Therefore in matrix notation:
xt = arg min(θ(x)− β)TS−1(θ(x)− β),
where: θ(x) = (θ1(x), . . . , θn(x)), β = (β1, . . . , βn), and acovariance matrix of εi , S = diag{σ2
1, . . . , σ2n}.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
AOA maximum likelihood estimator (MLE)
Minimization problem:
xt = arg min(θ(x)− β)TS−1(θ(x)− β),
First solution: Newton-Gauss iteration method.
xt,k+1 = xt,k+(θx(xt,k)TS−1θx(xt,k)
)−1θx(xt,k)TS−1 (β − θ(xt,k)) ,
where θx(xt,k) denotes the partial derterivative of θ withrespect to x evaluated at point xt,k .
This method requires an initial estimate close enough to thetrue minimum of the cost function.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
AOA — Stansfield approach
xt = arg min(θ(x)− β)TS−1(θ(x)− β),
Second solution: Stansfield approach. Assumption:measurement error is small enough such that εi ≈ sin εi .
The cost function to minimize becomes:n∑
i=1
sin2(θi (x)− βi )σ2i
We can use the relation
sin(θi (x)− βi ) = sin θi (x) cosβi − cos θi (x) sinβi
=(y − yi ) cosβi − (x − xi ) sinβi
ri,
where ri =√
(x − xi )2 + (y − yi )2.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
AOA — Stansfield approach
Cost function to minimize:n∑
i=1
sin2(θi (x)− βi )σ2i
=n∑
i=1
[(y − yi ) cosβi − (x − xi ) sinβi ]2
σ2i r
2i
= (Ax− b)TR−1S−1(Ax− b),
where
A =
sinβ1 − cosβ1...
...sinβn − cosβn
b =
x1 sinβ1 − y1 cosβ1...
xn sinβn − yn cosβn
R = diag{r2
1 , . . . , r2n}
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
AOA — Stansfield approach
Cost function to minimize:
xt = arg min(Ax− b)TR−1S−1(Ax− b),
Stansfield assumes that the cost function weakly depends onR.
Under these assumptions, the minimization of cost functionwith respect to xt is a well known problem and the solution isgiven by:
xt =(ATR−1S−1A
)−1ATR−1S−1b
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Distance-based localization techniquesGlobal Positioning System (GPS)
31 GPS satellites sending theinformation about satellitespositions and precise time themessage was transmitted.
One-way propagation timemeasurement.
Theoretically, measure of distancefrom 3 satellites is sufficient tocalculate the position of thereceiver.
Practically, the distance fromfourth satellite is necessary forclock synchronization.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Distance-based localization techniques
Generally in a WSN, we measure vector of distancesd̃ = (d̃1, . . . , d̃n) to n anchors.
Let d(x) = (d1(x), . . . , dn(x)) be the vector of real distancesfrom point x to anchors.
Then the location estimation problem can be formulated usinga maximum likelihood approach as:
xt = arg min[d(x)− d̃
]TS−1
[d(x)− d̃
],
where S is the covariance matrix of the distance measurementerrors.
This equation can be solved in similar way to AOA-basedtechnique.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
TDOA-based localization techniques
Given the TDOA measurement ∆ti ,jwe get a hyperbola equation
∆ti ,j = ti − tj
=1
c(‖ri − rt‖ − ‖rj − rt‖) ,
for rt . In fact we must consider thedifference between the measuredvalue ∆t̃i ,j and the real value ∆ti ,j .
∆t̃i ,j = ∆ti ,j + εi ,j
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
TDOA-based localization techniques
For n receivers we get a system of n − 1 linearly independentequations: ∆t̃1,n
...∆t̃n−1,n
=
‖r1−rt‖−‖rn−rt‖
c...
‖rn−1−rt‖−‖rn−rt‖c
+
ε1,n...
εn−1,n
Let ∆t̃ = (∆t̃1,n, . . . ,∆t̃n−1,n), f(r) denotes the vector(
1
c(‖r1 − r‖ − ‖rn − r‖) , . . . , 1
c(‖rn−1 − r‖ − ‖rn − r‖)
)and ε = (ε1,n, . . . , εn−1,n)
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
TDOA-based localization techniques
We can write our system of equations in the following way:
∆t̃− f(rt) = ε
We want to minimize the sum∑n
i=1 ε2i .
