基于互补氧化物半导体(CMOS)相机卷帘快门效应的可见光通信系统比特速率越高, 拍摄的图片中每个比特对应的像素列数越少, 且像素灰度值波动加剧, 严重影响数据解调性能。针对这一问题, 文章提出采用全局和局部两个动态阈值判决结合分段降采样的解调算法, 首先由图片中全部待解调列的灰度值拟合得到全局动态阈值, 判决后检测出所有数据帧头位置, 然后根据各帧对应列的灰度值分别拟合出局部阈值, 最后对各帧判决结果分段降采样恢复原始比特序列。实验结果表明, 当相机卷帘快门的列扫描频率为103.68 kHz时, 能正确解调的最小比特分辨率为2.962, 对应的最大比特速率和有效数据速率分别为35和10.8 kbit/s。

In Complementary Metal Oxide Semiconductor (CMOS) camera-based visible light communication system using the rolling shutter effect, the number of pixel columns representing one bit will decrease and the fluctuation of grayscale values became serious with the increasing of system bit rate, which leads to the degradation of demodulation performance. A novel demodulation algorithm based on global and local dynamic thresholds and segmented downsampling is proposed. The global dynamic threshold is fitted by grayscale values of all columns in an image, and frame headers contained in the image are located. Then the local dynamic thresholds are fitted respectively by the grayscale values in each data frame. Finally, the result of grayscale decision is segmented downsampling to recover the transmitted bit sequence. The experimental results show that when the column scanning frequency of the rolling shutter is 103.68 kHz, the algorithm is feasible with 2.962 pixels/bit, where the maximum bit rate and net data rate can reach 35 and 10.8 kbit/s, respectively.