UAV Trajectory Estimation and Deviation Analysis for Contingency Management in Urban Environments

Contingency management of Unmanned Aircraft System (UAS) is an essential part of UAS Traffic Management (UTM). One of such contingencies is the loss of positional information due to weak or loss of Global Positioning System (GPS) signals, which will compromise the safety of the overall UTM system. This paper investigates the UAV trajectory estimation problem when GPS signal is weak or unavailable in urban environments. This research serves two purposes: Firstly, the study employed Extended Kalman Filter (EKF) to estimate the UAV true trajectory when GPS signal is intermittent or unavailable; Secondly, this work analyzed the deviations between pre-defined trajectory and estimated ones in different signal scenarios. The simulation results show that: (1) for uniform distribution of GPS signal, the estimated trajectory will deviate linearly with the decrease of signal density up until a density of 0.1hz and increase exponentially after that; and (2) for non-uniform distribution, the Gaussian distribution performed the worst, followed by random distribution and Sine distribution.