Characterization of Image Receivers for Optical Wireless Location Technology

Abstract

In this letter, image receivers are characterized to address the challenges of indoor positioning with optical wireless location systems. Image receivers are studied according to their field-of-view (FOV) characteristics: 1) the first image receiver uses a wide-FOV (95°) microlens and 2) the second image receiver uses an ultrawide-FOV (130°) microlens. An angle of arrival characterization of the image receiver is used to quantify azimuthal, φ, and polar, θ, angles of incident light from optical beacons. A dilution of position (DOP) characterization is used to quantify geometrical effects of the optical beacon distribution. It is found that the ultrawide-FOV microlens (with a mean positioning error of 1.5 cm) can better image widely separated optical beacons, and thus operate at a lower DOP, compared with the wide-FOV microlens (with a mean positioning error of 3.2 cm). Index Terms-Angle of arrival (AOA), indoor optical positioning, image sensor. 1041-1135

Tunnel lane‐positioning system for autonomous driving cars using LED chromaticity and fuzzy logic system

“…For example, each LED illuminator must have an ID, and additional devices are required. In addition, multiple LED illuminators are required for position estimation, and it is impossible to measure the entire space where the light spreads [13][14][15][16][17].…”

“…However, the position cannot be measured if strong illumination occurs near the sensor. This problem can be prevented depending on the location of the actual RGB sensor [13][14][15][16][17].…”

“…The change of the color temperatures is converted into the chromaticity values, and the position is estimated by using a fuzzy logic system designed in this study. The current positioning methods using LEDs are based on assigning an ID, whereas this study conducts position estimation using chromaticity [12][13][14][15][16][17][18]. The average error of the conventional positioning system is approximately 2 cm-22 cm [12][13][14][15][16][17][18].…”

Wireless Location Technology Of Gauss Particle Filter Under NLOS Environment

“…Relevant parameter are setting as follows: BS1=(0,0), BS2=(0,100), BS3= ) 50 , 3 100 ( , the initial position of mobile station is (10,10), the speed of mobile station is (2,4) Fig. 1.In the same conditions, the Gauss -PF is much closer to the real trajectory.…”

“…In recent years, wireless positioning technology based on the cellular network has been widely used in many fields such as target tracking [1], image processing [2], and map navigation [3]. Cellular network of wireless location mainly includes the signal strength (SS) positioning method, the angle of arrivals (AOA) positioning method and the time difference of arrival (TDOA) positioning method, and the positioning method based on time difference of arrival become the most commonly used method due to the simple algorithm, high positioning accuracy.…”