Impact of carrier frequency offset and phase noise on the steering vector for 3D drone localization based on angle of arrival (AOA)

Recently, the issue of localizing GPS-denied drones has become a challenge that has attracted attention of researchers. This simulation study focuses on the impact of phase noise (PN) and Carrier Frequency Offset (CFO) on the steering vector of three-dimensional Angle of Arrival (AOA)-based drone localization. The simulation involves a drone that continuously transmits signals, which are then received by multiple base station (BS) receivers equipped with 4 ×4 Uniform Rectangular Array (URA) arranged in a hexagonal cell structure. The base stations possess known locations, and the Inter-site Distance (ISD) between adjacent base stations remains identical. Each base station (BS) receiver receives the signals with different phase noise (PN) and carrier frequency offset (CFO). In this simulation study, we apply Multiple Signal Classification (MUSIC) algorithm to estimate the direction of the drone at each base station receivers. Subsequently, we employ the least squares (LS) method to approximate an unknown point that maintains the minimum distance from the 3D lines connecting the base stations to the drone, after the 3D-AOA estimation. In order to track the movement of the drone, we apply the Extended Kalman filter (EKF). To validate our proposed approach, we conduct numerical and simulation analyses.