article

Simultaneous adaptive localization of a wireless sensor network

Authors:

Koushil Sreenath,

Frank L. Lewis,

Dan O. PopaAuthors Info & Claims

ACM SIGMOBILE Mobile Computing and Communications Review, Volume 11, Issue 2

Pages 14 - 28

https://doi.org/10.1145/1282221.1282223

Published: 01 April 2007 Publication History

Abstract

A range-free approach for adaptive localization of un-localized sensor nodes employing a mobile robot with GPS is detailed. A mobile robot navigates through the sensor deployment area broadcasting its positional estimate and the uncertainty in its estimate. Distributed computationally-inexpensive, discrete-time Kalman Filters, implemented on each static sensor node, fuse information obtained over time from the robot to decrease the uncertainty in each node's location estimate. On the other hand, due to dead reckoning and other systematic errors, the robot loses positional accuracy over time. Updates from GPS and from the localized sensor nodes serve in improving the localization uncertainty of the robot. A Continuous-Discrete Extended Kalman Filter (CD EKF) running on the mobile robot fuses information from multiple distinct sources (GPS, various sensors nodes) for robot navigation. This two-part procedure achieves simultaneous localization of the sensor nodes and the mobile robot. Also presented is an adaptive localization strategy to navigate the mobile robot to the area of least localized sensor nodes. This ensures that the robot maneuvers to an area where the sensor nodes possess the largest uncertainty in location, so that it can maximize the usefulness of its positional information in best localizing the overall network.

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Cited By

Lian BWan YZhang YLiu MLewis FChai T(2022)Distributed Kalman Consensus Filter for Estimation With Moving TargetsIEEE Transactions on Cybernetics10.1109/TCYB.2020.302900752:6(5242-5254)Online publication date: Jun-2022
https://doi.org/10.1109/TCYB.2020.3029007
Xiong HSichitiu M(2019)A Lightweight Localization Solution for Small, Low Resources WSNsJournal of Sensor and Actuator Networks10.3390/jsan80200268:2(26)Online publication date: 5-May-2019
https://doi.org/10.3390/jsan8020026
Evans WKirkpatrick DLöffler MStaals F(2016)Minimizing Co-location Potential of Moving EntitiesSIAM Journal on Computing10.1137/15M103121745:5(1870-1893)Online publication date: Jan-2016
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Index Terms

Simultaneous adaptive localization of a wireless sensor network
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems
2. Networks

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Published In

cover image ACM SIGMOBILE Mobile Computing and Communications Review

ACM SIGMOBILE Mobile Computing and Communications Review Volume 11, Issue 2

April 2007

72 pages

ISSN:1559-1662

EISSN:1931-1222

DOI:10.1145/1282221

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Copyright © 2007 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 2007

Published in SIGMOBILE Volume 11, Issue 2

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Cited By

Lian BWan YZhang YLiu MLewis FChai T(2022)Distributed Kalman Consensus Filter for Estimation With Moving TargetsIEEE Transactions on Cybernetics10.1109/TCYB.2020.302900752:6(5242-5254)Online publication date: Jun-2022
https://doi.org/10.1109/TCYB.2020.3029007
Xiong HSichitiu M(2019)A Lightweight Localization Solution for Small, Low Resources WSNsJournal of Sensor and Actuator Networks10.3390/jsan80200268:2(26)Online publication date: 5-May-2019
https://doi.org/10.3390/jsan8020026
Evans WKirkpatrick DLöffler MStaals F(2016)Minimizing Co-location Potential of Moving EntitiesSIAM Journal on Computing10.1137/15M103121745:5(1870-1893)Online publication date: Jan-2016
https://doi.org/10.1137/15M1031217
Xiong HSichitiu M(2016)KickLoc: Simple, Distributed Localization for Wireless Sensor Networks2016 IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)10.1109/MASS.2016.037(228-236)Online publication date: Oct-2016
https://doi.org/10.1109/MASS.2016.037
Bulten WRossum AHaselager W(2016)Human SLAM, Indoor Localisation of Devices and Users2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2015.19(211-222)Online publication date: Apr-2016
https://doi.org/10.1109/IoTDI.2015.19
Evans WKirkpatrick DLöffler MStaals Fda Fonseca GLewiner TPeñaranda LChan TKlein R(2013)Competitive query strategies for minimising the ply of the potential locations of moving pointsProceedings of the twenty-ninth annual symposium on Computational geometry10.1145/2462356.2462395(155-164)Online publication date: 17-Jun-2013
https://dl.acm.org/doi/10.1145/2462356.2462395
Wong GLiu HChu XLeung YXie C(2013)Efficient broadcasting in multi-hop wireless networks with a realistic physical layerAd Hoc Networks10.1016/j.adhoc.2010.12.00111:4(1305-1318)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1016/j.adhoc.2010.12.001
Trivedi NBalakrishnan N(2011)Learning on the job: Smoothing for Simultaneous Localization and Tracking in sensor networks2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing10.1109/ISSNIP.2011.6146557(449-454)Online publication date: Dec-2011
https://doi.org/10.1109/ISSNIP.2011.6146557
Wang JGhosh RDas S(2010)A survey on sensor localizationJournal of Control Theory and Applications10.1007/s11768-010-9187-78:1(2-11)Online publication date: 7-Jan-2010
https://doi.org/10.1007/s11768-010-9187-7
Das SWang JGhosh RReiger R(2010)Algorithmic Aspects of Sensor LocalizationTheoretical Aspects of Distributed Computing in Sensor Networks10.1007/978-3-642-14849-1_9(257-291)Online publication date: 8-Nov-2010
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