Nonlinear filtering effects of intrawell matched stochastic resonance with barrier constrainted duffing system for ship radiated line signature extraction

Dong, Haitao; Shen, Xiaohong; He, Ke; Wang, Haiyan

doi:10.1016/j.chaos.2020.110428

Cited by 23 publications

(18 citation statements)

References 59 publications

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“…It is intuitive to add new degrees of freedom for better characterizing and controlling of the particle's response. Hence, a potential constraint is further adopted here to ease the insufficient time-scale matching constraint [37]. By this means, the mathematical framework of matched stochastic resonance can be further generalized by intuitively adding a constraint of barrier factor K as below,…”

Section: Framework Of Intrawell Matched Stochastic Resonance With Potential Constraintmentioning

confidence: 99%

“…To address this problem, it can be known from [24,37] that in matching high frequency, signals require extremely large system parameters. As for practical engineering fields, the frequency of received signals generally varies from tens to thousands of Hertz, and hence, the order of magnitude for a matched potential parameter should be extremely large, especially for parameter b as there is a relationship with b ∝ a 4 .…”

Section: Adaptive Strategy For Optimized Implementationmentioning

confidence: 99%

“…There is lack of flexibility in matching the escape time scale and the relaxation time only with the damping effect. In our previous work [37], the nonlinear filtering effects of intrawell matched stochastic resonance is analyzed, which have shown a superior filtering performance as well as a wider range of frequency response. This can give us a guidance to ease the large sampling frequency limitation.…”

Section: Introductionmentioning

confidence: 99%

“…On the basis of the aforementioned analyses, this paper proposes a novel parameterized filter implementation on adaptive intrawell matched stochastic resonance (AIMSR) with a potential constrained Duffing system. As can be seen in [24,37] matching a high frequency signal requires extremely large system parameters. This refers to a large range of parameter searching interval to limit the computational efficiency and parameterized realization, especially in an embedded system.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars

Dong

Shen

et al. 2020

Sensors

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Remote passive sonar detection and classification are challenging problems that require the user to extract signatures under low signal-to-noise (SNR) ratio conditions. Adaptive line enhancers (ALEs) have been widely utilized in passive sonars for enhancing narrowband discrete components, but the performance is limited. In this paper, we propose an adaptive intrawell matched stochastic resonance (AIMSR) method, aiming to break through the limitation of the conventional ALE by nonlinear filtering effects. To make it practically applicable, we addressed two problems: (1) the parameterized implementation of stochastic resonance (SR) under the low sampling rate condition and (2) the feasibility of realization in an embedded system with low computational complexity. For the first problem, the framework of intrawell matched stochastic resonance with potential constraint is implemented with three distinct merits: (a) it can ease the insufficient time-scale matching constraint so as to weaken the uncertain affect on potential parameter tuning; (b) the inaccurate noise intensity estimation can be eased; (c) it can release the limitation on system response which allows a higher input frequency in breaking through the large sampling rate limitation. For the second problem, we assumed a particular case to ease the potential parameter a o p t = 1 . As a result, the computation complexity is greatly reduced, and the extremely large parameter limitation is relaxed simultaneously. Simulation analyses are conducted with a discrete line signature and harmonic related line signature that reflect the superior filtering performance with limited sampling rate conditions; without loss of generality of detection, we considered two circumstances corresponding to H 1 (periodic signal with noise) and H 0 (pure noise) hypotheses, respectively, which indicates the detection performance fairly well. Application verification was experimentally conducted in a reservoir with an autonomous underwater vehicle (AUV) to validate the feasibility and efficiency of the proposed method. The results indicate that the proposed method surpasses the conventional ALE method in lower frequency contexts, where there is about 10 dB improvement for the fundamental frequency in the sense of power spectrum density (PSD).

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Section: Framework Of Intrawell Matched Stochastic Resonance With Potential Constraintmentioning

confidence: 99%

Section: Adaptive Strategy For Optimized Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars

Dong

Shen

et al. 2020

Sensors

Self Cite

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“…Using the sensitivity of the CPT to system parameter perturbation and its noise immunity, it can achieve extremely low SNR detection in the case of fewer measurement data points and arbitrary colored noise background [ 26 , 27 ]. Therefore, compared with the traditional detection method, this method can detect the signal with lower SNR, and is not limited by the statistical characteristics of the noise [ 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Research on the Cooperative Detection of Stochastic Resonance and Chaos for Weak SNR Signals in Measurement While Drilling

Yang

Zhang

et al. 2021

Sensors

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In the process of drilling, severe downhole vibration causes attitude measurement sensors to be erroneous; the errors will accumulate gradually during the inclination calculation. As a result, the ultimate well path could deviate away from the planned trajectory. In order to solve this problem, this paper utilized the stochastic resonance (SR) and chaos phase transition (CPT) produced by the second-order Duffing system to identify the frequency and estimate the parameters of the signal during measurement while drilling. Firstly, the idea of a variable-scale is introduced in order to reconstruct the frequency of the attitude measurement signal, and an SR frequency detection model based on a scale transformation Duffing system is established in order to meet the frequency limit condition of the SR. Then, an attitude measurement signal with a known frequency value is input into the Duffing chaos system, and the scale transformation is used again to make the frequency value meet the parameter requirement of chaos detection. Finally, two Duffing oscillators with different initial phases of their driving signal are combined in order to estimate the amplitude and phase parameters of the measurement signal by using their CPT characteristics. The results of the laboratory test and the field-drilling data demonstrated that the proposed algorithm has good immunity to the interference noise in the attitude measurement sensor, improving the solution accuracy of the inclination in a severe noise environment and thus ensuring the dynamic stability of the well trajectory.

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Harmonic-Gaussian double-well potential stochastic resonance with its application to enhance weak fault characteristics of machinery

et al. 2023

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Although noise is ubiquitous and unwanted in detecting weak signals, the phenomenon of stochastic resonance (SR) is beneficial for enhancing weak signals embedded in signals with strong background noise. Taking into account that nonlinear systems are crucial ingredients to activate the SR, here we investigate the SR in the cases of overdamped and underdamped harmonic-Gaussian double-well potential systems subjected to noise and a periodic force. We derive and measure the analytic expression of the output signal-to-noise ratio (SNR) and the steady-state probability density (SPD) function under approximate adiabatic conditions. When the harmonic-Gaussian double-well potential loses its stability, we can observe the antiresonance phenomenon, whereas adding the damped factor into the overdamped system can change the stability of the harmonic-Gaussian double-well potential, resulting that the antiresonance behavior disappears in the underdamped system. Then, we use the overdamped and underdamped harmonic-Gaussian double-well potential

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Nonlinear filtering effects of intrawell matched stochastic resonance with barrier constrainted duffing system for ship radiated line signature extraction

Cited by 23 publications

References 59 publications

Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars

Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars

Research on the Cooperative Detection of Stochastic Resonance and Chaos for Weak SNR Signals in Measurement While Drilling

Harmonic-Gaussian double-well potential stochastic resonance with its application to enhance weak fault characteristics of machinery

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