## 1 Introduction  
Visible light provides not only illumination but also communication, which is called visible light communication (VLC). Many applications based on VLC have been developing such as intelligent public illumination [1], indoor communication [2; 3], indoor positioning [4; 5], intelligent transport systems [6; 7], etc. Some studies also combine VLC with other communication techniques. In Reference [8], characteristics of WiFi and VLC are described, and a practical framework is demonstrated for both technologies to coexist, further enhancing the communication performances. In the VLC field, most of the studies are limited to indoor and the outdoor applications are less explored [9]. A VLC system mainly includes two parts: a transmitter and a receiver. The transmitter modulates the Light Emitting Diode (LED)-produced light and the receiver, based on a photodiode (PD) or an image sensor, extracts the data signal from modulated light beam. A PD-based VLC system realizes communicating by receiving the light intensity of different LEDs, it costs less, and has a fast response time, which makes it possible to measure a small period of time of signal arrival; however, the main flaw of PD is that it is not stable enough, especially in an outdoor environment. In our previous works [10; 11; 12; 13; 14], we have completed a series of research projects regarding VLC-based on PD, and it can be found that PDs are sensitive to the direction of the light beam and the interference of the background light or the reflection of the surrounding objects, the communication based on PDs would be affected and even fail. Therefore, for the weakness of PDs mentioned above, an image sensor performs better in the field of OVLC applications. To our knowledge, studies on image-sensor-based OVLC, where LEDs are used as a transmitter and a high-speed camera is used as the receiver, such as intelligent transport systems, are mainly aiming at increasing transmission speed, reducing the BER (bit error rate), or solving other normal communication problems. In most of the existing image-sensor-based VLC studies, the transmitter (signal source) or the receiver (camera) is fixed, or the background of received images is already clean and information can be demodulated directly from these images, such as in References [15; 16; 17], where only signal source LEDs are left in images after adjusting the exposure time of the camera. In addition, in the field of visible light positioning (VLP) based on VLC, which is most closely related to tracking algorithm research, few studies take accuracy, robustness, and real-time ability into consideration simultaneously. In Reference [18], a MiniMax filter is used to estimate the trajectory of the terminal (receiver), which can only support low speed motion (poor real-time ability) and is merely theoretically simulated. In Reference [19], a positioning accuracy of 7.5 cm is provided while robustness (such as motion blur, background interference) is ignored. Reference [20] proposed a probability-based algorithm to track the signal source LED under a motion blur situation, whose method is similar to our previous work [4]. While, in Reference [20], only simulation experiments were carried out and there no practical experimental results are given, making it only theoretically feasible. All these works have not taken background interference into consideration, which is the main obstacle in the applications of OVLC system. However, it is worth mentioning that image-sensor-based VLC is unlike other communication techniques, which means that there will be different interferences (luminous or reflective objects) that are left in the images though adjusting exposure time, especially in an outdoor dynamic scenario.