Enhancing Direction-of-Arrival Estimation via Sliding Window and Filtering of Phase-Differences
Moisés Ramires, Fernando J. Aranda, Joaquín Torres-Sospedra, Adriano J. C. Moreira, Filipe Meneses · 2025
Indoor Positioning has grown considerably in recent years due to technological advancements and its usefulness for product tracking, pedestrian navigation, or autonomous driving. Indoor Positioning systems comprise three main components: the supporting technology, the underlying measurements, and the position estimation algorithm/method. One measurement that has been attracting attention recently is Direction of Arrival (DoA). DoA represents the direction from which a signal is impinging on a receiver. However, DoA measurements are affected by noise, interference, multipath propagation, and obstructions in the Line of Sight (LoS). In this work, we propose an approach to mitigate these problems and improve DoA estimation by applying filtering to the phase-differences obtained from each pair of elements in Linear Antenna Arrays. The results show that the accuracy in DoA estimation using filtering benefits the most inside the Field-of-View (FoV) of$-\mathbf{4 0}^{\circ}$to$\mathbf{4 0}$. Among the several discussed methods, Z-Score provides the best average error of 5.79° inside the$-40^{\circ}$to 40°.