Estimation of Heading Angle Difference Between User and Smartphone Utilizing Gravitational Acceleration Extraction

Lee, Hansung; Lee, Jaemyeon; Cho, Jaegeol; Chang, Namseok

doi:10.1109/jsen.2016.2538824

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…In order to obtain more accurate user headings, especially in the situation of unconstrained smartphone poses, it is better to use some complex algorithms to calculate the user heading, rather than use readings directly from the electronic compass. Some researchers have published relevant research results on this issue, like [ 30 , 33 , 34 ], but it is maybe still hard to estimate the exact user heading for crowdsourcing data, so during the algorithm design, we made great efforts to minimize the reliance on heading, mainly including: The proposed method uses angular velocity changes for turning detection and road segmentation, which makes it free from magnetic interference. We use the mean value of detected user headings to indicate the road segment orientation, which can partly eliminate heading errors due to local magnetic field anomalies and other short duration errors.…”

Section: Resultsmentioning

confidence: 99%

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing

Lai

et al. 2018

Sensors

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Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy.

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Section: Resultsmentioning

confidence: 99%

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing

Lai

et al. 2018

Sensors

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“…Recently, 'g' of (979 832 568.9 ± 5.0) μGal was determined in the KRISS Watt balance system [12]. In recent past, many researchers have done gravitational acceleration computations by using innovative ideas with complicated systems [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Development of gravitational acceleration measurement set up based on laser beams

Das¹,

Das²,

Ghodke³

et al. 2021

AJCT

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In this paper, using three parallel laser beams system we have calculated the value of gravitational acceleration (g) by deriving a simple equation, where there is no velocity term, is reported. The numerator of the equation is always positive irrespective of distances. The setup consists of commonly available three red laser light-emitting diodes and three sensors using very common fast transistors. A free-fall object intercepts the laser beams to produce three voltage pulses across the collector-emitters of three transistors. These voltage pulses are fed to a storage oscilloscope for measuring the two time-intervals between two subsequent gaps of three laser beams with millisecond resolutions. Time intervals are also measured by two-microsecond timers in microsecond resolution. The object may fall from any height above first laser beam, but the 'g' calculated remains the same. Measurements were done by letting an object fall from two different heights, six times from each height, and the average value of 'g' of 9.8036916315 meters per second squared is calculated using the data of two-microsecond timers, which has a 0.03% deviation from the standard value of 9.80665 meters per second squared. Results obtained using microsecond timers are more accurate than that obtained using oscilloscope millisecond data.

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“…Most existing heading estimation solutions deploy traditional attitude estimation based approaches [9,10]. The user heading is estimated by adding a fixed user heading offset to the estimated device forward heading.…”

Section: Introductionmentioning

confidence: 99%

Robust Heading Estimation for Indoor Pedestrian Navigation Using Unconstrained Smartphones

Deng

Liu

et al. 2018

Wireless Communications and Mobile Computing

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Heading estimation using inertial sensors built-in smartphones has been considered as a central problem for indoor pedestrian navigation. For practical daily lives, it is necessary for heading estimation to allow an unconstrained use of smartphones, which means the varying device carrying positions and orientations. As a result, three special human body motion states, namely, random hand movements, carrying position transitions, and user turns, are introduced. However, most existing heading estimation approaches neglect the three motion states, which may render large estimation errors. We propose a robust heading estimation system adapting to the unconstrained use of smartphones. A novel detection and classification method is developed to detect the three motion states timely and discriminate them accurately. For normal working, the user heading is estimated by a PCA-based approach. If a user turn occurs, it is estimated by adding horizontal heading change to previous user heading directly. If one of the other two motion states occurs, it is obtained by averaging estimation results of the adjacent normal walking steps. Finally, an outlier filtering algorithm is developed to smooth the estimation results. Experimental results show that our approach is capable of handling the unconstrained situation of smartphones and outperforms previous approaches in terms of accuracy and applicability.

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Estimation of Heading Angle Difference Between User and Smartphone Utilizing Gravitational Acceleration Extraction

Cited by 6 publications

References 13 publications

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing

Development of gravitational acceleration measurement set up based on laser beams

Robust Heading Estimation for Indoor Pedestrian Navigation Using Unconstrained Smartphones

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