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The Development and Analysis of Beamforming Algorithms Used for Designing an Acoustic Camera

Received: 8 November 2019     Accepted: 29 November 2019     Published: 6 December 2019
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Abstract

This paper discusses the beamforming algorithms used in developing an acoustic camera which can be used for the purpose of localizing sound sources. In order to design an acoustic camera which can display results in the form of an intensity map, it is necessary to determine the beamformed signal for all the desired incident angles, i.e. for all the desired pairs of azimuth and elevation angles. For the purpose of obtaining the beamformed signal required for localization of sound sources, two beamforming algorithms, which differ in the domain in which the beamforming is performed, were developed named respectively DASt.m and DASf.m. The aforementioned algorithms are implemented in the numerical computing environment MATLAB and furthermore compared in this paper. The beamforming was carried out using both of the aforementioned algorithms for all desired azimuth and elevation angle pairs and the obtained results were compared. In order to compare these two developed beamforming algorithms measurements were conducted in an open space using a Uniform Circular Array (UCA). The utilized UCA consists of 16 identical omnidirectional microphones which form a basic circular acoustic camera. The research showed that the DASf.m algorithm gives better results than the DASt.m algorithm, especially for the intensity maps of the average of the signal.

Published in American Journal of Environmental Science and Engineering (Volume 3, Issue 4)

This article belongs to the Special Issue Smart Cities – Innovative Approaches

DOI 10.11648/j.ajese.20190304.15
Page(s) 94-102
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Beamforming, Delay and Sum Algorithm, Time Difference of Arrival, Acoustic Camera, Uniform Circular Array

References
[1] J. Grythe, Acoustic camera and beampattern, Technical Note Norsonic, Oslo, Norway, 2015.
[2] K. Tontiwattanakul, J. Hongweing, P. Trakulsatjawat and P. Noimai, “Design and build of a planar acoustic camera using digital microphones”, 5th International Conference on Engineering, Applied Sciences and Technology (ICEAST), 2019.
[3] B. Zimmermann and C. Studer, FPGA-based Real-Time Acoustic Camera Prototype, Proc. of IEEE Int. Symp. on Circuits and Systems (ISCAS), Paris, France, 2010.
[4] J. Stamac, S. Grubesa and A. Petosic, “Designing the Acoustic Camera using MATLAB with respect to different types of microphone arrays”, Second International Colloquium on Smart Grid Metrology, SMAGRIMET 2019.
[5] M. Brandstein and D. Ward, Microphone Arrays: Signal Processing Techniques and Applications, Digital Signal Processing. Springer, 2001.
[6] T. E. Tuncer and B. Friedlander, Classical and Modern Direction-of-Arrival Estimation, Academic Press, 2009.
[7] E. T. Roig, Elisabet, Beamforming Techniques for Environmental Noise, Brüel & Kjær, 2009.
[8] J. Benesty, J. Cheng and Y. Huang, Microphone Array Signal Processing, Springer-Verlang, 2008.
[9] http://www.labbookpages.co.uk/audio/beamforming/delaySum.html
[10] B. D. Van Veen and K. M. Buckley, Beamforming: A versatile approach to spatial filtering, IEEE ASSP Mag., 5 (2), 1988.
[11] https://www.gras.dk/products/special-microphone/array-microphones/product/178-40ph
[12] https://www.dji.com/hr/spark
[13] N. Wu, Z. Qu, W. Si, and S. Jiao, DOA and Polarization Estimation Using an Electromagnetic Vector Sensor Uniform Circular Array Based on the ESPRIT Algorithm, settings, Sensors, 16 (12), 2016.
[14] National Instruments device cDAQ-9174 http://www.ni.com/en-rs/support/model.cdaq-9174.html
[15] S. W. Smith, The Scientist and Engineer's Guide to Digital Signal Processing, California Technical Publishing, 1997.
Cite This Article
  • APA Style

