Indoor Localization Using Commodity Wi-Fi APs: Techniques and Challenges

Kandel, Laxima Niure; Yu, Shucheng

doi:10.1109/iccnc.2019.8685501

Cited by 15 publications

(2 citation statements)

References 35 publications

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“…Some IPS-related reviews have over 200 references [16,17,18,19,20,21] or even over 300 references [22]. The insights presented in the rest of this paper are mainly based on 62 IPS-related survey works [6,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,…”

Section: An Overview Of Ips Solutionsmentioning

confidence: 99%

A Meta-Review of Indoor Positioning Systems

Mendoza-Silva

Torres-Sospedra

Huerta

2019

Sensors

203

130

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An accurate and reliable Indoor Positioning System (IPS) applicable to most indoor scenarios has been sought for many years. The number of technologies, techniques, and approaches in general used in IPS proposals is remarkable. Such diversity, coupled with the lack of strict and verifiable evaluations, leads to difficulties for appreciating the true value of most proposals. This paper provides a meta-review that performed a comprehensive compilation of 62 survey papers in the area of indoor positioning. The paper provides the reader with an introduction to IPS and the different technologies, techniques, and some methods commonly employed. The introduction is supported by consensus found in the selected surveys and referenced using them. Thus, the meta-review allows the reader to inspect the IPS current state at a glance and serve as a guide for the reader to easily find further details on each technology used in IPS. The analyses of the meta-review contributed with insights on the abundance and academic significance of published IPS proposals using the criterion of the number of citations. Moreover, 75 works are identified as relevant works in the research topic from a selection of about 4000 works cited in the analyzed surveys.

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Section: An Overview Of Ips Solutionsmentioning

confidence: 99%

A Meta-Review of Indoor Positioning Systems

Mendoza-Silva

Torres-Sospedra

Huerta

2019

Sensors

203

130

View full text Add to dashboard Cite

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“…Limited by incomplete coverage of satellite signals, the performance of Global Positioning System (GPS) that widely used outdoors cannot be well performed indoors, thus diverse indoor positioning technologies have been proposed in the past two decades. The existing techniques can be roughly divided into these categories-vision-based [6,7], sensor-based [2,8] and wireless-based including Wi-Fi [9,10], Bluetooth [11,12], acoustic signals [13], ultra-wideband (UWB) [14,15] and so forth. Among the above technologies employed for indoor localization system, WiFi-based positioning method has attracted increasing attention as a promising technology due to its convenience of flexible deployment, low configuration cost and high availability [10].…”

Section: Introductionmentioning

confidence: 99%

Indoor NLOS Positioning System Based on Enhanced CSI Feature with Intrusion Adaptability

Han

Shi

Deng

et al. 2020

Sensors

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With the wide deployment of commercial WiFi devices, the fine-grained channel state information (CSI) has received widespread attention with broad application domain including indoor localization and intrusion detection. From the perspective of practicality, dynamic intrusion may be confused under non-line-of-sight (NLOS) conditions and the continuous operation of passive positioning system will bring much unnecessary computation. In this paper, we propose an enhanced CSI-based indoor positioning system with pre-intrusion detection suitable for NLOS scenarios (C-InP). It mainly consists of two modules: intrusion detection and positioning estimation. The introduction of detection module is a prerequisite for positioning module. In order to improve the discrimination of features under NLOS conditions, we propose a modified calibration method for phase transformation while the amplitude outliers are filtered by the variance distribution with the median sequence. In addition, binary and improved multiple support vector classification (SVC) models are established to realize NLOS intrusion detection and high-discrimination fingerprint localization, respectively. Comprehensive experimental verification is carried out in typical indoor scenarios. Experimental results show that C-InP outperforms the existing system in NLOS environments, where the mean distance error (MDE) reached 0.49 m in the integrated room and 0.81 m in the complex garage, respectively.

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