Monte-Carlo simulation of the impact of LED power uncertainty on visible light positioning accuracy

This paper presents a simulation study of the impact of Light Emitting Diode (LED) output power uncertainty on the accuracy of Received Signal Strength (RSS)-based Visible Light Positioning (VLP). The actual emitted power of a LED is never exactly equal to the value that is tabulated in the datasheet, with possible variations (or tolerances) up to 20%. Since RSS-based VLP builds on converting estimated channel attenuations to distances and locations, this uncertainty will impact VLP accuracy in real-life setups. A typical configuration with four LEDs is assumed here, and a Monte-Carlo simulation is executed to investigate the distribution of the resulting positioning errors for four tolerance values at seven locations. It is shown that median errors are the highest just below the LEDs. When tolerance values on the LED power increase from 5% to 20%, median errors vary from at most 2 cm to at most 10 cm. Maximal errors can be as high as 17 cm just below the LED, already for tolerance values of only 5%, and increase up to 40 cm for tolerance values of 20%

New photodiode responsivity model for RSS-based VLP

Visible Light Positioning (VLP) might enable auspicious tracking systems, well-suited for low-cost and route-configurable autonomous guided vehicles. Yielding the high accuracy required, necessitates a detailed modelling of a photodiode (PD) receiver's angular characteristics. Still lacking, current RSS-based VLP systems implicitly cope by measuring and (arbitrarily) fitting the received power - distance relation. Upon PD changeover, a recalibration is needed. In this paper, it is shown that adequately modelling the receiver's angular dependencies (i.e. the responsivity) obsoletes the calibrating fit. Hereto, a new responsivity model is proposed, which is a function of the square of the incidence angle rather than its cosine. An extensive measurement set highlights that this model better matches the measured angular characteristics. In terms of the coefficient of determination R2, the new model outscores the baseline Lambertian and generalised Lambertian responsivity models by 1.64% and 0.17% for a Lambertian-like receiver, and by 133% and 1.24% for a non-Lambertian-resembling receiver

On the impact of LED power uncertainty on the accuracy of 2D and 3D visible light positioning

This paper presents a simulation study of the impact of Light Emitting Diode (LED) output power uncertainty on the accuracy of Received Signal Strength (RSS)-based two-dimensional (2D) and three-dimensional (3D) Visible Light Positioning (VLP). The actual emitted power of a LED is never exactly equal to the value that is tabulated in the datasheet, with possible variations (or tolerances) up to 20%. Since RSS-based VLP builds on converting estimated channel attenuations to distances and locations, this uncertainty will impact VLP accuracy in real-life setups. For 2D, a typical configuration with four LEDs is assumed here, and a Monte-Carlo simulation is executed to investigate the distribution of the resulting positioning errors for four tolerance values at seven locations. It is shown that median errors are the highest just below the LEDs, when using a traditional Least-Squares minimization metric. When tolerance values on the LED power increase from 5% to 20%, median errors vary from at most 2 cm to at most 10 cm. Maximal errors can be as high as 17 cm just below the LED, already for tolerance values of only 5%, and increase up to 40 cm for tolerance values of 20%. An alternative cost metric using normalized Least-Squares minimization makes the errors spatially more homogeneously distributed and reduces them by 35%. For a 3D case, median errors of around 5 cm for a tolerance value of 5% increase to as much as 22 cm for a tolerance value of 20%. As the receiver heights increase, positioning errors decrease significantly

An analysis of the impact of LED tilt on visible light positioning accuracy

Whereas the impact of photodiode noise and reflections is heavily studied in Visible Light Positioning (VLP), an often underestimated deterioration of VLP accuracy is caused by tilt of the Light Emitting Diodes (LEDs). Small LED tilts may be hard to avoid and can have a significant impact on the claimed centimeter-accuracy of VLP systems. This paper presents a Monte-Carlo-based simulation study of the impact of LED tilt on the accuracy of Received Signal Strength (RSS)-based VLP for different localization approaches. Results show that trilateration performs worse than (normalized) Least Squares algorithms, but mainly outside the LED square. Moreover, depending on inter-LED distance and LED height, median tilt-induced errors are in the range between 1 and 6 cm for small LED tilts, with errors scaling linearly with the LED tilt severity. Two methods are proposed to estimate and correct for LED tilts and their performance is compared

Impact of a photodiode's angular characteristics on RSS-based VLP accuracy

Photodiode (PD)-based Visible Light Positioning (VLP)-based localisation systems seem propitious for the low-cost tracking and route-configurable navigation of automated guided vehicles, found in warehouse settings. Delivering the required high accuracy, currently necessitates measuring and fitting the received power - distance relation. This paper shows that accurately modelling the PD receiver & x2019;s angular characteristics obsoletes this calibrating fit, while still providing accurate positioning estimates. A new responsivity model Square (SQ) is proposed, which is a function of the square of the incidence angle rather than its cosine. Both its aptitude in matching real-life propagation and its associated localisation accuracy are verified using two extensive measurement sets, each detailing the propagation of a PD moving across a 2D plane 3 m below a 4-LED plane. SQ is compared to the responsivity and calibration fit models available in the literature. In conjunction with model-based fingerprinting positioning, SQ outscores the Lambertian and generalised Lambertian model in terms of the 90(th) percentile root-mean-square error (rMSE) $p_{90}$ by 45.36 cm (83.1 & x0025;) and 0.84 cm (8.4 & x0025;) respectively for the non-Lambertian-like receiver. $SQ$ exhibits an equivalent performance as the generalised Lambertian model for the Lambertian-like photodiode. Accounting for the appropriate receiver model can also boost trilateration & x2019;s rMSE. A 50(th) percentile rMSE reduction of respectively 1.87 cm and 2.66 cm is found in the setup