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Simultaneous Estimation of Azimuth and Elevation Angles Using a Decision Tree-Based Method.
Carballeira, Anabel Reyes; de Figueiredo, Felipe A P; Brito, Jose Marcos C.
Afiliação
  • Carballeira AR; National Institute of Telecommunications INATEL, Av. João de Camargo, 510-Centro, Santa Rita do Sapucaí 37540-000, MG, Brazil.
  • de Figueiredo FAP; National Institute of Telecommunications INATEL, Av. João de Camargo, 510-Centro, Santa Rita do Sapucaí 37540-000, MG, Brazil.
  • Brito JMC; National Institute of Telecommunications INATEL, Av. João de Camargo, 510-Centro, Santa Rita do Sapucaí 37540-000, MG, Brazil.
Sensors (Basel) ; 23(16)2023 Aug 11.
Article em En | MEDLINE | ID: mdl-37631651
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. Our results demonstrate an average reduction of over 90% in the prediction error and 50% in the prediction time achieved by our proposal when compared to the MUSIC algorithm. These results establish DTs as competitive alternatives for DOA estimation in signal reception systems.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça