TY - GEN
T1 - Adopting Centroid and Amended Trilateration for better accuracy of range-based non-GPS localization
AU - Md Din, Marina
AU - Jamil, Norziana
AU - Nik Ahmad Aziz, Nik Fariz
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/25
Y1 - 2018/10/25
N2 - There has been massive amount of research have been conducted in the area of indoor positioning systems specifically it's upwards research trending in Localization Based Services (LBS) within a non-open space environment or in the vicinity of high rise buildings due to the incapability of Global Positioning System (GPS) to do so. Most of the indoor localization techniques proposed by researchers to discover an optimized solution for indoor location tracking that has high precision and accuracy. This paper proposes a model for better accuracy on range-based localization algorithm in non-GPS positioning systems. The proposed model adopts the enhanced Kalman Filter (KF) and Centroid Localization Algorithm that can manipulate noise signal from raw Received Signal Strength Indicator (RSSI). There are 12 tests conducted in two different environments; at the area with less-obstacles and at the area with more obstacles. Three different algorithms are deployed with and without KF where a series of observations and comparisons are made to measure the effectiveness and reliability of KF implementation. Our analysis and finding show that the proposed model improves the accuracy percentage by more than 80%.
AB - There has been massive amount of research have been conducted in the area of indoor positioning systems specifically it's upwards research trending in Localization Based Services (LBS) within a non-open space environment or in the vicinity of high rise buildings due to the incapability of Global Positioning System (GPS) to do so. Most of the indoor localization techniques proposed by researchers to discover an optimized solution for indoor location tracking that has high precision and accuracy. This paper proposes a model for better accuracy on range-based localization algorithm in non-GPS positioning systems. The proposed model adopts the enhanced Kalman Filter (KF) and Centroid Localization Algorithm that can manipulate noise signal from raw Received Signal Strength Indicator (RSSI). There are 12 tests conducted in two different environments; at the area with less-obstacles and at the area with more obstacles. Three different algorithms are deployed with and without KF where a series of observations and comparisons are made to measure the effectiveness and reliability of KF implementation. Our analysis and finding show that the proposed model improves the accuracy percentage by more than 80%.
KW - Centroid Localization Algorithm
KW - Indoor Localization Tracking
KW - Kalman Filter
KW - RSSI
KW - Trilateration
KW - Wi-Fi technology
UR - http://www.scopus.com/inward/record.url?scp=85057119153&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85057119153&partnerID=8YFLogxK
U2 - 10.1109/ICCOINS.2018.8510605
DO - 10.1109/ICCOINS.2018.8510605
M3 - Conference contribution
AN - SCOPUS:85057119153
T3 - 2018 4th International Conference on Computer and Information Sciences: Revolutionising Digital Landscape for Sustainable Smart Society, ICCOINS 2018 - Proceedings
BT - 2018 4th International Conference on Computer and Information Sciences
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Computer and Information Sciences, ICCOINS 2018
Y2 - 13 August 2018 through 14 August 2018
ER -