We can again assume that εi is a zero-mean Gaussian noise withvariance σ2
i . Denote the covariance matrix diag{σ21, . . . , σ
2n} by S.
We get the same equation as in AOA case:
rt = arg min[∆t̃− f(r)
]TS−1
[∆t̃− f(r)
]T.
Therefore the recursive solution is
rt,k+1 = rt,k +(fr(rt,k)TS−1fr(rt,k)
)−1fr(rt,k)TS−1
[∆t̃− f(rt,k)
] Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Lighthouse approach to one-hop localization
Using lighthouse approach wemeasure the distances dX , dY , dZfrom 3 perpendicular axes X ,Y ,Z .
Equations for receiver coordinates:
d2X = y2 + z2
d2Y = z2 + x2
d2Z = x2 + y2
8 solutions corresponding 8quadrants in the coordinate system.
We know a priori in whichquadrant the receiver is located.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
RSS-profiling-based localization
This technique consists of two phases:
Building the RSS map of the entire area,Fitting the measured RSS vector from a non-anchor node intothe appropriate part of the map.
The accuracy of this techique depends on both phasesaccuracy.
The major practical obstacle: changes in the environmentrequire (possibly costly) recalculation of the model.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
LANDMARCIndoor Location Sensing Using Active RFID
LANDMARC
An experiment presenting the application of RSS-based localizationtechnique with use of the RFID system.
Radio-frequency identification (RFID)
RFID system consists of RFID readers and RFID tags.
RFID reader can read data emitted from RFID tags.
RFID readers and tags use a defined radio frequency andprotocol to transmit and receive data.
RFID reader used in this experiment has 8 different powerlevels, therefore it can estimate the distance to the RFID tagusing RSS technique.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
LANDMARC
16 reference RFID tags withknown positions,
8 tracking RFID tags tolocalize,
4 RFID readers estimating thedistance to tags due tomeasurements on power levels1–8.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
LANDMARC
RSS varies due to both static obstructions and dynamichuman movement.
Therefore, direct estimation of the distance to a tracking tagfrom RSS leads to big errors.
Instead we can compare RSS from a tracking tag to RSS froma reference tag with a known position.
Let Pi (t) denotes a RSS from tag t (either tracking orreferenced) measured by reader i (i ∈ {1, . . . , n}).
The distance between tags a and b can be defined as follows:
Ea,b =
√√√√ n∑i=1
(Pi (a)− Pi (b))2
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
LANDMARC
Coordinates of the tracking tag can be estimated as aweighted mean of coordinates of the k closest (due to Ea,b)reference tags:
rt =k∑
i=1
wi ri .
Empirically, in LANDMARC, weights wi are given by:
wi =1/E 2
t,i∑kj=1 1/E 2
t,j
.
Experiments for different values of k ∈ {1, 2, 3, 4, 5} showedthat the best accuracy of this estimation we get for k = 4.
This result was easy to predict, because all the reference tagswere placed in a grid array.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
AOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
Summary of LANDMARC experiment
We can implement relatively cheap indoor localization systemwith accuracy under 2 m using RFID.
Unfortunately, RFID products do not provide RSSmeasurement, only report ”detectable” or ”not detectable” ineach of 8 power levels.
Moreover, it takes about 1 minute to scan in all 8 power levels.
Another problem: the power levels detected from two tagsmay be different due to the variation of the chips and circuits,as well as batteries.
Dynamic environment is one of the main reasons forincreasing measurement errors. (A person standing in front ofa tag may greatly increase the error).
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Multi-hop localization techniques
Multi-hop localization technique
The non-anchor nodes are not necessarily the one-hop neighbors ofthe anchors.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Connectivity-based multi-hop localization algorithms
Connectivity-based algorithms
They do not rely on any of the described measurementtechniques.
Instead they use the connectivity information who is withinthe communications range of whom.
Connectivity metric
The ratio of the number of transmitter signals succesfullyreceived to the total number of signals from that transmitter.
Transmitters whose connectivity metric exceeds a certainthreshold (e.g. 90%) are called reference points.
A receiver at an unknown location uses the centroid of itsreference points as its location estimate.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Distance vector (DV-hop) approach
All anchors flood their locations to other nodes in the network.
