Published April 30, 2020 | Version v1
Journal article Open

Forming a method for determining the coordinates of sound anomalies based on data from a computerized microphone system

Authors/Creators

  • 1. Petro Mohyla Black Sea National University

Description

Special features in the process of determining the coordinates of sound anomalies according to the sound series were considered. Sound anomalies have been shown to be a source of information about events, phenomena that are already occurring, or are their harbingers. It has been stated that audio interception systems complement thermal imagers and provide savings in financial and human resources when used in combination with the benefits of unmanned aerial vehicles. The methods facilitating solution of the problem of surveillance and prediction by finding coordinates of sound anomalies were presented. Indirect methods for solving problems of searching for sound anomaly coordinates with three microphones in accordance with a linear scheme of approximants and linear and quadratic approximation were proposed. Solutions were reduced to analytical complete expressions that make it possible to calculate coordinates according to the input conditions for three or four microphones. Also, a problem of finding coordinates of a sound anomaly for three and four microphones was set and solved by direct methods. Solutions were presented as expressions that make it possible to calculate coordinates of sound anomalies. Numerical experiments were performed during which coordinates of sound anomalies, the absolute error of their determination at each iteration, and total time spent for calculation were found. Systems with coordinates of microphones and sound sources almost identical or coinciding have been shown to have the greatest error. Under these conditions, for direct methods, values of the equation coefficients decreased to almost zero or turned to zero and the difference of values of the sought coordinates between iterations increased sharply which slowed down the process of solution convergence. It was shown that the application of approximate methods to the search for coordinates by solving the minimization problems with the involvement of the recurrent approximation method makes it possible to construct simple algorithms. Their implementation to solve the problems of numerical experiments has given quick and practically accurate coordinate values. It was found, that the application of algorithms to the methods of logical analysis and rules of logical inference reduces the number of iterations and the total calculation time

Files

Forming a method for determining the coordinates of sound anomalies based on data from a computerized microphone system.pdf

Files (226.0 kB)

