This article proposes an efficient integrated navigation algorithm to secure reliable navigation solutions in urban flight environments where satellite navigation is not available. Also, this study investigates a new sensor deployment and filter configuration that can perform real-time navigation onboard small drones by reducing the complexity and computational burden of the conventional point cloud-based pose estimation. The proposed method first derives the geometric relationship between the ranging vector and the known three-dimensional map, where the number of range sensors and deployment structure is refined. Then, we designed the inertial navigation filter structure combining the derived measurement model and evaluated the estimation performance in a realistic urban flight environment. The validity of the proposed algorithm is verified through both error analysis using a simulator with a high-fidelity model and real navigation error analysis from onboard flight test adjacent to urban buildings. In conclusion, this paper presents a distinctive navigation method from the existing point cloud-based approaches and the performance of real-time three-dimensional navigation with a position error of about 1–2 m in satellite unavailability environment.

中文翻译：

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基于几何测距和GIS地图的城市空中导航综合导航系统设计与性能验证

本文提出了一种高效的集成导航算法，以确保在无法使用卫星导航的城市飞行环境中获得可靠的导航解决方案。此外，本研究调查了一种新的传感器部署和过滤器配置，它可以通过降低传统的基于点云的姿态估计的复杂性和计算负担来在小型无人机上执行实时导航。所提出的方法首先推导出测距向量与已知三维地图之间的几何关系，其中对距离传感器的数量和部署结构进行了细化。然后，我们结合导出的测量模型设计了惯性导航滤波器结构，并评估了在现实城市飞行环境中的估计性能。通过使用具有高保真模型的模拟器的误差分析和来自城市建筑物附近的机载飞行试验的真实导航误差分析，验证了所提出算法的有效性。总之，本文提出了一种不同于现有基于点云的方法的独特导航方法，以及在卫星不可用环境下位置误差约为 1-2 m 的实时三维导航性能。