Visible Light Positioning Based on Calibrated Propagation Model

Alam, Fakhrul; Parr, Baden; Mander, Susan

doi:10.1109/lsens.2018.2889270

Cited by 19 publications

(17 citation statements)

References 18 publications

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“…For example, UWB systems often correct the bias on the distance measurements [ 8 ]. VLP systems based on RSS sometimes calibrate the gain [ 30 ] or Lambertian emission order [ 33 ]. For the calibration of range-based systems, we can again distinguish a few possible methods: Manual measurements Known locations of receiver(s) and/or transmitters Interbeacon ranging (autocalibration) Network optimization …”

Section: Related Workmentioning

confidence: 99%

“…In [ 31 , 32 ], calibration of transmitter coordinates based on known receiver locations was proposed. Similarly, Ref [ 33 , 37 ] were able to calibrate the channel model based on known receiver locations. However, these works either did not indicate how the receiver position should be obtained [ 31 , 32 , 33 ] or used an additional positioning system to obtain it [ 37 ].…”

Section: Related Workmentioning

confidence: 99%

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Calibration of Visible Light Positioning Systems with a Mobile Robot

Amsters

Demeester

Stevens

et al. 2021

Sensors

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Most indoor positioning systems require calibration before use. Fingerprinting requires the construction of a signal strength map, while ranging systems need the coordinates of the beacons. Calibration approaches exist for positioning systems that use Wi-Fi, radio frequency identification or ultrawideband. However, few examples are available for the calibration of visible light positioning systems. Most works focused on obtaining the channel model parameters or performed a calibration based on known receiver locations. In this paper, we describe an improved procedure that uses a mobile robot for data collection and is able to obtain a map of the environment with the beacon locations and their identities. Compared to previous work, the error is almost halved. Additionally, this approach does not require prior knowledge of the number of light sources or the receiver location. We demonstrate that the system performs well under a wide range of lighting conditions and investigate the influence of parameters such as the robot trajectory, camera resolution and field of view. Finally, we also close the loop between calibration and positioning and show that our approach has similar or better accuracy than manual calibration.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Calibration of Visible Light Positioning Systems with a Mobile Robot

Amsters

Demeester

Stevens

et al. 2021

Sensors

View full text Add to dashboard Cite

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“…Here P t n is the transmitted power, m n is the Lambertian order, ϕ n is the irradiance angle, A is the physical area of the detector, and θ n is the incidence angle. If the PD and the luminaries are parallel, it is relatively straightforward to simplify (1) as in [59] to…”

Section: A Rangingmentioning

confidence: 99%

“…1) from the n-th luminaire. During the offline stage, the Lambertian propagation model is calibrated using the method outlined in [59] by taking RSS measurement at a select small number of locations. Once m n (the only unknown in (2)) is estimated through the calibration process, the ranging can be performed by rearranging (2) as…”

Section: A Rangingmentioning

confidence: 99%

“…The RSS-distance model was calibrated based on the measurements performed at the 12 offline locations. The calibrations locations were chosen by following the guidelines presented in [59] while ensuring that each chosen offline location captures multiple regions of the Lambertian RSS-distance model for several luminaires. There were 639 additional locations within the test space, designated live locations, where RSS measurements were carried out to estimate the localization accuracy.…”

Section: Implementation Of the Vlp System And Experimental Setupmentioning

confidence: 99%

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Indoor Visible Light Positioning Using Spring-Relaxation Technique in Real-World Setting

et al. 2019

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GPS has limitations in indoor applications. Consequently, other indoor localization techniques and systems are active areas of research. Visible Light Positioning (VLP) is a promising option, especially given the growing popularity of LED-based lighting and the expected adoption of the forthcoming Visible Light Communication (VLC). This paper reports a novel VLP technique. The developed technique uses received signal strength for ranging. It is followed by the iterative estimation of a location using spring relaxation. The performance of the proposed technique was experimentally evaluated in indoor settings and benchmarked against the lateration-and fingerprint-based localization approaches in multiple scenarios. The obtained results demonstrate that the proposed VLP approach offers an opportunity to outperform the existing techniques in terms of localization accuracy and precision. INDEX TERMS Indoor localization, visible light positioning (VLP), indoor positioning system (IPS), received signal strength (RSS).

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