用事件相机同时实现可见光通信与定位,车在隧道里也能准确定位。
Performance Evaluation of an Integrated System for Visible Light Communication and Positioning Using an Event Camera
- 事件相机结合沃尔什码识别多LED,实现通信与定位同步
- 30km/h下100米内定位误差小于0.75米,误码率低于0.01
- 首个车载单相机集成式可见光定位系统,适合智能驾驶场景
事件相机具备高时间分辨率和高动态范围,能有效捕捉快速运动物体并应对极端光照对比场景(如隧道出口)。本研究提出一种新型自定位系统,将可见光通信(VLC)与可见光定位(VLP)集成于单一事件相机中。车辆在无GPS环境(如隧道)中,通过VLC从LED发射器获取坐标信息,并利用相位仅相关(POC)方法估计到各发射器的距离。多个发射端安装的LED采用沃尔什-哈达玛码分配唯一导频序列,事件相机通过信号相关性识别视野内各光源,实现清晰分离与识别。该机制支持多输入单输出(MISO)高容量通信与精确距离估计。据我们所知,这是首个基于单事件相机的车载协同VLC与VLP系统。实测在30 km/h(8.3 m/s)速度下进行,100米范围内距离估计均方根误差(RMSE)低于0.75米,误码率(BER)始终低于0.01。
原文摘要 · Abstract (English)
Event cameras, featuring high temporal resolution and high dynamic range, offer visual sensing capabilities comparable to conventional image sensors while capturing fast-moving objects and handling scenes with extreme lighting contrasts such as tunnel exits. Leveraging these properties, this study proposes a novel self-localization system that integrates visible light communication (VLC) and visible light positioning (VLP) within a single event camera. The system enables a vehicle to estimate its position even in GPS-denied environments, such as tunnels, by using VLC to obtain coordinate information from LED transmitters and VLP to estimate the distance to each transmitter. Multiple LEDs are installed on the transmitter side, each assigned a unique pilot sequence based on Walsh-Hadamard codes. The event camera identifies individual LEDs within its field of view by correlating the received signal with these codes, allowing clear separation and recognition of each light source. This mechanism enables simultaneous high-capacity MISO (multi-input single-output) communication through VLC and precise distance estimation via phase-only correlation (POC) between multiple LED pairs. To the best of our knowledge, this is the first vehicle-mounted system to achieve simultaneous VLC and VLP functionalities using a single event camera. Field experiments were conducted by mounting the system on a vehicle traveling at 30 km/h (8.3 m/s). The results demonstrated robust real-world performance, with a root mean square error (RMSE) of distance estimation within 0.75 m for ranges up to 100 m and a bit error rate (BER) below 0.01 across the same range.
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