A 3D Fingerprinting Positioning Method Based on Cellular Networks

Wang, Yaohui; Hu, Li; Luo, Xin-long; Sun, Qibo; Liu, Jin-nan

doi:10.1155/2014/248981

Cited by 14 publications

(9 citation statements)

References 14 publications

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“…A new 3D fingerprint matching scheme called Fingerprint Correlation Localization (FCL) powered by an Enhanced Nearest Neighbor Localization (ENNL) algorithm is presented in [143]. Authors employ cell matching degree and choose the best reasonable fingerprint according to the correlation of its surrounding points, while improving search efficiency across the radiomap by introducing a new searching window.…”

Section: A Cellular-based Solutionsmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

369

171

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Abstract-Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer, networking, industrial, health care, public safety, and emergency response use cases. To fully exploit the potential of location awareness and enable new advanced location-based services, localization algorithms need to be combined with complementary technologies including accurate height estimation, i.e., three dimensional location, reliable user mobility classification, and efficient indoor mapping solutions. This survey provides a comprehensive review of such enabling technologies. In particular, we present cellular localization systems including recent results on 5G localization, and solutions based on Wireless Local Area Networks (WLAN), highlighting those that are capable of computing 3D location in multi-floor indoor environments. We overview range-free localization schemes, which have been traditionally explored in Wireless Sensor Networks (WSN) and are nowadays gaining attention for several envisioned Internet of Things (IoT) applications. We also present user mobility estimation techniques, particularly those applicable in cellular networks, that can improve localization and tracking accuracy. Regarding the mapping of physical space inside buildings for aiding tracking and navigation applications, we study recent advances and focus on smartphone-based indoor Simultaneous Localization and Mapping (SLAM) approaches.The survey concludes with service availability and system scalability considerations, as well as security and privacy concerns in location architectures, discusses the technology roadmap, and identifies future research directions.

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Section: A Cellular-based Solutionsmentioning

confidence: 99%

“…• Vertical Positioning: Cellular-based solutions in academic and industrial research [138]- [143] as well as commercial 3D location systems [144]- [146], WLAN-based approaches [147]- [153], and sensor-based solutions [154]- [165].…”

mentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

369

171

View full text Add to dashboard Cite

show abstract

“…The deployment of LTE heterogeneous networks is also of special interest for indoor positioning. Most of the vertical positioning techniques are based on E-CID methods [21] and RFPM or fingerprinting algorithms by using RSS measurements [22]. Simulation results in [7] and [8] report a vertical accuracy below 3 meters in scenarios with indoor small cells.…”

Section: Gpp Ltementioning

confidence: 99%

Floor Detection with Indoor Vertical Positioning in LTE Femtocell Networks

Peral-Rosado

Bavaro

López-Salcedo

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

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Vertical positioning is nowadays a topic of high interest in indoor environments, due to the stringent requirements on indoor location accuracy for emergency calls, such as E911. Thus, indoor positioning techniques are investigated to achieve floor detection in order to fulfill these legal mandates. The use of Long Term Evolution (LTE) heterogeneous networks is an attractive solution due to the combination of communications and positioning capabilities. This paper provides an overview of the existing floor detection techniques. Practical results using Global Navigation Satellite Systems (GNSS), inertial sensors, barometer, and LTE signals are obtained in an experimental LTE femtocell network, within a deployment in a two-story building. Probabilities of floor detection above 67% of the cases are found for the positioning solutions assessed.

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“…In order to address the above issues, based on our previous work [11], a cost function-based localization algorithm is proposed to address the problem of missing and unreliable anchor nodes in section B. Furthermore, to reduce the influence of the variability of radio channel characteristics, we construct a spatial context constraint area for accurate fingerprint matching in section C.…”

Section: A System Modelmentioning

confidence: 99%

Indoor localization for sparse wireless networks with heterogeneous information

Wang

Sun

et al. 2015

2015 International Conference on Information Networking (ICOIN)

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Wireless indoor localization is crucial in ubiquitous computing environments. Although accurate and efficient indoor localization can be provided in dense wireless networks, most existing algorithms fail to locate a mobile user in sparse deployment networks. In order to address this issue, this paper presents a new fingerprinting localization algorithm based on cost function where received signal strengths from heterogeneous wireless networks are applied. To further improve the positioning accuracy, a spatial context constraint area for fingerprint matching is constructed based on the continuity and smoothness of pedestrian movement trajectories. Experimental results show that the proposed algorithm using heterogeneous information can significantly improve the accuracy of indoor pedestrian localization in sparse wireless networks.

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A 3D Fingerprinting Positioning Method Based on Cellular Networks

Cited by 14 publications

References 14 publications

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Floor Detection with Indoor Vertical Positioning in LTE Femtocell Networks

Indoor localization for sparse wireless networks with heterogeneous information

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