This research paper proposes the construction of an mathematical model of infrasound signal propagation. The constructed model contains the following set of input data: standard deviation of measurement noise, infrasound wave propagation velocity, sensor coordinates, azimuth, and time of infrasound signal reception by sensors. The specified accuracy of the input data is discussed and justified. The main theoretical modeling methods are a combination of azimuth based triangulated value averaging and Bayesian infrasound source localization. The result of the modeling is a Python software module with the ability to set input data and obtain a point with the coordinates of the location of the infrasound signal source, the distance of the sensors to it. Visualization of the results of mathematical modeling is provided for the purpose of verification of the obtained results, further studies of the influence of the accuracy of input data. The obtained modeling results are expected to be used to fill data samples for further research on infrasound signal localization using machine learning method sand tools; for iterative improvement of the current mathematical model.
[1] Banerji B., Pande S. Sound Source Triangulation Game. 2007. Cornell College of Engineering. https://www.ece.cornell.edu/
[2] Blom P. S., Marcillo O., Arrowsmith S. J. Improved Bayesian Infrasonic Source Localization for regional infrasound. Geophysical Journal International. 2015. vol. 203, № 3. pp. 1682–1693. https://doi.org/10.1093/gji/ggv387.
[3] Liaschuk O. I. GEODYNAMICS. GEODYNAMICS. 2015. vol. 1(18)2015, № 1(18). pp. 36–44. URL: https://doi.org/10.23939/jgd2015.01.036.
[4] Trembach B. Метод просторової ідентифікації джерела акустичних сигналів у двовимірному хеммінговому просторі. Computer systems and network. 2017. vol. 1, № 1. pp. 166–177. https://doi.org/10.23939/csn2017.881.166.
[5] Multiple Signal Classification-Based Impact Localizationin Composite Structures Using Optimized Ensemble Empirical Mode Decomposition/ Y.Zhong et all. Applied Sciences. 2018. vol. 8, № 9. pp. 1447. https://doi.org/10.3390/app8091447
[6] The Generalized Cross-Correlation Method for Time Delay Estimation of Infrasound Signal / M. Liang та ін. 2015 Fifth International Conference on Instrumentation & Measurement, Computer, Communicationand Control (IMCCC), м. Qinhuangdao, China, 18–20.09.2015 р. 2015. https://doi.org/10.1109/imccc.2015.283
[7] Time Domain Analysisvs Frequency Domain Analysis: A Guideand Comparison. Cadence PCB Design&Analysis. https://resources.pcb.cadence.com/blog/2020-time-domain-analysis-vs-freq....
[8] Infrasound Source Localization of Distributed Stations Using Sparse Bayesian Learningand Bayesian Information Fusion / R. Wang et all. Remote Sensing. 2022. vol. 14, № 13. pp. 3181. https://doi.org/10.3390/rs14133181
[9] Evaluating the location capabilities of a regional infrasonic network in Utah, US, using both raytracing-derived and empirical-derived celerity-range and backazimuth models / F. K. Dannemann Dugick et all. Geophysical Journal International. 2022. Vol. 229, № 3. pp. 2133–2146. https://doi.org/10.1093/gji/ggac027
[10] Gibbons S. Report on remotein frasonic location accuracy for Ground Truth Events. European Commission, 2017. 25 с. https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5b5135e8f&appId=PPGMS