A Cellular Network Database for Fingerprint Positioning Systems

Gubiani, Donatella; Gallo, Paolo; Viel, Andrea; Torre, Andrea Dalla; Montanari, Angelo

doi:10.1007/978-3-030-30278-8_14

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…However, the antiinterference ability of WLAN signals is not suitable for a port container with such interference, and it is generally used as a method of indoor positioning [10][11][12]. A cellular network has the advantage of wide coverage and can be used as an auxiliary system for BDS [13]. However, the positioning accuracy of the cellular network is usually above the m level [14].…”

Section: Introductionmentioning

confidence: 99%

A Fusion Localization Algorithm with Adaptive Kalman Gain for Port Container Seamless Positioning

Yue

Xu²,

Xue

et al. 2022

Wireless Communications and Mobile Computing

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BeiDou Navigation Satellite System (BDS) has provided high-precision, reliable positioning, navigation, and timing services anywhere in the world since the end of 2020. However, the positioning performance of BDS does not behave well like the other global navigation satellite systems (GNSS) in the transition areas indoor and outdoor, particularly in container ports, because the navigation signals are blocked and reflected by containers. In order to solve the above problem, as the pulse radio ultra-wideband (UWB) has the characteristics of high positioning accuracy, high multipath resolution, large bandwidth, and high communication rate, it is used as the Beidou auxiliary system, and the two are combined. In addition, the positioning algorithm greatly affects BDS/UWB integrated positioning performance. The single Newton iterative least square (LS) positioning algorithm does not take into account the continuity of position in time, leading to disordered positioning results and large positioning errors. For obtaining high positioning accuracy, the Kalman filter (KF) is introduced to process the output results of the LS algorithm, and a fusion localization algorithm of the Newton iterative least square and Kalman filter (LS-KF) with adaptive Kalman gain is proposed in this paper. The fusion algorithm can solve effectively the problem that the Kalman gain approaches a stable state after multiple observation epochs, resulting in a constant ratio between the predicted and the measured states. Besides, the algorithm can be used to assess the confidence of each measurement state, determine the Kalman gain adaptive adjustment factor according to the obtained confidence, and further adjust the Kalman gain through the adaptive factor. Theoretical analysis and simulation results show that the proposed algorithm can improve the overall positioning accuracy and anti-interference ability.

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Section: Introductionmentioning

confidence: 99%

A Fusion Localization Algorithm with Adaptive Kalman Gain for Port Container Seamless Positioning

Yue

Xu²,

Xue

et al. 2022

Wireless Communications and Mobile Computing

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Fingerprinting of Cellular Infrastructure Based on Broadcast Information

Bhattacharjee,

Cecconello,

Kuipers

et al. 2024

Lecture Notes in Computer Science

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OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

Alhomayani

Mahoor

2021

Sci Data

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In recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

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A Cellular Network Database for Fingerprint Positioning Systems

Cited by 4 publications

References 9 publications

A Fusion Localization Algorithm with Adaptive Kalman Gain for Port Container Seamless Positioning

A Fusion Localization Algorithm with Adaptive Kalman Gain for Port Container Seamless Positioning

Fingerprinting of Cellular Infrastructure Based on Broadcast Information

OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

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