Carballeira, A.R.; de Figueiredo, F.A.P.; Brito, J.M.C. Simultaneous Estimation of Azimuth and Elevation Angles Using a Decision Tree-Based Method. Sensors2023, 23, 7114.
Carballeira, A.R.; de Figueiredo, F.A.P.; Brito, J.M.C. Simultaneous Estimation of Azimuth and Elevation Angles Using a Decision Tree-Based Method. Sensors 2023, 23, 7114.
Carballeira, A.R.; de Figueiredo, F.A.P.; Brito, J.M.C. Simultaneous Estimation of Azimuth and Elevation Angles Using a Decision Tree-Based Method. Sensors2023, 23, 7114.
Carballeira, A.R.; de Figueiredo, F.A.P.; Brito, J.M.C. Simultaneous Estimation of Azimuth and Elevation Angles Using a Decision Tree-Based Method. Sensors 2023, 23, 7114.
Abstract
This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.
Keywords
Direction of Arrival; Machine Learning; correlation matrix; Decision Tree; MUSIC 1. Introduction
Subject
Engineering, Telecommunications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
