Improving GPS positioning accuracy using weighted Kalman Filter and variance estimation methods

Accurate positioning plays a crucial role in the navigation of moving objects. This paper introduces a new, fast, and accurate GPS positioning algorithm using weighting Kalman Filter (KF) based on the variance estimation method. The proposed method is evaluated using three different motion scenarios, including straight movement in the air with a velocity of 90 m/s and circular movement with velocities of 100 m/s and 500 m/s. The experimental results demonstrate that using the suggested method, the positioning accuracy for all three scenarios increases up to 30 percent as compared to two predominant methods (i.e., recursive least squares and KF). © 2019, Deutsches Zentrum für Luft- und Raumfahrt e.V.