Accurate Localization of Passive Sensors Using Multiple Impedance Measurements

Slottke, Eric; Wittneben, A.

doi:10.1109/vtcspring.2014.7022806

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…In this section, we treat the nuisance parameter o ag separately in a rigorous way, in order to alleviate the problem of high dimensionality in (11).…”

Section: B Parameter Space Reduction From 5d To 3dmentioning

confidence: 99%

“…This way, we transformed the 5D minimization problem (11) into an alternating minimization procedure consisting of a 3D p-step and a 2D o-step: an iterative solver applied to (14) requires the computation of ôp through (13) after every update of position hypothesis p.…”

Section: B Parameter Space Reduction From 5d To 3dmentioning

confidence: 99%

“…Most papers on near-field localization employ the dipole approximation, e.g., [3]- [9]. For coplanar 2D localization of a passive LC resonator, least squares estimation errors were compared to the CRLB in [11]. In distinction from planar coil setups, the use of tri-axial coil arrays at the anchors and/or the agent allows for simpler localization schemes [3], [4], [12], [13].…”

Section: Introductionmentioning

confidence: 99%

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Robust near-field 3D localization of an unaligned single-coil agent using unobtrusive anchors

Dumphart

Slottke

Wittneben

2017

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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The magnetic near-field provides a suitable means for indoor localization, due to its insensitivity to the environment and strong spatial gradients. We consider indoor localization setups consisting of flat coils, allowing for convenient integration of the agent coil into a mobile device (e.g., a smart phone or wristband) and flush mounting of the anchor coils to walls. In order to study such setups systematically, we first express the Cramér-Rao lower bound (CRLB) on the position error for unknown orientation and evaluate its distribution within a square room of variable size, using 15 × 10 cm anchor coils and a commercial NFC antenna at the agent. Thereby, we find cm-accuracy being achievable in a room of 10 × 10 × 3 meters with 12 flat wallmounted anchors and with 10 mW used for the generation of magnetic fields. Practically achieving such estimation performance is, however, difficult because of the nonconvex 5D likelihood function. To that end, we propose a fast and accurate weighted least squares (WLS) algorithm which is insensitive to initialization. This is enabled by effectively eliminating the orientation nuisance parameter in a rigorous fashion and scaling the individual anchor observations, leading to a smoothed 3D cost function. Using WLS estimates to initialize a maximum-likelihood (ML) solver yields accuracy near the theoretical limit in up to 98% of cases, thus enabling robust indoor localization with unobtrusive infrastructure, with a computational efficiency suitable for real-time processing.

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“…In this section, we treat the nuisance parameter o ag separately in a rigorous way, in order to alleviate the problem of high dimensionality in (11).…”

Section: B Parameter Space Reduction From 5d To 3dmentioning

confidence: 99%