Decentralized Positioning Algorithm for Relative Nodes Localization in Wireless Body Area Networks
Pages 698 - 706
Abstract
Wireless Body Area Networks (WBAN) can offer motion capture capabilities through peer-to-peer ranging and on-body nodes positioning, by relying on transmitted signals and data packets. In this paper, we describe a solution to localize wireless nodes relatively to a body-strapped Local Coordinate System (LCS). In particular, we consider coupling a Constrained Distributed Weighted Multi-Dimensional Scaling algorithm (CDWMDS), which asynchronously estimates the nodes' locations under geometric constraints related to fixed-length links, with new messages censoring, location updates scheduling and forced measurements symmetry. The idea is to mitigate error propagation (e.g. with respect to the fastest nodes), as well as harmful effects caused by the loss of critical packets. We also introduce a real beacon-aided Time Division Multiple Access (TDMA) scheme to suitably support both peer-to-peer ranging and decentralized positioning transactions under real-time constraints. Simulation results are provided to assess the performance of the proposed solution for various levels of connectivity and ranging quality, showing interesting gains on the average location error per node under moderate pedestrian mobility. Comparisons are finally provided with a more conventional centralized and synchronous Multidimensional Scaling (MDS) algorithm that would require completing the matrix of measured distances under partial network connectivity.
References
[1]
Ben Hamida E, Maman M, Denis B, Ouvry L (2010) Localization performance in wireless body sensor networks with beacon enabled mac and space-time dependent channel model. In: Personal, Indoor and Mobile Radio Communications Workshops (PIMRC Workshops), 2010 IEEE 21st International Symposium on, pp 128---133
[2]
Costa A, Patwari N, Hero O (2006) Distributed weighted-multidimensional scaling for node localization in sensor networks. ACM Trans Sen Netw 2(1):39---64
[3]
Gezici S, Tian Z, Giannakis G, Kobayashi H, Molisch A, Poor H, Sahinoglu Z (2005) Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks. Signal Proc Mag, IEEE 22(4):70---84
[4]
Hamie J, Denis B, D'Errico R, Richard C (2012a) Empirical modeling of intra-ban ranging errors based on ir-uwb toa estimation. In: Proceedings of the 7th International Conference on Body Area Networks, BodyNets'12, pp 139---144
[5]
Hamie J, Denis B, Richard C (2012b) Constrained decentralized algorithm for the relative localization of wearable wireless sensor nodes. In: Sensors, 2012 IEEE, pp 1---4
[6]
Hamie J, Denis B, Richard C (2012c) Nodes updates censoring and scheduling in constrained decentralized positioning for large-scale motion capture based on wireless body area networks. In: Proceedings of the 7th International Conference on Body Area Networks, BodyNets'12, pp 100---105
[7]
Kyung-Sup K, Ullah S, Ullah N (2010) An overview of ieee 802.15.6 standard. In: Applied Sciences in Biomedical and Communication Technologies (ISABEL), 2010 3rd International Symposium on, pp 1---6
[8]
Macagnano D, Destino G, Esposito F, Abreu G (2007) Mac performances for localization and tracking in wireless sensor networks. In: Positioning, Navigation and Communication, 2007. WPNC'07. 4th Workshop on, pp 297---302
[9]
Maman M, Dehmas F, D'Errico R, Ouvry L (2009) Evaluating a tdma mac for body area networks using a space-time dependant channel model. In: Personal, Indoor and Mobile Radio Communications, 2009 IEEE 20th International Symposium on, pp 2101---2105
[10]
Maman M, Denis B, Pezzin M, Piaget B, Ouvry L (2008) Synergetic mac and higher layers functionalities for uwb ldr-lt wireless networks. In: Ultra-Wideband, 2008. ICUWB 2008. IEEE International Conference on, pp 101---104
[11]
Mekonnen Z, Slottke E, Luecken H, Steiner C, Wittneben A (2010) Constrained maximum likelihood positioning for uwb based human motion tracking. In: Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on, pp 1---10
[12]
Mhedhbi M, Laaraiedh M, Uguen B (2012) Constrained lmds technique for human motion and gesture estimation. In: Positioning Navigation and Communication (WPNC), 2012 9th Workshop on, pp 89---93
[13]
Pantazis I (2005) Tracking human walking using marg sensors. Technical report, DTIC Document
[14]
Sahinoglu Z, Gezici S (2008) Ultra-wideband positioning systems: Theoretical limits, ranging algorithms, and protocols. Cambridge University Press, Cambridge
[15]
Shaban H, El-Nasr M, Buehrer R (2010) Toward a highly accurate ambulatory system for clinical gait analysis via uwb radios. Inf Technol Biomed, IEEE Transac 14(2):284---291
[16]
Ullah S, Mohaisen M, Alnuem M (2013) A review of ieee 802.15.6 mac, phy, and security specifications. International Journal of Distributed Sensor Networks 2013
- Decentralized Positioning Algorithm for Relative Nodes Localization in Wireless Body Area Networks
Recommendations
Nodes updates censoring and scheduling in constrained decentralized positioning for large-scale motion capture based on wireless body area networks
BodyNets '12: Proceedings of the 7th International Conference on Body Area NetworksWireless Body Area Networks (WBAN) are endowed with relatively raw but intrinsic motion capture capabilities through radiolocation, which may be of interest for home activity monitoring, large-scale postural rehabilitation or gaming applications. In ...
Asynchronous inter-network interference avoidance for wireless body area networks
This paper considers the internetwork interference problem in environments with multiple wireless body area networks (WBANs). We propose an asynchronous internetwork interference avoidance scheme (abbreviated as AIIA), which is based on the hybrid ...
Hybrid RSS/TOA wireless positioning with a mobile anchor in wireless sensor networks
ICUIMC '12: Proceedings of the 6th International Conference on Ubiquitous Information Management and CommunicationIn this paper, we propose a novel hybrid RSS/TOA positioning algorithm with a mobile anchor, which follows a spiral trajectory to cover the whole region of the wireless sensor networks (WSN). The conventional time of arrival (TOA) positioning algorithms ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © Copyright © 2014 Springer Science+Business Media New York.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 01 December 2014
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 28 Nov 2024
Other Metrics
Citations
View Options
View options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in