Benchmark Dataset of Ultra-Wideband Radio Based UAV Positioning

Precise positioning of the Unmanned Aerial Vehicle (UAV) is critical to conduct many sophisticated civil and military applications in challenging environments. Many of the-state-of-the-art positioning methods rely on active range sensors. Among many available ranging sensors, Ultra-wideband (UWB) can provide many benefits such as high precision, power efficiency, and not prone to multipath propagation and noise. Thus, the UWB has recently been attracting many interests from the research community as a complementary positioning sensor. However, there is a significant lack of UWB benchmark data available to support developing, testing and generalizing their own positioning methods using UWB sensors. In this paper, we present a unique benchmark dataset that provides UWB and IMU signals acquired by a Q-Drone system in a diverse environment, including an indoor, open field, close to buildings, underneath the bridge, and semi-open tunnel, as shown in Fig.1. This benchmark also provides ground truth of UAV positions independently measured with robotic total stations. In this paper, we present the characteristics of the UWB benchmark dataset, Q-Drone UAV platform and the results of the quality assessment conducted by a baseline positioning algorithm implemented with multilateration principal and non-linear optimization.