Effect of Weighted PDOP on Performance of Linear Kalman Filter for RTK Drone Data

The study established a theoretical relation between weighted position dilution of precision (WPDOP) and standard deviation (STD) of positioning error (
$\epsilon /\sigma _{R})$
derived by linear Kalman filter (KF). The obtained results exposed a rectangular hyperbolic relationship of WPDOP and STD of error. The RTK Drone data were collected around 50 min of interval (07:37 to 08:28 A.M.) on May 12, 2021, with respect to the base station located at 13.841°N; 100.288°E over Thailand region, and a numerical test has been carried out to demonstrate the proposed algorithm. The simulation results verified the theoretical hyperbolic relationship with the distinct flatness of the curve at the base and drone receiver. This different flatness from the experiments was anticipated because of the position errors for the highly nonlinear dynamics motion of the drone receiver while the base receiver is fixed at one location.