Abstract
In this work, the delay and sum (DAS) beamforming algorithm commonly used in several areas of engineering and robotics is modified and implemented for the identification and localization of acoustic sources. Its classical approach uses a systematic scanning of all points in a given space domain to localize a disturbance source. DAS is efficient when the searching area is small, but it becomes time consuming when the area increases, or when its topology is unknown. Here, an algorithm that uses beamforming information and a chaotic search scheme for optimal target localization is proposed. The algorithm is performed in two stages: first, the entire work area is mapped using chaotic sequences to determine a vector with the locations with a high probability of finding a source. The second stage initiates a search for a global optimum using chaotic walk trajectories. The proposed algorithm is tested with known analytical functions and then implemented using a time domain simulation of acoustic field and an array of sensors. The algorithm performance for the synthetic signals was compared with the traditional systematic scan. The results showed a reduction in searching time of 90% with similar localization accuracy as the typical beamforming.
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Acknowledgements
The authors thank CONACYT for providing financial support through the project CB-286907.
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Fernandez-Ramirez, K.I., Baltazar, A. (2018). Chaos Optimization Applied to a Beamforming Algorithm for Source Location. In: Batyrshin, I., Martínez-Villaseñor, M., Ponce Espinosa, H. (eds) Advances in Computational Intelligence. MICAI 2018. Lecture Notes in Computer Science(), vol 11289. Springer, Cham. https://doi.org/10.1007/978-3-030-04497-8_27
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DOI: https://doi.org/10.1007/978-3-030-04497-8_27
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