Influence Assessment of Distance to the Source of Pulse Signals With Harmonic Components on the Temporal Distortion of Their Forms

2024;
: cc. 61 - 67
1
Ivano-Frankivsk National Technical University of Oil and Gas
2
Прикарпатський національний університет імені Василя Стефаника

Within the scope of this article, periodic pulse signal typical samples with harmonic components have been analyzed, including their spectral fluctuations, changes in their frequency range, and the form of signal typical samples depending on the distance. Collected statistical information regarding changes in the duration of typical samples affected by distance change from the signal source to the sensor based on data collected during field experiments. Signal features by which typical samples can be recognized have been outlined and their duration effectively measured. The dynamics of frequency spectrum change and duration of repetitive typical samples have been presented depending on the distance to the signal source. Additionally, the frequency range and average duration range of the researched typical samples, and their variations have been provided based on the gathered statistics data.

  1. Zhao, Y., Niu, F., Liu, H., Jia, X., Yang, J., & Huo, S. (2020).Source‐receiver interferometric redatuming using sparse buried receivers to address complex near‐surface environ- ments: A case study of seismic imaging quality and time‐lapse repeatability. Journal of Geophysical Research: Solid       Earth,       125(6),       e2020JB019496.       DOI:https://doi.org/10.1029/2020JB019496 
  2. Saux, B., Borgmans, J., Raman, J., & Rombouts, P. (2024) Origin of Frequency-Dependent Distortion and Calibration for Ring Oscillator VCO ADCs, IEEE Trans. Circuits Syst. II:Exp. Briefs. DOI: https://doi.org/10.1109/tcsii.2024.3370121
  3. Wang, B., Chen, X., Li, Y., Zhou, Q., & Li, Y. (2022).Research on Time Sidelobe Analysis on Pulse Compression Signal. Journal of Physics: Conference Series, 2366(1), 012022.    DOI:   https://doi.org/10.1088/1742-6596/2366/1/012022
  4. From Signals  to Spectra: Exploring Crosscorrelation  with Fourier Transform update – Faster Capital. Faster Capital. Accessed: Apr. 11, 2024. [Online]. Available: https://fastercapital.com/content/From-Signals-to-Spectra-- Exploring-Crosscorrelation-with-Fourier-Transform- update.html#Crosscorrelation-in-Time-and-Frequency-Domains.html
  5. Damskägg, E. P., & Välimäki, V. (2017). Audio time stretch- ing using fuzzy classification of spectral bins. Applied Sci- ences, 7(12), 1293. DOI: 10.3390/app7121293
  6. Mariani, S., Liu, Y., & Cawley, P. (2021). Improving sensi- tivity and coverage of structural health monitoring using bulk ultrasonic waves. Structural Health Monitoring, 20(5), 2641- 2652. DOI: 10.1177/1475921720965121
  7. Dan, D., Wang, C., Pan, R., & Cao, Y. (2022). Online Sifting Technique for Structural Health Monitoring Data Based on Recursive EMD Processing Framework. Buildings, 12(9), 1312. DOI:10.3390/buildings12091312
  8. Zhou, W. (2022). Reaching the Frequency Resolution Limit in a Single-Shot Spectrum of an Ultra-Short Signal Pulse Us- ing an Analog Optical Auto-Correlation Technique. Journal of     Lightwave          Technology, 41(1),          114-119.DOI:10.1109/jlt.2022.3213188
  9. Gobron, K., Rebischung, P., Van Camp, M., Demoulin, A.,& de Viron, O. (2021). Influence of aperiodic non‐tidal at- mospheric and oceanic loading deformations on the stochas- tic properties of global GNSS vertical land motion time se- ries. Journal of Geophysical Research: Solid Earth, 126(9), e2021JB022370. DOI: 10.1029/2021jb022370
  10. Ruan, H., Zhang, L., & Long, T. (2016). Sinc interpolation based method for compensation of ionospheric dispersion ef- fects on BOC signals with high subcarrier rate. Science China.        Information        Sciences, 59(10),        102311.DOI:10.1007/s11432-016-5555-3
