Improved MDS-based localization

By Yi Shang, Wheeler Ruml. IEEE INFOCOM 2004, 2004

816 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/5a06f6d0d8cd29068ad03fb4ccde1ba0b7b3dd5a

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In Computer Networks and Communications

In Electrical and Electronic Engineering

In Ocean Engineering

Citations in the corpus

Wireless sensor network localization techniques (2007, background): “further improved their algorithm in [89] by dividing the entire sensor network into overlapping local regions.”
Locating the nodes: cooperative localization in wireless sensor networks (2005, methodology): “IEEE SIGNAL PROCESSING MAGAZINE [61] JULY 2005 [FIG3] AOA estimation methods.”
Scalable Localization with Mobility Prediction for Underwater Sensor Networks (2008, neutral): “been proposed [6]‐[9], [11], [13], [15], [18], [20]‐[24], [ 31 ], [33], [34].”
Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs (2005, methodology): “For example, multidimensional scaling (MDS) has been investigated for use in solving the localization problem in sensor networks [49], [50].”
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].”
Semidefinite programming based algorithms for sensor network localization (2006, methodology): “So an alternative distributed MDS and patching technique is explored in [Shang and Ruml 2004; Shang et al. 2004].”
A Theory of Network Localization (2006, methodology): “The previous approaches can be classified into two types: coarse-grained [10], [11], [28], [42], [50], [57] and fine-grained [1], [7], [12], [18], [37], [44], [46], [47], [49], [52], [53], [56].”
Localization systems for wireless sensor networks (2007, neutral): “[7, 45] that used multidimensional scale (MDS).”
Localization from connectivity in sensor networks (2004, methodology): “This paper is based on work reported at ACM MobiHoc 2003 [1] and IEEE Infocom 2004 [2].”
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].”
Data Based Identification and Prediction of Nonlinear and Complex Dynamical Systems (2016, neutral): “g, the multidimensional scaling method [260, 261].”
A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks (2016, methodology): “, MDA-MAP(C) [24], MDS-MAP(P) [25], Local MDS [26], dwMDS(G) [27] and HMDS [28] algorithms, have been introduced and analyzed.”
Distributed Sensor Localization in Random Environments Using Minimal Number of Anchor Nodes (2008, background): “Illustrative centralized localization algorithms include: maximum likelihood estimators that are formulated when the data is known to be described by a statistical model [4], [5]; multidimensional scaling (MDS) algorithms that formulate the localization problem as a least squares problem at a centra”