Investigation on UAS navigational uncertainty in urban-like environment

• Main Author: Shi, Pengxiang
• Other Authors: Mir Feroskhan
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Manufacturing
• Online Access: https://hdl.handle.net/10356/170609
• Institution: Nanyang Technological University

Unmanned aircraft systems (UASs) have gained significant popularity across various sectors in recent years due to their small size, agility, and user-friendly design. However, achieving precise positioning and orientation of UAVs in outdoor environments requires satellite navigation systems. To meet this requirement and ensure high accuracy in UAV positioning, this study introduces a model set of interactive multiple models filtering. Two observation models, the Dead Reckoning (DR) and the Kalman (KAL) model, are adopted to establish a centralized Kalman filtering model. This model utilizes standard motion path models to estimate the position of moving targets. Simulation experiments were conducted using a ROS (Robot Operating System) simulation system to validate the effectiveness of the proposed algorithm. The experiments involved collecting data and analysing the algorithm's performance in terms of accuracy and reliability. The results of the simulation experiments demonstrated the algorithm's high accuracy in UAV positioning and its effectiveness in addressing the challenges associated with positioning. The proposed UAV navigation and positioning fusion algorithm based on Kalman filtering holds excellent potential for improving the accuracy of UAV positioning in outdoor environments. Future research can focus on refining the algorithm and conducting real-world testing to further validate its performance in various scenarios.