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Indoor pedestrian localization using ibeacon and improved kalman filter
Kwangjae Sung
, Dong Kyu Roy Lee
,
Hwangnam Kim
*
*
Corresponding author for this work
Research output
:
Contribution to journal
›
Article
›
peer-review
35
Citations (Scopus)
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Dive into the research topics of 'Indoor pedestrian localization using ibeacon and improved kalman filter'. Together they form a unique fingerprint.
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Keyphrases
Particle Filter
100%
Indoor Pedestrian Localization
100%
IBeacon
100%
Improved Kalman Filter
100%
Sigma Points
83%
Kalman Particle Filter
83%
Unscented Kalman Filter
50%
Dead Reckoning
50%
Particle Filtering
50%
RSSI Fingerprinting
50%
Kalman Filter
33%
Energy Efficiency
33%
Positioning System
33%
Positioning Accuracy
33%
Computational Cost
33%
Location-aware
33%
Localization Scheme
33%
Computation Energy
33%
High-precision Positioning
33%
High Performance
16%
Smartphone
16%
Filter Method
16%
Fingerprinting
16%
Positional Information
16%
Computational Efficiency
16%
Popular
16%
Machine Learning
16%
Real Environment
16%
Location Information
16%
Radio Signal
16%
Satisfactory Performance
16%
Particle Method
16%
Random Motion
16%
Indoor Environment
16%
Indoor Positioning System
16%
Particle number
16%
Weighting Method
16%
Cost Efficiency
16%
Indoor Localization
16%
Human Being
16%
Localization Performance
16%
Localization Accuracy
16%
High Computational Efficiency
16%
Learning Scheme
16%
Drift Error
16%
Energy Localization
16%
User Motion
16%
Bayesian Filtering
16%
Position Determination
16%
Pedestrian Positioning
16%
Low-cost Inertial Sensors
16%
Sensor Motion
16%
Enhanced Kalman Filter
16%
Indoor Pedestrian Positioning
16%
Unscented Transformation
16%
Positioning Approach
16%
Indoor Positioning
16%
Bayesian Filter
16%
Engineering
Kalman Filter
100%
Particle Filter
100%
Sigma Point
45%
Filtering Algorithm
27%
Energy Conservation
18%
Computational Efficiency
18%
Energy Efficiency
18%
Computational Cost
18%
Energy Engineering
9%
Frequency Signal
9%
Radio Frequency
9%
Localization Performance
9%
Localization Accuracy
9%
Learning Scheme
9%
Inertial Sensor
9%
Indoor Positioning Systems
9%
Cost Efficiency
9%
Bayesian Filtering
9%
Random Motion
9%
Learning System
9%
Computer Science
Kalman Filter
100%
Particle Filter
100%
Dead Reckoning
27%
Energy Efficiency
18%
Computational Cost
18%
Computational Efficiency
18%
Biggest Challenge
9%
Energy Efficient
9%
Systems and Application
9%
Location Data
9%
Filtering Method
9%
Machine Learning Scheme
9%
Radio Frequency Signal
9%
Cost Efficiency
9%