# Design of OCC Indoor Positioning System Based on Flat Panel Light and Angle Sensor Assistance
## 4 Precise Positioning Assisted by Angle Sensors  
However, the light coverage of the flat panel light is larger, as shown in Figure 6. Assuming that the blue area is the light coverage area of this flat panel light, people use mobile terminals to take pictures and collect images of the flat panel light in this larger area, and the positioning information is transmitted to the cell phone terminal through the wireless optical link. Then, the image is decoded to obtain the LED-ID of this flat panel light after optimized processing, and the location information is obtained. Each point in this blue area photographed is the same location information, so this location information is relatively fuzzy, the positioning accuracy of the system is room level, and the specific accuracy error depends on the density of the flat-panel lamp laying in the area. However, for some scenes, this positioning accuracy cannot meet the positioning needs of people's production life, so this chapter will explore the precise positioning algorithm based on the iVLP system of flat panel lights. At present, the vast majority of VLP precise positioning techniques require at least a two-lamp system or a three-lamp system [22; 23] to precisely calculate the position based on  
Figure 5: Flow chart of the decoding code. Figure 6: LP-VLP system fuzzy locates the coverage area of a flat lamp. the relative positions between multiple lamps in an image or the time and angle differences between multiple light signals received at the receiver to obtain more accurate positioning information. However, for the flat lamp VLP system proposed in this paper, because of the large size of flat lamps, it is difficult to simultaneously capture two or more flat lamps clearly in one image, and the multi-lamp precise positioning is not applicable to this system. Therefore, this paper proposes a single-lamp precise positioning method based on angle (pose) sensor assistance to achieve visible light imaging positioning under sparse light sources. At present, the vast majority of cell phones integrate multiple sensors, including an accelerometer, a gyroscope, GPS and magnetic sensors, etc. As an example, the Honor v30 OXF-AN00 cell phone is shown in Figure 7a, which was used to acquire images in this study. The gyroscope belongs to the three-axis angle sensor, which is widely used and has the role of detecting the device's own behavior. The direction sensor of the phone is shown in Figure 7b, and the angle sensor detects the azimuth angle \(\theta\), the roll angle \(\gamma\), and the pitch angle \(\omega\) to determine the direction of the phone at this time. Among them, the azimuth angle indicates the rotation of the phone in the xy plane, 0 degrees in the due north direction; the roll angle, also known as the side tilt angle, takes values in the range of (\(-180\), \(180\)). The traditional dual lamp positioning method requires at least two LEDs to provide the corresponding position information [24], and in combination with the position relationship between the sender and receiver, the projection relationship of the light source on the same horizontal plane is calculated and combined with the trigonometric relationship for positioning. This system reduces the barcode size of the flat lamp cover from 100% to 80%. As shown in Figure 8, point A is the farthest point from the graphic code, and point O is the center point of the flat lamp. According to the fixed position of the flat lamp, i.e., the size information of the flat lamp, we can know the position coordinates of point A and point O. According to the position information of these two points, we can realize \"pseudo dual lamp positioning\". Figure 8: Ideal model of the adjusted graphic code. Figure 7: (**a**) Sensors included in the phone; (**b**) schematic diagram of the direction sensor.