Wireless positioning technologies and applications

By Alan Bensky. 2008

307 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/29ea2a339b3fbf20bd2604f58febfa1587a0dff2

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Citations in the corpus

Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning (2009, background): “Good recent over-views of these systems are provided by and Kolodziej and Hjelm (2006) and Bensky (2008).”
Indoor Positioning Technologies (2012, methodology): “A mathematical formulation of such a model – known as open field model – can be found in Bensky (2007).”
Pedestrian localisation for indoor environments (2008, methodology): “For example multi-lateration and multi-angulation algorithms are often used to calculate the position of an object based on multiple distance or angle-of-arrival measurements [22].”
A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation (2018, background): “, measured) at the UE, thus defining a hyperbola on which the user is located; see [211] for more details.”
Modern WLAN Fingerprinting Indoor Positioning Methods and Deployment Challenges (2016, background): “From a signaling perspective these approaches can be divided into two categories [12], [13]: (1) radiobased positioning such as Radio Frequency (RF) prox-”
On the requirements for successful GPS spoofing attacks (2011, methodology): “These can be transformed into three linear and one quadratic equation [1], defining the solutions for the location Li and time offset δ i .”
A survey of active and passive indoor localisation systems (2012, methodology): “Location sensing approaches can be classified as follows: location fingerprinting (scene analysis) [11], triangulation, trilateration, hyperbolic lateration, proximity, and dead reckoning [2,7,8,12].”