Robust distributed network localization with noisy range measurements

By David C. Moore, John J. Leonard, Daniela Rus, Seth J. Teller. ACM International Conference on Embedded Networked Sensor Systems, 2004

1,141 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/5e1c7fcad70403f2da76849eaf4551143c008116

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Citations in the corpus

Tracking unmodified smartphones using wi-fi monitors (2012, background): “The majority of work in this area, such as RADAR fingerprinting [6], outdoor Wi-Fi localization [10, 17] and sensor network localization [9, 27, 12, 20, 7] relies on the localized device being an active participant in the process.”
A Survey on Localization for Mobile Wireless Sensor Networks (2009, methodology): “We start by describing the three phases typically used in localization ([26], [27], [28]): (1) coordination, (2) measurement, and (3) position estimation.”
A survey on sensor localization (2010, methodology): “The idea of DV-coordinates was explored further in [ 33 ].”
Localization in Wireless Sensor Networks (2007, background): “The Euclidian scheme propagates the true distance to the anchor (a similar idea has been exploited in [7]).”
Data collection, storage, and retrieval with an underwater sensor network (2005, methodology): “Pairwise node distance data can then be used to perform 3D localization, similar to the 2D localization demonstrated in [20].”
FILA: Fine-grained indoor localization (2012, background): “works expect to address these problems by proposing ideas like eliminating erroneous links in computation [2], [3], [17].”
VIRE: Active RFID-based Localization Using Virtual Reference Elimination (2007, background): “Nevertheless, since RSSI is readily available in wireless communication without additional cost, RF-based localization has become a hot research issue [3].”
Wireless sensor network localization techniques (2007, background): “The analysis in [107], however, is not complete and there may be other criteria that may better characterize robustness of a given sub-network against distance measurement errors.”
Location, Localization, and Localizability (2010, background): “Moore et al. prove the probability of their algorithm constructing correct local maps and prove error lower bound on the local map positions.”
Internet of things: Vision, applications and research challenges (2012, background): “One topic addressed involves the surveillance of moving objects within a sensorized area [68], or the robustness of location detection schemes [69] as needed in the case of emergency networks [70].”
Localization Algorithms in Wireless Sensor Networks: Current Approaches and Future Challenges (2010, background): “(a) Flip ambiguity (b) Discontinuous Flex ambiguity [14]”
Scalable Localization with Mobility Prediction for Underwater Sensor Networks (2008, background): “2.2 Related Work on Localization Localization for terrestrial sensor networks has been widely explored, and a significant number of schemes have been proposed [29], [ 30 ], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44].”
A Theory of Network Localization (2006, methodology): “Since that work was originally published, the authors in [44] applied o ur conditions to produce a localization algorithm based on trilateration graphs under noisy distan ce measurements which is effective in relatively dense networks.”
Mobile-assisted localization in wireless sensor networks (2005, background): “Some of these localization schemes assume the availability of a fraction of anchor nodes with already known position information for computing node coordinates [22], [23], [2], [1], [24], while other schemes do not use anchor nodes [5], [3], [4], [25], [26], [7].”
State-of-the-art in protocol research for underwater acoustic sensor networks (2006, methodology): “Underwater localization can be achi eved by leveraging the low speed of sound in water, which permits acc urate timing of signals, and pairwise node distance data can b e used to perform 3D localization, similar to the 2D localization d emonstrated in [20].”
CSI-Based Indoor Localization (2013, background): “Index Terms—Indoor localization, channel state information, RSSI, physical layer Ç”