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College of Engineering
Anchor Nodes Placement for Effective
Passive Localization
Anchor Nodes Placement for Effective
Passive Localization
Karthikeyan Pasupathy
Major Advisor: Dr. Robert Akl
Department of Computer Science and Engineering
Karthikeyan Pasupathy
Major Advisor: Dr. Robert Akl
Department of Computer Science and Engineering
OutlineOutline
• Objective
• Overview of Sensor Networks
• Localization
• Motivation
• Anchor Node Placement
• Simulations and Results
• Conclusions and Future Directions
• Objective
• Overview of Sensor Networks
• Localization
• Motivation
• Anchor Node Placement
• Simulations and Results
• Conclusions and Future Directions04/20/23 2/46
ObjectiveObjective
• How to place anchor nodes for better passive localization ?
• How to place anchor nodes for better passive localization ?
04/20/23 3/46
Overview of Sensor NetworksOverview of Sensor Networks
• Made of tiny sensor nodes networked together
• Communicate wirelessly
• Made of tiny sensor nodes networked together
• Communicate wirelessly
04/20/23 4/46
Overview of Sensor NetworksOverview of Sensor Networks
• Architecture• Architecture
04/20/23 5/46
Overview of Sensor NetworksOverview of Sensor Networks
• Limitations
• Deployment
• Short lifetime
• Unmanned
• Limitations
• Deployment
• Short lifetime
• Unmanned
04/20/23 6/46
Overview of Sensor NetworksOverview of Sensor Networks
Applications
• Military
• Reconnaissance, surveillance, shooter’s location, target tracking etc.
• Environment
• Track animals, birds, environmental conditions; detect forest fires, floods
Applications
• Military
• Reconnaissance, surveillance, shooter’s location, target tracking etc.
• Environment
• Track animals, birds, environmental conditions; detect forest fires, floods
04/20/23 7/46
Overview of Sensor NetworksOverview of Sensor Networks
Applications
• Healthcare
• Monitor doctors, patients, drug administrators
• Hospitals – monitor physiological signals
• Medication – avoid wrong medication
Applications
• Healthcare
• Monitor doctors, patients, drug administrators
• Hospitals – monitor physiological signals
• Medication – avoid wrong medication
04/20/23 8/46
Overview of Sensor NetworksOverview of Sensor Networks
Applications
• Domestic
• Smart home
• Smart kindergarten
• Industry
• Machine diagnosis; monitor radiation, material fatigue, product quality
Applications
• Domestic
• Smart home
• Smart kindergarten
• Industry
• Machine diagnosis; monitor radiation, material fatigue, product quality
04/20/23 9/46
LocalizationLocalization
• Where are these nodes ?
• Local position
• Global position
• How to localize?
• GPS
• Where are these nodes ?
• Local position
• Global position
• How to localize?
• GPS
04/20/23 10/46
LocalizationLocalization
• Localization Systems
• Centralized
• Distributed
• Localization Systems
• Centralized
• Distributed
04/20/23 11/46
LocalizationLocalization
• Centralized
• Not limited by algorithm
• More accurate results
• Traffic congestion
• Computational complexity
• Centralized
• Not limited by algorithm
• More accurate results
• Traffic congestion
• Computational complexity
04/20/23 12/46
LocalizationLocalization
• Distributed
• Usually iterative
• Algorithms generally energy efficient and self organizing
• Less accurate
• Distributed
• Usually iterative
• Algorithms generally energy efficient and self organizing
• Less accurate
04/20/23 13/46
LocalizationLocalization
• Different techniques
• Received Signal Strength (RSS)
• Time of Arrival (TOA)
• Angle of Arrival (AOA)
• Different techniques
• Received Signal Strength (RSS)
• Time of Arrival (TOA)
• Angle of Arrival (AOA)
04/20/23 14/46
RSSRSS
• Signal strength
• Inverse Square law
• Error of several meters
• Less accurate
• Vulnerable to occlusions
• Signal strength
• Inverse Square law
• Error of several meters
• Less accurate
• Vulnerable to occlusions
04/20/23 15/46
Radio Hop CountRadio Hop Count
• Nodes separated by at most R
• Affected by hindrances
• Nodes separated by at most R
• Affected by hindrances
04/20/23 16/46
TOATOA
• Difference in propagation speed of signals
• Difference in propagation speed of signals
04/20/23 17/46
TOATOA
• More accurate
• Vulnerable to occlusions
• More accurate
• Vulnerable to occlusions
04/20/23 18/46
Angle of ArrivalAngle of Arrival
• Phase / Time difference recorded by an array of microphones
• Expensive
• Bulkier
• Not practical to implement
• Sensor size shrinks
• Phase / Time difference recorded by an array of microphones
• Expensive
• Bulkier
• Not practical to implement
• Sensor size shrinks
04/20/23 19/46
Passive LocalizationPassive Localization
• Why passive ?
