The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Distributed weighted-multidimensional scaling for node localization in sensor networks
Abstract
Accurate, distributed localization algorithms are needed for a wide variety of wireless sensor network applications. This article introduces a scalable, distributed weighted-multidimensional scaling (dwMDS) algorithm that adaptively emphasizes the most accurate range measurements and naturally accounts for communication constraints within the sensor network. Each node adaptively chooses a neighborhood of sensors, updates its position estimate by minimizing a local cost function and then passes this update to neighboring sensors. Derived bounds on communication requirements provide insight on the energy efficiency of the proposed distributed method versus a centralized approach. For received signal-strength (RSS) based range measurements, we demonstrate via simulation that location estimates are nearly unbiased with variance close to the Cramér-Rao lower bound. Further, RSS and time-of-arrival (TOA) channel measurements are used to demonstrate performance as good as the centralized maximum-likelihood estimator (MLE) in a real-world sensor network.
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Cites
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Self-citationAd hoc positioning system (APS)
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Cited by
Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning
Sun, Y., Babu, P., & Palomar, D. P. (2017) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2016.2601299 · Cited by 1,820
Metadata
- Authors
- Costa, J. A., Patwari, N., & Hero, A. O.
- Venue
- ACM Transactions on Sensor Networks
- Published
- 2006-02
- Volume
- 2
- Issue
- 1
- Pages
- 39-64
- ISSN
- 1550-4859 (ISSN-L)
- 1550-4867
- OpenAlex
- W1983874789
- Cited by
- 586
- References
- 23
- FWCI
- 38.12
- Type
- journal article
- Language
- en
- Open access
- closed
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