Real-Time Orientation-Invariant Magnetic Localization and Sensor Calibration Based on Closed-Form Models

Shen, Hui-Min; Hu, Liang; Qin, Longhui; Fu, Xin

doi:10.1109/lmag.2015.2460211

Cited by 13 publications

(6 citation statements)

References 12 publications

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“…In [22], Hu et al presented a linear algorithm by the matrix and algebra computations to localize a magnetic dipole according to the co-planarity among the magnetic field at the measured point and the dipole's position and orientation parameters. In our previous study [27], a closed-form analytical inverse model was proposed by introducing a PM-upright device. Di et al [28] defined a closed-form expression for the Jacobian of the magnetic field relative to the tracked target, and realized real-time localization with an alternative algorithm fusing inertial measurements.…”

Section: Introductionmentioning

confidence: 99%

Passive Magnetic Localization Based on Connotative Pre-Calibration for Tongue-Machine-Interface

Shen

Lian

et al. 2020

IEEE Access

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In human-machine-interface study, recognition of conscious human motion by contactless passive magnetic marked method can provide abundant information, such as PM marked tongue-machineinterface (TMI). However, solution of this nonlinear magnetic inverse problem heavily relies on initialization. This paper takes advantage of the motion characteristics constrained by physiological structure, and develops an enhanced algorithm for real-time full-pose passive magnetic localization in TMI application. In the proposed algorithm, a predetermined-discretized database is introduced, and provides reliable initializations for the nonlinear magnetic localization problem. This database presents the connotative relationships between the location and orientation of passive magnetic source, termed location-orientation mapping database (LOMD). The influence of initialization and LOMD constitution on solving the nonlinear inverse magnetic problem are studied through extensive simulations. Test bench evaluations are conducted on the designed experiment system. The experiment results show that about 38.5 % localization improvement can be achieved with a real-time tracking frequency up to 56.5 Hz.

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Section: Introductionmentioning

confidence: 99%

Passive Magnetic Localization Based on Connotative Pre-Calibration for Tongue-Machine-Interface

Shen

Lian

et al. 2020

IEEE Access

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“…Systems based on Wi-Fi, 2,3 Bluetooth, 4,5 UWB, 6 cellular networks, [7][8][9] or RFID 10 were proposed. Moreover, other sensors can also be used to estimate the position of mobile devices, including measurements of sound, ultrasound, 11 magnetic field, 12 cameras, light, 13 or inertial forces. 14 However, solutions based on radio signals seem to be most frequently proposed.…”

Section: Introductionmentioning

confidence: 99%

Challenges introduced by heterogeneous devices for Wi‐Fi–based indoor localization

Machaj

Brída

Majer

2019

Concurrency and Computation

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Summary In the recent time, Wi‐Fi–based indoor positioning attracts a high number of researchers worldwide because of its relatively easy implementation on widely available smart phones. Indoor positioning services can potentially open new markets for service providers and, thus, allow new ways to increase their income. A number of Wi‐Fi–enabled devices have grown significantly as well as coverage of buildings with Wi‐Fi signals, which can be considered ubiquitous nowadays. Recently, there has been a vast number of novel algorithms proposed for Wi‐Fi signals; however, they were mostly tested using only one type of device. In this paper, we will investigate the feasibility of Wi‐Fi–based positioning on different devices and highlight some of the problems that researchers have to face during the proposal of novel positioning algorithms. We have tested different devices in both laboratory and real conditions to see how they perform and which parameters can have a negative impact on the performance of the positioning system.

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“…In [9], the authors consider the interactions between these parameters and propose a comprehensive calibration method based on a nonlinear least square model, employing the NM algorithm to minimize fitting error between the modeled and measured magnetic fields. In [20], the authors proposed closed-form models for orientation-invariant magnetic localization and sensor calibration. In order to ensure the calibration accuracy, usually a great number of calibration samples are required to cover the span of dipole variables (i.e., 3-D position and 2-D orientation).…”

Section: Introductionmentioning

confidence: 99%

Joint Magnetic Calibration and Localization Based on Expectation Maximization for Tongue Tracking

Lü

Yang

Okkelberg

et al. 2018

IEEE Trans. Biomed. Eng.

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Real-Time Orientation-Invariant Magnetic Localization and Sensor Calibration Based on Closed-Form Models

Cited by 13 publications

References 12 publications

Passive Magnetic Localization Based on Connotative Pre-Calibration for Tongue-Machine-Interface

Passive Magnetic Localization Based on Connotative Pre-Calibration for Tongue-Machine-Interface

Challenges introduced by heterogeneous devices for Wi‐Fi–based indoor localization

Joint Magnetic Calibration and Localization Based on Expectation Maximization for Tongue Tracking

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