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A practical underwater information sensing system based on intermittent chaos under the background of Lévy noise
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A practical underwater information sensing system based on intermittent chaos under the background of Lévy noise
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A practical underwater information sensing system based on intermittent chaos under the background of Lévy noise
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Journal Article
A practical underwater information sensing system based on intermittent chaos under the background of Lévy noise
2022
Overview
Nowadays, 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 α=1.5 and noise intensity 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 α=1.5, deflection parameter β=0 and noise intensity D=0.1, the sensing error rate of our system with unknown frequency is 0.054%, the lowest sensing signal amplitude is 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%.
Publisher
Springer Nature B.V