    Sanja Grubesa, Jasna Stamac, Ivan Krizanic, Antonio Petosic. (2019). The Development and Analysis of Beamforming Algorithms Used for Designing an Acoustic Camera. American Journal of Environmental Science and Engineering, 3(4), 94-102. https://doi.org/10.11648/j.ajese.20190304.15

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    ACS Style

    Sanja Grubesa; Jasna Stamac; Ivan Krizanic; Antonio Petosic. The Development and Analysis of Beamforming Algorithms Used for Designing an Acoustic Camera. Am. J. Environ. Sci. Eng. 2019, 3(4), 94-102. doi: 10.11648/j.ajese.20190304.15

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    AMA Style

    Sanja Grubesa, Jasna Stamac, Ivan Krizanic, Antonio Petosic. The Development and Analysis of Beamforming Algorithms Used for Designing an Acoustic Camera. Am J Environ Sci Eng. 2019;3(4):94-102. doi: 10.11648/j.ajese.20190304.15

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  • @article{10.11648/j.ajese.20190304.15,
      author = {Sanja Grubesa and Jasna Stamac and Ivan Krizanic and Antonio Petosic},
      title = {The Development and Analysis of Beamforming Algorithms Used for Designing an Acoustic Camera},
      journal = {American Journal of Environmental Science and Engineering},
      volume = {3},
      number = {4},
      pages = {94-102},
      doi = {10.11648/j.ajese.20190304.15},
      url = {https://doi.org/10.11648/j.ajese.20190304.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajese.20190304.15},
      abstract = {This paper discusses the beamforming algorithms used in developing an acoustic camera which can be used for the purpose of localizing sound sources. In order to design an acoustic camera which can display results in the form of an intensity map, it is necessary to determine the beamformed signal for all the desired incident angles, i.e. for all the desired pairs of azimuth and elevation angles. For the purpose of obtaining the beamformed signal required for localization of sound sources, two beamforming algorithms, which differ in the domain in which the beamforming is performed, were developed named respectively DASt.m and DASf.m. The aforementioned algorithms are implemented in the numerical computing environment MATLAB and furthermore compared in this paper. The beamforming was carried out using both of the aforementioned algorithms for all desired azimuth and elevation angle pairs and the obtained results were compared. In order to compare these two developed beamforming algorithms measurements were conducted in an open space using a Uniform Circular Array (UCA). The utilized UCA consists of 16 identical omnidirectional microphones which form a basic circular acoustic camera. The research showed that the DASf.m algorithm gives better results than the DASt.m algorithm, especially for the intensity maps of the average of the signal.},
     year = {2019}
    }
    

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    JF  - American Journal of Environmental Science and Engineering
    JO  - American Journal of Environmental Science and Engineering
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    AB  - This paper discusses the beamforming algorithms used in developing an acoustic camera which can be used for the purpose of localizing sound sources. In order to design an acoustic camera which can display results in the form of an intensity map, it is necessary to determine the beamformed signal for all the desired incident angles, i.e. for all the desired pairs of azimuth and elevation angles. For the purpose of obtaining the beamformed signal required for localization of sound sources, two beamforming algorithms, which differ in the domain in which the beamforming is performed, were developed named respectively DASt.m and DASf.m. The aforementioned algorithms are implemented in the numerical computing environment MATLAB and furthermore compared in this paper. The beamforming was carried out using both of the aforementioned algorithms for all desired azimuth and elevation angle pairs and the obtained results were compared. In order to compare these two developed beamforming algorithms measurements were conducted in an open space using a Uniform Circular Array (UCA). The utilized UCA consists of 16 identical omnidirectional microphones which form a basic circular acoustic camera. The research showed that the DASf.m algorithm gives better results than the DASt.m algorithm, especially for the intensity maps of the average of the signal.
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Author Information
  • Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

  • Geolux d. o. o., Zagreb, Croatia

  • Geolux d. o. o., Zagreb, Croatia

  • Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

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