2026-06-29T22:13:38Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/97012024-11-16T01:05:15Zcom_10259_8983com_10259_5086com_10259_2604col_10259_9699
Repositorio Institucional de la Universidad de Burgos
author
Ruiz González, Rubén
author
Gómez Gil, Jaime
author
Gómez Gil, Francisco Javier
author
Navas-Gracia, Luis M.
2024-11-15T10:31:28Z
2024-11-15T10:31:28Z
2017-12
978-1-5090-1012-7
2168-9229
http://hdl.handle.net/10259/9701
10.1109/ICSENS.2017.8233986
Signal source localization and separation are key tasks for many applications. In this paper, a new deterministic method is proposed for estimating the 3D location and separating multiple acoustic or vibration sources, simultaneously active. The method is based on TDOA measurements obtained via crosscorrelation. Then, with the information from the estimated locations, source separation is achieved. The performance of the method was evaluated, only through simulations, in terms of accuracy and computational load. The obtained results, with SNR=6dB, showed estimation errors for the localization method always bounded below 10 centimeters, obtaining the best results with a lower number of sources and a higher number of receivers. Furthermore, the computational load was substantially reduced as compared to exhaustive search, being the gain more noticeable for a higher number of sources. The corresponding error for the separation of the original source signals was bounded below 25%, for 2 sources and 6 receivers. Thus, there are strong evidences that the here-proposed method is accurate and robust enough, while being efficient in computational terms, so many applications can benefit from its use.
eng
Acoustics
Blind source localization and separation
Independent sources
Single-path
Time Difference of Arrival (TDOA)
Vibration
Blind 3D localization and separation of multiple vibration and acoustic sources simultaneously active
info:eu-repo/semantics/conferenceObject
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URL
https://riubu.ubu.es/bitstream/10259/9701/3/Ruiz-EEE_Sensors_2017.pdf
File
MD5
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application/pdf
Ruiz-EEE_Sensors_2017.pdf