Autors: Marinov, M. B., Ganev, B. T., Djermanova, N., Tashev, T.D.
Title: Analysis of Sensors Noise Performance Using Allan Deviation
Keywords: Allan deviation, Allan variance, Analysis method, CO2 sensor

Abstract: The paper presents the noise analysis of different sensor types using Allan Variance (AV). Compared to the conventional variance that assesses the variation around the mean value of the aggregate data surveyed, AV estimates variations by averaging measurements for different periods. This approach often leads to the possibility of directly distinguishing the different noise types and to better convergence of the process of assessing their levels. An important advantage of this method is that there is no need for any further transformations. According to IEEE recommendations, the AV approach is the preferred method for identifying stochastic error and for determining the type of noise in different types of inertial sensors. The purpose of this work is to study the applicability of the AV analysis method for efficient noise analysis for other types of sensors such as CO2 and MEMS pressure sensors

References

    Issue

    28th International Scientific Conference Electronics, 12 September 2019 through 14 September 2019, vol. ET 2019 - Proceedings, issue 28, pp. Article number 8878552, 2019, Bulgaria, Institute of Electrical and Electronics Engineers Inc., DOI 10.1109/ET.2019.8878552

    Copyright IEEE

    Цитирания (Citation/s):
    1. Nedyalkov, I., Stefanov, A., Georgiev, G., Application of technologies from telecommunication networks for the protection of data generated from power electronic devices, 2020 PCIM Europe Conference Proceedings 1, pp. 1157-1164 - 2020 - в издания, индексирани в Scopus или Web of Science
    2. Kalupahana, A.I.K., Balaji, A.N., Xiao, X., Peh, L.-S. SeRaNDiP - Leveraging Inherent Sensor Random Noise for Differential Privacy Preservation in Wearable Community Sensing Applications. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7(2),3596252. 2023. DOI: 10.1145/3596252 - 2023 - в издания, индексирани в Scopus или Web of Science
    3. Belo, F.A., Soares, M.B., Lima Filho, A.C., Lima, T.L.D.V., Adissi, M.O. Accuracy and Precision Improvement of Temperature Measurement Using Statistical Analysis/Central Limit Theorem. M.O. DOI: 10.3390/s23063210 - 2023 - в издания, индексирани в Scopus или Web of Science
    4. Liao H., Zhao Y., Zheng K., Bao H., Jiang S., Ho H.L., Gao S., Wang Y., Jin W. Stimulated Raman photothermal spectroscopy for gas sensing in a hollow-core optical fiber. Optica, 11 (12), pp. 1682 - 1689. DOI: 10.1364/OPTICA.528840 - 2024 - в издания, индексирани в Scopus или Web of Science
    5. Gaßner S., Essing S., Tumpold D., Schmitt K., Wöllenstein J. Miniaturized two-chamber photoacoustic CO2 sensor with a wafer-bonded MEMS (micro-electro-mechanical systems) detector. (2024) Journal of Sensors and Sensor Systems, 13 (2), pp. 219 - 226. DOI: 10.5194/jsss-13-219-2024 - 2024 - в издания, индексирани в Scopus или Web of Science
    6. Chen Z., Li H., Yu H., Zhao Y., Zhang C., Zhang H. Research on UAV Flight Parameter Identification Method Based on Launch Force and Airspeed. (2024) Sensors, 24 (5), art. no. 1597. DOI: 10.3390/s24051597. - 2024 - в издания, индексирани в Scopus или Web of Science
    7. Zhu Y., Chang G., Yang M. Application of Akaike information criterion in selecting random error model for inertial measurement unit [应用赤池信息量准则优选惯性元器件的随机误差模型]. (2024) Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology, 32 (2), pp. 180 - 186. DOI: 10.13695/j.cnki.12-1222/o3.2024.02.010 - 2024 - в издания, индексирани в Scopus или Web of Science
    8. Neelam, Kandeepan S., Panja S. Phase Noise Analysis of Time Transfer over White Rabbit-Network Based Optical Fibre Links. (2024) Sensors, 24 (2), art. no. 381. DOI: 10.3390/s24020381. - 2024 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus