Distributed weighted-multidimensional scaling for node localization in sensor networks

By Jose A. Costa, Neal Patwari, A. Hero. TOSN, 2006

590 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/edc1bc5218387aea9e8d78ae5df5a9b9595aed82

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In Computer Networks and Communications

In Electrical and Electronic Engineering

In Ocean Engineering

Citations in the corpus

Locating in fingerprint space: wireless indoor localization with little human intervention (2012, methodology): “Seeing inter-device distances as a metric of dissimilarity, many approaches of network localization adopt MDS as a tool for calculating the locations of wireless devices [28, 8].”
Smartphones Based Crowdsourcing for Indoor Localization (2015, methodology): “Seeing inter-device distances as a metric of dissimilarity, many approaches of network localization adopt MDS as a tool for calculating the locations of wireless devices [8], [30].”
Distributed Sensor Localization in Random Environments Using Minimal Number of Anchor Nodes (2008, methodology): “A distributed multidimensional scaling algorithm is presented in [17].”