Navigation in Global Positioning System–denied environments is notoriously difficult for small unmanned aerial vehicles due to reduction of visible satellites and urban canyon multipath interference. Several existing methods can be used for navigating in a constrained environment, but they often require additional specific sensing hardware for a localization solution or only provide local frame navigation. Autonomous systems often include LiDAR and RGB cameras for mapping, sensing, or obstacle avoidance. Utilizing these sensors for navigation could provide the only or complimentary localization solutions to other Global Positioning System–denied localization methods in a global or local frame, especially in urban canyons where unique landmarks can be identified. Information from scanning LiDAR can be correlated with camera pixel coordinates and used to range unique visual landmarks that have known locations. The present work included surface function fitting to reduce ranging error to spherical landmarks since multiple lasers were able to range each landmark. Simulation and experimental validation of the unique camera–LiDAR modified trilateration process was undertaken using colored light orbs as landmarks with a 16-laser scanning LiDAR and known positions. Position error was computed and verified that the position estimate process was successful at varying landmark configurations and viewing angles in simulation. Experimental results verified the process while also providing higher accuracy than a previous method of using a single point on landmark surfaces, for the tested setup.

由于可见卫星减少和城市峡谷多路径干扰，小型无人机在全球定位系统拒绝环境中导航是出了名的困难。几种现有的方法可用于在受限环境中导航，但它们通常需要额外的特定传感硬件来实现定位解决方案或仅提供局部框架导航。自主系统通常包括用于测绘、传感或避障的 LiDAR 和 RGB 摄像头。利用这些传感器进行导航可以为其他全球定位系统拒绝定位方法提供唯一或互补的定位解决方案，尤其是在可以识别独特地标的城市峡谷中。来自扫描 LiDAR 的信息可以与相机像素坐标相关联，并用于确定具有已知位置的独特视觉地标。目前的工作包括表面函数拟合，以减少对球形地标的测距误差，因为多个激光器能够对每个地标进行测距。使用彩色光球作为具有 16 激光扫描 LiDAR 和已知位置的地标，对独特的相机 - LiDAR 改进的三边测量过程进行了模拟和实验验证。计算位置误差并验证位置估计过程在模拟中的不同地标配置和视角下是成功的。实验结果验证了该过程，同时还为测试设置提供了比以前在地标表面上使用单点的方法更高的精度。