Hanan Beit-On

Papers

Total Citations

H-Index

About

Hanan Beit-On is a researcher whose work centers on acoustic signal processing, with a particular focus on source localization and array processing. Her key research areas include direction-of-arrival (DoA) estimation, coherent signal subspace methods (CSSM), and the development of robust algorithms for real-world acoustic environments. Her most notable contribution is her work on "Focusing and Frequency Smoothing for Arbitrary Arrays With Application to Speaker Localization" (2020, 11 citations), which advances the CSSM framework by improving focusing techniques that align signal subspaces across frequencies—a critical step for accurately localizing coherent sources in challenging acoustic settings. This work has practical implications for speaker localization in robotics and smart environments. Beit-On also contributed to the LOCalization And TrAcking (LOCATA) challenge, where she co-authored a description of algorithms for Ben-Gurion University's submission (2018, 2 citations), demonstrating her ability to apply theoretical methods to benchmark tasks using platforms like the Nao robot and Eigenmike array. Her research bridges theory and application, offering valuable tools for engineers and researchers working on acoustic scene analysis and human-robot interaction.