Abstract
AbstractNowadays, the increasingly complex and changeable marine environment makes the signals received by the underwater sensing equipment not only contain the weak signals radiated by underwater targets but also accompanied by marine solid background noise, which leads to the degradation and distortion of underwater acoustic signals and the decline of underwater communication quality. Under the severe influence of ocean noise, the underwater acoustic sensing and acquisition system will have the problems of high SNR ratio threshold, minimal sensing bandwidth, and unable to sense the signal with unknown frequency effectively. The Lévy noise model has been selected to describe the marine noise environment and explain its scientificity in this paper. A parameter estimation method for Lévy noise is proposed. Under the condition of characteristic index $$\alpha =1.5$$
α
=
1.5
and noise intensity $$D=0.1$$
D
=
0.1
of the Lévy noise model, the estimated mean values of parameters are 1.5026 and 1.1664. The estimated variances are 0.0034 and 0.0046, which proves the effectiveness and applicability of the estimation method. Then, an improved dual-coupled Duffing oscillator sensing system is proposed to sense the weak signals with unknown frequency under Lévy noise. Under the background of Lévy with characteristic index $$\alpha =1.5$$
α
=
1.5
, deflection parameter $$\beta =0$$
β
=
0
and noise intensity $$D=0.1$$
D
=
0.1
, the sensing error rate of our system with unknown frequency is $$0.054\%$$
0.054
%
, the lowest sensing signal amplitude is $$A=0.010$$
A
=
0.010
, the lowest sensing SNR ratio is − 23.9254 dB, and the frequency of multi-frequency weak signals to be measured can be obtained. The estimation error of frequency sensing is $$0.33\%$$
0.33
%
.
Funder
National Natural Science Foundation of China
the Frontier Science and Technology Innovation Projects of National Key R&D Program
the Sichuan Science and Technology Innovation Platform and Talent Plan
the Sichuan Science and Technology Support Plan
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Computer Science Applications,Signal Processing
Reference50 articles.
1. D. Chen, Z. Zhao, X. Qin, Y. Luo, M. Cao, H. Xu, A. Liu, Magleak: a learning-based side-channel attack for password recognition with multiple sensors in IIoT environment. IEEE Trans. Ind. Inf. (2020)
2. N. Zhang, P. Yang, S. Zhang, D. Chen, W. Zhuang, B. Liang, X.S. Shen, Software defined networking enabled wireless network virtualization: challenges and solutions. IEEE Netw. 31(5), 42–49 (2017). https://doi.org/10.1109/MNET.2017.1600248
3. N. Zhang, P. Yang, J. Ren, D. Chen, L. Yu, X. Shen, Synergy of big data and 5g wireless networks: opportunities, approaches, and challenges. IEEE Wirel. Commun. 25(1), 12–18 (2018). https://doi.org/10.1109/MWC.2018.1700193
4. H. Gao, C. Liu, A hybrid approach to trust node assessment and management for vanets cooperative data communication: historical interaction perspective. IEEE Intell. Transp. Syst. Trans. 1–10 (2021)
5. L. Ale, N. Zhang, H. Wu, D. Chen, T. Han, Online proactive caching in mobile edge computing using bidirectional deep recurrent neural network. IEEE Internet Things J. 6(3), 5520–5530 (2019)
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