Additional details

References

  • Nazirov, E. K., Nazirova, T. A. (2018). Emergency notification system "АСЕН." Scientific Bulletin of UNFU, 28 (1), 140–144. doi: https://doi.org/10.15421/40280128
  • Seah, C. E., Hwang, I. (2009). Stochastic Linear Hybrid Systems: Modeling, Estimation, and Application in Air Traffic Control. IEEE Transactions on Control Systems Technology, 17 (3), 563–575. doi: https://doi.org/10.1109/tcst.2008.2001377
  • Camacho, E. F., Ramirez, D. R., Limon, D., Muñoz de la Peña, D., Alamo, T. (2010). Model predictive control techniques for hybrid systems. Annual Reviews in Control, 34 (1), 21–31. doi: https://doi.org/10.1016/j.arcontrol.2010.02.002
  • SPOTLITE - Electro-Optical Small-Arms Fire Detection System. Available at: https://defense-update.com/20060726_spotlite.html
  • PILAR - Ground Version. Available at: http://metravib.acoemgroup.com/defence/catalog/PILAR---GROUND-VERSION
  • Yong, J., Wang, D.-Y. (2015). Impact of noise on hearing in the military. Military Medical Research, 2 (1), 6. doi: https://doi.org/10.1186/s40779-015-0034-5
  • Rascon, C., Meza, I. (2017). Localization of sound sources in robotics: A review. Robotics and Autonomous Systems, 96, 184–210. doi: https://doi.org/10.1016/j.robot.2017.07.011
  • Boomerang III. Available at: https://www.raytheon.com/capabilities/products/boomerang
  • Yang, X., Xing, H., Ji, X. (2018). Sound Source Omnidirectional Positioning Calibration Method Based on Microphone Observation Angle. Complexity, 2018, 1–15. doi: https://doi.org/10.1155/2018/2317853
  • Kakaya tehnika pozvolit vyigrat' voynu s terroristami. Available at: http://www.autoconsulting.com.ua/article.php?sid=30908
  • Nguyen, L., Valls Miro, J., Qiu, X. (2019). Multilevel B-Splines-Based Learning Approach for Sound Source Localization. IEEE Sensors Journal, 19 (10), 3871–3881. doi: https://doi.org/10.1109/jsen.2019.2895854
  • L'vov, A. V., Agapov, M. N., Tishchenko, A. I. (2010). Triangulyatsionnaya sistema opredeleniya koordinat istochnika zvuka. Polzunovskiy vestnik, 2, 159–162.
  • Risoud, M., Hanson, J.-N., Gauvrit, F., Renard, C., Lemesre, P.-E., Bonne, N.-X., Vincent, C. (2018). Sound source localization. European Annals of Otorhinolaryngology, Head and Neck Diseases, 135 (4), 259–264. doi: https://doi.org/10.1016/j.anorl.2018.04.009
  • Döbler, D., Heilmann, G., Ohm, M. (2010). Automatic detection of microphone coordinates. 3rd Berlin Beamforming Conference. Available at: http://www.bebec.eu/Downloads/BeBeC2010/Papers/BeBeC-2010-15.pdf
  • Byelozyorov, Zh. O. (2016). Analysis of the algorithm for calculating the coordinates of the shot and its practical implementation on the basis of mobile device in cooperation with the UAV. Naukovi pratsi ChNU im. Petra Mohyly. Seriya: Kompiuterni tekhnolohiyi, 287 (275), 34–40.
  • Palahin, O. V., Vasiukhin, M. I., Kasim, A. M., Ivanyk, Yu. Yu., Dolynnyi, V. V. (2015). Metody ta zasoby pobudovy dynamichnykh stsenariyiv u navihatsiynykh heoinformatsiynykh systemakh. Perspektyvy rozvytku avtomatyzovanykh system upravlinnia viyskamy ta heoinformatsiynykh system: zbirnyk materialiv naukovo-praktychnoi konferentsiyi. Lviv: ASV, 185–200.
  • Engel, J., Sturm, J., Cremers, D. (2012). Camera-based navigation of a low-cost quadrocopter. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. doi: https://doi.org/10.1109/iros.2012.6385458
  • Bilenko, O. I., Hunko, H. L. (2015). Vyznachennia parametriv zvuku postrilu, yaki vplyvaiut na vykonannia spetsyfichnykh vohnevykh zavdan sylamy bezpeky ta pidliahatymut rehlamentatsiyi. Perspektyvy rozvytku ozbroiennia ta viyskovoi tekhniky sukhoputnykh viysk. Zbirnyk tez dopovidei Mizhnarodnoi naukovo-tekhnichnoi konferentsiyi. Lviv, 14–15.
  • Krainyk, Y., Darnapuk, Y. (2019). Configurable Description of FPGA-based Control System for Sensor Processing. 2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT). doi: https://doi.org/10.1109/elit.2019.8892313
  • Trounov, A. N. (1984). Аpplication of sensory modules for adaptive robots. IFS Publication. Robot Vision and Sensory Control, 285–294.
  • Musiyenko, M. P., Zhuravska, I. M., Kulakovska, I. V., Kulakovska, A. V. (2016). Simulation the behavior of robot sub-swarm in spatial corridors. 2016 IEEE 36th International Conference on Electronics and Nanotechnology (ELNANO). doi: https://doi.org/10.1109/elnano.2016.7493090
