IEEE Access (Jan 2020)

Magnetic Anomaly Signal Detection Using Parallel Monostable Stochastic Resonance System

  • Wang Liu,
  • Zhongyan Liu,
  • Qi Zhang,
  • Yujing Xu,
  • Shuchang Liu,
  • Zhuo Chen,
  • Canlin Zhu,
  • Ze Wang,
  • Mengchun Pan,
  • Jiafei Hu,
  • Peisen Li

DOI
https://doi.org/10.1109/ACCESS.2020.3020881
Journal volume & issue
Vol. 8
pp. 162230 – 162237

Abstract

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The nonlinear stochastic resonance (SR) system possesses the ability of taking advantage of noise to enhance the weak signal when the SR system, signal and noise reach to the matching relation. It provides an effective approach to detect the weak magnetic anomaly signal in low signal-to-noise ratio. However, in practical applications, the measured magnetic anomaly signal may be a peak signal, a trough signal, or a combination of the two due to the uncertainty of magnetic target orientation. Hence it is difficult to maintain a good detection performance with single SR system because the SR system output is directly influenced by signal waveforms. Aiming to this, a new strategy using the parallel monostable SR (PMSR) system is proposed, which can ensure the good detection performance regardless of a peak signal, a trough signal, or a combination of the two. Besides, we take the kurtosis index as the criterion and search the optimal system parameters in SR system. The simulation and experiment results indicate its availability, validity and that it can achieve a good detection performance in different waveforms. It can be expected to be widely used in the field of magnetic anomaly detection with PMSR system.

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