Application of Kalman Filtering Approach on Signal Angle-of-Arrival Estimates

Abstract

This study focuses on modifying the Kalman Filtering (KF) approach, whose measurement noise suppression capability had been proven many times, especially in multidimensional positioning problems, to serve one-dimensional signal angle-of-arrival (AoA) measurements, and examining the overall AoA estimation performance. In order to evaluate the AoA estimation performance of the proposed KF model via the mean square error (MSE) metric, median filtering and smoothing approaches that have been employed in similar problems and systems are examined. The estimation performances of the filtering approaches have been demonstrated via the computer simulations in MATLAB environment. It was shown that the proposed KF model stands out as a successful approach in terms of measurement noise and outlier suppression.