Hybrid RF mapping and Kalman filtered spring relaxation for sensor network localization
An accurate and low-cost hybrid solution to the problem of autonomous self-localization in wireless sensor networks (WSN) is presented. The solution is designed to perform robustly under challenging radio propagation conditions in mind, while requiring low deployment efforts, and utilizing only low-...
Saved in:
Main Authors: | Fong, A. C. M., Seet, Boon-Chong, Zhang, Qing, Foh, Chuan Heng |
---|---|
Other Authors: | School of Computer Engineering |
Format: | Article |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/96045 http://hdl.handle.net/10220/11365 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Variable elasticity spring-relaxation: improving the accuracy of localization for WSNs with unknown path loss exponent
by: Zhang, Qing, et al.
Published: (2013) -
Study of spring-relaxation technique for cooperative localization in wireless sensor networks
by: Zhang, Qing
Published: (2013) -
Fusion of WiFi, smartphone sensors and landmarks using the Kalman filter for indoor localization
by: Chen, Zhenghua, et al.
Published: (2015) -
Kalman filtering for navigation application
by: Zhou, JingJing.
Published: (2011) -
Privacy-aware Kalman filtering
by: Song, Yang, et al.
Published: (2020)