  11. Zhou, W., Lv, Z., Deng, X., & Ke, Y. (2022). A new induced GNSS spoofing detection method based on weighted second- order central moment. IEEE Sensors Journal, 22(12), 12064- 12078. DOI: 10.1109/jsen.2022.3174019
  12. Zhuang, C., Zhao, H., Sun, C., & Feng, W. (2020). Detection and classification of GNSS signal distortions based on quad- ratic  discriminant  analysis. IEEE  Access, 8,  25221-25236.DOI:10.1109/access.2020.2965617
  13. Li, X., Wang, C., Zhu, C., Wang, S., Li, W., Wang, L., &Zhu, W. (2022). Coseismic deformation field extraction and fault slip inversion of the 2021 Yangbi Mw 6.1 earthquake, Yunnan Province, based on time-Series InSAR. Remote Sensing, 14(4), 1017. DOI: 10.3390/rs14041017
  14. Sun, Y., & Ochiai, H. (2021). Performance analysis and comparison of clipped and filtered OFDM systems with it- erative distortion recovery techniques. IEEE Transactions on Wireless              Communications, 20(11),      7389-7403.DOI:10.1109/twc.2021.3083537
  15. Soares de Alcantara, D., Balestrassi, P. P., Freitas Gomes, J. H., & Carvalho Castro, C. A. (2020).  Vibrations  in CDFW. Entropy, 22(6), 704. DOI: 10.3390/e22060704
  16. Wu D., Zhuo X., Chen Y., Ren G., & Deng W. (2022) An Approach to Vibration Signal Analysis Using Quantum Probability. Advances Transdisciplinary Eng., vol. 24. 336– 342. DOI: 10.3233/atde220455
  17. Han, B., Zhang, G., Wang, J., Wang, X., Jia, S., & He, J. (2020). Research and application of regularized sparse filter- ing model for intelligent fault diagnosis under large speed fluctuation. IEEE             Access, 8,                39809-39818.DOI:10.1109/access.2020.2975531
  18. Chen, D., Han, J., Cui, X., & Fan, J. (2018). Identification and evaluation for the dynamic signals caused by pressure fluctuation of aerostatic slider. Industrial Lubrication and Tribology, 70(6), 927-934. DOI: 10.1108/ilt-11-2016-0271
  19. Wang, G.; Zhou, Y.; Min, R.; Du, E.; Wang, C. (2023).Principle and Recent Development in Photonic Time-Stretch Imaging. Photonics, 10(7),      817.DOI: https://doi.org/10.3390/photonics10070817
  20. Gui, Y. F., & Dou, W. B. (2008). Phenomena of paired echoes and transmission characteristics of the pulse signal in dispersive transmission lines with discontinuities. Progress In       Electromagnetics       Research       B, 5,       225-240.DOI: https://doi.org/10.2528/pierb08022202
  21. Six, P. W. M., & serial USART, P. (2015). 8-bit AVR Microcontroller  with  32K  Bytes  In-System  Programmable Flash. Atmel-7810-Automotive-Microcontrollers-ATmega328P_Datasheet.     pdf.      [Online].      Available: https://ww1.microchip.com/downloads/en/DeviceDoc/Atmel-7810-Automotive-M...
  22. Vanchak V. S., Melnychuk S. I., & Manuliak I. Z. (2023). Frequency spectrum distortion of periodic impulse signals with harmonic components affected by distance to the source. In materials of All-Ukrainian scientific and practical conference “IT in education and industry”, Ivano-Frankivsk, Ukraine, Oct. 12, 2023. Ivano-Frankivsk: IFNTUOG. 217–218.
  23. Vanchak V. S., Melnychuk S. I., & Manuliak I. Z. (2023). Efficiency of low-pass filters based on FFT for SNR im- provement of periodic impulse signals with harmonic com- ponents. In materials of XII-th scientific and practical con- ference “Problems of informatics and computer technolo- gies”, Ivano-Frankivsk, Ukraine, Nov. 10-12, 2023. Cherniv- tsi: Yuriy Fedkovych Chernivtsi National Technical Univer- sity. 71–73.
  24. Voronych, A., Nykolaychuk, L., Grynchyshyn, T., Hryha, V., Melnychuk, S., & Nykolaychuk, Y. (2020, September). De- velopment of Theory, Scope and Tools for Entropy Signals and Data Processing. In 2020 10th International Conference on Advanced Computer Information Technologies (ACIT), Deggendorf, Germany, Sept. 16-18, 2023. IEEE. 260-264. DOI:  https://doi.org/10.1109/ACIT49673.2020.9208912