## 1 Introduction  
Indoor positioning has become a popular research topic in the past few decades owing to the demand for location-based services. The positioning system has useful applications for tracking patients in medical centers, tracking assets, personal tracking, and positioning people inside airports. The most popular positioning technology is the global positioning system (GPS), which receives signals from several satellites [1]. However, GPS with line-of-sight (LOS) signal transmissions exhibit many complexities owing to the signal being blocked by buildings and walls of indoor positioning systems. Therefore, many alternative techniques exist for indoor positioning, such as Wi-Fi [2], radio-frequency identification [3], ultra-wideband [4], and ZigBee [5]. Among these techniques, radio-frequency (RF)-based positioning is low cost and offers better coverage [6]. However, because of multipath fading and signal interference, its positioning accuracy is still uncertain. In recent years, visible light communication (VLC)-based indoor positioning systems have garnered significant attention. Due to the advantages of high data rate, eco-friendliness, and high security, VLC is a reliable technology [7]. Visible light allows LOS communication between a transmitter and receiver [8]. Finally, VLC technology can minimize the hardware cost by using existing lighting infrastructure [9]. In recent years, several smartphone image sensor-based visible light positioning approaches have been proposed and implemented [10, 11, 12, 13]. Only single LED-based and received-signal-strength (RSS)/angle-of-arrival (AoA)-based localization systems in which an image sensor is employed as a receiver device were demonstrated in [14]. In [15], a positioning system was implemented using a double-LED as transmitter and an image sensor as a receiver that was capable of providing several centimeters of positioning accuracy in three-dimensional (3-D) systems. The authors in [16] implemented3-D VLC positioning based on the angle difference of arrival using an image sensor as a receiver. In [16], it provided 3.20-14.66 cm positioning accuracy and used small-size color LEDs, which may cause a practical challenge for implementation of a system using rolling shutter mode image sensor based-positioning. A VLC and mobile image sensor-based indoor positioning system using a single LED was implemented in [17]; from the system description, the experimental testbed and achieved lower positioning accuracy at 4.47 cm were not clear. In [18], the proposed indoor positioning using VLC and image sensor provided an accuracy of 6.96 cm. Geometry-based positioning primarily uses the concept of signal trilateration or triangulation. Therefore, the target photosensor receives the signal from multiple transmitter luminaires and calculates the distance from each luminaire. Geometry-based positioning systems using RSS/trilateration and smartphone (light sensor and inertial measurement unit i.e., IMU) have been reported in [19]. A time-difference-of-arrival and multilateration-based visible light positioning system has been proposed [20; 21]. An AOA/trilateration-based indoor positioning system using four LEDs and a camera image sensor was reported in [22]. It provides 15.6 cm positioning accuracy with a 1.8 m \(\times\) 1.8 m \(\times\) 3.5 m testbed, and the study implemented the positioning result on a simulation basis, where it required an auxiliary device, such as one extra camera. A commercial camera (Model: Canon EOS 7D Mark II) image sensor-based VLP system using the trilateration method was reported in [23]; it was 5 cm and 6.6 cm for the height of 120 and 180 cm. In this study, we utilized a visible light infrastructure with many LEDs and a multilateration-based localization algorithm to locate an image sensor in a wide range of indoor environments with a high precision system. The proposed system does not require the support of any additional devices at the receiver terminal.