Improving the visible light communication localization system using Kalman filtering with averaging

Eman Shawky; Mohamed El-Shimy; Amr Mokhtar; El-Sayed A. El-Badawy; Hossam M. H. Shalaby; Hossam M. H. Shalaby

doi:10.1364/JOSAB.395056

Journal of the Optical Society of America B
Vol. 37,
Issue 11,
pp. A130-A138
(2020)
•https://doi.org/10.1364/JOSAB.395056

Improving the visible light communication localization system using Kalman filtering with averaging

Eman Shawky, Mohamed El-Shimy, Amr Mokhtar, El-Sayed A. El-Badawy, and Hossam M. H. Shalaby

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Eman Shawky, Mohamed El-Shimy, Amr Mokhtar, El-Sayed A. El-Badawy, and Hossam M. H. Shalaby, "Improving the visible light communication localization system using Kalman filtering with averaging," J. Opt. Soc. Am. B 37, A130-A138 (2020)

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Abstract

Two techniques are proposed for improving the accuracy of localization estimation in indoor visible light communication systems, namely, averaging and Kalman filtering with averaging schemes. In the averaging technique, the receiver position is estimated using the received signal strength (RSS) indication method multiple times (e.g., $N$ samples), and the acquired estimations are averaged over all samples. To further improve the localization, the Kalman filtering algorithm is adopted to estimate the received power over $N$ samples, followed by applying the RSS technique on the average received power. The proposed techniques are analyzed mathematically, considering the effects of both line-of-sight (LOS) and first-reflection from non-LOS propagations. The performance of the proposed techniques is determined by evaluating the positioning errors in a typical room. The results are compared to that of the traditional RSS system. Simulation results reveal that an improvement of about 33.3% in the average positioning error is achievable when using the averaging scheme as compared to that of the traditional RSS scheme. This improvement increases to 72.2% when adopting the proposed Kalman filtering scheme.

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Parameter	Value
Room dimensions	$5 \times 5 \times 3 m^{3}$
Number of transmitters	4
Total transmitted power per $T_{x}$	30 W
Locations of LEDs	$(1.25, 1.25, 3)$ , $(1.25, 3.75, 3)$ , $(3.75, 1.25, 3)$ , $(3.75, 3.75, 3) m$
FOV of photodetector	70°
Signal-to-noise ratio (SNR)	20
Active area of photodetector	$1 {c m}^{2}$
Wall reflectivity $ρ$	0.8
Number of samples	50
Range of receiver in room	(1–3.5) m over both $x$ , $y$ axes

Localization	Average Positioning	Percentage
Method	Error	Improvement
Traditional RSS	18 cm	–
Averaging RSS	12 cm	33.3%
Kalman filtering	5 cm	72.2%

References	System Parameters	Reference Accuracy	Averaging System Accuracy	Kalman Filtering Accuracy
[3]	LOS, $F O V = 80^{\circ}$ , $P_{T} = 10 W$ ,	5 cm	3.7 cm	3.1 cm
[3]	$A_{R} = 0.5 {c m}^{2}$ , $(5, 5, 3) m^{3}$ , RSS
[5]	LOS/NLOS, $F O V = 10 - 180^{\circ}$ ,	13.95 cm	9.1 cm	4.8 cm
[5]	$P_{T} = 1.9 W$ , $A_{R} = 0.81 {c m}^{2}$ ,
[7]	LOS, $F O V = 85^{\circ}$ , $P_{T} = 1 W$ ,	10 cm	6.17 cm	1.75 cm
[7]	$A_{R} = 0.81 {c m}^{2}$ , $(5, 4, 3) m^{3}$ , (AOA, RSS)
[12]	LOS, $F O V = 80^{\circ}$ , $P_{T} = 17 W$ ,	14.5 cm	17.4 cm	3.5 cm
[12]	$A_{R} = 1 {c m}^{2}$ , $(3.6, 3.26, 2.5) m^{3}$ , EKF
[13]	LOS, $F O V = 25^{\circ}$ , $P_{T} = 17 W$ ,	5 cm	11 cm	2.3 cm
[13]	$A_{R} = 1 {c m}^{2}$ , $(6, 6, 3) m^{3}$ , EKF

Parameter	Value
Room dimensions	$5 \times 5 \times 3 m^{3}$
Number of transmitters	4
Total transmitted power per $T_{x}$	30 W
Locations of LEDs	$(1.25, 1.25, 3)$ , $(1.25, 3.75, 3)$ , $(3.75, 1.25, 3)$ , $(3.75, 3.75, 3) m$
FOV of photodetector	70°
Signal-to-noise ratio (SNR)	20
Active area of photodetector	$1 {c m}^{2}$
Wall reflectivity $ρ$	0.8
Number of samples	50
Range of receiver in room	(1–3.5) m over both $x$ , $y$ axes

Localization	Average Positioning	Percentage
Method	Error	Improvement
Traditional RSS	18 cm	–
Averaging RSS	12 cm	33.3%
Kalman filtering	5 cm	72.2%

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Journal of the Optical Society of America B