Indoor geolocation science and technology

By Kaveh Pahlavan, Xinrong Li, Juha-Pekka Mäkelä. IEEE Communications Magazine, 2002

969 citations recorded by the source corpus.

This article presents an overview of the technical aspects of the existing technologies for wireless indoor location systems. The two major challenges for accurate location finding in indoor areas are the complexity of radio propagation and the ad hoc nature of the deployed infrastructure in these areas. Because of these difficulties a variety of signaling techniques, overall system architectures, and location finding algorithms are emerging for this application. This article provides a fundamental understanding of the issues related to indoor geolocation science that are needed for design and performance evaluation of emerging indoor geolocation systems.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/d14c3b065b0f3c2121d618736468906a851eba6a

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Citations in the corpus

Survey of Wireless Indoor Positioning Techniques and Systems (2007, methodology): “This method is also called phase of arrival (POA) [2].”
Phase based spatial identification of UHF RFID tags (2010, methodology): “Classical wireless approaches to positioning employ triangulation using received signal strength indicator (RSSI) as in cell phones and time difference of arrival (TDOA) as in GPS. Good overviews of wireless positioning techniques can be found in [1-5].”
Position Accuracy of Time-of-Arrival Based Ranging Using Visible Light With Application in Indoor Localization Systems (2013, background): “Despite extensive research on RF-based solutions, the major challenge of strong multipath interference means that there is no accurate, low cost, low power system available [1], [2].”
Modeling of indoor positioning systems based on location fingerprinting (2004, methodology): “Figure 2 from [6] illustrates these components and their relationships.”
A Theoretical Foundation of Network Localization and Navigation (2018, neutral): “[11] K.”
Localization Algorithms and Strategies for Wireless Sensor Networks: Monitoring and Surveillance Techniques for Target Tracking (2009, background): “As a result, the DP can experience severe fading (Pahlavan et al., 2002).”
Application of Local Differential Privacy to Collection of Indoor Positioning Data (2018, background): “In order to make such indoor location-based service possible, it is essential to accurately estimate the indoor position of a user; thus, related technologies have been actively studied over the last decade [13], [14], [19], [26].”
Super-resolution TOA estimation with diversity for indoor geolocation (2004, background): “However, in indoor and urban areas, due to severe multipath conditions and the complexity of the radio propagation, the DLOS cannot always be accurately detected [2], [3].”
Fundamental Limits of Wideband Localization— Part I: A General Framework (2010, background): “L OCATION-AWARENESS plays a crucial role in many wireless network applications, such as localization services in next generation cellular networks [1], search-and-rescue operations [2], [3], logistics [4], and blue force tracking in battlefields [5].”
TDOA-based optical wireless indoor localization using LED ceiling lamps (2011, background): “However, the positioning systems based on IR or ultrasonic require an additional cost and time to deploy a network infrastructure of location sensors, and system based on RF have difficulties in acquiring accurate location coordinates caused by multipath fading and non-line of sight (non-LOS) condit”
RSS-Based Location Estimation with Unknown Pathloss Model (2006, background): “[ 3 ]. In addition, location estimation is an essential building block of wireless sensor networks [5].”