The messages are propagated hop-by-hop and there is ahop-count in the message.
Each node maintains the least number of hops that is awayfrom an anchor.
When an anchor receives a message from another anchor, itestimates the average distance of one hop to this anchor andsends it back to the network as a correction factor.
When receiving the correction factor, a non-anchor node isable to estimate its distance to anchors and performs estimateits location.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Connectivity-based multi-hop localization algorithms
The most attractive feature
Simplicity of algorithms
Limitations
They can only provide a coarse grained estimate of location.
The localization error is highly dependent on the node density,the number of anchors and the network topology (i.e. requiresa high node density, a lot of anchors and a regular network).
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Distance-based multi-hop localization algorithms
The core of distance-based localization algorithms
Use of inter-sensor distance measurements in a sensor network tolocate the entire network.
Centralized algorithms
use a single central processor tocollect all the individualinter-sensor distance data andproduce a map of the entiresensor network.
Distributed algorithms
rely on self-localization of eachnode in the sensor network usingthe distances the node measuresand the local information itcollects from its neighbors.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Centralized distance-based localization algorithms
Centralized distance-based multi-hop localization algorithms
Technique widely used in road traffic monitoring and control,environmental monitoring, health monitoring and precisionagriculture monitoring networks.
Feasible to implement.
High likelihood of providing more accurate location estimatesthan those provided by distributed algorithms.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Centralized distance-based localization algorithms
Multidimensional scaling (MDS) approach
The whole sensor network is divided into smaller groups whereadjacent groups may share common sensors.
Each group contains at least three anchors or sensors whoselocations have already been estimated.
MDS is used to estimate the relative locations of sensors ineach group and build local maps. Local maps are thenstitched together to form an estimated global map by utilizingcommon sensors between adjacent local maps.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Distributed distance-based localization algorithms
Distributed distance-based multi-hop localization algorithms
Extension of the distributed connectivity-based localizationalgorithms.
DV-distance algorithm
Obtained from DV-hop connectivity-based algorithm
Propagates measured distance among neighboring nodesinstead of hop count.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Table of Contents
1 Measurement techniques used in localizationAngle-of-arrival (AOA) measurementsDistance-related measurementsReceived signal strength (RSS) profiling measurements
2 One-hop localization algorithmsAOA-based localization techniquesDistance-based localization techniquesRSS-profiling-based localization
3 Multi-hop localization algorithmsConnectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Centralized vs distributed algorithms
Pro centralized algorithms
Centralized algorithms are likely to provide more accuratelocation estimates than distributed algorithms.
In distributed algorithms error propagation may cause biggerinaccuracies of the final results.
Distributed algorithms are more difficult to design (locallyoptimal algorithms may not perform well in a global sense).
Distributed algorithms generally require multiple iterations toarrive a stable solution and therefore may be slower thancentralized.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Centralized vs distributed algorithms
Pro distributed algorithms
Decentralized localization is harder than centralized — anyalgorithm for decentralized localization can be applied tocentralized problems, but not the reverse.
Centralized algorithms are not feasible to be implemented forlarge scale sensor networks.
Centralized algorithms require higher computationalcomplexity than distributed algoritms.
In large networks distributed algorithms are moreenergy-efficient than centralized algorithms.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Summary
There are many different techniques available for WSNlocalization.
Typically, localization algorithms based on AOA andpropagation time measurements are able to achieve betteraccuracy than RSS techniques.
However, that accuracy is achieved at the expense of higherequipment cost.
It is possible to establish relatively cheap indoor localizationsystem in WSN using RFID equipment.
Lukasz Mazurek Localization in WSN
Measurement techniques used in localizationOne-hop localization algorithms
Multi-hop localization algorithms
Connectivity-based multi-hop localization algorithmsDistance-based multi-hop localization algorithmsCentralized vs distributed algorithms
Bibliography I
Guoqiang Mao, Barıs Fidan and Brian D.O. AndersonWirless Sensor Network Localization Techniques.Computer Networks, 2529-2553, 2007.
Lionel M. Ni and Yunhao Liu.LANDMARC: Indoor Location Sensing using active RFIDWireless Networks 10, 701-710, 2004.
Lukasz Mazurek Localization in WSN