Cellular-Connected UAV Flight Velocity Estimation Using a 3D Linear Path

Abstract

Estimation of the flight velocity of unmanned aerial vehicles (UAVs) in cellular networks is essential for effective resource management. In this letter, we present a novel approach for estimating the flying velocity of a cellular-connected UAV along a three-dimensional (3D) linear trajectory using handover count. The azimuth and elevation angles of the UAV, along with its velocity, ground base station (GBS) density, and the handover control parameters, all have a significant impact on the handover count for a UAV flying along a 3D linear path. To provide a realistic description of the wireless environment, we use stochastic geometry in our system model to depict the distribution of GBSs with a density of $\lambda $ . We use the observed handover count as the primary input and structure the velocity estimate problem as a maximum likelihood estimate (MLE) problem. The Cramér-Rao Lower Bound (CRLB) for the UAV estimated velocity is also determined. The proposed estimator shows statistical efficiency, as its variance closely matches the Cramér-Rao Lower Bound (CRLB). The numerical findings validate the accuracy of our approach for estimating the velocity of the UAV in a realistic cellular environment.