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Fractional-order asymmetric memristive hyperchaotic oscillator with adjustable hysteresis width and its application in underwater unmanned vehicle detection

  • Hanjiang National Laboratory
  • Northwestern Polytechnical University Xian

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, a fractional-order grid-scroll asymmetric memristive hyperchaotic oscillator with adjustable hysteresis width is proposed. By introducing asymmetric memristor and adjustable hysteresis width, a hyperchaotic oscillator with infinite equilibrium point is constructed under the fractional frame, which realizes the scalability of attractor structure and flexible regulation of system dynamic behavior. Numerical analysis shows that the system can stably generate a double-scroll hyperchaotic attractor under appropriate parameters, and it shows controllable state sensitivity to external weak disturbance near the critical drive, which provides a good dynamic basis for weak signal detection. On this basis, taking advantage of the transition from critical chaos to intermittent chaos, the proposed fractional-order hyperchaotic system is further applied to the detection of underwater unmanned vehicle radiated noise. In view of the unknown frequency, the geometric frequency sequence is introduced to construct a multi-subsystem detection structure, and the target frequency is extracted by combining feature mode decomposition and envelope analysis. The detection results of analog and measured signals show that the proposed method can achieve accurate frequency estimation on the current validation dataset, with all measured-signal relative errors below 0.6%, indicating the effectiveness of the proposed hyperchaotic system and its detection potential under real underwater acoustic conditions.

Original languageEnglish
Article number118557
JournalChaos, Solitons and Fractals
Volume210
DOIs
StatePublished - Sep 2026

Keywords

  • Asymmetric memristor
  • Fractional-order hyperchaotic
  • Non-linear dynamics
  • Radiated noise
  • Signal detection

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