METHODS OF DETERMINING THE COORDINATES OF THE ACOUSTIC SIGNAL SOURCE
DOI:
https://doi.org/10.24025/2306-4412.3.2022.260586Keywords:
determination of coordinates, acoustic signals, minimum method, maximum method, radiolocation, direction finding, artificial neural network, deep learning, soundAbstract
The article carries out a literature review and investigates the existing methods of determining the coordinates of the location of the acoustic signal source. The advantages and disadvantages of passive and active methods given in the article are highlighted. These methods can be used in aviation,cosmonautics, mechanical engineering and other fields of science and technology, where measurements are used, and are designed to determine the coordinates of the acoustic signal source. Recently, there has been a growing interest in using neural networks to solve various problems and their application in various fields. With the help of artificial neural networks, it is possible to process, analyze and summarize information. The authors of the article have compared the method of determining the coordinates of the location of the acoustic signal source using an artificial neural network with existing methods. In this method, the presence of a signal from the acoustic signal source at the reception points is determined by receiving and registering the signal at spatially separated points with known coordinates and further determining the difference in signal propagation times from the source to the signal reception points. The presence of a signal is determined by the middle of the area of the received signal. The number of signal reception points is set at the training stage of the artificial neural network according to the minimum error criterion in determining the coordinates of the acoustic signal source. The time differences of signal propagation from the source to the signal reception points are determined between all reception points, which are located in an orderly or random manner, and these time differences arefed to the input of a previously trained artificial neural network, at the output of which the coordinates of the acoustic signal source are obtained. The application of this method allows to determine the coordinates of the acoustic signal source without having prior information about the distance to the acoustic signal source or any other characteristics of the object, to determine the coordinates of non-periodic signals, to simplify the process of measuring time intervals and calculating coordinates.
References
С. О. Козерук, О. І. Нижник, та Н. І. Лисенко, Акустичні інформаційні системи. Київ, Україна: КПІ ім. Ігоря Сікорського, 2018.
N. Roman, W. DeLiang, and G. J. Brown, "Speech segregation based on sound localization", The Journal of the Acoustical Society of America, vol. 14, no. 4, p. 2236, July 2003. [Online]. Available: https://doi.org/10.1121/1.1610463. Accessed on: Aug. 23, 2021.
F. Papi, D. Tarchi, M. Vespe, F. Oliveri, F. Borghese, G. Aulicino, and A. Vollero, "Radiolocation and tracking of automatic identification system signals for maritime situational awareness", IET Radar, Sonar & Navigation, vol. 9, no. 5, pp. 568-580, June 2015. [Online]. Available: http://dx.doi.org/10.1049/iet-rsn.2014.0292. Accessed on: Aug. 23, 2021.
D. Byrne, and W. Noble, "Optimizing sound localization with hearing AIDS", Trends in amplification, vol. 3, no. 2, pp. 51-73, June 1998. [Online]. Available: https://doi.org/10.1177/108471389800300202. Accessed on: Sept. 1, 2021.
S. Cheinet, and Th. Broglin, "Sensitivity of shot detection and localization to environmental propagation", Applied Acoustics, vol. 93, pp. 97-105, June 2015. [Online]. Available: https://doi.org/10.1016/j.apacoust.2015.01.021. Accessed on: Dec. 10, 2021.
Ahrens, K. D. Lund, M. Marschall, and T. Dau, "Sound source localization with varying amount of visual information in virtual reality", Plos One, vol. 14, no. 3, March 2019. [Online]. Available: https://doi.org/10.1371/journal.pone.0214603. Accessed on: July 1, 2021.
M. A. Steadman, C. Kim, and J.-H. Lestang, "Short-term effects of sound localization training in virtual reality", Scientific Reports, vol. 9, Dec. 2019. [Online]. Available: https://doi.org/10.1038/s41598-019-54811-w. Accessed on: Dec. 11, 2021.
C. Rascon, and I. Meza, "Localization of sound sources in robotics: A review", Robotics and Autonomous Systems, vol. 96, pp. 184-210, Oct. 2017. [Online]. Available: https://doi.org/10.1016/j.robot.2017.07.011. Accessed on: Jan. 15, 2022.
Richard Hammond's Big: Volkswagen Mega Factory, season 1, episode 1, m. 29:15, February 2020. [Online]. Available: https://www.amazon.com/Richard-Hammonds-Big-Season-1/dp/B084NX8FLZ. Accessed on: Oct. 21, 2021.
L. Chehami, E. Moulin, J. de Rosny, C. Prada, O. B. Matar, F. Benmeddour, and J. Assaad, "Detection and localization of a defect in a reverberant plate using acoustic field correlation", Journal of Applied Physics, American Institute of Physics, vol. 115, pp. 104901-1-7, March 2014. [Online]. Available: https://doi.org/10.1063/1.4867522. Accessed on: June 1, 2022.
L. Sun, and Y. Li, "Acoustic emission sound source localization for crack in the pipeline", In Proc. Chinese Control and Decision Conf., 2010, pp. 4298-4301. [Online]. Available: https://doi.org/10.1109/CCDC.2010.5498373. Accessed on: May 15, 2022.
D. Salvati, C. Drioli, and G. L. Foresti, "Sound source and microphone localization from acoustic impulse responses", in Proc. IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1459-1463, Oct. 2016. [Online]. Available: https://doi.org/10.1109/LSP.2016.2601878. Accessed on: Febr. 18, 2022.
C. Kim, A. Menon, M. Bacchiani, and R. Stern, "Sound source separation using phase difference and reliable mask selection selection", in Proc. 2018 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Apr. 2018, pp. 5559-5563. [Online]. Available: https://doi.org/10.1109/ICASSP.2018.8462269. Accessed on: Sept. 1, 2021.
L. Wang, and A. Cavallaro, "Timefrequency processing for sound source localization from a micro aerial vehicle", in Proc. 2017 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), March 2017, pp. 496-500. [Online]. Available: https://doi.org/10.1109/ICASSP.2017.7952205. Accessed on: May 15, 2022.
Schasse, C. Tendyck, and R. Martin, "Source localization based on the doppler effect", in Proc. 2012 Int. Workshop on Acoustic Signal Enhancement (IWAENC), Sept. 2012, pp. 1-4. [Online]. Available: https://ieeexplore.ieee.org/document/6309397. Accessed on: Nov. 11, 2021.
J. Pak, and L. W. Shin, "Sound localization based on phase difference enhancement using deep neural networks", in Proc. IEEE/ACM Transactions on Audio, Speech, and Language Processing, May 2019, pp. 1335-1345. [Online]. Available: https://doi.org/10.1109/TASLP.2019.2919378. Accessed on: Dec. 11, 2021.
M. Ranjkesh, and R. Hasanzadeh, "A fast and accurate sound source localization method using the optimal combination of SRP and TDOA methodologies", Journal of Information Systems and Telecommunication, vol. 3, no. 2, pp. 100-108, Apr. 2015. [Online]. Available: https://doi.org/10.7508/jist.2015.02.005. Accessed on: Oct. 1, 2021.
M. Đurković, "Localization, tracking, and separation of sound sources for cognitive robots", Dissertation, Technische Universität München, Munich, Germany, 2012.
R. A. Brualdi, Introductory Combinatorics, 5th ed. Reading, Pearson Prentice Hall, 2010. [Online]. Available: https://www.academia.edu/
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