  • Zhuravska, I., Kulakovska, I., Musiyenko, M. (2018). Development of a method for determining the area of operation of unmanned vehicles formation by using the graph theory. Eastern-European Journal of Enterprise Technologies, 2 (3 (92)), 4–12. doi: https://doi.org/10.15587/1729-4061.2018.128745
  • Zhuravska, I. Musiyenko, M., Tohoiev, O. (2019). Development the Heat Leak Detection Method for Hidden Thermal Objects by Means the Information-Measuring Computer System. Proceedings of the Second International Workshop on Computer Modeling and Intelligent Systems (CMIS-2019), 2353, 350–364. Available at: http://ceur-ws.org/Vol-2353/paper28.pdf
  • Kryvoruchko, A. V. (2012). Ohliad ta porivnialnyi analiz tekhnichnykh system vyiavlennia pozytsiyi snaipera. Suchasna spetsialna tekhnika, 3, 75–81. 2012. Available at: http://elar.naiau.kiev.ua/jspui/bitstream/123456789/2468/1/%d0%9a%d1%80%d0%b8%d0%b2%d0%be%d1%80%d1%83%d1%87%d0%ba%d0%be%20%d0%90.%20%d0%92..pdf
  • Babichev, V. I., Shigin, A. V., Morozov, V. I., Golomidov, B. A., Larin, D. V., Larin, A. V. et. al. (2011). Pat. No. 2453790 RF. Sposob strel'by artilleriyskimi snaryadami s zakrytyh ognevyh pozitsiy. No. 2011104932/28; declareted: 10.02.2011; published: 20.06.2012, Bul. No. 17. Available at: http://www.freepatent.ru/patents/2453790
  • Gorshkov, A. I. (2001). Pat. No. 2215972 RF. Sistemy navedeniya. declareted: 28.09.2001; published: 10.11.2003. Available at: http://www.freepatent.ru/patents/2215972
  • Tkachenko, V. N., Khashan, T. S., Manuilenko, R. I. (2013). Extreme formulation of the problem of determining the origin of the sound source in information redundancy conditions. Iskusstvenniy intellekt, 3, 462–469.
  • Trembach, B. R., Kochan, R. V. (2016). Analiz pokhybky vymiriuvannia kuta napriamu na tsil rozpodilenoiu systemoiu zvukovoi artyleriyskoi rozvidky. Vymiriuvalna tekhnika ta metrolohiya, 77, 177–182.
  • Kochan, R., Trembach, B., Kochan, O. (2019). Methodical error of targets bearing by sound artillery intelligence system. Measuring Equipment and Metrology, 80 (3), 10–14. doi: https://doi.org/10.23939/istcmtm2019.03.010
  • Taringoo, F., Caines, P. E. (2010). Gradient-geodesic HMP algorithms for the optimization of Hybrid systems based on the geometry of switching manifolds. 49th IEEE Conference on Decision and Control (CDC). doi: https://doi.org/10.1109/cdc.2010.5717541
  • Banitalebi, A., Ahmad, R., Abd Aziz, M. I. (2012). A direct method for optimal control problem. International Journal of Pure and Applied Mathematics, 81 (1), 33–47.
  • Dal Bianco, N., Bertolazzi, E., Biral, F., Massaro, M. (2018). Comparison of direct and indirect methods for minimum lap time optimal control problems. Vehicle System Dynamics, 57 (5), 665–696. doi: https://doi.org/10.1080/00423114.2018.1480048
  • Trunov, A. (2017). Theoretical predicting the probability of electron detachment for radical of cell photo acceptor. 2017 IEEE 37th International Conference on Electronics and Nanotechnology (ELNANO). doi: https://doi.org/10.1109/elnano.2017.7939776
  • Trunov, A., Malcheniuk, A. (2018). Recurrent network as a tool for calibration in automated systems and interactive simulators. Eastern-European Journal of Enterprise Technologies, 2 (9 (92)), 54–60. doi: https://doi.org/10.15587/1729-4061.2018.126498
  • Trunov, A. (2017). Recurrent Approximation in the Tasks of the Neural Network Synthesis for the Control of Process of Phototherapy. Chap. 10. Computer Systems for Healthcare and Medicin. Denmark, 213–248.
  • Trunov, A. (2018). Transformation of operations with fuzzy sets for solving the problems on optimal motion of crewless unmanned vehicles. Eastern-European Journal of Enterprise Technologies, 4 (4 (94)), 43–50. doi: https://doi.org/10.15587/1729-4061.2018.140641
  • Trunov, A. (2016). Recurrent approximation as the tool for expansion of functions and modes of operation of neural network. Eastern-European Journal of Enterprise Technologies, 5 (4 (83)), 41–48. doi: https://doi.org/10.15587/1729-4061.2016.81298
  • Trunov, A. (2019). Forming a мetodology for transforming a model as the basis for expanding its informativeness. Eastern-European Journal of Enterprise Technologies, 5 (4 (101)), 34–43. doi: https://doi.org/10.15587/1729-4061.2019.181866