Title: Research on abnormal data recognition method of optical network based on WiFi triangular location

Authors: Bingchen Lin

Addresses: Department of Science and Engineering, Jiaozuo Normal College, Jiaozuo, 454000, Henan Province, China

Abstract: In order to overcome the problems of low recognition accuracy and poor reliability of traditional optical network abnormal data identification methods, a new optical network abnormal data recognition method based on WiFi triangulation positioning is proposed. Time series analysis method is used to analyse the channel model of optical network to obtain the temporal characteristics of abnormal data in optical network. Hyperbolic frequency modulation decomposition method is used to detect the time domain characteristics of abnormal data, and the total energy of abnormal data in time and frequency domain is obtained. The abnormal data signal model is established by the energy density characteristics of abnormal data, and the specific position of abnormal data in the abnormal data signal model after filtering is identified by using WiFi triangle positioning algorithm. The experimental results show that the accuracy of the method is higher than 95%, and the recognition performance is good.

Keywords: WiFi; triangulation; channel model; total time-frequency energy; energy density characteristics.

DOI: 10.1504/IJAACS.2023.132506

International Journal of Autonomous and Adaptive Communications Systems, 2023 Vol.16 No.4, pp.357 - 375

Received: 29 Jun 2020
Accepted: 09 Nov 2020
Published online: 25 Jul 2023 *

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