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Robust distributed node localization with error management
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Source International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing table of contents
Florence, Italy
SESSION: Location and membership services table of contents
Pages: 250 - 261  
Year of Publication: 2006
ISBN:1-59593-368-9
Authors
Juan Liu  Palo Alto Research Center
Ying Zhang  Palo Alto Research Center
Feng Zhao  Microsoft Research
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

Location knowledge of nodes in a network is essential for many tasks such as routing, cooperative sensing, or service delivery in ad hoc, mobile, or sensor networks. This paper introduces a novel iterative method ILS for node localization starting with a relatively small number of anchor nodes in a large network. At each iteration, nodes are localized using a least-squares based algorithm. The computation is lightweight, fast, and any-time. To prevent error from propagating and accumulating during the iteration, the error control mechanism of the algorithm uses an error registry to select nodes that participate in the localization, based on their relative contribution to the localization accuracy. Simulation results have shown that the active selection strategy significantly mitigates the effect of error propagation. The algorithm has been tested on a network of Berkeley Mica2 motes with ultrasound TOA ranging devices. We have compared the algorithm with more global methods such as MDS-MAP and SDP-based algorithm both in simulation and on real hardware. The iterative localization achieves comparable location accuracy in both cases, compared to the more global methods, and has the advantage of being fully decentralized.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Juan Liu: colleagues
Ying Zhang: colleagues
Feng Zhao: colleagues