• Nodes are silent
• Advantages
• No external source for signals
• Can work with existing data
• Can be used in most outdoor applications
• Why passive ?
• Nodes are silent
• Advantages
• No external source for signals
• Can work with existing data
• Can be used in most outdoor applications
04/20/23 20/46
Passive LocalizationPassive Localization
• Disadvantages
• Centralized
• Not suitable for indoor applications
• Disadvantages
• Centralized
• Not suitable for indoor applications
04/20/23 21/46
Passive LocalizationPassive Localization
• Event detection
• Projected distances
• Localization
• Distance Matrix
• SVD
• Event detection
• Projected distances
• Localization
• Distance Matrix
• SVD
04/20/23 22/46
Passive LocalizationPassive Localization
• Localization
• Linear Combination coefficients
• Localization
• Linear Combination coefficients
04/20/23 23/46
MotivationMotivation
• Deployment of anchor nodes at specific position not easy
• Function of anchor nodes are different in passive localization
• Deployment of anchor nodes at specific position not easy
• Function of anchor nodes are different in passive localization
04/20/23 24/46
Anchor Node PlacementAnchor Node Placement
• Density
• Better to have more anchor nodes
• Deployment and hardware costs
• Redundancy
• Geometry
• No three anchor nodes may be linearly related
• Density
• Better to have more anchor nodes
• Deployment and hardware costs
• Redundancy
• Geometry
• No three anchor nodes may be linearly related
04/20/23 25/46
Simulations and resultsSimulations and results
Assumptions:
• Propagation velocity – unity
• Clocks - time synchronized.
• Global events - distributed around the network.
• Signal processing – skipped
Assumptions:
• Propagation velocity – unity
• Clocks - time synchronized.
• Global events - distributed around the network.
• Signal processing – skipped
04/20/23 26/46
Simulations and resultsSimulations and results
Assumptions:
• Ideal case – no redundancy
• Global event – static sources
Assumptions:
• Ideal case – no redundancy
• Global event – static sources
04/20/23 27/46
Simulations and ResultsSimulations and Results
User Interface: User Interface:
04/20/23 28/46
Simulations and ResultsSimulations and Results
Localization Error:Localization Error:
04/20/23 29/46
Simulations and ResultsSimulations and Results
Random deploymentRandom deployment
n = 10, k = 3
04/20/23 30/46
Simulations and ResultsSimulations and Results
Random deploymentRandom deployment
n = 10, e = 20
04/20/23 31/46
Simulations and ResultsSimulations and Results
Manual deployment – Sparse networkManual deployment – Sparse network
(Lerr = 15.52%)
∆ Sensor Nodes
+ Computed position
● Anchor Nodes
04/20/23 32/46
Simulations and ResultsSimulations and Results
Manual deployment – Sparse networkManual deployment – Sparse network
(Lerr = 9.68 %)
04/20/23 33/46
Simulations and ResultsSimulations and Results
Manual deployment – Sparse networkManual deployment – Sparse network
(Lerr = 5.75 %)
04/20/23 34/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 18.63 %)
04/20/23 35/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 12.24 %)
04/20/23 36/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 43.75 %)
04/20/23 37/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 586.54 %)
04/20/23 38/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 14.92 %)
04/20/23 39/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 14.11 %)
04/20/23 40/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 11.57 %)
04/20/23 41/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 11.32 %)
04/20/23 42/46
Simulations and ResultsSimulations and Results
Manual deployment – Dense networkManual deployment – Dense network
(Lerr = 11.54 %)
04/20/23 43/46
ConclusionsConclusions
• Investigated positioning of anchor nodes
• Better to deploy anchor nodes at the center of the network
• Less linearity – Better localization
• Placing at right angles
• Real situations may be different
• Investigated positioning of anchor nodes
• Better to deploy anchor nodes at the center of the network
• Less linearity – Better localization
• Placing at right angles
• Real situations may be different
04/20/23 44/46
Future DirectionsFuture Directions
• Implementation on motes.
• Third dimension
• Time synchronization
• Mobile global events
• Implementation on motes.
• Third dimension
• Time synchronization
• Mobile global events
04/20/23 45/46
Questions ?Questions ?
04/20/23 46/46