While visible light communication (VLC) has become the candidate for the wireless technology of the 21st century due to its inherent advantages, VLC based positioning also has a great chance of becoming the standard approach to positioning. Within the last few years, many studies on VLC based positioning have been published, but there are not many survey works in this field. In this paper, an in-depth survey of VLC based positioning systems is provided. More than 100 papers ranging from pioneering papers to the state-of-the-art in the field were collected and classified based on the positioning algorithms, the types of receivers, and the multiplexing techniques. In addition, current issues and research trends in VLC based positioning are discussed.
This paper elucidates the fundamentals of visible light communication systems that use the rolling shutter mechanism of CMOS sensors. All related information involving different subjects, such as photometry, camera operation, photography and image processing, are studied in tandem to explain the system. Then, the system performance is analyzed with respect to signal quality and data rate. To this end, a measure of signal quality, the signal to interference plus noise ratio (SINR), is formulated. Finally, a simulation is conducted to verify the analysis.
This paper proposes a probability-based algorithm to track the LED in vehicle visible light communication systems using a camera. In this system, the transmitters are the vehicles' front and rear LED lights. The receivers are high speed cameras that take a series of images of the LEDs. The data embedded in the light is extracted by first detecting the position of the LEDs in these images. Traditionally, LEDs are detected according to pixel intensity. However, when the vehicle is moving, motion blur occurs in the LED images, making it difficult to detect the LEDs. Particularly at high speeds, some frames are blurred at a high degree, which makes it impossible to detect the LED as well as extract the information embedded in these frames. The proposed algorithm relies not only on the pixel intensity, but also on the optical flow of the LEDs and on statistical information obtained from previous frames. Based on this information, the conditional probability that a pixel belongs to a LED is calculated. Then, the position of LED is determined based on this probability. To verify the suitability of the proposed algorithm, simulations are conducted by considering the incidents that can happen in a real-world situation, including a change in the position of the LEDs at each frame, as well as motion blur due to the vehicle speed.
This paper presents a visible light-communication-based vehicle-to-vehicle tracking system using a new positioning algorithm and modified version of the Kalman filter. In this system, LED head and tail lamps on the vehicles are used to transmit the positioning signals to other vehicles. Two CMOS dashboard cameras on each vehicle are used to receive these signals. From the geometric relationship between two cameras and the images of LEDs captured by these two cameras, the instantaneous position of the target vehicle can be determined, given that at least one LED of the target vehicle is in the view frame of the two cameras. The discrete positioning result always contains unavoidable errors, which consist of systematic errors caused by the CMOS rolling shutter artifact and the weak spatial separability of the sensor, and other random errors. The contribution of this paper is twofold. First, a new positioning algorithm with two compensation mechanisms is proposed to eliminate systematic errors. Second, a modified Kalman filter is proposed to filter out random errors to achieve a smooth and accurate tracking result for the vehicle position. The performance of the system is verified through simulations.INDEX TERMS Visible light communication, vehicle, tracking, camera, Kalman filter.
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