Localization error modeling of hybrid fingerprint-based techniques for indoor ultra-wideband systems

Bogdani, Eleni; Vouyioukas, Demosthenes; Νομικός, Νικόλαος

doi:10.1007/s11235-015-0116-4

Cited by 11 publications

(4 citation statements)

References 34 publications

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“…Whereas some utilize UWB (Ultra Wideband) technology, mainly due to the fact that UWB signals are well-suited for communication and tracking systems, as they provide increased tolerance to localization errors due to the finite time resolution of the transmitted pulses and their large bandwidth. An investigation of UWB and hybrid-UWB schemes may be found in [2].…”

Section: Positioning and Navigation With Mobile Devicesmentioning

confidence: 99%

Quality of Satellite Communication in Selected Mobile Android Smartphones

Falkowski-Gilski

2021

IAPGOS

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Today, thanks to mobile devices, satellite communication is available to anyone and everywhere. Gaining information on one’s position using GNSS (Global Navigation Satellite Systems), particularly in unknown urban environments, had become an everyday activity. With the widespread of mobile devices, particularly smartphones, each person can obtain information considering his or her location anytime and everywhere. This paper is focused on a study, considering the quality of satellite communication in case of selected mobile terminals. It describes a measurement campaign carried out in varying urban environments, including a set of Android-powered smartphones coming from different manufacturers. Based on this, respective conclusions and remarks are given, which can aid consumers as well as device manufacturers and application developers.

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Section: Positioning and Navigation With Mobile Devicesmentioning

confidence: 99%

Quality of Satellite Communication in Selected Mobile Android Smartphones

Falkowski-Gilski

2021

IAPGOS

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“…Fingerprinting is widely adopted technique for UWB localization [20,21]. It is specially used for complex indoor environments with mostly NLOS propagation conditions, where the goal is to achieve high localization accuracy, [22][23][24].…”

Section: Related Workmentioning

confidence: 99%

Experimental Evaluation of Machine Learning Algorithms for Fingerprinting Indoor Localization

Đošić,

Jovanović,

Stojanović

et al. 2021

FU Aut Cont Rob

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One of the most preferred range-free indoor localization methods is the location fingerprinting. In the fingerprinting localization phase machine learning algorithms have widespread usage in estimating positions of the target node. The real challenge in indoor localization systems is to find out the proper machine learning algorithm. In this paper, three different machine learning algorithms for training the fingerprint database were used. We analysed the localization accuracy depending on a fingerprint density and number of line-of-sight (LOS) anchors. Experiments confirmed that Gaussian processes algorithm is superior to all other machine learning algorithms. The results prove that the localization accuracy can be achieved with a sub-decimetre resolution under typical real-world conditions.

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“…Therefore, the upsurge of research and positioning has been transferred to the indoor localization. The existing indoor localization systems are mainly based on Wireless Local Area Network (WLAN) [6], Bluetooth Low Energy (BLE) [7], Micro Electro Mechanical Systems (MEMS) [8], Radio Frequency Identification (RFID) [9], and Ultra Wideband (UWB) [10]. Working in the same frequency band as WLAN, Bluetooth technology has attracted extensive attention of researchers.…”

Section: Introductionmentioning

confidence: 99%

Cost-efficient BLE fingerprint database construction approach via multi-quadric RBF interpolation

Xie

Jin

Zhou

et al. 2019

J Wireless Com Network

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The demand for indoor localization is becoming urgent, but the traditional location fingerprint approach takes a lot of manpower and time to construct a fine-grained location fingerprint database. To address this problem, we propose to use the approach of combining dynamic collection of fingerprint samples with Radial Basis Function (RBF) interpolation. Specifically, the raw sparse fingerprint database is constructed from a small number of fingerprints collected on a few paths, in which the pedestrian track correction algorithm improves the validity and accuracy of the sparse fingerprint database. Then, the RBF interpolation approach is applied to enrich the sparse fingerprint database, in which the Genetic Algorithm (GA) is used to optimize the free shape parameter and the cutoff radius is determined according to the experimental results. Extensive experiments show that the proposed approach guarantees high interpolation and localization accuracy and also significantly reduces the effort of manual collection of fingerprint samples.

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Localization error modeling of hybrid fingerprint-based techniques for indoor ultra-wideband systems

Cited by 11 publications

References 34 publications

Quality of Satellite Communication in Selected Mobile Android Smartphones

Quality of Satellite Communication in Selected Mobile Android Smartphones

Experimental Evaluation of Machine Learning Algorithms for Fingerprinting Indoor Localization

Cost-efficient BLE fingerprint database construction approach via multi-quadric RBF interpolation

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