Abstract

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.

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