A UAV Localization System Based on Double UWB Tags and IMU for Landing Platform

Qingxi Zeng, Yu Jin,Haonan Yu, Xia You

IEEE SENSORS JOURNAL(2023)

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Abstract
The successful landing of unmanned aerial vehicles (UAVs) on unmanned vehicle landing platforms is critical for resolving the problem of insufficient range of UAVs in practical missions. Existing localization techniques for autonomous UAV landing are primarily vision-based, but this method is limited due to reliance on external lighting conditions. In this article, we propose a localization system for UAV landing on a mobile platform, which can be conveniently deployed on an unmanned vehicle landing platform. Four ultra wideband (UWB) anchors were deployed on the 0.8 x 1.4 m rectangular unmanned vehicle landing platform. The spacing of the two tags installed on the UAV and the ranging information was used as constraints, and the linear least squares (LLSs) method was used to calculate the iterative initial coordinates of the gradient descent method to solve for the positions of the two UWB tags and fuse them with the inertial measurement unit (IMU) data to provide accurate coordinate for the safe landing of the UAV. By comparing the experiments with the LLSs method in five experiments, it is demonstrated that the average RMSE of the localization system proposed in this article is reduced by 61%.
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Key words
Inertial measurement unit (IMU), Kalman filter, landing, localization, unmanned aerial vehicle (UAV), ultra wideband (UWB)
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